Acceptance by laypersons and medical professionals of the personalized eHealth platform, eHealthMonitor - Griebel, Lena; Kolominsky-Rabas, Peter; Schaller, Sandra; Siudyka, Jakub; Sierpinski, Radoslaw; Papapavlou, Dimitrios; Simeonidou, Aliki; Prokosch, Hans-Ulrich; Sedlmayr, Martin (Informatics For Health & Social Care, 2016)
Often, eHealth services are not accepted because of factors such as eHealth literacy or trust. Within this study, eHealthMonitor was evaluated in three European countries (Germany, Greece, and Poland) by medical professionals and laypersons with respect to numerous acceptance factors.Questionnaires were created on the basis of factors from literature and with the help of scales which have already been validated. A qualitative survey was conducted in Germany, Poland, and Greece.The eHealth literacy of all participants was medium/high. Laypersons mostly agreed that they could easily become skillful with eHealthMonitor and that other people thought that they should use eHealthMonitor. Amongst medical professionals, a large number were afraid that eHealthMonitor could violate their privacy or the privacy of their patients. Overall, the participants thought that eHealthMonitor was a good concept and that they would use it.The main hindrances to the use of eHealthMonitor were found in trust issues including data privacy. In the future, more research on the linkage of all measured factors is needed, for example, to address the question of whether highly educated people tend to mistrust eHealth information more than people with lower levels of education.
EVALuna2:171

Accessing complex patient data from Arden Syntax Medical Logic Modules - Kraus, Stefan; Enders, M; Prokosch, Hans-Ulrich; Castellanos, I; Lenz, Richard; Sedlmayr, Martin (Artificial Intelligence in Medicine, 2015)

Accessing complex patient data from Arden Syntax Medical Logic Modules - Kraus, Stefan; Enders, Martin; Prokosch, Hans-Ulrich; Castellanos, Ixchel; Lenz, Richard; Sedlmayr, Martin (Artificial Intelligence in Medicine, 2018)
OBJECTIVE: Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden Syntax Medical Logic Modules must be able to retrieve patient data from the electronic medical record in order to enable automated decision making. For patient data with a simple structure, for instance a list of laboratory results, or, in a broader view, any patient data with a list or table structure, this mapping process is straightforward. Nevertheless, if patient data are of a complex nested structure the mapping process may become tedious. Two clinical requirements - to process complex microbiology data and to decrease the time between a critical laboratory event and its alerting by monitoring Health Level 7 (HL7) communication - have triggered the investigation of approaches for providing complex patient data from electronic medical records inside Arden Syntax Medical Logic Modules. METHODS AND MATERIALS: The data mapping capabilities of current versions of the Arden Syntax standard as well as interfaces and data mapping capabilities of three different Arden Syntax environments have been analyzed. We found and implemented three different approaches to map a test sample of complex microbiology data for 22 patients and measured their execution times and memory usage. Based on one of these approaches, we mapped entire HL7 messages onto congruent Arden Syntax objects. RESULTS: While current versions of Arden Syntax support the mapping of list and table structures, complex data structures are so far unsupported. We identified three different approaches to map complex data from electronic patient records onto Arden Syntax variables; each of these approaches successfully mapped a test sample of complex microbiology data. The first approach was implemented in Arden Syntax itself, the second one inside the interface component of one of the investigated Arden Syntax environments. The third one was based on deserialization of Extended Markup Language (XML) data. Mean execution times of the approaches to map the test sample were 497ms, 382ms, and 84ms. Peak memory usage amounted to 3MB, 3MB, and 6MB. CONCLUSION: The most promising approach by far was to map arbitrary XML structures onto congruent complex data types of Arden Syntax through deserialization. This approach is generic insofar as a data mapper based on this approach can transform any patient data provided in appropriate XML format. Therefore it could help overcome a major obstacle for integrating clinical decision support functions into clinical information systems. Theoretically, the deserialization approach would even allow mapping entire patient records onto Arden Syntax objects in one single step. We recommend extending the Arden Syntax specification with an appropriate XML data format.
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Access to and use of Data for better Healthcare: A Plea for a cooperative data and Research Infrastructure of Statutory and Private Health Insurers and the Network University Medicine (NUM) Datennutzung für eine bessere Gesundheitsversorgung-Plädoyer für eine kooperative Forschungsdatenplattform der gesetzlichen und privaten Krankenversicherung und dem Netzwerk Universitätsmedizin (NUM) - Schmitt, Jochen; Ihle, Peter; Schoffer, Olaf; Reese, Jens Peter; Ortmann, Steffen; Swart, Enno; Hanß, Sabine; Hoffmann, Falk; Stallmann, Christoph; Kraus, Monika; Semler, Sebastian Claudius; Heyder, Ralf; et al. (Gesundheitswesen, 2024)
With the Network of University Medicine (NUM) and the Medical Informatics Initiative (MII), the BMBF is funding two pioneering, structure-building research measures that are now being merged. The data integration centers (DIZ) of the MII are to be consolidated in the NUM. The aim is to establish a standardized research infrastructure within which the existing data from the clinical routine care of the 36 German university hospitals, from clinical cohorts and clinical-epidemiological studies can be used for various research questions upon request and via coordinated processes. The legal basis for this was the MII's "Informed Broad Consent" , which had been agreed upon with ethics committees and data protection authorities and implemented in all NUM locations, with a so-called "health insurance module" that allows the collection and linking of routine medical data from statutory health insurance funds (GKV) and private health insurers (PKV) as a category of care-related data (VeDa). Linking this routine data with data from hospital information systems offers particularly high potential, as no single data source provides a complete picture of medical care and the two data sources complement each other optimally. The aim now is to integrate this routine data into the NUM's secure, transparent and participatory research infrastructure in a strategic partnership with statutory health insurance funds and private health insurance companies. This promotes Germany in its role as a research location and makes a decisive contribution to improving the quality and safety of healthcare in Germany in an evidence-based manner.
CRIS-Team Scopus Importer:2025-02-04
Keywords: consent; health services research; infra structure; linkage; routine healthcare data; university medicine

A comprehensive method protocol for annotation and integrated functional understanding of lncRNAs - Kunz, Meik; Wolf, Beat; Fuchs, Maximilian; Christoph, Jan; Xiao, Ke; Thum, Thomas; Atlan, David; Prokosch, Hans-Ulrich; Dandekar, Thomas (Briefings in Bioinformatics, 2019)
Long non-coding RNAs (lncRNAs) are of fundamental biological importance; however, their functional role is often unclear or loosely defined as experimental characterization is challenging and bioinformatic methods are limited. We developed a novel integrated method protocol for the annotation and detailed functional characterization of lncRNAs within the genome. It combines annotation, normalization and gene expression with sequence-structure conservation, functional interactome and promoter analysis. Our protocol allows an analysis based on the tissue and biological context, and is powerful in functional characterization of experimental and clinical RNA-Seq datasets including existing lncRNAs. This is demonstrated on the uncharacterized lncRNA GATA6-AS1 in dilated cardiomyopathy.
EVALuna2:209483

A Digital Cognitive Aid for Anesthesia to Support Intraoperative Crisis Management: Results of the User-Centered Design Process - Schild, Stefanie; Sedlmayr, Brita; Schumacher, Ann-Kathrin; Sedlmayr, Martin; Prokosch, Hans-Ulrich; St. Pierre, Michael (JMIR mHealth and uHealth, 2019)
Background: Stressful situations during intraoperative emergencies have negative impact on human cognitive functions. Consequently, task performance may decrease and patient safety may be compromised. Cognitive aids can counteract these effects and support anesthesiologists in their crisis management. The Professional Association of German Anesthesiologists set up a project to develop a comprehensive set of digital cognitive aids for intraoperative emergencies. A parallel development for several software platforms and stationary and mobile devices will accommodate the inhomogeneity of the information technology infrastructure within German anesthesia departments.
CRIS-Team WoS Importer:2019-05-24

A Federated Online Search Tool for Biospecimens (Sample Locator): Usability Study - Schüttler, Christina; Huth, Verena; von Jagwitz-Biegnitz, Magdaléna; Lablans, Martin; Prokosch, Hans-Ulrich; Griebel, Lena (Journal of Medical Internet Research, 2020)
BACKGROUND: The German Biobank Alliance (GBA) aims to establish a cross-site biobank network. For this endeavor, the so-called Sample Locator, a federated search tool for biospecimens and related data, has been developed, forming the heart of its information technology (IT) infrastructure. OBJECTIVE: To ensure the sustainable use of such a tool, we included researchers as participants in an end user-based usability evaluation. METHODS: To develop a prototype ready for evaluation, we needed input from GBA IT experts. Thus, we conducted a 2-day workshop with 8 GBA IT team members. The focus was on the respective steps of a user-centered design process. With the acquired knowledge, the participants designed low-fidelity mock-ups. The main ideas of these mock-ups were discussed, extracted, and summarized into a comprehensive prototype using Microsoft PowerPoint. Furthermore, we created a questionnaire concerning the usability of the prototype, including the System Usability Scale (SUS), questions on negative and positive aspects, and typical tasks to be fulfilled with the tool. Subsequently, the prototype was pretested on the basis of this questionnaire with researchers who have a biobank background. Based on this preliminary work, the usability analysis was ultimately carried out with researchers and the results were evaluated. RESULTS: Altogether, 27 researchers familiar with sample requests evaluated the prototype. The analysis of the feedback certified a good usability, given that the Sample Locator prototype was seen as intuitive and user-friendly by 74% (20/27) of the participants. The total SUS score by the 25 persons that completed the questionnaire was 80.4, indicating good system usability. Still, the evaluation provided useful advice on optimization potential (eg, offering a help function). CONCLUSIONS: The findings of this usability analysis indicate that the considerations regarding a user-friendly application that have been made in the development process so far strongly coincide with the perception of the study participants. Nevertheless, it was important to engage prospective end users to ensure that the previous development is going in the desired direction and that the Sample Locator will be used in the future. The user comments and suggestions for improvement will be considered in upcoming iterations for refinement.
CRIS-Team Scopus Importer:2020-08-28
Keywords: biological specimen banks; evaluation; research; software tools; user interface

A FHIR has been lit on gICS: facilitating the standardised exchange of informed consent in a large network of university medicine - Bialke, Martin; Geidel, Lars; Hampf, Christopher; Blumentritt, Arne; Penndorf, Peter; Schuldt, Ronny; Moser, Frank-Michael; Lang, Stefan; Werner, Patrick; Staeubert, Sebastian; Hund, Hauke; Albashiti, Fady; et al. (BMC Medical Informatics and Decision Making, 2022)
Background: The Federal Ministry of Education and Research of Germany (BMBF) funds a network of university medicines (NUM) to support COVID-19 and pandemic research at national level. The "COVID-19 Data Exchange Platform " (CODEX) as part of NUM establishes a harmonised infrastructure that supports research use of COVID-19 datasets. The broad consent (BC) of the Medical Informatics Initiative (MII) is agreed by all German federal states and forms the legal base for data processing. All 34 participating university hospitals (NUM sites) work upon a harmonised infrastructural as well as legal basis for their data protection-compliant collection and transfer of their research dataset to the central CODEX platform. Each NUM site ensures that the exchanged consent information conforms to the already-balloted HL7 FHIR consent profiles and the interoperability concept of the MII Task Force "Consent Implementation " (TFCI). The Independent Trusted Third-Party (TTP) of the University Medicine Greifswald supports data protection-compliant data processing and provides the consent management solutions gICS. Methods: Based on a stakeholder dialogue a required set of FHIR-functionalities was identified and technically specified supported by official FHIR experts. Next, a "TTP-FHIR Gateway " for the HL7 FHIR-compliant exchange of consent information using gICS was implemented. A last step included external integration tests and the development of a pre-configured consent template for the BC for the NUM sites. Results: A FHIR-compliant gICS-release and a corresponding consent template for the BC were provided to all NUM sites in June 2021. All FHIR functionalities comply with the already-balloted FHIR consent profiles of the HL7 Working Group Consent Management. The consent template simplifies the technical BC rollout and the corresponding implementation of the TFCI interoperability concept at the NUM sites. Conclusions: This article shows that a HL7 FHIR-compliant and interoperable nationwide exchange of consent information could be built using of the consent management software gICS and the provided TTP-FHIR Gateway. The initial functional scope of the solution covers the requirements identified in the NUM-CODEX setting. The semantic correctness of these functionalities was validated by project-partners from the Ludwig-Maximilian University in Munich. The production rollout of the solution package to all NUM sites has started successfully.
CRIS-Team WoS Importer:2023-01-13

A framework for criteria-based selection and processing of fast healthcare interoperability resources (FHIR) data for statistical analysis: Design and implementation study - Gründner, Julian; Gulden, Christian; Kampf, Marvin; Mate, Sebastian; Prokosch, Hans-Ulrich; Zierk, Jakob (JMIR Medical Informatics, 2021)
Background: The harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and transforming original clinical data. The Fast Healthcare Interoperability Resources (FHIR) format was designed primarily to represent clinical processes; therefore, it closely resembles the clinical data model and is more widely available across modern electronic health records. However, no common standardized data format is directly suitable for statistical analyses, and data need to be preprocessed before statistical analysis. Objective: This study aimed to elucidate how FHIR data can be queried directly with a preprocessing service and be used for statistical analyses. Methods: We propose that the binary JavaScript Object Notation format of the PostgreSQL (PSQL) open source database is suitable for not only storing FHIR data, but also extending it with preprocessing and filtering services, which directly transform data stored in FHIR format into prepared data subsets for statistical analysis. We specified an interface for this preprocessor, implemented and deployed it at University Hospital Erlangen-Nürnberg, generated 3 sample data sets, and analyzed the available data. Results: We imported real-world patient data from 2016 to 2018 into a standard PSQL database, generating a dataset of approximately 35.5 million FHIR resources, including “Patient,” “Encounter,” “Condition” (diagnoses specified using International Classification of Diseases codes), “Procedure,” and “Observation” (laboratory test results). We then integrated the developed preprocessing service with the PSQL database and the locally installed web-based KETOS analysis platform. Advanced statistical analyses were feasible using the developed framework using 3 clinically relevant scenarios (data-driven establishment of hemoglobin reference intervals, assessment of anemia prevalence in patients with cancer, and investigation of the adverse effects of drugs). Conclusions: This study shows how the standard open source database PSQL can be used to store FHIR data and be integrated with a specifically developed preprocessing and analysis framework. This enables dataset generation with advanced medical criteria and the integration of subsequent statistical analysis. The web-based preprocessing service can be deployed locally at the hospital level, protecting patients’ privacy while being integrated with existing open source data analysis tools currently being developed across Germany.
CRIS-Team Scopus Importer:2021-04-16
Keywords: Data analysis; Data harmonization; Data repositories; Data science; Data standardization; Digital medical information; EHealth; Fast healthcare interoperability resources; HL7 FHIR; Medical information; Patient privacy

A Governance Framework for the Implementation and Operation of AI Applications in a University Hospital - Apfelbacher, Timo; Koçman, Sude Eda; Prokosch, Hans-Ulrich; Christoph, Jan (Digital Health and Informatics Innovations for Sustainable Health Care Systems. Proceedings of MIE 2024, 2024)
Background: Artificial intelligence (AI) is becoming increasingly important in everyday life and medical care with a notable gap between AI development in medicine there and its practical implementation in university hospitals. Objective: The aim was to develop a governance framework to guide the procurement and implementation of AI applications in university hospitals. Methods: Seven role-play expert interviews were conducted with interviewees from two university hospitals, simulating realistic AI system implementation scenarios. Results: A detailed governance framework was developed, divided into the sections general considerations, system selection criteria, and implementation. Further, a condensed version of the checklist was also derived. Conclusion: Many aspects of AI applications in medical care, such as the establishment of an AI board, remain, along with numerous concerns about the technology. These findings provide valuable insights into the topic.
CRIS-Team Scopus Importer:2024-10-25
Keywords: Algorithms; Artificial Intelligence; Clinical; Expert Systems; Governance; Machine Learning; Physicians; Software; University Hospitals

AHD2FHIR: A Tool for Mapping of Natural Language Annotations to Fast Healthcare Interoperability Resources - A Technical Case Report. - Scheible, Raphael; Caliskan, Deniz; Fischer, Patrick; Thomczyk, Fabian; Zabka, Susanne; Schneider, Henning; Boeker, Martin; Schulz, Stefan; Prokosch, Hans-Ulrich; Gulden, Christian (Studies in health technology and informatics, 2022)
A significant portion of data in Electronic Health Records is only available as unstructured text, such as surgical or finding reports, clinical notes and discharge summaries. To use this data for secondary purposes, natural language processing (NLP) tools are required to extract structured information. Furthermore, for interoperable use, harmonization of the data is necessary. HL7 Fast Healthcare Interoperability Resources (FHIR), an emerging standard for exchanging healthcare data, defines such a structured format. For German-language medical NLP, the tool Averbis Health Discovery (AHD) represents a comprehensive solution. AHD offers a proprietary REST interface for text analysis pipelines. To build a bridge between FHIR and this interface, we created a service that translates the communication around AHD from and to FHIR. The application is available under an open source license.
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Algorithmic Summaries of Perioperative Blood Pressure Fluctuations - Toddenroth, Dennis; Ganslandt, Thomas; Drescher, Caroline; Weith, Thomas; Prokosch, Hans-Ulrich; Schüttler, Jürgen; Münster, Tino (Studies in health technology and informatics, 2016)
Automated perioperative measurements such as cardiovascular monitoring data are commonly compared to established upper and lower thresholds, but could also allow for more complex interpretations. Analyzing such time series in extensive electronic medical records for research purposes may itself require customized automation, so we developed a set of algorithms for quantifying different aspects of temporal fluctuations. We implemented conventional measures of dispersion, summaries of absolute gradients between successive values, and Poincaré plots. We aggregated the severity and duration of hypotensive episodes by calculating the average area under different mean arterial pressure (MAP) thresholds. We applied these methods to 30,452 de-identified MAP series, and analyzed the similarity between alternative indices via hierarchical clustering. To explore the potential utility of these propositional metrics, we computed their statistical association with presumed complications due to cardiovascular instability. We observed that hierarchical clustering reliably segregated features that had been designed to quantify dissimilar aspects. Summaries of temporary hypotension turned out to be significantly increased among patient subgroups with subsequent signs of a complicated recovery. These associations were even stronger for measures that were specifically geared to capturing short-term MAP variability. These observations suggest the potential capability of our proposed algorithms for quantifying heterogeneous aspects of short-term MAP fluctuations. Future research might also target a wider selection of outcomes and other attributes that may be subject to intraoperative variability.
EVALuna2:161
Keywords: Advanced algorithmic analyses; Clinical times series; EMR reuse

Aligning Biobanks and Data Integration Centers Efficiently (ABIDE_MI) - Prokosch, Hans-Ulrich; Baber, Ronny; Bollmann, Paula; Gebhardt, Marie; Gründner, Julian; Hummel, Michael (Healthcare of the Future 2022, 2022)
ABIDE_MI is a complementary funded 18 months project within the German Medical Informatics Initiative (MII), which aims to align IT infrastructures and regulatory/governance structures between biobanks/biobanking IT and the MII data integration centres (DIC) at German university hospitals. A major task in 2021 was the systematic collection of all documents describing rules, as well as proposal/contract templates for data and biosample use and access at each of the participating 24 university hospitals and their comparison with MII-wide consented data sharing principles, documents and governance structures. This comparison revealed large heterogeneity across the ABIDE_MI sites and further, redundant structures/regulations currently established at the German university hospitals. A second task was the design and stepwise development of an IT network infrastructure with central components (data and biosample query portal) and decentralized standardized FHIR servers to capture the standardized FHIR-based core data set modules (resources) defined within the MII working group "Interoperability". Subsequent steps in the project are the harmonization of the data and biosample sharing governance/regulation frameworks at each ABIDE_MI site, creating synergies for the research infrastructures at the German university hospitals and to link those resources to the German Portal for Medical Research Data and with the BBMRI-ERIC Directory and Negotiator tools.
CRIS-Team Scopus Importer:2022-05-27
Keywords: Biobank networks; data and biosample sharing; medical informatics initiative; real world data

A method for the graphical modeling of relative temporal constraints - Mate, Sebastian; Bürkle, Thomas; Kapsner, Lorenz; Toddenroth, Dennis; Kampf, Marvin; Sedlmayr, Martin; Castellanos, Ixchel; Prokosch, Hans-Ulrich; Kraus, Stefan (Journal of Biomedical Informatics, 2019)
Searching for patient cohorts in electronic patient data often requires the definition of temporal constraints between the selection criteria. However, beyond a certain degree of temporal complexity, the non-graphical, form-based approaches implemented in current translational research platforms may be limited when modeling such constraints. In our opinion, there is a need for an easily accessible and implementable, fully graphical method for creating temporal queries. We aim to respond to this challenge with a new graphical notation. Based on Allen's time interval algebra, it allows for modeling temporal queries by arranging simple horizontal bars depicting symbolic time intervals. To make our approach applicable to complex temporal patterns, we apply two extensions: with duration intervals, we enable the inference about relative temporal distances between patient events, and with time interval modifiers, we support counting and excluding patient events, as well as constraining numeric values. We describe how to generate database queries from this notation. We provide a prototypical implementation, consisting of a temporal query modeling frontend and an experimental backend that connects to an i2b2 system. We evaluate our modeling approach on the MIMIC-III database to demonstrate that it can be used for modeling typical temporal phenotyping queries. Data availability statement The source code (licensed under the GNU General Public License v3.0) is available on GitHub (https://github.com/sebmate/AllenGUI and https://github.com/sebmate/AllenSPARQL). Also supplied are the development i2b2 dataset (with the 13 artificial patients) and the SQL scripts to populate the i2b2 system with the MIMIC-III data. Please note that the software is of prototypical character and provided “as is”, without any warranties.
CRIS-Team Scopus Importer:2019-11-15
Keywords: Data integration; Data retrieval; Patient cohort identification; Phenotyping; Phenotyping algorithms; Temporal queries

A Multi-User Terminology Mapping Toolbox - Mate, Sebastian; Seuchter, Susanne A.; Ehrenberg, Katharina; Deppenwiese, Noemi; Zierk, Jakob; Prokosch, Hans-Ulrich; Kraska, Detlef; Kapsner, Lorenz (German Medical Data Sciences: Bringing Data to Life, 2021)
Semantic interoperability is a major challenge in multi-center data sharing projects, a challenge that the German Initiative for Medical Informatics is taking up. With respect to laboratory data, enriching site-specific tests and measurements with LOINC codes appears to be a crucial step in supporting cross-institutional research. However, this effort is very time-consuming, as it requires expert knowledge of local site specifics. To ease this process, we developed a generic manual collaborative terminology mapping tool, the MIRACUM Mapper. It allows the creation of arbitrary mapping workflows involving different user roles. A mapping workflow with two user roles has been implemented at University Hospital Erlangen to support the local LOINC mapping. Additionally, the MIRACUM LabVisualizeR provides summary statistics and visualizations of analyte data. We developed a toolbox that facilitates the collaborative creation of mappings and streamlines the review as well as the validation process. The two tools are available under an open source license.
CRIS-Team Scopus Importer:2021-06-11
Keywords: Interoperability; Laboratory; LOINC; Secondary Use; Terminology

An Abstraction Layer to Facilitate Technical Interoperability Between Medical Records and Knowledge Modules - Staudigel, Martin; Prokosch, Hans-Ulrich; Kraus, Stefan (Studies in health technology and informatics, 2017)
Integrating clinical decision support (CDS) functions into an existing hospital information system (HIS) is often a tedious task. This problem area is so pervasive that the Arden Syntax, a widely used standard for CDS functions, assigned a specific designation, the so-called "curly braces problem". It derives from a pair of curly braces used to encapsulate any parameters required for the interactions with a HIS. The traditional approach is to leave the problem area of technical interoperability entirely to the specific institution, possibly entailing a considerable amount of initial programming work. This study describes a reusable and expandable solution to this problem in the form of an abstraction layer. Our study comprised an analytical phase in which we investigated the data source access capabilities of five Arden Syntax environments. Building on the results, we implemented a working prototype that is capable of querying heterogeneous data sources, which facilitates a straightforward connection of new data sources with existing and future communication protocols and standards. From our point of view, the technical aspects of the "curly braces problem" with respect to data source access have changed over the years, insofar as technical progress lead to defacto standards for data storage, data querying and inter-system communication. An agreement on such a convention, together with the supply of commonly used data source adapters could promote the further dissemination of the Arden Syntax as a standard for representing and sharing medical knowledge.
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Analysis and classification of oncology activities on the way to workflow based single source documentation in clinical information systems - Wagner, Stefan; Beckmann, Matthias; Wullich, Bernd; Seggewies, Christof; Ries, Markus; Buerkle, Thomas; Prokosch, Hans-Ulrich (BMC Medical Informatics and Decision Making, 2015)
Today, cancer documentation is still a tedious task involving many different information systems even within a single institution and it is rarely supported by appropriate documentation workflows.In a comprehensive 14 step analysis we compiled diagnostic and therapeutic pathways for 13 cancer entities using a mixed approach of document analysis, workflow analysis, expert interviews, workflow modelling and feedback loops. These pathways were stepwise classified and categorized to create a final set of grouped pathways and workflows including electronic documentation forms.A total of 73 workflows for the 13 entities based on 82 paper documentation forms additionally to computer based documentation systems were compiled in a 724 page document comprising 130 figures, 94 tables and 23 tumour classifications as well as 12 follow-up tables. Stepwise classification made it possible to derive grouped diagnostic and therapeutic pathways for the three major classes - solid entities with surgical therapy - solid entities with surgical and additional therapeutic activities and - non-solid entities. For these classes it was possible to deduct common documentation workflows to support workflow-guided single-source documentation.Clinical documentation activities within a Comprehensive Cancer Center can likely be realized in a set of three documentation workflows with conditional branching in a modern workflow supporting clinical information system.
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An Analysis of Erlangen University Hospital's Billing Data on Utility-Based De-Identification. - Kampf, Marvin; Kraska, Detlef; Prokosch, Hans-Ulrich (Studies in health technology and informatics, 2019)
BACKGROUND: To make patient care data more accessible for research, German university hospitals join forces in the course of the Medical Informatics Initiative. In a first step, the administrative data of university hospitals is made available for federated utilization. Project-specific de-identification of this data is necessary to satisfy privacy laws. OBJECTIVE: We want to make a statement about the population uniqueness of the data. By generalizing the data, we try to reduce uniqueness and improve k-anonymity. METHODS: We analyze quasi-identifying attributes of the Erlangen University Hospital's billing data regarding population uniqueness and re-identification risk. We count individuals per equality class (k) to measure uniqueness. RESULTS: Because of the diagnoses and procedures being particularly unique in combination with sex and age of the patients, the data set is not anonymized in matters of k-anonymity with k > 1 . We are able to reduce population uniqueness with generalization and suppression of unique domains. CONCLUSION: To create k-anonymity with k > 1 while still maintaining a particular utility of the data, we need to apply further established strategies of de-identification.
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An analysis of Erlangen University Hospital's billing data on utility-based de-identification - Kampf, Marvin; Kraska, Detlef; Prokosch, Hans-Ulrich (Proceedings of the EFMI 2019 Special Topic Conference, 2019)
Background: To make patient care data more accessible for research, German university hospitals join forces in the course of the Medical Informatics Initiative. In a first step, the administrative data of university hospitals is made available for federated utilization. Project-specific de-identification of this data is necessary to satisfy privacy laws. Objective: We want to make a statement about the population uniqueness of the data. By generalizing the data, we try to reduce uniqueness and improve k-anonymity. Methods: We analyze quasi-identifying attributes of the Erlangen University Hospital's billing data regarding population uniqueness and re-identification risk. We count individuals per equality class (k) to measure uniqueness. Results: Because of the diagnoses and procedures being particularly unique in combination with sex and age of the patients, the data set is not anonymized in matters of k-anonymity with k > 1. We are able to reduce population uniqueness with generalization and suppression of unique domains. Conclusion: To create k-anonymity with k > 1 while still maintaining a particular utility of the data, we need to apply further established strategies of de-identification.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Data privacy; K-anonymity; Population uniqueness; Risk; Secondary use

A nationwide registry for recurrent urolithiasis in the upper urinary tract - The RECUR study protocol. - Schoenthaler, Martin; Fichtner, Urs Alexander; Boeker, Martin; Zoeller, Daniela; Binder, Harald; Prokosch, Hans-Ulrich; Praus, Friederike; Walther, Tabea; Glienke, Maximilian; Horki, Petar; Gratzke, Christian; Farin-Glattacker, Erik (BMC Health Services Research, 2022)
BACKGROUND: Urinary stone disease is a widespread disease with tremendous impact on those affected and on societies around the globe. Nevertheless, clinical and health care research in this area seem to lag far behind cardiovascular diseases or cancer. This may be due to the lack of an immediate deadly threat from the disease and therefore less public and professional interest. However, the patients suffer from recurring, sometimes intense pain and often must be treated in hospital. Long-term morbidity includes doubled rates of chronic kidney disease and arterial hypertension after at least one stone-related event. Observational studies, more specifically, registries and other electronic data sets have been proposed as a means of filling critical gaps in evidence. We propose a nationwide digital and fully automated registry as part of the German Ministry for Education and Research (BMBF) call for the "establishment of model registries". METHODS: RECUR builds on the technical infrastructure of Germany's Medical Informatics Initiative. Local data integration centres (DIC) of participating medical universities will collect pseudonymized and harmonized data from respective hospital information systems. In addition to their clinical data, participants will provide patient reported outcomes using a mobile patient app. Scientific data exploration includes queries and analysis of federated data from DICs of eleven participating sites. All primary patient data will remain at the participating sites at all times. With comprehensive data from this longitudinal registry, we will be able to describe the disease burden, to determine and validate risk factors, and to evaluate treatments. Implementation and operation of the RECUR registry will be funded by the BMBF for five years. Subsequently, the registry is to be continued by the German Society of Urology without significant costs for study personnel. DISCUSSION: The proposed registry will substantially improve the structural and procedural framework for patients with recurrent urolithiasis. This includes advanced diagnostic algorithms and treatment pathways. The registry will help us identify those patients who will most benefit from specific interventions to prevent recurrences. The RECUR study protocol and the registry's technical architecture including full digitalization and automation of almost all registry-associated proceedings can be transferred to future registries. TRIAL REGISTRATION: This study is registered at the German Clinical Trial Register (Deutsches Register Klinischer Studien), DRKS-ID DRKS00026923 , date of registration January, 11th 2022.
EVALuna2:528243

An extension of the arden syntax to facilitate clinical document generation - Kraus, Stefan; Toddenroth, Dennis; Unberath, Philipp; Prokosch, Hans-Ulrich; Hueske-Kraus, Dirk (Healthcare of the Future - Bridging the Information Gap, 2019)
While clinical information systems usually store patient records in database tables, human interpretations as well as information transfer between institutions often require that clinical data can be represented as documents. To automate document generation from patient data in conjunction with the rich computational facilities of clinical decision support, we propose a template-based extension of the Arden Syntax, and discuss the benefits and limitations observed during a pilot application for patient recruitment. While the original Arden Syntax supports string concatenation as well as the substitution of unnamed placeholders, we integrated an additional method based on embedding expressions into strings. A dedicated parser identifies the expressions and automatically substitutes them at runtime, which can for example be harnessed to display the most recent value from a time series. The resulting mechanism supports the generation of extensive clinical documents without the need to apply specific operators. To evaluate the proposed extension, we implemented an Arden module that identifies an intensive care patient cohort that conforms to the eligibility criteria of a clinical trial and outputs a concise patient overview in different document formats. While string interpolation in the original Arden standard has been tailored to clinical event monitoring, we interpret that our accessible approach usefully extends Arden's data-to-text capabilities. Future research might target the development of an interactive template editor that would hide the complexity of formatting directives and conditional expressions behind a graphical user interface, and explore how computer-linguistic formalisms might facilitate advanced features such as automatic inflections of verbs and nouns.
CRIS-Team Scopus Importer:2019-05-02
Keywords: Arden Syntax; Clinical document generation; Natural language generation; String interpolation

An Extension of the Arden Syntax to Facilitate Clinical Document Generation. - Kraus, Stefan; Toddenroth, Dennis; Unberath, Philipp; Prokosch, Hans-Ulrich; Hueske-Kraus, Dirk (ICT for Health Science Research, 2019)
While clinical information systems usually store patient records in database tables, human interpretations as well as information transfer between institutions often require that clinical data can be represented as documents. To automate document generation from patient data in conjunction with the rich computational facilities of clinical decision support, we propose a template-based extension of the Arden Syntax, and discuss the benefits and limitations observed during a pilot application for patient recruitment. While the original Arden Syntax supports string concatenation as well as the substitution of unnamed placeholders, we integrated an additional method based on embedding expressions into strings. A dedicated parser identifies the expressions and automatically substitutes them at runtime, which can for example be harnessed to display the most recent value from a time series. The resulting mechanism supports the generation of extensive clinical documents without the need to apply specific operators. To evaluate the proposed extension, we implemented an Arden module that identifies an intensive care patient cohort that conforms to the eligibility criteria of a clinical trial and outputs a concise patient overview in different document formats. While string interpolation in the original Arden standard has been tailored to clinical event monitoring, we interpret that our accessible approach usefully extends Arden's data-to-text capabilities. Future research might target the development of an interactive template editor that would hide the complexity of formatting directives and conditional expressions behind a graphical user interface, and explore how computer-linguistic formalisms might facilitate advanced features such as automatic inflections of verbs and nouns.
EVALuna2:209495

Ansatz und Risikoanalyse für ein Smart Object Network im Krankenhaus - Sedlmayr, Martin; Becker, Andreas; Münch, Ulli; Meier, Fritz; Prokosch, Hans-Ulrich; Ganslandt, Thomas (INFORMATIK 2009 - Im Focus das Leben, Beitrage der 39. Jahrestagung der Gesellschaft fur Informatik e.V. (GI), 2009)
CRIS-Team Scopus Importer:2021-11-16

Ansatz und Risikoanalyse für ein Smart Object Network im Krankenhaus - Sedlmayr, Martin; Becker, Andreas; Münch, Ulli; Meier, Fritz; Prokosch, Hans-Ulrich; Ganslandt, Thomas (Mobiles Computing in der Medizin - Proceedings zum 9. Workshop der GI- und GMDS-Arbeitsgruppe Mobile Informationstechnologie in der Medizin, MoCoMed 2009, 2009)
CRIS-Team Scopus Importer:2021-11-16

A pipeline for the fully automated estimation of continuous reference intervals using real-world data - Ammer, Tatjana; Schützenmeister, André; Prokosch, Hans-Ulrich; Rauh, Manfred; Rank, Christopher M.; Zierk, Jakob (Scientific Reports, 2023)
Reference intervals are essential for interpreting laboratory test results. Continuous reference intervals precisely capture physiological age-specific dynamics that occur throughout life, and thus have the potential to improve clinical decision-making. However, established approaches for estimating continuous reference intervals require samples from healthy individuals, and are therefore substantially restricted. Indirect methods operating on routine measurements enable the estimation of one-dimensional reference intervals, however, no automated approach exists that integrates the dependency on a continuous covariate like age. We propose an integrated pipeline for the fully automated estimation of continuous reference intervals expressed as a generalized additive model for location, scale and shape based on discrete model estimates using an indirect method (refineR). The results are free of subjective user-input, enable conversion of test results into z-scores and can be integrated into laboratory information systems. Comparison of our results to established and validated reference intervals from the CALIPER and PEDREF studies and manufacturers’ package inserts shows good agreement of reference limits, indicating that the proposed pipeline generates high-quality results. In conclusion, the developed pipeline enables the generation of high-precision percentile charts and continuous reference intervals. It represents the first parameter-less and fully automated solution for the indirect estimation of continuous reference intervals.
CRIS-Team Scopus Importer:2023-09-01

Applied Practice and Possible Leverage Points for Information Technology Support for Patient Screening in Clinical Trials: Qualitative Study - Becker, Linda; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Newe, Axel (JMIR Medical Informatics, 2020)
Background: Clinical trials are one of the most challenging and meaningful designs in medical research. One essential step before starting a clinical trial is screening, that is, to identify patients who fulfill the inclusion criteria and do not fulfill the exclusion criteria. The screening step for clinical trials might be supported by modern information technology (IT). Objective: This explorative study aimed (1) to obtain insights into which tools for feasibility estimations and patient screening are actually used in clinical routine and (2) to determine which method and type of IT support could benefit clinical staff. Methods: Semistandardized interviews were conducted in 5 wards (cardiology, gynecology, gastroenterology, nephrology, and palliative care) in a German university hospital. Of the 5 interviewees, 4 were directly involved in patient screening. Three of them were clinicians, 1 was a study nurse, and 1 was a research assistant. Results: The existing state of study feasibility estimation and the screening procedure were dominated by human communication and estimations from memory, although there were many possibilities for IT support. Success mostly depended on the experience and personal motivation of the clinical staff. Electronic support has been used but with little importance so far. Searches in ward-specific patient registers (databases) and searches in clinical information systems were reported. Furthermore, free-text searches in medical reports were mentioned. For potential future applications, a preference for either proactive or passive systems was not expressed. Most of the interviewees saw the potential for the improvement of the actual systems, but they were also largely satisfied with the outcomes of the current approach. Most of the interviewees were interested in learning more about the various ways in which IT could support and relieve them in their clinical routine. Conclusions: Overall, IT support currently plays a minor role in the screening step for clinical trials. The lack of IT usage and the estimations made from memory reported by all the participants might constrain cognitive resources, which might distract from clinical routine. We conclude that electronic support for the screening step for clinical trials is still a challenge and that education of the staff about the possibilities for electronic support in clinical trials is necessary.<br
Keywords: clinical trial; patient screening; electronic support; clinical information systems; inclusion criteria; exclusion criteria; feasibility studies; mobile phone

A Queue-Poll Extension and DataSHIELD: Standardised, Monitored, Indirect and Secure Access to Sensitive Data. - Gründner, Julian; Prokosch, Hans-Ulrich; Schindler, Sebastian; Lenz, Stefan; Binder, Harald (ICT for Health Science Research, 2019)
Analyzing data across hospitals and institutions without the data leaving the hospitals and adding institutions to a trusted network is an important part of privacy preserving data analysis. This work implements a queue-poll extension and integrates with DataSHIELD to allow for a standardized, monitored, indirect and secure access to data. The extension was created using the HTTP protocol and requests are not pushed into a participating institution but are sent to a server outside an institutional network. These requests are then pulled into the institution from within, executed and the response sent back to the outside server, which relays the request back to the request sender. We found that the requests were slower than a direct push request, but also that the integration of new institutions into the network was easily achieved. We propose that future work should focus on optimizing the monitoring and speed of the service. The service created here could reduce the barriers to entry for institutions to form an analysis network and can be used not only to drive analysis but also the sharing of resulting information and models.
EVALuna2:209491

A queue-poll extension and DataSHIELD: Standardised, monitored, indirect and secure access to sensitive data - Gründner, Julian; Prokosch, Hans-Ulrich; Schindler, Sebastian; Lenz, Stefan; Binder, Harald (Proceedings of the EFMI 2019 Special Topic Conference, 2019)
Analyzing data across hospitals and institutions without the data leaving the hospitals and adding institutions to a trusted network is an important part of privacy preserving data analysis. This work implements a queue-poll extension and integrates with DataSHIELD to allow for a standardized, monitored, indirect and secure access to data. The extension was created using the HTTP protocol and requests are not pushed into a participating institution but are sent to a server outside an institutional network. These requests are then pulled into the institution from within, executed and the response sent back to the outside server, which relays the request back to the request sender. We found that the requests were slower than a direct push request, but also that the integration of new institutions into the network was easily achieved. We propose that future work should focus on optimizing the monitoring and speed of the service. The service created here could reduce the barriers to entry for institutions to form an analysis network and can be used not only to drive analysis but also the sharing of resulting information and models.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Data analysis network; Data governance; Distributed privacy preserving analysis; Machine-learning

A REST Service for the Visualization of Clinical Time Series Data in the Context of Clinical Decision Support. - Unberath, Philipp; Prokosch, Hans-Ulrich; Kraus, Stefan (ICT for Health Science Research, 2019)
BACKGROUND: University Hospital Erlangen provides clinical decision support (CDS) functions in the intensive care setting, that are based on the Arden Syntax standard. These CDS functions generate extensive output, including patient data charts. In the course of the migration of our CDS platform we revised the charting tool because although the tool was generally perceived as useful, the clinical users reported several shortcomings. OBJECTIVE: During the migration of our CDS platform, we aimed at resolving the reported shortcomings and at developing a reusable and parameterizable charting tool, driven by best practices and requirements of local clinicians. METHODS: We conducted a requirements analysis with local clinicians and searched the literature for well-established guidelines for clinical charts. Using a charting library, we then implemented the tool based on the found criteria and provided it with a REST interface. RESULTS: The criteria catalog included 18 requirements, all of which were successfully implemented. The new charting tool fully replaced the previous implementation in clinical routine. It also provides a web interface that enables clinicians to configure charts without programming skills. CONCLUSION: The new charting tool combines local preferences with best practices for visualization of clinical time series data. With its REST interface and reusable design it can be easily integrated in existing CDS platforms.
EVALuna2:209494

A REST service for the visualization of clinical time series data in the context of clinical decision support - Unberath, Philipp; Prokosch, Hans-Ulrich; Kraus, Stefan (Proceedings of the EFMI 2019 Special Topic Conference, 2019)
Background: University Hospital Erlangen provides clinical decision support (CDS) functions in the intensive care setting, that are based on the Arden Syntax standard. These CDS functions generate extensive output, including patient data charts. In the course of the migration of our CDS platform we revised the charting tool because although the tool was generally perceived as useful, the clinical users reported several shortcomings. Objective: During the migration of our CDS platform, we aimed at resolving the reported shortcomings and at developing a reusable and parameterizable charting tool, driven by best practices and requirements of local clinicians. Methods: We conducted a requirements analysis with local clinicians and searched the literature for well-established guidelines for clinical charts. Using a charting library, we then implemented the tool based on the found criteria and provided it with a REST interface. Results: The criteria catalog included 18 requirements, all of which were successfully implemented. The new charting tool fully replaced the previous implementation in clinical routine. It also provides a web interface that enables clinicians to configure charts without programming skills. Conclusion: The new charting tool combines local preferences with best practices for visualization of clinical time series data. With its REST interface and reusable design it can be easily integrated in existing CDS platforms.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Clinical decision support; Patient data charts; Visualization

A scoping review of cloud computing in healthcare - Griebel, Lena; Prokosch, Hans-Ulrich; Köpcke, Felix; Toddenroth, Dennis; Christoph, Jan; Leb, Ines; Engel, Igor; Sedlmayr, Martin (BMC Medical Informatics and Decision Making, 2015)
Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an "OMICS-context", e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain.MEDLINE was searched in July 2013 and in December 2014 for publications containing the terms "cloud computing" and "cloud-based". Each journal and conference article was categorized and summarized independently by two researchers who consolidated their findings.102 publications have been analyzed and 6 main topics have been found: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Commonly used features are broad network access for sharing and accessing data and rapid elasticity to dynamically adapt to computing demands. Eight articles favor the pay-for-use characteristics of cloud-based services avoiding upfront investments. Nevertheless, while 22 articles present very general potentials of cloud computing in the medical domain and 66 articles describe conceptual or prototypic projects, only 14 articles report from successful implementations. Further, in many articles cloud computing is seen as an analogy to internet-/web-based data sharing and the characteristics of the particular cloud computing approach are unfortunately not really illustrated.Even though cloud computing in healthcare is of growing interest only few successful implementations yet exist and many papers just use the term "cloud" synonymously for "using virtual machines" or "web-based" with no described benefit of the cloud paradigm. The biggest threat to the adoption in the healthcare domain is caused by involving external cloud partners: many issues of data safety and security are still to be solved. Until then, cloud computing is favored more for singular, individual features such as elasticity, pay-per-use and broad network access, rather than as cloud paradigm on its own.
EVALuna2:144

Association of mineral and bone biomarkers with adverse cardiovascular outcomes and mortality in the German Chronic Kidney Disease (GCKD) cohort - Reimer, Katharina Charlotte; Nadal, Jennifer; Meiselbach, Heike; Schmid, Matthias; Schultheiss, Ulla T.; Kotsis, Fruzsina; Stockmann, Helena; Friedrich, Nele; Nauck, Matthias; Krane, Vera; Eckardt, Kai-Uwe; Schneider, Markus; et al. (Bone Research, 2023)
Mineral and bone disorder (MBD) in chronic kidney disease (CKD) is tightly linked to cardiovascular disease (CVD). In this study, we aimed to compare the prognostic value of nine MBD biomarkers to determine those associated best with adverse cardiovascular (CV) outcomes and mortality. In 5 217 participants of the German CKD (GCKD) study enrolled with an estimated glomerular filtration rate (eGFR) between 30–60 mL·min−1 per 1.73 m2 or overt proteinuria, serum osteoprotegerin (OPG), C-terminal fibroblast growth factor-23 (FGF23), intact parathyroid hormone (iPTH), bone alkaline phosphatase (BAP), cross-linked C-telopeptide of type 1 collagen (CTX1), procollagen 1 intact N-terminal propeptide (P1NP), phosphate, calcium, and 25-OH vitamin D were measured at baseline. Participants with missing values among these parameters (n = 971) were excluded, leaving a total of 4 246 participants for analysis. During a median follow-up of 6.5 years, 387 non-CV deaths, 173 CV deaths, 645 nonfatal major adverse CV events (MACEs) and 368 hospitalizations for congestive heart failure (CHF) were observed. OPG and FGF23 were associated with all outcomes, with the highest hazard ratios (HRs) for OPG. In the final Cox regression model, adjusted for CV risk factors, including kidney function and all other investigated biomarkers, each standard deviation increase in OPG was associated with non-CV death (HR 1.76, 95% CI: 1.35–2.30), CV death (HR 2.18, 95% CI: 1.50–3.16), MACE (HR 1.38, 95% CI: 1.12–1.71) and hospitalization for CHF (HR 2.05, 95% CI: 1.56–2.69). Out of the nine biomarkers examined, stratification based on serum OPG best identified the CKD patients who were at the highest risk for any adverse CV outcome and mortality.
CRIS-Team Scopus Importer:2023-11-10

Attitudes and Acceptance Towards Artificial Intelligence in Medical Care. - Holzner, Dana; Apfelbacher, Timo; Rödle, Wolfgang; Schüttler, Christina; Prokosch, Hans-Ulrich; Mikolajczyk, Rafael; Negash, Sarah; Kartschmit, Nadja; Manuilova, Iryna; Buch, Charlotte; Gundlack, Jana; Christoph, Jan (Studies in health technology and informatics, 2022)
BACKGROUND: Artificial intelligence (AI) in medicine is a very topical issue. As far as the attitudes and perspectives of the different stakeholders in healthcare are concerned, there is still much to be explored. OBJECTIVE: Our aim was to determine attitudes and aspects towards acceptance of AI applications from the perspective of physicians in university hospitals. METHODS: We conducted individual exploratory expert interviews. Low fidelity mockups were used to show interviewees potential application areas of AI in clinical care. RESULTS: In principle, physicians are open to the use of AI in medical care. However, they are critical of some aspects such as data protection or the lack of explainability of the systems. CONCLUSION: Although some trends in attitudes e.g., on the challenges or benefits of using AI became clear, it is necessary to conduct further research as intended by the subsequent PEAK project.
EVALuna2:528248

A User-Centered Design Approach for a Screening App for People With Cognitive Impairment (digiDEM-SCREEN): Development and Usability Study - Zeiler, Michael; Dietzel, Nikolas; Haug, Fabian; Haug, Julian; Kammerer, Klaus; Pryss, Rüdiger; Heuschmann, Peter; Grässel, Elmar; Kolominsky-Rabas, Peter; Prokosch, Hans-Ulrich (JMIR Human Factors, 2025)
Background: Dementia is a widespread syndrome that currently affects more than 55 million people worldwide. Digital screening instruments are one way to increase diagnosis rates. Developing an app for older adults presents several challenges, both technical and social. In order to make the app user-friendly, feedback from potential future end users is crucial during this development process. Objective: This study aimed to establish a user-centered design process for the development of digiDEM-SCREEN, a user-friendly app to support early identification of persons with slight symptoms of dementia. Methods: This research used qualitative and quantitative methods and involved 3 key stakeholder groups: the digiDEM research team, the software development team, and the target user group (older adults ≥65 years with and without cognitive impairments). The development of the screening app was based on an already existing and scientifically analyzed screening test (Self-Administered Tasks Uncovering Risk of Neurodegeneration; SATURN). An initial prototype was developed based on the recommendations for mobile health apps and the teams’ experiences. The prototype was tested in several iterations by various end users and continuously improved. The app’s usability was evaluated using the System Usability Scale (SUS), and verbal feedback by the end users was obtained using the think-aloud method. Results: The translation process during test development took linguistic and cultural aspects into account. The texts were also adapted to the German-speaking context. Additional instructions were developed and supplemented. The test was administered using different randomization options to minimize learning effects. digiDEM-SCREEN was developed as a tablet and smartphone app. In the first focus group discussion, the developers identified and corrected the most significant criticism in the next version. Based on the iterative improvement process, only minor issues needed to be addressed after the final focus group discussion. The SUS score increased with each version (score of 72.5 for V1 vs 82.4 for V2), while the verbal feedback from end users also improved. Conclusions: The development of digiDEM-SCREEN serves as an excellent example of the importance of involving experts and potential end users in the design and development process of health apps. Close collaboration with end users leads to products that not only meet current standards but also address the actual needs and expectations of users. This is also a crucial step toward promoting broader adoption of such digital tools. This research highlights the significance of a user-centered design approach, allowing content, text, and design to be optimally tailored to the needs of the target audience. From these findings, it can be concluded that future projects in the field of health apps would also benefit from a similar approach.
CRIS-Team Scopus Importer:2025-02-14
Keywords: aging; cognitive disorder; cognitive impairment; dementia; design; development; digiDEM; feedback; mHealth; mobile app; mobile health; older adults; screening; usability; user centred; user-centered

Availability of Structured Data Elements in Electronic Health Records for Supporting Patient Recruitment in Clinical Trials. - Vass, Albert; Reinecke, Ines; Boeker, Martin; Prokosch, Hans-Ulrich; Gulden, Christian (Studies in health technology and informatics, 2022)
Automated identification of eligible patients for clinical trials is an evident secondary use for electronic health records (EHR) data accumulated during routine care. This task requires relevant data elements to be both available in the EHR and in a structured form. This work analyzes these data quality dimensions of EHR data elements corresponding to a selection of frequent eligibility criteria over a total of 436 patient records at 10 university hospitals within the MIRACUM consortium. Data elements from demographics, diagnosis and laboratory findings are typically structured with a completeness of 73 % to 88 % while medication as well as procedures are rather untructured with a completeness of only 44 %. The results can be used to derive suggestions for data quality improvement measures with respect to patient recruitment as well as to serve as a baseline to quantify future developments.
EVALuna2:528246

BiasCorrector: Fast and accurate correction of all types of experimental biases in quantitative DNA methylation data derived by different technologies - Kapsner, Lorenz; Zavgorodnij, Mikhail G.; Majorova, Svetlana P.; Hotz-Wagenblatt, Agnes; Kolychev, Oleg V.; Lebedev, Igor N.; Hoheisel, Jörg D.; Hartmann, Arndt; Bauer, Andrea; Mate, Sebastian; Prokosch, Hans-Ulrich; Haller, Florian; et al. (International Journal of Cancer, 2021)
Quantification of DNA methylation in neoplastic cells is crucial both from mechanistic and diagnostic perspectives. However, such measurements are prone to different experimental biases. Polymerase chain reaction (PCR) bias results in an unequal recovery of methylated and unmethylated alleles at the sample preparation step. Post-PCR biases get introduced additionally by the readout processes. Correcting the biases is more practicable than optimising experimental conditions, as demonstrated previously. However, utilisation of our earlier developed algorithm strongly necessitates automation. Here, we present two R packages: rBiasCorrection, the core algorithms to correct biases; and BiasCorrector, its web-based graphical user interface frontend. The software detects and analyses experimental biases in calibration DNA samples at a single base resolution by using cubic polynomial and hyperbolic regression. The correction coefficients from the best regression type are employed to compensate for the bias. Three common technologies—bisulphite pyrosequencing, next-generation sequencing and oligonucleotide microarrays—were used to comprehensively test BiasCorrector. We demonstrate the accuracy of BiasCorrector's performance and reveal technology-specific PCR- and post-PCR biases. BiasCorrector effectively eliminates biases regardless of their nature, locus, the number of interrogated methylation sites and the detection method, thus representing a user-friendly tool for producing accurate epigenetic results.
CRIS-Team Scopus Importer:2021-06-04
Keywords: BiasCorrector; cancer; DNA methylation; PCR-bias; post-PCR bias

Biobanks, translational research and medical informatics - Schüttler, Christina; Jahns, R.; Prokosch, Hans-Ulrich; Wach, Sven; Wullich, Bernd (Die Urologie, 2022)
When we think of medical research, one intuitively associates it with the analysis of study data collected for a specific research question or with the secondary use of patient data from routine care. However, these are not the only sources for answering scientific questions. Especially for translational research, tissue and liquid samples such as blood, DNA or other body fluids provide essential insights into disease pathogenesis, development of new therapies and treatment decisions. Access to these biomedical materials is provided by so-called biobanks. By collecting, characterizing, documenting and, if necessary, processing human biospecimens in accordance with high quality standards, they can support research of the causes of diseases, early diagnosis and the targeted treatment of diseases, or make a significant contribution to the investigation of common diseases.
CRIS-Team WoS Importer:2022-09-16

Case-based visualization of a patient cohort using SEER epidemiologic data - Maier, Christian; Bürkle, Thomas; Prokosch, Hans-Ulrich; Ganslandt, Thomas (Studies in health technology and informatics, 2014)
Data from cancer registries can be used to track the epidemiology of cancer and can potentially serve to guide individual diagnostic and treatment decisions. Even though some cancer registry datasets have been made publicly available for scientific and clinical use, few applications have so far provided direct access to these data from within the patient context of an electronic patient record. The goal of this project was to implement a proof-of-concept integration of the public SEER (Surveillance, Epidemiology and End Results) cancer registry dataset with a digital breast cancer tumor board at a German university hospital and to determine its utility in the clinical settings. The integration was successfully established, using data from routine documentation to provide dynamic visualizations of cohort composition and Kaplan-Meier survival plots. Evaluation feedback was favorable regarding the concept and implementation, but highlighted that important data elements, e.g. receptor status data, were missing in the SEER dataset, limiting clinical value of the system.
EVALuna2:119

Challenges and Experiences Extending the cBioPortal for Cancer Genomics to a Molecular Tumor Board Platform. - Reimer, Niklas; Unberath, Philipp; Busch, Hauke; Börries, Melanie; Metzger, Patrick; Ustjanzew, Arsenij; Renner, Christopher; Prokosch, Hans-Ulrich; Christoph, Jan (Studies in health technology and informatics, 2021)
In Molecular Tumor Boards (MTBs), therapy recommendations for cancer patients are discussed. To aid decision-making based on the patient's molecular profile, the research platform cBioPortal was extended based on users' requirements. Additionally, a comprehensive dockerized workflow was developed to support the deployment of cBioPortal and connected services. In this work, we present the challenges and experiences of nearly two years of implementing and deploying an MTB platform based on cBioPortal and compare those to findings of a previous study.
EVALuna2:512349

Classification of Patient Portals Described in Evaluation Studies Using the TOPCOP Taxonomy - Leb, Ines; Magnin, Selina; Boeker, Martin; Prokosch, Hans-Ulrich; Ammenwerth, Elske; Glöggler, Michael (Healthcare of the Future 2022, 2022)
Many patient portals have been introduced and evaluated in recent years. The results of evaluation studies are difficult to compare, however, as the evaluated patient portal is often not clearly or only incompletely described in the publication. This problem is common to evaluations in health informatics. We evaluated the completeness of descriptions of patient portals in 15 exemplary evaluation publications using the TOPCOP taxonomy. Our results show that core functionalities such as portal design, patient communication, educational features, or system notifications were quite clearly described in all 15 evaluation studies. Other descriptions, such as web accessibility or data management, were often not provided. We conclude that taxonomies such as TOPCOP should be used and even required for describing interventions in evaluation papers.
CRIS-Team Scopus Importer:2022-05-27
Keywords: evaluation; health informatics; information management; Patient portal; taxonomy

Clinical decision support systems in child and adolescent psychiatry: a systematic review - Koposov, Roman; Fossum, Sturla; Frodl, Thomas; Nytrø, Øystein; Leventhal, Bennett; Sourander, Andre; Quaglini, Silvana; Molteni, Massimo; de la Iglesia Vayá, María; Prokosch, Hans-Ulrich; Barbarini, Nicola; Milham, Michael Peter; et al. (European Child & Adolescent Psychiatry, 2017)
Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.
EVALuna2:183

Comparison of electronic health record system functionalities to support the patient recruitment process in clinical trials - Schreiweis, Bjoern; Trinczek, Benjamin; Köpcke, Felix; Leusch, Thomas; Majeed, Raphael W.; Wenk, Joachim; Bergh, Bjoern; Ohmann, Christian; Roehrig, Rainer; Dugas, Martin; Prokosch, Hans-Ulrich (International Journal of Medical Informatics, 2014)
Reusing data from electronic health records for clinical and translational research and especially for patient recruitment has been tackled in a broader manner since about a decade. Most projects found in the literature however focus on standalone systems and proprietary implementations at one particular institution often for only one singular trial and no generic evaluation of EHR systems for their applicability to support the patient recruitment process does yet exist. Thus we sought to assess whether the current generation of EHR systems in Germany provides modules/tools, which can readily be applied for IT-supported patient recruitment scenarios.We first analysed the EHR portfolio implemented at German University Hospitals and then selected 5 sites with five different EHR implementations covering all major commercial systems applied in German University Hospitals. Further, major functionalities required for patient recruitment support have been defined and the five sample EHRs and their standard tools have been compared to the major functionalities.In our analysis of the site's hospital information system environments (with four commercial EHR systems and one self-developed system) we found that - even though no dedicated module for patient recruitment has been provided - most EHR products comprise generic tools such as workflow engines, querying capabilities, report generators and direct SQL-based database access which can be applied as query modules, screening lists and notification components for patient recruitment support. A major limitation of all current EHR products however is that they provide no dedicated data structures and functionalities for implementing and maintaining a local trial registry.At the five sites with standard EHR tools the typical functionalities of the patient recruitment process could be mostly implemented. However, no EHR component is yet directly dedicated to support research requirements such as patient recruitment. We recommend for future developments that EHR customers and vendors focus much more on the provision of dedicated patient recruitment modules.
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Complementing Medical Records with Precalculated Data Items to Facilitate Decision Support and Phenotyping. - Kraus, Stefan; Prokosch, Hans-Ulrich (ICT for Health Science Research, 2019)
The Arden Syntax is a standard for clinical decision support functions in the form of Medical Logic Modules (MLMs). While the data type system of the early versions was limited to flat lists, later versions introduced an object type, supporting complex data structures, even up to entire electronic medical records (EMRs). Such objects are static insofar as their structure cannot be modified at MLM runtime. University Hospital Erlangen uses an experimental Arden Syntax version termed PLAIN, which provides an integrated mapper for arbitrary data structures, including entire EMRs. To facilitate knowledge encoding and reduce MLM complexity, we searched for a way to complement patient records with precalculated data items. We modified the object data type in two ways. The first was to include a statement for the explicit creation of new attributes; the second was to implicitly create an attribute whenever a value is assigned to a previously non-existing attribute. As a proof of concept, we complemented the ventilation section of every accessed EMR with a patient-individual recommendation for the expiratory tidal volume. A means to extend the structure of an object at runtime provides several advantages. The precalculated data items need no longer be calculated by the MLMs themselves, which reduces complexity and facilitates code maintenance. This might be beneficial not only for clinical decision support, but also with respect to the use of Arden Syntax language constructs for phenotyping queries, as well as with respect to the frequently required preprocessing of EMR data.
EVALuna2:209493

Complementing medical records with precalculated data items to facilitate decision support and phenotyping - Kraus, Stefan; Prokosch, Hans-Ulrich (ICT for Health Science Research - Proceedings of the EFMI 2019 Special Topic Conference, 2019)
The Arden Syntax is a standard for clinical decision support functions in the form of Medical Logic Modules (MLMs). While the data type system of the early versions was limited to flat lists, later versions introduced an object type, supporting complex data structures, even up to entire electronic medical records (EMRs). Such objects are static insofar as their structure cannot be modified at MLM runtime. University Hospital Erlangen uses an experimental Arden Syntax version termed PLAIN, which provides an integrated mapper for arbitrary data structures, including entire EMRs. To facilitate knowledge encoding and reduce MLM complexity, we searched for a way to complement patient records with precalculated data items. We modified the object data type in two ways. The first was to include a statement for the explicit creation of new attributes; the second was to implicitly create an attribute whenever a value is assigned to a previously non-existing attribute. As a proof of concept, we complemented the ventilation section of every accessed EMR with a patient-individual recommendation for the expiratory tidal volume. A means to extend the structure of an object at runtime provides several advantages. The precalculated data items need no longer be calculated by the MLMs themselves, which reduces complexity and facilitates code maintenance. This might be beneficial not only for clinical decision support, but also with respect to the use of Arden Syntax language constructs for phenotyping queries, as well as with respect to the frequently required preprocessing of EMR data.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Arden Syntax; Clinical decision support; Electronic medical records

Concept and implementation of a study dashboard module for a continuous monitoring of trial recruitment and documentation - Toddenroth, Dennis; Sivagnanasundaram, Janakan; Prokosch, Hans-Ulrich; Ganslandt, Thomas (Journal of Biomedical Informatics, 2016)
EVALuna2:168
Keywords: Data management for clinical trials; Procedures for maintaining databases; Workflows for data and safety monitoring

Concept to gain trust for a German personal health record system using public cloud and FHIR - Ploner, Nico; Neurath, Markus; Schoenthaler, Martin; Zielke, Andreas; Prokosch, Hans-Ulrich (Journal of Biomedical Informatics, 2019)
Objective: Although a national Personal Health Record (PHR) infrastructure was supposed to have been introduced in Germany by law in 2006 and different providers are entering the market, no system has yet been widely adopted in Germany. There is also little information available on how current technical advancements affect German patients' and physicians' trust in PHR systems. Methods: Supporting scenarios obtained from clinicians, this study proposes a concept for a German PHR system using a public cloud infrastructure, smartphone access and focusing on trust, privacy, and interoperability. In advance to an eventual implementation, a multi-center questionnaire study has been conducted to predict patients' and physicians' intention to use that system and evaluate their trust in different providers of such a system. Results: Our results show that both patients and physicians are highly likely to use the PHR based on the present concept. Trust in healthcare providers exceeds trust in other institutions like private companies, health insurance companies, or even governmental institutions when offering such a PHR system. Conclusions: We recommend the implementation of this PHR system. To maximize patients' and physicians' trust in the system, it should be offered to patients by their healthcare provider. Further evaluation regarding its actual adoption and expected improvement in patient outcome based on the scenarios is advisable.
CRIS-Team Scopus Importer:2019-07-26
Keywords: Electronic medical records; FHIR; Health information exchange; Personal health records

Conceptual Modeling for Prospective Health Technology Assessment - Gantner-Bär, Marion; Djanatliev, Anatoli; Prokosch, Hans-Ulrich; Sedlmayr, Martin (Studies in health technology and informatics, 2012)
Prospective Health Technology Assessment (ProHTA) is a new and innovative approach to analyze and assess new technologies, methods and procedures in health care. Simulation processes are used to model innovations before the cost-intensive design and development phase. Thus effects on patient care, the health care system as well as health economics aspects can be estimated. To generate simulation models a valid information base is necessary and therefore conceptual modeling is most suitable. Project-specifically improved methods and characteristics of simulation modeling are combined in the ProHTA Conceptual Modeling Process and initially implemented for acute ischemic stroke treatment in Germany. Additionally the project aims at simulation of other diseases and health care systems as well. ProHTA is an interdisciplinary research project within the Cluster of Excellence for Medical Technology - Medical Valley European Metropolitan Region Nuremberg (EMN), which is funded by the German Federal Ministry of Education and Research (BMBF), project grant No. 01EX1013B. © 2012 European Federation for Medical Informatics and IOS Press. All rights reserved.
UnivIS-Import:2015-03-09:Pub.2012.tech.IMMD.IMMD7.concep
Keywords: Conceptual model; Conceptual modeling; Health care; Health economics; Ischemic stroke treatment; Prospective health technology assessment; Simulation

Controlling my genome with my smartphone: first clinical experiences of the PROMISE system - Amr, Ali; Hinderer, Marc; Griebel, Lena; Deuber, Dominic; Egger, Christoph; Sedaghat-Hamedani, Farbod; Kayvanpour, Elham; Huhn, Daniel; Haas, Jan; Frese, Karen; Schweig, Marc; Marnau, Ninja; et al. (Clinical Research in Cardiology, 2021)
Background: The development of Precision Medicine strategies requires high-dimensional phenotypic and genomic data, both of which are highly privacy-sensitive data types. Conventional data management systems lack the capabilities to sufficiently handle the expected large quantities of such sensitive data in a secure manner. PROMISE is a genetic data management concept that implements a highly secure platform for data exchange while preserving patient interests, privacy, and autonomy. Methods: The concept of PROMISE to democratize genetic data was developed by an interdisciplinary team. It integrates a sophisticated cryptographic concept that allows only the patient to grant selective access to defined parts of his genetic information with single DNA base-pair resolution cryptography. The PROMISE system was developed for research purposes to evaluate the concept in a pilot study with nineteen cardiomyopathy patients undergoing genotyping, questionnaires, and longitudinal follow-up. Results: The safety of genetic data was very important to 79%, and patients generally regarded the data as highly sensitive. More than half the patients reported that their attitude towards the handling of genetic data has changed after using the PROMISE app for 4 months (median). The patients reported higher confidence in data security and willingness to share their data with commercial third parties, including pharmaceutical companies (increase from 5 to 32%). Conclusion: PROMISE democratizes genomic data by a transparent, secure, and patient-centric approach. This clinical pilot study evaluating a genetic data infrastructure is unique and shows that patient’s acceptance of data sharing can be increased by patient-centric decision-making. Graphic abstract: [Figure not available: see fulltext.]
CRIS-Team Scopus Importer:2021-11-05
Keywords: Big data democratization; Data security; Digital health; Genetic data transfer; Privacy; Whole-genome sequencing

Corrigendum to: “Resistance to antibacterial therapy in pediatric febrile urinary tract infectionsda single-center analysis” [J Pediatr Urol 16 (2020) 71–79] (Journal of Pediatric Urology (2020) 16(1) (71–79), (S1477513119303389), (10.1016/j.jpurol.2019.10.018)) - Raupach, Thomas; Held, Jürgen; Prokosch, Hans-Ulrich; Rascher, Wolfgang; Zierk, Jakob (Journal of Pediatric Urology, 2022)
In order to fulfil the requirements of the doctoral office of the Friedrich-Alexander-University Erlangan-Nuremberg (FAU), the following updates have been made to the abovementioned article: Affiliation ‘a’ now reads as: Department of Pediatrics and Adolescent Medicine, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany. The following has been added to the Acknowledgements: The present work was performed in fulfilment of the requirements for obtaining the degree “Dr. med. (Doctor medicinae) at the Friedrich-Alexander University Erlangen-Nuremberg (FAU)”.
CRIS-Team Scopus Importer:2024-12-16

Creating a Medication Therapy Observational Research Database from an Electronic Medical Record: Challenges and Data Curation - Rödle, Wolfgang; Prokosch, Hans-Ulrich; Neumann, Eva; Toni, Irmgard; Haering-Zahn, Julia; Neubert, Antje; Eberl, Sonja (Applied Clinical Informatics, 2024)
Background: Observational research has shown its potential to complement experimental research and clinical trials by secondary use of treatment data from hospital care processes. It can also be applied to better understand pediatric drug utilization for establishing safer drug therapy. Clinical documentation processes often limit data quality in pediatric medical records requiring data curation steps, which are mostly underestimated. Objectives: The objectives of this study were to transform and curate data from a departmental electronic medical record into an observational research database. We particularly aim at identifying data quality problems, illustrating reasons for such problems and describing the systematic data curation process established to create high-quality data for observational research. Methods: Data were extracted from an electronic medical record used by four wards of a German university children's hospital from April 2012 to June 2020. A four-step data preparation, mapping, and curation process was established. Data quality of the generated dataset was firstly assessed following an established 3 × 3 Data Quality Assessment guideline and secondly by comparing a sample subset of the database with an existing gold standard. Results: The generated dataset consists of 770,158 medication dispensations associated with 89,955 different drug exposures from 21,285 clinical encounters. A total of 6,840 different narrative drug therapy descriptions were mapped to 1,139 standard terms for drug exposures. Regarding the quality criterion correctness, the database was consistent and had overall a high agreement with our gold standard. Conclusion: Despite large amounts of freetext descriptions and contextual knowledge implicitly included in the electronic medical record, we were able to identify relevant data quality issues and to establish a semi-automated data curation process leading to a high-quality observational research database. Because of inconsistent dosage information in the original documentation this database is limited to a drug utilization database without detailed dosage information.
CRIS-Team Scopus Importer:2024-02-23
Keywords: data curation; Data Quality Assessment; electronic medical records; medication data; pediatrics

Das Internet als Informationsquelle für pflegende Angehörige eines Demenzpatienten - Grässel, Elmar; Bleich, Stefan; Meyer-Wegener, Klaus; Schmidt, Ute; Kornhuber, Johannes; Prokosch, Hans-Ulrich (Psychiatrische Praxis, 2009)
Objective: What significance has the Internet as a source of information for family caregivers of dementia patients? Methods: In Middle Franconia (Germany), 391 family caregivers were requested to participate in a questionnaire-based postal survey about the significance of the Internet and other sources of information on dementia. The family caregivers in question were the relatives of patients of the Memory Clinic at Erlangen University Psychiatric Hospital, members of the Alzheimer's Society of Middle Franconia or the Nuremberg Family Counselling Society. Results: Younger and better-educated family caregivers more often own a computer with Internet access than older ones. The Internet is in 4th place on their list of sources of information. Although doctors are by far the most important source, counselling centres and literature are rated only just before the Internet. Conclusions: The Internet is particularly significant for the younger better-educated family caregivers, independent of gender, as a source of information on the diagnosis and treatment of dementia. © Georg Thieme Verlag KG Stuttgart.
UnivIS-Import:2015-03-09:Pub.2009.tech.IMMD.IMMD6.dasint
Keywords: Dementia; Family caregivers; Internet use; Sources of information

Data Model Requirements for a Digital Cognitive Aid for Anesthesia to Support Intraoperative Crisis Management - Schild, Stefanie; Gründner, Julian; Gulden, Christian; Prokosch, Hans-Ulrich; St. Pierre, Michael; Sedlmayr, Martin (Applied Clinical Informatics, 2020)
OBJECTIVE: The aim of this study is to define data model requirements supporting the development of a digital cognitive aid (CA) for intraoperative crisis management in anesthesia, including medical emergency text modules (text elements) and branches or loops within emergency instructions (control structures) as well as their properties, data types, and value ranges. METHODS: The analysis process comprised three steps: reviewing the structure of paper-based CAs to identify common text elements and control structures, identifying requirements derived from content, design, and purpose of a digital CA, and validating requirements by loading exemplary emergency checklist data into the resulting prototype data model. RESULTS: The analysis of paper-based CAs identified 19 general text elements and two control structures. Aggregating these elements and analyzing the content, design and purpose of a digital CA revealed 20 relevant data model requirements. These included checklist tags to enable different search options, structured checklist action steps (items) in groups and subgroups, and additional information on each item. Checklist and Item were identified as two main classes of the prototype data model. A data object built according to this model was successfully integrated into a digital CA prototype. CONCLUSION: To enable consistent design and interactivity with the content, presentation of critical medical information in a digital CA for crisis management requires a uniform structure. So far it has not been investigated which requirements need to be met by a data model for this purpose. The results of this study define the requirements and structure that enable the presentation of critical medical information. Further research is needed to develop a comprehensive data model for a digital CA for crisis management in anesthesia, including supplementation of requirements resulting from simulation studies and feasibility analyses regarding existing data models. This model may also be a useful template for developing data models for CAs in other medical domains.
CRIS-Team Scopus Importer:2020-03-27

Design and Implementation of a Single Source Multipurpose Hospital-Wide Clinical Trial Registry - Sommer, Marcus; Kirchner, Melanie; Gulden, Christian; Egloffstein, Sainab; Lux, Michael P.; Beckmann, Matthias; Mackensen, Andreas; Prokosch, Hans-Ulrich (ICT FOR HEALTH SCIENCE RESEARCH, 2019)
CRIS-Team WoS Importer:2021-10-18

Design and Implementation of a Single Source Multipurpose Hospital-Wide Clinical Trial Registry - Sommer, Marcus; Kirchner, Melanie; Gulden, Christian; Egloffstein, Sainab; Lux, Michael P.; Beckmann, Matthias; Mackensen, Andreas; Prokosch, Hans-Ulrich (Studies in health technology and informatics, 2019)
IT-supported patient recruitment, serious adverse event reporting as well as making information about clinical trials accessible to the public on websites, are still major challenges in clinical trials. Too often the distribution of information about trials being performed within a hospital across numerous institutions and IT systems is a barrier to provide efficient IT support for such scenarios. Thus, the essential prerequisite to mastering those challenges is to achieve one single point of truth with adequate, complete, accurate and up-to-date information about all clinical trials running at a hospital. We describe the design and implementation of such a single source clinical trial registry serving multiple purposes at a university hospital.
CRIS-Team Scopus Importer:2019-05-02
Keywords: Clinical trials as topic; electronic health record; registries

Design and Implementation of a Single Source Multipurpose Hospital-Wide Clinical Trial Registry. - Sommer, Marcus; Kirchner, Melanie; Gulden, Christian; Egloffstein, Sainab; Lux, Michael P.; Beckmann, Matthias; Mackensen, Andreas; Prokosch, Hans-Ulrich (Studies in health technology and informatics, 2019)
IT-supported patient recruitment, serious adverse event reporting as well as making information about clinical trials accessible to the public on websites, are still major challenges in clinical trials. Too often the distribution of information about trials being performed within a hospital across numerous institutions and IT systems is a barrier to provide efficient IT support for such scenarios. Thus, the essential prerequisite to mastering those challenges is to achieve one single point of truth with adequate, complete, accurate and up-to-date information about all clinical trials running at a hospital. We describe the design and implementation of such a single source clinical trial registry serving multiple purposes at a university hospital.
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Designing a Framework of Components to Support Patient Engagement in Research - Öfelein, Matthias; Reichold, Michael; Maier, Christian; Prokosch, Hans-Ulrich (German Medical Data Sciences: Shaping Change – Creative Solutions for Innovative Medicine, 2019)
In the context of the German Medical Informatics Initiative (MII), where data reuse and data sharing are major goals, cross-site, long-term research on patient care data can only be conducted lawfully with informed patient consent. Thus, the MII consent working group developed a template form for patient information and broad consent based on work that has been done for a former biobank project. The broad consent enables the patient to consent to the use of a wide range of the documented data including research purposes. Therefore, a user-friendly tool is needed which not only supports the storage and maintenance of the patient's consents but also allows him to easily review or withdraw his consents. Furthermore, the tool should allow the patient to review the use of his data in research projects and possible publications. This is why we developed a concept of how such a tool could be integrated into the clinical and research system landscape and implemented a prototype as a proof of concept.
CRIS-Team Scopus Importer:2019-09-24
Keywords: Consent Management; Data Sharing; Informed Consent; Patient Participation

Designing and Implementing an IT Architecture for a Digital Multicenter Dementia Registry: DigiDEM Bayern - Reichold, Michael; Dietzel, Nikolas; Chmelirsch, Christina; Kolominsky-Rabas, Peter; Grässel, Elmar; Prokosch, Hans-Ulrich (Applied Clinical Informatics, 2021)
Background Registries are an essential research tool to investigate the long-term course of diseases and their impact on the affected. The project digiDEM Bayern will set up a prospective dementia registry to collect long-term data of people with dementia and their caregivers in Bavaria (Germany) supported by more than 300 research partners. Objective The objective of this article is to outline an information technology (IT) architecture for the integration of a registry and comprehensive participant management in a dementia study. Measures to ensure high data quality, study governance, along with data privacy, and security are to be included in the architecture. Methods The architecture was developed based on an iterative, stakeholder-oriented process. The development was inspired by the Twin Peaks Model that focuses on the codevelopment of requirements and architecture. We gradually moved from a general to a detailed understanding of both the requirements and design through a series of iterations. The experience learned from the pilot phase was integrated into a further iterative process of continuous improvement of the architecture. Results The infrastructure provides a standardized workflow to support the electronic data collection and trace each participant's study process. Therefore, the implementation consists of three systems: (1) electronic data capture system for Web-based or offline app-based data collection; (2) participant management system for the administration of the identity data of participants and research partners as well as of the overall study governance process; and (3) videoconferencing software for conducting interviews online. First experiences in the pilot phase have proven the feasibility of the framework. Conclusion This article outlines an IT architecture to integrate a registry and participant management in a dementia research project. The framework was discussed and developed with the involvement of numerous stakeholders. Due to its adaptability of used software systems, a transfer to other projects should be easily possible.
CRIS-Team Scopus Importer:2021-06-25
Keywords: data collection; dementia; participant management; registries; research planning and conduct; workflow

Design of an interactive web application for teaching uncertainty interpretations of clinical tests - Neher, Sebastian; Kapsner, Lorenz; Prokosch, Hans-Ulrich; Toddenroth, Dennis (Studies in Health Technology and Informatics, 2021)
Background: Assessing the uncertainty of diagnostic findings is essential for advising patients. Previous research has demonstrated the difficulty of computing the expected correctness of positive or negative results, although clinical decision support (CDS) tools promise to facilitate adequate interpretations. Objectives: To teach the potential utility of CDS tools to medical students, we designed an interactive software module that computes and visualizes relevant probabilities from typical inputs. Methods: We reviewed the literature on recommended graphical approaches and decided to support contingency tables, plain table formats, tree diagrams, and icon arrays. Results: We implemented these functions in a single-page web application, which was configured to complement our local learning management system where students also access interpretation tasks. Conclusion: Our technical choices promoted a rapid implementation. We intend to explore the utility of the tool during some upcoming courses. Future developments could also model a more complex clinical reality where the likelihood of alternative diagnoses is estimated from sets of clinical investigations.
CRIS-Team Scopus Importer:2021-10-22
Keywords: Bayes Theorem; Clinical Decision Support; Medical Education

Developing New Analysis Functions for a Translational Research Platform: Extending the cBioPortal for Cancer Genomics. - Unberath, Philipp; Knell, Christian; Prokosch, Hans-Ulrich; Christoph, Jan (ICT for Health Science Research, 2019)
BACKGROUND: The cBioPortal is a prevalent open-source translational research platform, allowing private instances and extensions. OBJECTIVE: Our aim was to build up an own instance of cBioPortal, identify missing functionality by interviewing researchers, and implementing these extensions. METHODS: We examined the code base of the cBioPortal and conducted a requirements analysis with researchers. Then an own extension was implemented and a usability evaluation was performed. RESULTS: We developed a new tab in the results view of cBioPortal adding the option to analyze the correlation of gene expression and mutation patterns. CONCLUSION: While extending the cBioPortal is possible, there are still some challenges to overcome. A plug-in concept and a more detailed documentation would greatly facilitate the development of own extensions.
EVALuna2:209492

Developing new analysis functions for a translational research platform: Extending the cBioPortal for cancer genomics - Unberath, Philipp; Knell, Christian; Prokosch, Hans-Ulrich; Christoph, Jan (Proceedings of the EFMI 2019 Special Topic Conference, 2019)
Background: The cBioPortal is a prevalent open-source translational research platform, allowing private instances and extensions. Objective: Our aim was to build up an own instance of cBioPortal, identify missing functionality by interviewing researchers, and implementing these extensions. Methods: We examined the code base of the cBioPortal and conducted a requirements analysis with researchers. Then an own extension was implemented and a usability evaluation was performed. Results: We developed a new tab in the results view of cBioPortal adding the option to analyze the correlation of gene expression and mutation patterns. Conclusion: While extending the cBioPortal is possible, there are still some challenges to overcome. A plug-in concept and a more detailed documentation would greatly facilitate the development of own extensions.
CRIS-Team Scopus Importer:2019-05-09
Keywords: cBioPortal; Genomics; MI-I; MIRACUM; Translational research

Development and Evaluation of a Web-Based Paediatric Drug Information System for Germany - Zahn, Julia; Wimmer, Stefan; Rödle, Wolfgang; Toni, Irmgard; Sedlmayr, Brita; Prokosch, Hans-Ulrich; Rascher, Wolfgang; Neubert, Antje (Pharmacy, 2021)
Background: Off-label use is frequent in paediatrics but that does not necessarily mean that the risk-benefit ratio is negative. Nevertheless, evidence-based data is essential for safe drug therapy. In Germany, there is no publicly available compendium providing transparent, evidence-based information for paediatric pharmacotherapy to date. This work describes the development of a web-based paediatric drug information system (PDIS) for Germany and its evaluation by health care professionals (HCP). Methods: Since 2012, a PDIS is being developed by the authors and is supported by the Federal Ministry of Health since 2016. Dosing recommendations were established based on systematic literature reviews and subsequent evaluation by clinical experts. The prototype was evaluated by HCP. Based on the results, the further development was concluded. Results: 92% of HCP believed that the PDIS could improve the quality of prescribing, as currently available information is deficient. Besides the license and formulations, dosing recommendations were the most relevant modules. A dosage calculator was the most wanted improvement. To facilitate sustainability of future development, a collaboration with the Dutch Kinderformularium was established. As of 2021, the database will be available to German HCP. Conclusion: The fundamentals for a German PDIS were established, and vital steps were taken towards successful continuation.
CRIS-Team WoS Importer:2021-04-16

Development and Usability Analysis of a Multimedia eConsent Solution - Schneiderheinze, Hauke; Prokosch, Hans-Ulrich; Apel, Hendrik; Bellut, Laura; Wullich, Bernd; Trollmann, Regina; Schüttler, Christina (German Medical Data Sciences: Shaping Change – Creative Solutions for Innovative Medicine, 2019)
BACKGROUND: More and more medical data is being stored digitally in routine care. The secondary use of patient data is only possible to a limited extent for data protection reasons. In order to enable a long-term and far-reaching use of secondary data, a possible approach is to obtain "broad consent" from patients, e.g. on research projects whose purpose is still unknown at the time of consent. OBJECTIVE: To develop and evaluate an interactive eConsent prototype that presents the extensive contents of the "broad consent" in multimedia form for the purpose of a successful and resource-efficient information and consent process. METHODS: The eConsent prototype was designed on basis of a literature review and in accordance with the goals of the German medical informatics initiative. User tests and subsequent questionnaire surveys using the System Usability Scale (SUS) were carried out with patients from a university hospital to assess the prototype's usability. The study was conducted in a quasi-experimental, one-group posttest-only design. RESULTS: The created interactive prototype can present the contents acoustically and visually and offers the possibility to retrieve additional information. With a SUS score of 84,1/100 the results indicate a very good usability of the prototype. CONCLUSION: The next steps will include further refinements of the prototype based on the feedback received and a subsequent study with a broader user group aimed at introducing an eConsent tool as part of a patient portal.
CRIS-Team Scopus Importer:2019-09-24
Keywords: Informed consent; multimedia; patient participation; patient portals

Development of a SNOMED CT Mapping Process and Tool at a Data Integration Centre - Lessons Learned - Riedel, Andrea; Deppenwiese, Noemi; Thiele, Lucas; Prokosch, Hans-Ulrich; Herzog, Annalena (Studies in Health Technology and Informatics, 2024)
Introduction 16 million German-language free-text laboratory test results are the basis of the daily diagnostic routine of 17 laboratories within the University Hospital Erlangen. As part of the Medical Informatics Initiative, the local data integration centre is responsible for the accessibility of routine care data for medical research. Following the core data set, international interoperability standards such as FHIR and the English-language medical terminology SNOMED CT are used to create harmonised data. To represent each non-numeric laboratory test result within the base module profile ObservationLab, the need for a map and supporting tooling arose. State of the Art Due to the requirement of a n:n map and a data safety-compliant local instance, publicly available tools (e.g., SNAP2SNOMED) were insufficient. Concept and Implementation Therefore, we developed (1) an incremental mapping-validation process with different iteration cycles and (2) a customised mapping tool via Microsoft Access. Time, labour, and cost efficiency played a decisive role. First iterations were used to define requirements (e.g., multiple user access). Lessons Learned The successful process and tool implementation and the described lessons learned (e.g., cheat sheet) will assist other German hospitals in creating local maps for inter-consortia data exchange and research. In the future, qualitative and quantitative analysis results will be published.
CRIS-Team Scopus Importer:2024-10-25
Keywords: Clinical Laboratory Information Systems; Data Curation; Health Information Interoperability; Systematized Nomenclature of Medicine; Terminology as Topic

Development of a Standardized Rating Tool for Drug Alerts to Reduce Information Overload - Pfistermeister, Barbara; Sedlmayr, Brita; Patapovas, Andrius; Suttner, Gerald; Tektas, Ozan; Tarkhov, Aleksey; Kornhuber, Johannes; Fromm, Martin; Buerkle, Thomas; Prokosch, Hans-Ulrich; Maas, Renke (Methods of Information in Medicine, 2016)
A well-known problem in current clinical decision support systems (CDSS) is the high number of alerts, which are often medically incorrect or irrelevant. This may lead to the so-called alert fatigue, an overriding of alerts, including those that are clinically relevant, and underuse of CDSS in general.The aim of our study was to develop and to apply a standardized tool that allows its users to evaluate the quality of system-generated drug alerts. The users' ratings can subsequently be used to derive recommendations for developing a filter function to reduce irrelevant alerts.We developed a rating tool for drug alerts and performed a web-based evaluation study that also included a user review of alerts. In this study the following categories were evaluated: "data linked correctly", "medically correct", "action required", "medication change", "critical alert", "information gained" and "show again". For this purpose, 20 anonymized clinical cases were randomly selected and displayed in our customized CDSS research prototype, which used the summary of product characteristics (SPC) for alert generation. All the alerts that were provided were evaluated by 13 physicians. The users' ratings were used to derive a filtering algorithm to reduce overalerting.In total, our CDSS research prototype generated 399 alerts. In 98 % of all alerts, medication data were rated as linked correctly to drug information; in 93 %, the alerts were assessed as "medically correct"; 19.5 % of all alerts were rated as "show again". The interrater-agreement was, on average, 68.4 %. After the application of our filtering algorithm, the rate of alerts that should be shown again decreased to 14.8 %.The new standardized rating tool supports a standardized feedback of user-perceived clinical relevance of CDSS alerts. Overall, the results indicated that physicians may consider the majority of alerts formally correct but clinically irrelevant and override them. Filtering may help to reduce overalerting and increase the specificity of a CDSS.
EVALuna2:172

Die digitalen Fortschrittshubs Gesundheit – Gemeinsame Datennutzung über die Universitätsmedizin hinaus - Krefting, Dagmar; Bavendiek, Udo; Fischer, Joachim; Marx, Gernot; Molinnus, Denise; Panholzer, Torsten; Prokosch, Hans-Ulrich; Leb, Ines; Weidner, Jens; Sedlmayr, Martin (Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2024)
The digital health progress hubs pilot the extensibility of the concepts and solutions of the Medical Informatics Initiative to improve regional healthcare and research. The six funded projects address different diseases, areas in regional healthcare, and methods of cross-institutional data linking and use. Despite the diversity of the scenarios and regional conditions, the technical, regulatory, and organizational challenges and barriers that the progress hubs encounter in the actual implementation of the solutions are often similar. This results in some common approaches to solutions, but also in political demands that go beyond the Health Data Utilization Act, which is considered a welcome improvement by the progress hubs. In this article, we present the digital progress hubs and discuss achievements, challenges, and approaches to solutions that enable the shared use of data from university hospitals and non-academic institutions in the healthcare system and can make a sustainable contribution to improving medical care and research.
CRIS-Team Scopus Importer:2024-06-21
Keywords: Data integration; Digitalization; Interoperability; Intersectoral healthcare; Medicine; Patient journey

Die Medizininformatik-Initiative im Überblick – Aufbau einer Gesundheitsforschungsdateninfrastruktur in Deutschland - Semler, Sebastian C.; Boeker, Martin; Eils, Roland; Krefting, Dagmar; Loeffler, Markus; Bussmann, Jens; Wissing, Frank; Prokosch, Hans-Ulrich (Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2024)
The Medical Informatics Initiative (MII) funded by the Federal Ministry of Education and Research (BMBF) 2016–2027 is successfully laying the foundations for data-based medicine in Germany. As part of this funding, 51 new professorships, 21 junior research groups, and various new degree programs have been established to strengthen teaching, training, and continuing education in the field of medical informatics and to improve expertise in medical data sciences. A joint decentralized federated research data infrastructure encompassing the entire university medical center and its partners was created in the form of data integration centers (DIC) at all locations and the German Portal for Medical Research Data (FDPG) as a central access point. A modular core dataset (KDS) was defined and implemented for the secondary use of patient treatment data with consistent use of international standards (e.g., FHIR, SNOMED CT, and LOINC). An officially approved nationwide broad consent was introduced as the legal basis. The first data exports and data use projects have been carried out, embedded in an overarching usage policy and standardized contractual regulations. The further development of the MII health research data infrastructures within the cooperative framework of the Network of University Medicine (NUM) offers an excellent starting point for a German contribution to the upcoming European Health Data Space (EHDS), which opens opportunities for Germany as a medical research location.
CRIS-Team Scopus Importer:2024-06-14
Keywords: Data use and access; Medical informatics; Research data infrastructure; Secondary use of health data; Standardization

Digital Dementia Registry Bavaria - DigiDEM Bayern: Study protocol for a multicentre, prospective, longitudinal register study - Dietzel, Nikolas; Kürten, Lara; Karrer, Linda; Reichold, Michael; Köhler, Laura; Nagel, Andreas; Chmelirsch, Christina; Seebahn, Kathrin; Hladik, Markus; Meuer, Sebastian; Kirchner, Anna; Holm, Kristina; et al. (BMJ Open, 2021)
Introduction Dementia is one of the most relevant widespread diseases, with a prevalence of currently 50 million people with dementia worldwide. The care of people with dementia will be one of the major challenges for healthcare systems worldwide. Digitalisation offers new possibilities to improve both dementia healthcare and health outcomes research as a fundament for national healthcare planning. The a € Digital Dementia Registry Bavaria - digiDEM Bayern' aims to improve the understanding of the complexity and long-term progression of dementia and the current care situation in Bavaria. Moreover, by offering digital services, digiDEM will actively contribute to improving the care situation in Bavaria. Methods and analysis digiDEM will recruit people with dementia and their family caregivers in all administrative regions of Bavaria. All participants will undergo dementia screening prior to study inclusion in order to identify people with mild cognitive impairment and mild-to-moderate dementia. Participants will be followed up over a period of three years. Sociodemographic data, type of dementia, symptoms, diagnosis, cognitive trajectories, activities of daily living, behavioural and psychological symptoms, falls, resource utilisation, caregiver burden, quality of life, needs of people with dementia and their caregivers, mobility, use of media and sources of information will be assessed. The project will implement a digital web-based platform for data collection. Data will be collected by means of standardised online or face-to-face interviews. Ethics and dissemination The study obtained ethical approval from the Ethics Committee of the Medical Faculty of Friedrich-Alexander-University Erlangen-Nürnberg (FAU) (application number: 253_20 B). Findings will be used for evidence-based decision-making for health decision-makers in order to optimise dementia healthcare in the state of Bavaria. Specific analyses will be conducted for the participating research partners. Results of the study will be published in peer-reviewed journals.
CRIS-Team Scopus Importer:2021-02-26
Keywords: dementia; neurology; public health

Digital patient communication: Improving the hospital-patient relationship - Prokosch, Hans-Ulrich; Schüttler, Christina; Schraudt, Michaela; Öfelein, Matthias; Maier, Christian (Healthcare of the Future - Bridging the Information Gap, 2019)
Digitally engaging patients in their care processes was for many years limited to sharing care related documents (e.g. laboratory or radiology findings, discharge letters) with them through personal electronic health records. Newer concepts have led to the establishment of patient portals as patient frontends to a hospital´s electronic health record. Rarely however have complete patient pathways with pre-hospitalization, inpatient stay and post-hospitalization been evaluated to identify chains of communication processes involving clinical care scenarios, as well as subsequent home monitoring scenarios. Neither have such approaches been integrated with digital communication processes related to a patient´s engagement in medical research projects. In order to enhance hospital-patient relationships in a holistic manner, we hypothesize that an integrated environment (e.g. patient portal) supporting shared decision making and communication in a patient´s care situation and in the same time providing communication processes for patient research engagement will optimize the patient-hospital relationship and be supportive in binding a patient to this care providing institution.
CRIS-Team Scopus Importer:2019-05-02
Keywords: Digital patient communication; Electronic patient portal

Digital Patient Communication: Improving the Hospital-Patient Relationship. - Prokosch, Hans-Ulrich; Schüttler, Christina; Schraudt, Michaela; Öfelein, Matthias; Maier, Christian (Studies in health technology and informatics, 2019)
Digitally engaging patients in their care processes was for many years limited to sharing care related documents (e.g. laboratory or radiology findings, discharge letters) with them through personal electronic health records. Newer concepts have led to the establishment of patient portals as patient frontends to a hospitalś electronic health record. Rarely however have complete patient pathways with pre-hospitalization, inpatient stay and post-hospitalization been evaluated to identify chains of communication processes involving clinical care scenarios, as well as subsequent home monitoring scenarios. Neither have such approaches been integrated with digital communication processes related to a patientś engagement in medical research projects. In order to enhance hospital-patient relationships in a holistic manner, we hypothesize that an integrated environment (e.g. patient portal) supporting shared decision making and communication in a patient´s care situation and in the same time providing communication processes for patient research engagement will optimize the patient-hospital relationship and be supportive in binding a patient to this care providing institution.
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Digital screening tool for the assessment of cognitive impairment in unsupervised setting - DigiDEM-SCREEN: Study protocol for a validation study - Zeiler, Michael; Dietzel, Nikolas; Kammerer, Klaus; Frick, Ulrich; Pryss, Rüdiger; Heuschmann, Peter; Prokosch, Hans-Ulrich; Grässel, Elmar; Kolominsky-Rabas, Peter (BMJ Open, 2025)
Introduction Dementia is one of the most relevant widespread diseases, with a prevalence of currently 55 million people with dementia worldwide. However, about 60-75% of people with dementia have not yet received a formal diagnosis. Asymptomatic screening of cognitive impairments using neuropsychiatric tests has been proven to efficiently enhance diagnosis rates. Digital screening tools, in particular, provide the advantage of being accessible without spatial or time restrictions. The study aims to validate a digital cognitive screening test (digiDEM-SCREEN) as an app in the German language. Methods and analysis This is a multicentre study in Bavaria. Participants are people with mild cognitive impairment, people with dementia in an early stage and cognitively healthy people. Recruitment will take place in specialised diagnostic facilities (memory outpatient clinics). 135 participants are aimed based on a power analysis. Sociodemographic data, diagnosis and results of neuropsychiatric tests (Consortium to Establish a Registry for Alzheimer's Disease, Montreal Cognitive Assessment, digiDEM-SCREEN) will be collected at one point per person via electronic data capturing. The sensitivity, specificity and corresponding cut-off values will be determined based on receiver-operating-characteristic curves. The correlation of the digiDEM-SCREEN test with existing cognitive screening/testing procedures will be analysed. Ethics and dissemination The study obtained ethical approval from the Ethics Committee of the Julius-Maximilians-Universität of Würzburg (JMU) (application number: 177/23-sc). The test will give feedback about the current cognitive status and possible cognitive impairments that should lead to the users seeking further diagnostic measures by medical professionals. It will be accessible free of charge in established app stores. The results of the validation study will be published in peer-reviewed journals.
CRIS-Team Scopus Importer:2025-01-31
Keywords: Chronic Disease; Cognition; Dementia; eHealth; GERIATRIC MEDICINE

Does Voluntary Work Contribute to Cognitive Performance? – An International Systematic Review - Keefer, Anne; Steichele, Kathrin; Grässel, Elmar; Prokosch, Hans-Ulrich; Kolominsky-Rabas, Peter (Journal of Multidisciplinary Healthcare, 2023)
Introduction: There is a need for knowledge on activities that can reduce cognitive decline and dementia risk. Volunteering is a productive activity that entails social, physical, and cognitive functions. Therefore, volunteering could be a protective factor for cognitive loss. Thus, this review aims to examine the associations between volunteering and volunteers’ cognition and to identify influencing variables. Methods: Six international literature databases were searched for relevant articles published between 2017 and 2021 (ALOIS, CENTRAL, CINAL, Embase, PsycINFO, PubMed). Quantitative studies of all study designs were included. The primary outcome was the volunteers’ cognition measured by objective, internationally established psychometric function tests. Two authors independently assessed the eligibility and quality of the studies. A narrative synthesis was performed using all studies included in this review. The methodology was in line with the PRISMA guidelines. Results: Fourteen studies met the inclusion criteria and were included. Seven of the included studies confirmed that volunteering positively affects the volunteers’ cognitive function. Two other studies identified an association between volunteer activity and volunteers’ cognition using cross-sectional measurements. In particular, women and people with a low level of education benefit from the positive effects and associations. The study quality of the included articles was moderate to weak. Discussion: Our review suggests that volunteering can improve volunteers’ cognition. Unfortunately, little attention is given to specific volunteer activities and the frequency of engagement. Additionally, more attention is needed on various risk factors of cognitive impairment.
CRIS-Team Scopus Importer:2023-05-26
Keywords: cognitive health; dementia prevention; health promotion; social engagement

D@tenflut: Fünf Vorträge.Erlanger Universitätstage Amberg/Ansbach 2016 - Freiburg, Rudolf; Büttner, Sebastian; Glasze, Georg; Meyer-Wegener, Klaus; Prokosch, Hans-Ulrich (FAU University Press, 2017)
The volume analyses the manifold changes caused by digitalisation. The volume presents an introduction and five studies of the impact of digitalisation on the fields of sociology, geography, media studies, medicine and computer scienc
Keywords: Big data; psychology; hermeneutics; internet bubble; sociology; geography; medicine; wearables; computer science

Effectiveness of IT-supported patient recruitment: study protocol for an interrupted time series study at ten German university hospitals - Boeker, Martin; Zöller, Daniela; Blasini, Romina; Macho, Philipp; Helfer, Sven; Behrens, Max; Prokosch, Hans-Ulrich; Gulden, Christian (Trials, 2024)
Background: As part of the German Medical Informatics Initiative, the MIRACUM project establishes data integration centers across ten German university hospitals. The embedded MIRACUM Use Case “Alerting in Care - IT Support for Patient Recruitment”, aims to support the recruitment into clinical trials by automatically querying the repositories for patients satisfying eligibility criteria and presenting them as screening candidates. The objective of this study is to investigate whether the developed recruitment tool has a positive effect on study recruitment within a multi-center environment by increasing the number of participants. Its secondary objective is the measurement of organizational burden and user satisfaction of the provided IT solution. Methods: The study uses an Interrupted Time Series Design with a duration of 15 months. All trials start in the control phase of randomized length with regular recruitment and change to the intervention phase with additional IT support. The intervention consists of the application of a recruitment-support system which uses patient data collected in general care for screening according to specific criteria. The inclusion and exclusion criteria of all selected trials are translated into a machine-readable format using the OHDSI ATLAS tool. All patient data from the data integration centers is regularly checked against these criteria. The primary outcome is the number of participants recruited per trial and week standardized by the targeted number of participants per week and the expected recruitment duration of the specific trial. Secondary outcomes are usability, usefulness, and efficacy of the recruitment support. Sample size calculation based on simple parallel group assumption can demonstrate an effect size of d=0.57 on a significance level of 5% and a power of 80% with a total number of 100 trials (10 per site). Data describing the included trials and the recruitment process is collected at each site. The primary analysis will be conducted using linear mixed models with the actual recruitment number per week and trial standardized by the expected recruitment number per week and trial as the dependent variable. Discussion: The application of an IT-supported recruitment solution developed in the MIRACUM consortium leads to an increased number of recruited participants in studies at German university hospitals. It supports employees engaged in the recruitment of trial participants and is easy to integrate in their daily work.
CRIS-Team Scopus Importer:2024-03-01
Keywords: Clinical trial; Clinical trial recruitment support; Hospital information system; Patient recruitment

Effects of staff training and electronic event monitoring on long-term adherence to lung-protective ventilation recommendations - Castellanos, Ixchel; Martin, Marcus; Kraus, Stefan; Bürkle, Thomas; Prokosch, Hans-Ulrich; Schüttler, Jürgen; Toddenroth, Dennis (Journal of Critical Care, 2017)
To investigate long-term effects of staff training and electronic clinical decision support (CDS) on adherence to lung-protective ventilation recommendations.In 2012, group instructions and workshops at two surgical intensive care units (ICUs) started, focusing on standardized protocols for mechanical ventilation and volutrauma prevention. Subsequently implemented CDS functions continuously monitor ventilation parameters, and from 2015 triggered graphical notifications when tidal volume (VT) violated individual thresholds. To estimate the effects of these educational and technical interventions, we retrospectively analyzed nine years of VT records from routine care. As outcome measures, we calculated relative frequencies of settings that conform to recommendations, case-specific mean excess VT, and total ICU survival.Assessing 571,478 VT records from 10,241 ICU cases indicated that adherence during pressure-controlled ventilation improved significantly after both interventions; the share of conforming VT records increased from 61.6% to 83.0% and then 86.0%. Despite increasing case severity, ICU survival remained nearly constant over time.Staff training effectively improves adherence to lung-protective ventilation strategies. The observed CDS effect seemed less pronounced, although it can easily be adapted to new recommendations. Both interventions, which futures studies could deploy in combination, promise to improve the precision of mechanical ventilation.
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EHealth Interventions for Dementia Using WordPress Plugins as a Flexible Dissemination for Dementia Service Providers - Reichold, Michael; Selau, Marina; Grässel, Elmar; Kolominsky-Rabas, Peter; Prokosch, Hans-Ulrich (Studies in Health Technology and Informatics, 2021)
The benefits of eHealth interventions for people with dementia and their informal caregivers have been demonstrated in several studies. In times of contact restrictions, digital solutions have become increasingly important, especially for people with dementia and their mostly elderly caregiving relatives, which are at increased risk of severe illness from COVID-19. As in many other health areas, there is a lack of digital interventions in the dementia landscape that are successfully implemented (i.e., put into practice), especially digital interventions that are scientifically evaluated. Evaluated and proven effective digital interventions exist, but these often do not find their way from research into practice and stay on low-level implementation readiness. Within the project digiDEM Bayern, a digital platform with digital services and interventions for people affected by dementia (people with dementia, caregivers, volunteers and interested citizens) is established. As one digital intervention for informal caregivers, the Angehörigenampel (caregivers' traffic-light) was developed, which is able to assess the physical and psychological burden of caregivers. This can help to counteract the health effects of caregiving burden early on before it is too late. The development of the digital intervention as a WordPress-plugin was kept generic so that it can easily be adapted to other languages on further websites. The intervention as a plugin' approach demonstrates an easy and flexible way of deploying eHealth interventions to other service providers, especially from other countries. The implementation barriers for other service providers are low enough for them to be able to easily integrate the eHealth intervention on their website, enabling more caregivers to benefit from the disseminated eHealth intervention.
CRIS-Team Scopus Importer:2021-06-04

EHR-Independent Predictive Decision Support Architecture Based on OMOP - Unberath, Philipp; Prokosch, Hans-Ulrich; Gründner, Julian; Erpenbeck, Marcel; Maier, Christian; Christoph, Jan (Applied Clinical Informatics, 2020)
BACKGROUND: The increasing availability of molecular and clinical data of cancer patients combined with novel machine learning techniques has the potential to enhance clinical decision support, example, for assessing a patient's relapse risk. While these prediction models often produce promising results, a deployment in clinical settings is rarely pursued. OBJECTIVES: In this study, we demonstrate how prediction tools can be integrated generically into a clinical setting and provide an exemplary use case for predicting relapse risk in melanoma patients. METHODS: To make the decision support architecture independent of the electronic health record (EHR) and transferable to different hospital environments, it was based on the widely used Observational Medical Outcomes Partnership (OMOP) common data model (CDM) rather than on a proprietary EHR data structure. The usability of our exemplary implementation was evaluated by means of conducting user interviews including the thinking-aloud protocol and the system usability scale (SUS) questionnaire. RESULTS: An extract-transform-load process was developed to extract relevant clinical and molecular data from their original sources and map them to OMOP. Further, the OMOP WebAPI was adapted to retrieve all data for a single patient and transfer them into the decision support Web application for enabling physicians to easily consult the prediction service including monitoring of transferred data. The evaluation of the application resulted in a SUS score of 86.7. CONCLUSION: This work proposes an EHR-independent means of integrating prediction models for deployment in clinical settings, utilizing the OMOP CDM. The usability evaluation revealed that the application is generally suitable for routine use while also illustrating small aspects for improvement.
CRIS-Team Scopus Importer:2020-06-16

Electronic Support for Retrospective Analysis in the Field of Radiation Oncology: Proof of Principle Using an Example of Fractionated Stereotactic Radiotherapy of 251 Meningioma Patients - Rutzner, Sandra; Fietkau, Rainer; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Lubgan, Dorota (Frontiers in Oncology, 2017)
The purpose of this study is to verify the possible benefit of a clinical data warehouse (DWH) for retrospective analysis in the field of radiation oncology.We manually and electronically (using DWH) evaluated demographic, radiotherapy, and outcome data from 251 meningioma patients, who were irradiated from January 2002 to January 2015 at the Department of Radiation Oncology of the Erlangen University Hospital. Furthermore, we linked the Oncology Information System (OIS) MOSAIQ(®) to the DWH in order to gain access to irradiation data. We compared the manual and electronic data retrieval method in terms of congruence of data, corresponding time, and personal requirements (physician, physicist, scientific associate).The electronically supported data retrieval (DWH) showed an average of 93.9% correct data and significantly (p = 0.009) better result compared to manual data retrieval (91.2%). Utilizing a DWH enables the user to replace large amounts of manual activities (668 h), offers the ability to significantly reduce data collection time and labor demand (35 h), while simultaneously improving data quality. In our case, work time for manually data retrieval was 637 h for the scientific assistant, 26 h for the medical physicist, and 5 h for the physician (total 668 h).Our study shows that a DWH is particularly useful for retrospective analysis in the radiation oncology field. Routine clinical data for a large patient group can be provided ready for analysis to the scientist and data collection time can be significantly reduced. Furthermore, linking multiple data sources in a DWH offers the ability to improve data quality for retrospective analysis, and future research can be simplified.
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Empowering Researchers to Query Medical Data and Biospecimens by Ensuring Appropriate Usability of a Feasibility Tool: Evaluation Study - Schüttler, Christina; Zerlik, Maria; Gründner, Julian; Köhler, Thomas; Rosenau, Lorenz; Prokosch, Hans-Ulrich; Sedlmayr, Brita (JMIR Human Factors, 2023)
Background: The Aligning Biobanking and Data Integration Centers Efficiently project aims to harmonize technologies and governance structures of German university hospitals and their biobanks to facilitate searching for patient data and biospecimens. The central element will be a feasibility tool for researchers to query the availability of samples and data to determine the feasibility of their study project. Objective: The objectives of the study were as follows: an evaluation of the overall user interface usability of the feasibility tool, the identification of critical usability issues, comprehensibility of the underlying ontology operability, and analysis of user feedback on additional functionalities. From these, recommendations for quality-of-use optimization, focusing on more intuitive usability, were derived. Methods: To achieve the study goal, an exploratory usability test consisting of 2 main parts was conducted. In the first part, the thinking aloud method (test participants express their thoughts aloud throughout their use of the tool) was complemented by a quantitative questionnaire. In the second part, the interview method was combined with supplementary mock-ups to collect users’ opinions on possible additional features. Results: The study cohort rated global usability of the feasibility tool based on the System Usability Scale with a good score of 81.25. The tasks assigned posed certain challenges. No participant was able to solve all tasks correctly. A detailed analysis showed that this was mostly because of minor issues. This impression was confirmed by the recorded statements, which described the tool as intuitive and user friendly. The feedback also provided useful insights regarding which critical usability problems occur and need to be addressed promptly. Conclusions: The findings indicate that the prototype of the Aligning Biobanking and Data Integration Centers Efficiently feasibility tool is headed in the right direction. Nevertheless, we see potential for optimization primarily in the display of the search functions, the unambiguous distinguishability of criteria, and the visibility of their associated classification system. Overall, it can be stated that the combination of different tools used to evaluate the feasibility tool provided a comprehensive picture of its usability.
CRIS-Team Scopus Importer:2023-06-02
Keywords: clinical research informatics; feasibility queries; ontology; usability evaluation; user interface; user-centered design

Enhancing refiner - Improving performance of reference interval estimation for skewed distributions - Ammer, Tatjana; Schutzenmeister, A.; Prokosch, Hans-Ulrich; Rauh, Manfred; Zierk, Jakob; Rank, C. M. (CLINICA CHIMICA ACTA, 2022)
CRIS-Team WoS Importer:2022-07-08

Erratum: Evaluation of three feasibility tools for identifying patient data and biospecimen availability: Comparative usability study (JMIR Medical Informatics (2021) 9:7 (e25531) DOI: 10.2196/25531) - Schüttler, Christina; Prokosch, Hans-Ulrich; Sedlmayr, Martin; Sedlmayr, Brita (JMIR Medical Informatics, 2021)
In "Evaluation of Three Feasibility Tools for Identifying Patient Data and Biospecimen Availability: Comparative Usability Study" (JMIR Med Inform 2021;9(7):e25531) the authors noted one error. In the originally published manuscript, a funding code was not included in the "Acknowledgments" section. The following sentence has now been added to this section: This work is additionally supported by the German Federal Ministry of Education and Research under the funding code 01EY1701. The complete “Acknowledgments” section originally read as follows: The authors would like to thank all participating MIRACUM locations—Dresden, Erlangen, Frankfurt am Main, Freiburg, Gießen, Greifswald, Magdeburg, and Mannheim. The authors would like to specially thank all scientists and researchers who participated in this study and provided a valuable insight into the usability of the different query builders through their loud thoughts and questionnaire evaluations. The authors would also like to thank Stefanie Schild (Erlangen), Renate Häuslschmid (Freiburg), and Preetha Moorthy (Mannheim) for their support in pretesting the tasks and questionnaires. This study was conducted as part of MIRACUM. MIRACUM is funded by the German Federal Ministry of Education and Research within the Medical Informatics Funding Scheme under the funding codes 01ZZ1801A and 01ZZ1801L. The present work was performed in fulfillment of the requirements for obtaining the degree “Dr. rer. biol. hum.” from the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (CS). This has been corrected to: The authors would like to thank all participating MIRACUM locations—Dresden, Erlangen, Frankfurt am Main, Freiburg, Gießen, Greifswald, Magdeburg, and Mannheim. The authors would like to specially thank all scientists and researchers who participated in this study and provided a valuable insight into the usability of the different query builders through their loud thoughts and questionnaire evaluations. The authors would also like to thank Stefanie Schild (Erlangen), Renate Häuslschmid (Freiburg), and Preetha Moorthy (Mannheim) for their support in pretesting the tasks and questionnaires. This study was conducted as part of MIRACUM. MIRACUM is funded by the German Federal Ministry of Education and Research within the Medical Informatics Funding Scheme under the funding codes 01ZZ1801A and 01ZZ1801L. This work is additionally supported by the German Federal Ministry of Education and Research under the funding code 01EY1701. The present work was performed in fulfillment of the requirements for obtaining the degree “Dr. rer. biol. hum.” from the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (CS). The correction will appear in the online version of the paper on the JMIR Publications website on October 8, 2021, together. with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.
CRIS-Team Scopus Importer:2021-11-05

Erratum to: Requirements for a cross-location biobank IT infrastructure : Survey of stakeholder input on the establishment of a biobank network of the German Biobank Alliance (GBA) - Schüttler, Christina; Buschhueter, N.; Doellinger, C.; Ebert, L.; Hummel, M.; Linde, J.; Prokosch, Hans-Ulrich; Proynova, R.; Lablans, M. (Pathologe, 2018)
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Establishing an Interoperable Clinical Trial Information System Within MIRACUM. - Hasselblatt, Hanna; Andrae, Johanna; Tassoni, Adrian; Fitzer, Kai; Bahls, Thomas; Prokosch, Hans-Ulrich; Boeker, Martin (ICT for Health Science Research, 2019)
In the long-run we wish to demonstrate the power of linking clinical trial information to routine health records for straightforward patient recruitment - not only at each single hospital but in a large German consortium (called MIRACUM). In such architecture a hospital wide clinical trial registry (CTR) plays a major role. All such site specific CTR however, also need to be interoperable and support automated data provision for a central MIRACUM wide trial registry. Based on a survey of already existing trial information systems at each partner site and a comparison of their functionality, a joint requirement specification was created, a minimal MIRACUM wide trial core dataset was defined and an architecture was designed in which each MIRACUM partner could keep their autonomous system decision. Partners could however also join forces in a cooperative enhancement of a new open source trial registry. Thus, sites with no trial registry could be supported by the others and synergies used. Finally, the newly developed CTR will allow modular site specific add-ons and can also take over the function of the MIRACUM wide trial registry. In this paper we describe the process, how such a consortium-wide CTR was designed and developed, while always keeping cross-site interoperability as a major requirement.
EVALuna2:209489

Establishing an interoperable clinical trial information system within MIRACUM - Hasselblatt, Hanna; Andrae, Johanna; Tassoni, Adrian; Fitzer, Kai; Bahls, Thomas; Prokosch, Hans-Ulrich; Boeker, Martin (Proceedings of the EFMI 2019 Special Topic Conference Studies in Health Technology and Informatics, 2019)
In the long-run we wish to demonstrate the power of linking clinical trial information to routine health records for straightforward patient recruitment - not only at each single hospital but in a large German consortium (called MIRACUM). In such architecture a hospital wide clinical trial registry (CTR) plays a major role. All such site specific CTR however, also need to be interoperable and support automated data provision for a central MIRACUM wide trial registry. Based on a survey of already existing trial information systems at each partner site and a comparison of their functionality, a joint requirement specification was created, a minimal MIRACUM wide trial core dataset was defined and an architecture was designed in which each MIRACUM partner could keep their autonomous system decision. Partners could however also join forces in a cooperative enhancement of a new open source trial registry. Thus, sites with no trial registry could be supported by the others and synergies used. Finally, the newly developed CTR will allow modular site specific add-ons and can also take over the function of the MIRACUM wide trial registry. In this paper we describe the process, how such a consortium-wide CTR was designed and developed, while always keeping cross-site interoperability as a major requirement.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Clinical trial registry; Health information system; MI-I; MIRACUM

Evaluating predictive modeling algorithms to assess patient eligibility for clinical trials from routine data - Köpcke, Felix; Lubgan, Dorota; Fietkau, Rainer; Scholler, Axel; Nau, Carla; Stürzl, Michael; Croner, Roland S.; Prokosch, Hans-Ulrich; Toddenroth, Dennis (BMC Medical Informatics and Decision Making, 2013)
Background: The necessity to translate eligibility criteria from free text into decision rules that are compatible with data from the electronic health record (EHR) constitutes the main challenge when developing and deploying clinical trial recruitment support systems. Recruitment decisions based on case-based reasoning, i.e. using past cases rather than explicit rules, could dispense with the need for translating eligibility criteria and could also be implemented largely independently from the terminology of the EHR's database. We evaluated the feasibility of predictive modeling to assess the eligibility of patients for clinical trials and report on a prototype's performance for different system configurations. Methods. The prototype worked by using existing basic patient data of manually assessed eligible and ineligible patients to induce prediction models. Performance was measured retrospectively for three clinical trials by plotting receiver operating characteristic curves and comparing the area under the curve (ROC-AUC) for different prediction algorithms, different sizes of the learning set and different numbers and aggregation levels of the patient attributes. Results: Random forests were generally among the best performing models with a maximum ROC-AUC of 0.81 (CI: 0.72-0.88) for trial A, 0.96 (CI: 0.95-0.97) for trial B and 0.99 (CI: 0.98-0.99) for trial C. The full potential of this algorithm was reached after learning from approximately 200 manually screened patients (eligible and ineligible). Neither block- nor category-level aggregation of diagnosis and procedure codes influenced the algorithms' performance substantially. Conclusions: Our results indicate that predictive modeling is a feasible approach to support patient recruitment into clinical trials. Its major advantages over the commonly applied rule-based systems are its independency from the concrete representation of eligibility criteria and EHR data and its potential for automation. © 2013 Köpcke et al.; licensee BioMed Central Ltd.
UnivIS-Import:2015-04-14:Pub.2013.tech.IMMD.infome.evalua_3

Evaluation of a clinical decision support system for rare diseases: a qualitative study - Schaaf, Jannik; Sedlmayr, Martin; Sedlmayr, Brita; Prokosch, Hans-Ulrich; Storf, Holger (BMC Medical Informatics and Decision Making, 2021)
Background: Rare Diseases (RDs) are difficult to diagnose. Clinical Decision Support Systems (CDSS) could support the diagnosis for RDs. The Medical Informatics in Research and Medicine (MIRACUM) consortium developed a CDSS for RDs based on distributed clinical data from eight German university hospitals. To support the diagnosis for difficult patient cases, the CDSS uses data from the different hospitals to perform a patient similarity analysis to obtain an indication of a diagnosis. To optimize our CDSS, we conducted a qualitative study to investigate usability and functionality of our designed CDSS. Methods: We performed a Thinking Aloud Test (TA-Test) with RDs experts working in Rare Diseases Centers (RDCs) at MIRACUM locations which are specialized in diagnosis and treatment of RDs. An instruction sheet with tasks was prepared that the participants should perform with the CDSS during the study. The TA-Test was recorded on audio and video, whereas the resulting transcripts were analysed with a qualitative content analysis, as a ruled-guided fixed procedure to analyse text-based data. Furthermore, a questionnaire was handed out at the end of the study including the System Usability Scale (SUS). Results: A total of eight experts from eight MIRACUM locations with an established RDC were included in the study. Results indicate that more detailed information about patients, such as descriptive attributes or findings, can help the system perform better. The system was rated positively in terms of functionality, such as functions that enable the user to obtain an overview of similar patients or medical history of a patient. However, there is a lack of transparency in the results of the CDSS patient similarity analysis. The study participants often stated that the system should present the user with an overview of exact symptoms, diagnosis, and other characteristics that define two patients as similar. In the usability section, the CDSS received a score of 73.21 points, which is ranked as good usability. Conclusions: This qualitative study investigated the usability and functionality of a CDSS of RDs. Despite positive feedback about functionality of system, the CDSS still requires some revisions and improvement in transparency of the patient similarity analysis.
CRIS-Team Scopus Importer:2021-03-05
Keywords: Clinical decision support systems; Computer-assisted diagnosis; Rare diseases; Usability

Evaluation of a Digital Dementia Registry's IT Architecture After a Three-Year Period in Practice: digiDEM Bayern - Zeiler, Michael; Dietzel, Nikolas; Kolominsky-Rabas, Peter; Grässel, Elmar; Prokosch, Hans-Ulrich (Studies in health technology and informatics, 2024)
INTRODUCTION: The project "digiDEM Bayern" aims to set up a registry with long-term follow-up data on people with dementia and their family caregivers. For that purpose an Electronic Data Capture (EDC) system linked with a Participant Management (PM) system has been established. This study evaluates the acceptance and usability of the IT tools supporting all data management processes in order to further improve the system and associated processes. METHODS: For this purpose we collected the key numbers of the registry, and used the System Usability Scale (SUS) to evaluate the interactions of the data management systems in a wide area. RESULTS: Thirty-six research partners (RP) and six study team (ST) members completed the anonymous online survey. The EDC system overall reached an average SUS score of 73.42 and the PM system of 77.92. DISCUSSION: The two systems fulfil their required task and, therefore, simplify the work of the RP in the data collection process and of the ST during the data quality checks. CONCLUSION: Integrating the used systems is therefore recommended for registry studies in other medical areas.
CRIS-Team Scopus Importer:2024-05-10
Keywords: Dementia; Evaluation; IT Architecture; Online Survey; Registry

Evaluation of an Interactive Visualization Tool for the Interpretation of Pediatric Laboratory Test Results - Hirschmann, Johannes; Sedlmayr, Brita; Zierk, Jakob; Rauh, Manfred; Metzler, Markus; Prokosch, Hans-Ulrich; Toddenroth, Dennis (Studies in health technology and informatics, 2017)
The physiological age-related development of pediatric laboratory results interferes with pathological derangements, which can complicate the interpretation of test results. Recently proposed continuous reference intervals (RIs) promise to be beneficial, although their clinical use may depend on graphical presentations. To estimate the clinical utility of continuous RIs, we developed and evaluated an interactive visualization tool, and examined the differentiation of hemoglobinopathies that is attainable based on the underlying innovative RI model. The implemented web application allows users to easily enter laboratory test results, and displays various visualizations in conjunction with the corresponding RIs, such as charts and personalized Z-scores. To evaluate the usability of the visualization tool, we conducted concurrent think-aloud sessions with four physicians, who were prompted to solve a set of typical interpretation tasks, and acquired additional information through a questionnaire including the System Usability Scale (SUS). We used 85 de-identified clinical cases for an exemplified assessment of how well model-based interpretations of blood count parameters reproduced previously diagnosed hemoglobinopathies. Usability tests as well as questionnaire responses indicated that the developed tool was well received by the physicians. Results from the think-aloud evaluation revealed only minor problems and the tool reached an average SUS score of 86.9, suggesting good usability. Hemoglobinopathy discrimination depended on the considered subtype, although the overall performance of the novel method rivaled the one of the conventional approach. The interactive visualization of innovative continuous reference intervals demonstrated promising results, which justifies further testing on the path towards clinical routine.
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Evaluation of a Patient-Facing Digital Prototype for Perioperative Risk Assessment. - Mang, Jonathan; Schild, Stefanie; Prokosch, Hans-Ulrich; Jeleazcov, Christian; Heinrich, Anne; Toddenroth, Dennis (Studies in health technology and informatics, 2019)
Preparations for anesthesiological management of patients build on preoperative patient self-reports concerning risk factors and comorbidities. In this setting, electronic documentation could facilitate innovative computerized functions, although patient-facing digital questionnaires require appropriate tools that patients can access effectively. To explore the feasibility of an electronic application for preoperative data acquisition directly from patients, a digital, tablet-based prototypical application has been developed within a user-centered design process in order to replace a previously used paper-based anamnesis sheet for perioperative risk evaluation. The implemented prototype has been extensively tested and iteratively improved to progressively provide an easy-to-use data entry function. To assess the suitability of this tool for everyday data acquisition by patients and physicians and to identify usability problems, the stepwise development process was accompanied by a heuristic evaluation as well as a think-aloud evaluation, while another 56 participating patients completed a feedback sheet according to ISO 9241/10. The latter method detected additional usability problems that occurred during the use of the application, which contributed to iterative improvements of the prototype. Throughout the development process, 81 issues were identified and largely resolved. After these revisions of the prototype, the number of problems found per tester decreased from 4.75 to 0.96, while the overall rating increased to 6.14 out of 7 points (SD = 1.2). These improvements demonstrate the value and efficiency of such a user-centered design process and illustrate that a user-friendly patient-facing digital data entry can replace preoperative paper questionnaires for anesthesiological management.
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Evaluation of a patient-facing digital prototype for perioperative risk assessment - Mang, Jonathan; Schild, Stefanie; Prokosch, Hans-Ulrich; Jeleazcov, Christian; Heinrich, Anne; Toddenroth, Dennis (ICT for Health Science Research - Proceedings of the EFMI 2019 Special Topic Conference, 2019)
Preparations for anesthesiological management of patients build on preoperative patient self-reports concerning risk factors and comorbidities. In this setting, electronic documentation could facilitate innovative computerized functions, although patient-facing digital questionnaires require appropriate tools that patients can access effectively. To explore the feasibility of an electronic application for preoperative data acquisition directly from patients, a digital, tablet-based prototypical application has been developed within a user-centered design process in order to replace a previously used paper-based anamnesis sheet for perioperative risk evaluation. The implemented prototype has been extensively tested and iteratively improved to progressively provide an easy-to-use data entry function. To assess the suitability of this tool for everyday data acquisition by patients and physicians and to identify usability problems, the stepwise development process was accompanied by a heuristic evaluation as well as a think-aloud evaluation, while another 56 participating patients completed a feedback sheet according to ISO 9241/10. The latter method detected additional usability problems that occurred during the use of the application, which contributed to iterative improvements of the prototype. Throughout the development process, 81 issues were identified and largely resolved. After these revisions of the prototype, the number of problems found per tester decreased from 4.75 to 0.96, while the overall rating increased to 6.14 out of 7 points (SD = 1.2). These improvements demonstrate the value and efficiency of such a user-centered design process and illustrate that a user-friendly patient-facing digital data entry can replace preoperative paper questionnaires for anesthesiological management.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Anesthesiologic patient history; Digital questionnaire; ISO 9241; Usability evaluation

Evaluation of Different Learning Algorithms of Neural Networks for Drug Dosing Recommendations in Pediatrics - Rödle, Wolfgang; Caliskan, Deniz; Prokosch, Hans-Ulrich; Kraus, Stefan (dHealth 2020 – Biomedical Informatics for Health and Care, 2020)
Publicly accessible databases with evidence-based information on drug dosages for children and adolescents are not available in Germany. In previous work a prototypical web-based online platform for pediatric dosing recommendation has been developed. Quality assured maintenance of such a database is a time consuming effort. Recent work has shown that it is possible to use routinely documented data for machine learning approaches in order to create models for future decision support tools. This work describes the development of a prototype for pediatric dosing recommendations on the basis of routine drug prescriptions. Since they are structured for daily clinical use, not for machine learning, they include a substantial proportion of narrative text that requires preprocessing with consideration of medical and pharmaceutical knowledge. Three different learning algorithms have been applied and compared. The genetic algorithm with backpropagation has achieved the highest accuracy in the predictions. Our study constitutes a first step towards pediatric dosing recommendations, but there are multiple additional steps to be taken before a routine use might be considered, such as an evaluation by experienced physicians.
CRIS-Team Scopus Importer:2020-09-11
Keywords: computer; drug dosage calculations; machine learning; neural networks; pediatrics

Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis - Blasini, Romina; Strantz, Cosima; Gulden, Christian; Helfer, Sven; Lidke, Jakub; Prokosch, Hans-Ulrich; Sohrabi, Keywan; Schneider, Henning (JMIR Formative Research, 2024)
Background: Clinical trials (CTs) are crucial for medical research; however, they frequently fall short of the requisite number of participants who meet all eligibility criteria (EC). A clinical trial recruitment support system (CTRSS) is developed to help identify potential participants by performing a search on a specific data pool. The accuracy of the search results is directly related to the quality of the data used for comparison. Data accessibility can present challenges, making it crucial to identify the necessary data for a CTRSS to query. Prior research has examined the data elements frequently used in CT EC but has not evaluated which criteria are actually used to search for participants. Although all EC must be met to enroll a person in a CT, not all criteria have the same importance when searching for potential participants in an existing data pool, such as an electronic health record, because some of the criteria are only relevant at the time of enrollment. Objective: In this study, we investigated which groups of data elements are relevant in practice for finding suitable participants and whether there are typical elements that are not relevant and can therefore be omitted. Methods: We asked trial experts and CTRSS developers to first categorize the EC of their CTs according to data element groups and then to classify them into 1 of 3 categories: necessary, complementary, and irrelevant. In addition, the experts assessed whether a criterion was documented (on paper or digitally) or whether it was information known only to the treating physicians or patients. Results: We reviewed 82 CTs with 1132 unique EC. Of these 1132 EC, 350 (30.9%) were considered necessary, 224 (19.8%) complementary, and 341 (30.1%) total irrelevant. To identify the most relevant data elements, we introduced the data element relevance index (DERI). This describes the percentage of studies in which the corresponding data element occurs and is also classified as necessary or supplementary. We found that the query of “diagnosis” was relevant for finding participants in 79 (96.3%) of the CTs. This group was followed by “date of birth/age” with a DERI of 85.4% (n=70) and “procedure” with a DERI of 35.4% (n=29). Conclusions: The distribution of data element groups in CTs has been heterogeneously described in previous works. Therefore, we recommend identifying the percentage of CTs in which data element groups can be found as a more reliable way to determine the relevance of EC. Only necessary and complementary criteria should be included in this DERI.
CRIS-Team Scopus Importer:2024-02-23
Keywords: automated clinical trials; classifications; clinical trial; clinical trial recruitment support system; clinical trials; criteria; CTRSS; data classification; data elements; data groups; participants; patient recruitment system; PRS; relevance

Evaluation of three feasibility tools for identifying patient data and biospecimen availability: Comparative usability study - Schüttler, Christina; Prokosch, Hans-Ulrich; Sedlmayr, Martin; Sedlmayr, Brita (JMIR Medical Informatics, 2021)
Background: To meet the growing importance of real-word data analysis, clinical data and biosamples must be timely made available. Feasibility platforms are often the first contact point for determining the availability of such data for specific research questions. Therefore, a user-friendly interface should be provided to enable access to this information easily. The German Medical Informatics Initiative also aims to establish such a platform for its infrastructure. Although some of these platforms are actively used, their tools still have limitations. Consequently, the Medical Informatics Initiative consortium MIRACUM (Medical Informatics in Research and Care in University Medicine) committed itself to analyzing the pros and cons of existing solutions and to designing an optimized graphical feasibility user interface. Objective: The aim of this study is to identify the system that is most user-friendly and thus forms the best basis for developing a harmonized tool. To achieve this goal, we carried out a comparative usability evaluation of existing tools used by researchers acting as end users. Methods: The evaluation included three preselected search tools and was conducted as a qualitative exploratory study with a randomized design over a period of 6 weeks. The tools in question were the MIRACUM i2b2 (Informatics for Integrating Biology and the Bedside) feasibility platform, OHDSI's (Observational Health Data Sciences and Informatics) ATLAS, and the Sample Locator of the German Biobank Alliance. The evaluation was conducted in the form of a web-based usability test (usability walkthrough combined with a web-based questionnaire) with participants aged between 26 and 63 years who work as medical doctors. Results: In total, 17 study participants evaluated the three tools. The overall evaluation of usability, which was based on the System Usability Scale, showed that the Sample Locator, with a mean System Usability Scale score of 77.03 (SD 20.62), was significantly superior to the other two tools (Wilcoxon test; Sample Locator vs i2b2: P=.047; Sample Locator vs ATLAS: P=.001). i2b2, with a score of 59.83 (SD 25.36), performed significantly better than ATLAS, which had a score of 27.81 (SD 21.79; Wilcoxon test; i2b2 vs ATLAS: P=.005). The analysis of the material generated by the usability walkthrough method confirmed these findings. ATLAS caused the most usability problems (n=66), followed by i2b2 (n=48) and the Sample Locator (n=22). Moreover, the Sample Locator achieved the highest ratings with respect to additional questions regarding satisfaction with the tools. Conclusions: This study provides data to develop a suitable basis for the selection of a harmonized tool for feasibility studies via concrete evaluation and a comparison of the usability of three different types of query builders. The feedback obtained from the participants during the usability test made it possible to identify user problems and positive design aspects of the individual tools and compare them qualitatively.
CRIS-Team Scopus Importer:2021-08-06
Keywords: Evaluation; Feasibility; Research; Software tools; User interface

Experiences of Transforming a Complex Nephrologic Care and Research Database into i2b2 Using the IDRT Tools - Maier, Christian; Christoph, Jan; Schmidt, Danilo; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Kraus, Stefan; Sedlmayr, Martin (Journal of Healthcare Engineering, 2019)
The secondary use of data from electronic medical records has become an important factor to determine and to identify various causes of disease. For this reason, applications like informatics for integrating biology and the bedside (i2b2) offer a GUI-based front end to select patient cohorts. To make use of those tools, however, clinical data need to be extracted from the Electronic Health Record (EHR) system and integrated into the data schema of i2b2. We used TBase, a documentation system for nephrologic transplantations, as a source system and applied the Integrated Data Repository Toolkit (IDRT) for the Extract, Transform, and Load (ETL) process to load the data into i2b2. Since i2b2 uses an entity-attribute-value (EAV) schema, which is a fundamentally different way of modeling data in comparison to a standard relational schema in TBase, we evaluated if (a) the data relationship of the source system entities can still be represented in the i2b2 schema and if (b) the IDRT is a suitable solution for loading the data of a comprehensive data schema like TBase into i2b2. For that reason, we identified entities in the TBase data schema which were relevant for answering questions on cohort identification. By doing so, we found out that the entities had different structures that needed to be handled differently for the ETL process. Furthermore, the use of IDRT revealed shortcomings with regard to large input data and specific data structures that are part of most modern EHR systems. However, this project also showed that our way of modeling the TBase data in i2b2 has been proven to be successful in terms of answering the most common questions of clinicians on cohort identification.
CRIS-Team WoS Importer:2019-03-06

Extractive summarization of clinical trial descriptions - Gulden, Christian; Kirchner, Melanie; Schüttler, Christina; Hinderer, Marc; Kampf, Marvin; Prokosch, Hans-Ulrich; Toddenroth, Dennis (International Journal of Medical Informatics, 2019)
Purpose: Text summarization of clinical trial descriptions has the potential to reduce the time required to familiarize oneself with the subject of studies by condensing long-form detailed descriptions to concise, meaning-preserving synopses. This work describes the process and quality of automatically generated summaries of clinical trial descriptions using extractive text summarization methods. Methods: We generated a novel dataset from the detailed descriptions and brief summaries of trials registered on clinicaltrials.gov. We executed several text summarization algorithms on the detailed descriptions in this corpus and calculated the standard ROUGE metrics using the brief summaries included in the record as a reference. To investigate the correlation of these metrics with human sentiments, four reviewers assessed the content-completeness of the generated summaries and the helpfulness of both the generated and reference summaries via a Likert scale questionnaire. Results: The filtering stages of the dataset generation process reduce the 277,228 trials registered on clinicaltrials.gov to 101,016 records usable for the summarization task. On average, the summaries in this corpus are 25% the length of the detailed descriptions. Of the evaluated text summarization methods, the TextRank algorithm exhibits the overall best performance with a ROUGE-1 F1 score of 0.3531, ROUGE-2 F1 score of 0.1723, and ROUGE-L F1 score of 0.3003. These scores correlate with the assessment of the helpfulness and content similarity by the human reviewers. Inter-rater agreement for the helpfulness and content similarity was slight and fair respectively (Fleiss’ kappa of 0.12 and 0.22). Conclusions: Extractive summarization is a viable tool for generating meaning-preserving synopses of detailed clinical trial descriptions. Further, the human evaluation has shown that the ROUGE-L F1 score is useful for rating the general quality of generated summaries of clinical trial descriptions in an automated way.
CRIS-Team Scopus Importer:2019-06-21
Keywords: Clinical trials; NLP; Text mining; Text summarization

Feasibility analysis of conducting observational studies with the electronic health record - von Lucadou, Marcel; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Toddenroth, Dennis (BMC Medical Informatics and Decision Making, 2019)
BACKGROUND: The secondary use of electronic health records (EHRs) promises to facilitate medical research. We reviewed general data requirements in observational studies and analyzed the feasibility of conducting observational studies with structured EHR data, in particular diagnosis and procedure codes. METHODS: After reviewing published observational studies from the University Hospital of Erlangen for general data requirements, we identified three different study populations for the feasibility analysis with eligibility criteria from three exemplary observational studies. For each study population, we evaluated the availability of relevant patient characteristics in our EHR, including outcome and exposure variables. To assess data quality, we computed distributions of relevant patient characteristics from the available structured EHR data and compared them to those of the original studies. We implemented computed phenotypes for patient characteristics where necessary. In random samples, we evaluated how well structured patient characteristics agreed with a gold standard from manually interpreted free texts. We categorized our findings using the four data quality dimensions "completeness", "correctness", "currency" and "granularity". RESULTS: Reviewing general data requirements, we found that some investigators supplement routine data with questionnaires, interviews and follow-up examinations. We included 847 subjects in the feasibility analysis (Study 1 n = 411, Study 2 n = 423, Study 3 n = 13). All eligibility criteria from two studies were available in structured data, while one study required computed phenotypes in eligibility criteria. In one study, we found that all necessary patient characteristics were documented at least once in either structured or unstructured data. In another study, all exposure and outcome variables were available in structured data, while in the other one unstructured data had to be consulted. The comparison of patient characteristics distributions, as computed from structured data, with those from the original study yielded similar distributions as well as indications of underreporting. We observed violations in all four data quality dimensions. CONCLUSIONS: While we found relevant patient characteristics available in structured EHR data, data quality problems may entail that it remains a case-by-case decision whether diagnosis and procedure codes are sufficient to underpin observational studies. Free-text data or subsequently supplementary study data may be important to complement a comprehensive patient history.
CRIS-Team Scopus Importer:2019-11-08
Keywords: Availability; Completeness; Correctness; Currency; Data quality; Electronic health record; Granularity; Observational study; Retrospective study

Finding the needle in the hay stack: An open architecture to support diagnosis of undiagnosed patients - Schaaf, Jannik; Boeker, Martin; Ganslandt, Thomas; Haverkamp, Christian; Hermann, Tim; Kadioglu, Dennis; Prokosch, Hans-Ulrich; Wagner, Thomas O.F.; Von Wagner, Michael; Schaefer, Johanna; Sedlmayr, Martin; Storf, Holger (Studies in Health Technology and Informatics, 2019)
Clinical Decision Support Systems (CDSS) are promising to support physicians in finding the right diagnosis of patients with rare diseases (RD). The MIRACUM consortium, which includes ten university hospitals in Germany, will establish a diagnosis support system for RD. This system conducts a similarity analysis on distributed clinical data with the aim to identify similar patient cases at each MIRACUM site to offer the physician a hint to a possible diagnosis.
CRIS-Team Scopus Importer:2019-09-20
Keywords: Clinical Decision Support; Data Science; Rare Diseases

First Steps to Evaluate an NLP Tool's Medication Extraction Accuracy from Discharge Letters - Caliskan, Deniz; Zierk, Jakob; Kraska, Detlef; Schulz, Stefan; Daumke, Philipp; Prokosch, Hans-Ulrich; Kapsner, Lorenz (German Medical Data Sciences: Bringing Data to Life, 2021)
INTRODUCTION: The aim of this study is to evaluate the use of a natural language processing (NLP) software to extract medication statements from unstructured medical discharge letters. METHODS: Ten randomly selected discharge letters were extracted from the data warehouse of the University Hospital Erlangen (UHE) and manually annotated to create a gold standard. The AHD NLP tool, provided by MIRACUM's industry partner was used to annotate these discharge letters. Annotations by the NLP tool where then compared to the gold standard on two levels: phrase precision (whether or not the whole medication statement has been identified correctly) and token precision (whether or not the medication name has been identified correctly within correctly discovered medication phrases). RESULTS: The NLP tool detected medication related phrases with an overall F-measure of 0.852. The medication name has been identified correctly with an overall F-measure of 0.936. DISCUSSION: This proof-of-concept study is a first step towards an automated scalable evaluation system for MIRACUM's industry partner's NLP tool by using a gold standard. Medication phrases and names have been correctly identified in most cases by the NLP system. Future effort needs to be put into extending and validating the gold standard.
CRIS-Team Scopus Importer:2021-06-11
Keywords: Data Analysis; Electronic Data Processing; Natural Language Processing; Patient Discharge Summary

From a Content Delivery Portal to a Knowledge Management System for Standardized Cancer Documentation - Schlue, Danijela; Mate, Sebastian; Haier, Jörg; Kadioglu, Dennis; Prokosch, Hans-Ulrich; Breil, Bernhard (Studies in health technology and informatics, 2017)
Heterogeneous tumor documentation and its challenges of interpretation of medical terms lead to problems in analyses of data from clinical and epidemiological cancer registries. The objective of this project was to design, implement and improve a national content delivery portal for oncological terms. Data elements of existing handbooks and documentation sources were analyzed, combined and summarized by medical experts of different comprehensive cancer centers. Informatics experts created a generic data model based on an existing metadata repository. In order to establish a national knowledge management system for standardized cancer documentation, a prototypical tumor wiki was designed and implemented. Requirements engineering techniques were applied to optimize this platform. It is targeted to user groups such as documentation officers, physicians and patients. The linkage to other information sources like PubMed and MeSH was realized.
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Funktionalität und Bedienung von eGENA, der elektronischen Gedächtnis- und Entscheidungshilfe für Notfälle in der Anästhesiologie - Neuhaus, C.; Schild, Stefanie; Eismann, H.; Baus, J.; Happel, O.; Heller, A. R.; Richter, T.; Weinert, M.; Sedlmayr, B.; Sedlmayr, M.; Prokosch, Hans-Ulrich; Schleppers, A.; et al. (Anästhesiologie & Intensivmedizin, 2020)
The German Cognitive Aid Working Group of the Professional Association of German Anaesthesiologists (BDA) and the German Society of Anaesthesiology and Intensive Care Medicine (DGAI) developed 'eGENA', a digital cognitive aid for intra- and postoperative emergencies using an iterative user-centred design process according to DIN EN ISO 9241-210. The digital cognitive aid is the first application for crisis management in anaesthesiology where detailed documentation of the development process was published. eGENA is a progressive web application (PWA) which stores information offline on stationary and mobile devices. The user can access information by first choosing a patient group (infant, adult, parturient) and then one of the following search options: 'resuscitation', 'alphabetical search', 'ABCDE approach', and 'body navigator'. The information accessed is further tailored to the patient's clinical status: 'awake' vs. 'anaesthetised', and 'haemodynamically stable' vs. 'haemodynamically unstable'. Information is not presented as one single continuous text, but rather subdivided into the tabs 'immediate action', 'diagnosis, and 'therapy'. Information not pertaining to the linear sequence of action is presented under 'symptoms' and 'differential diagnosis'. eGENA comprises more than 50 emergencies including those listed in the Helsinki Declaration on Patient Safety in Anaesthesiology for which institutions should have protocols. In addition, eGENA supports non-technical skills by providing impulses for decision-making, teamwork and resource management. Users can customise eGENA by editing locally relevant information and share the revised content. eGENA can be downloaded for free from the website of the Professional Association of German Anaesthesiologists and the German Society of Anaesthesiology and Intensive Care Medicine together with training material supporting the implementation.
CRIS-Team Scopus Importer:2020-09-18
Keywords: Cognitive Aid; Crisis Management; Decision-making; Memory; Web Application

Generation of a Fast Healthcare Interoperability Resources (FHIR)-based Ontology for Federated Feasibility Queries in the Context of COVID-19: Feasibility Study - Rosenau, Lorenz; Majeed, Raphael W.; Ingenerf, Josef; Kiel, Alexander; Kroll, Björn; Köhler, Thomas; Prokosch, Hans-Ulrich; Gründner, Julian (JMIR Medical Informatics, 2022)
Background: The COVID-19 pandemic highlighted the importance of making research data from all German hospitals available to scientists to respond to current and future pandemics promptly. The heterogeneous data originating from proprietary systems at hospitals' sites must be harmonized and accessible. The German Corona Consensus Dataset (GECCO) specifies how data for COVID-19 patients will be standardized in Fast Healthcare Interoperability Resources (FHIR) profiles across German hospitals. However, given the complexity of the FHIR standard, the data harmonization is not sufficient to make the data accessible. A simplified visual representation is needed to reduce the technical burden, while allowing feasibility queries. Objective: This study investigates how a search ontology can be automatically generated using FHIR profiles and a terminology server. Furthermore, it describes how this ontology can be used in a user interface (UI) and how a mapping and a terminology tree created together with the ontology can translate user input into FHIR queries. Methods: We used the FHIR profiles from the GECCO data set combined with a terminology server to generate an ontology and the required mapping files for the translation. We analyzed the profiles and identified search criteria for the visual representation. In this process, we reduced the complex profiles to code value pairs for improved usability. We enriched our ontology with the necessary information to display it in a UI. We also developed an intermediate query language to transform the queries from the UI to federated FHIR requests. Separation of concerns resulted in discrepancies between the criteria used in the intermediate query format and the target query language. Therefore, a mapping was created to reintroduce all information relevant for creating the query in its target language. Further, we generated a tree representation of the ontology hierarchy, which allows resolving child concepts in the process. Results: In the scope of this project, 82 (99%) of 83 elements defined in the GECCO profile were successfully implemented. We verified our solution based on an independently developed test patient. A discrepancy between the test data and the criteria was found in 6 cases due to different versions used to generate the test data and the UI profiles, the support for specific code systems, and the evaluation of postcoordinated Systematized Nomenclature of Medicine (SNOMED) codes. Our results highlight the need for governance mechanisms for version changes, concept mapping between values from different code systems encoding the same concept, and support for different unit dimensions. Conclusions: We developed an automatic process to generate ontology and mapping files for FHIR-formatted data. Our tests found that this process works for most of our chosen FHIR profile criteria. The process established here works directly with FHIR profiles and a terminology server, making it extendable to other FHIR profiles and demonstrating that automatic ontology generation on FHIR profiles is feasible.
CRIS-Team Scopus Importer:2022-05-20
Keywords: accessibility; automation; COVID-19; CQL; data; development; Fast Healthcare Interoperability Resource; feasibility; feasibility study; federated queries; FHIR; FHIR Search; Germany; harmonized; hospital; input; map; ontology; query; terminology; terminology server; user interface

German medical data sciences: Bringing data to life: Proceedings of the joint annual meeting of the German association of medical informatics, biometry and epidemiology (GMDS e.V.) and the Central European Network - International Biometric Society (CEN-IBS) 2020 in Berlin, Germany - Röhrig, Rainer; Beißbarth, Tim; Brannath, Werner; Prokosch, Hans-Ulrich; Schmidtmann, Irene; Stolpe, Susanne; Zapf, Antonia (IOS Press, 2021)
The COVID-19 pandemic has brought into sharp focus the need for the collection of data. Such data cannot be collected or provided without medical informatics, documentation and health data management. Nor can health data be evaluated and converted into a useful tool for making the important decisions that affect us all without biometrics and epidemiology, bioinformatics and systems biology. This book presents full papers from GMDS & CEN-IBS 2020, the first joint online conference of the German Association of Medical Informatics, Biometry and Epidemiology (GMDS) and the Central European Network & the International Biometric Society (CEN-IBS), held online between 6 and 11 September 2020. The title of the conference was Bringing Data to Life, a reference to the increasing amount of data in medical research which is inextricably related to the fast-developing digitalization of the health system. Many challenges must be addressed in order to make use of and benefit from these increasing sources of data, and these can only be faced if all disciplines related to data science work together. The conference aimed to bring together the diverse disciplines within data science, including medical informatics, bioinformatics, biostatistics, epidemiology, public health and medical documentation. Topics covered in the book include central themes relevant to society in general and advances in data technology which support innovations in medical research in particular. The book brings together many topics related to the provision and analysis of data in medicine, and will be of interest to all those working in the field.
CRIS-Team Scopus Importer:2021-10-15

Germany's Approach for the Secondary Use of Federated Real-World Data in the German Portal for Medical Research Data - Kleinert, Philip; Gebhardt, Marie; Buckow, Karoline; Gründner, Julian; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Semler, Sebastian C. (Studies in Health Technology and Informatics, 2024)
In the light of big data driven clinical research, fair access to real world clinical health data enables evidence to improve patient care. Germany's healthcare system provides an abundant data resource but unique challenges due to its federated nature, heterogeneity and high data-protection standards. The Medical Informatics Initiative (MII) developed concepts that are being implemented in the German Portal for Medical Research Data (FDPG) to grant access to distributed data-sources across state borders. The portal currently provides access to more than 10 million patient resources containing hundreds of millions of laboratory parameters, diagnostic reports, administered medications, procedures and specimens. Upcoming datasets include among others oncological data, molecular analysis results and microbiological findings. Here, we describe the philosophy, implementation and experience behind the framework: standardized access processes, interoperable fair data, software for in depth feasibility requests, tools to support researchers and hospital stakeholders alike as well as transparency measures to provide data use information for patients. Challenges remain to improve data quality and automatization of technical and organizational processes.
CRIS-Team Scopus Importer:2024-10-25
Keywords: Clinical Research Informatics; Federated IT Infrastructure; Real-World-Data; Secondary Use

High-resolution pediatric reference intervals for 15 biochemical analytes described using fractional polynomials - Zierk, Jakob; Baum, Hannsjörg; Bertram, Alexander; Boeker, Martin; Buchwald, Armin; Cario, Holger; Christoph, Jürgen; Frühwald, Michael C.; Groß, Hans Jürgen; Groening, Arndt; Gscheidmeier, Thomas; Hoff, Torsten; et al. (Clinical Chemistry and Laboratory Medicine, 2021)
Assessment of children's laboratory test results requires consideration of the extensive changes that occur during physiological development and result in pronounced sex- and age-specific dynamics in many biochemical analytes. Pediatric reference intervals have to account for these dynamics, but ethical and practical challenges limit the availability of appropriate pediatric reference intervals that cover children from birth to adulthood. We have therefore initiated the multi-center data-driven PEDREF project (Next-Generation Pediatric Reference Intervals) to create pediatric reference intervals using data from laboratory information systems. We analyzed laboratory test results from 638,683 patients (217,883-982,548 samples per analyte, a median of 603,745 test results per analyte, and 10,298,067 test results in total) performed during patient care in 13 German centers. Test results from children with repeat measurements were discarded, and we estimated the distribution of physiological test results using a validated statistical approach (kosmic). We report continuous pediatric reference intervals and percentile charts for alanine transaminase, aspartate transaminase, lactate dehydrogenase, alkaline phosphatase, γ-glutamyl-transferase, total protein, albumin, creatinine, urea, sodium, potassium, calcium, chloride, anorganic phosphate, and magnesium. Reference intervals are provided as tables and fractional polynomial functions (i.e., mathematical equations) that can be integrated into laboratory information systems. Additionally, Z-scores and percentiles enable the normalization of test results by age and sex to facilitate their interpretation across age groups. The provided reference intervals and percentile charts enable precise assessment of laboratory test results in children from birth to adulthood. Our findings highlight the pronounced dynamics in many biochemical analytes in neonates, which require particular consideration in reference intervals to support clinical decision making most effectively.
CRIS-Team Scopus Importer:2021-03-05
Keywords: continuous reference intervals; data mining; indirect reference intervals; pediatric reference intervals; percentile charts

Identifying barriers for implementation of computer based nursing documentation - Vollmer, Anne-Maria; Prokosch, Hans-Ulrich; Bürkle, Thomas (Studies in health technology and informatics, 2014)
This study was undertaken in the planning phase for the introduction of a comprehensive computer based nursing documentation system at Erlangen University Hospital. There, we expect a wide range of difficult organizational changes, because the nurses currently neither used computer based nursing documentation nor did they follow strongly the nursing process model within paper based documentation. Thus we were eager to recognize potential pitfalls early and to identify potential barriers for digital nursing documentation. In a questionnaire study we surveyed all German university hospitals for their experience with the implementation of computer based nursing documentation implementation. We received answers from 11 of the 23 hospitals. Furthermore we performed a questionnaire study about expectations and fears among the nurses of four pilot wards of our hospital. Most respondents stated a positive attitude towards the nursing process documentation, but many respondents note technical (e.g. bad performance of the software) and organizational barriers (e.g. lack of time).
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Impact of social network composition on cognitive decline: Digital Dementia Registry Bavaria (digiDEM Bayern) - Laininger, Lisa; Dietzel, Nikolas; Grässel, Elmar; Prokosch, Hans-Ulrich; Kolominsky-Rabas, Peter (PLoS ONE, 2024)
Background Currently, there is no curative treatment for dementia. The implementation of preventive measures is of great importance. Therefore, it is necessary to identify and address individual and modifiable risk factors. Social isolation, defined through social networks, is a factor that may influence the onset and progression of the disease. The networks of older people are mostly composed of either family or friends. The aim of this study is to examine the influence of social isolation and network composition on cognition over the course of 12 months in people with cognitive impairment. Methods Data basis is the multicentre, prospective, longitudinal register study ‘Digital Dementia Registery Bavaria—digiDEM Bayern‘. The degree of social isolation was assessed using the Lubben Social Network Scale- Revised (LSNS-R) and the degree of cognitive impairment using the Mini Mental State Examination (MMSE), conducted at baseline and after 12 months. Data were analysed using pre-post ANCOVA, adjusted for baseline MMSE, age, gender, education, living situation and Barthel-Index. Results 106 subjects (78.9 ± 8.2 years; 66% female) were included in the analysis. The mean MMSE score at baseline was 24.3 (SD = 3.6). Within the friendship subscore, risk for social isolation was highly prevalent (42.5%). Though, there was no difference between individuals with higher/ lower risk of social isolation within the friendship-network after adjusting for common risk factors in cognitive decline over time, F (1,98) = .046, p = .831, partial η2 = .000. Conclusion The results of this study showed that the risk of social isolation from friends is very high among people with cognitive impairment. However, social isolation does not appear to have a bearing influence on the course of cognition. Nevertheless, it is important for people with cognitive impairment to promote and maintain close social contacts with friends.
CRIS-Team Scopus Importer:2024-07-26

Implementation of a patient data management system : Effects on intensive care documentation - Castellanos, Ixchel; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Schüttler, Jürgen; Bürkle, Thomas (Anaesthesist, 2013)
Patient data management systems (PDMS) enable digital documentation on intensive care units (ICU) and have positive effects on completness, quality and quantity of documented information. A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. IT compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.A retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004-2006) and 5 years after (2007-2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.Systematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4 % in the year 2006 (before) to 8.5 % in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.The implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.
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Implementation of Task-Tracking Software for Clinical IT Management - Purohit, Anne-Maria; Brutscheck, Clemens; Prokosch, Hans-Ulrich; Ganslandt, Thomas; Schneider, Martin (Studies in health technology and informatics, 2017)
Often in clinical IT departments, many different methods and IT systems are used for task-tracking and project organization. Based on managers' personal preferences and knowledge about project management methods, tools differ from team to team and even from employee to employee. This causes communication problems, especially when tasks need to be done in cooperation with different teams. Monitoring tasks and resources becomes impossible: there are no defined deliverables, which prevents reliable deadlines. Because of these problems, we implemented task-tracking software which is now in use across all seven teams at the University Hospital Erlangen. Over a period of seven months, a working group defined types of tasks (project, routine task, etc.), workflows, and views to monitor the tasks of the 7 divisions, 20 teams and 340 different IT services. The software has been in use since December 2016.
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Keywords: Health information management; Information management; Project management

Implementing Pharmacogenomic Clinical Decision Support into German Hospitals - Hinderer, Marc; Boerries, Melanie; Boeker, Martin; Neumaier, Michael; Loubal, Frank-Peter; Acker, Till; Brunner, Manfred; Prokosch, Hans-Ulrich; Christoph, Jan (Studies in health technology and informatics, 2018)
BACKGROUND: Pharmacogenomic Clinical Decision Support Systems (CDSS) are considered to be the most feasible tool for adopting pharmacogenomic testing into clinical routine. OBJECTIVE: To discuss important factors for implementing pharmacogenomic CDSS into German hospitals. METHODS: We analyzed two relevant studies. Furthermore, we interviewed data privacy officers of three German university hospitals and examined relevant legal regulations in literature. RESULTS: There are three major barriers for implementing pharmacogenomic CDSS into German hospitals: (i) the legal uncertainty; (ii) the lack of machine-readable data; (iii) the remaining knowledge gap of both genetics and pharmacogenomics among physicians. CONCLUSION: The implementation of passive clinical decision support (CDS) for somatic mutations in the form of structured pharmacogenomic reports might be the most feasible CDS feature for clinicians in German hospitals.
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Improving COVID-19 Research of University Hospitals in Germany: Formative Usability Evaluation of the CODEX Feasibility Portal - Sedlmayr, Brita; Sedlmayr, Martin; Kroll, Bjoern; Prokosch, Hans-Ulrich; Gründner, Julian; Schüttler, Christina (Applied Clinical Informatics, 2022)
Background Within the German "Network University Medicine," a portal is to be developed to enable researchers to query on novel coronavirus disease 2019 (COVID-19) data from university hospitals for assessing the feasibility of a clinical study. Objectives The usability of a prototype for federated feasibility queries was evaluated to identify design strengths and weaknesses and derive improvement recommendations for further development. Methods In the course of a remote usability test with the thinking-aloud method and posttask interviews, 15 clinical researchers evaluated the usability of a prototype of the Feasibility Portal. The identified usability problems were rated according to severity, and improvement recommendations were derived. Results The design of the prototype was rated as simple, intuitive, and as usable with little effort. The usability test reported a total of 26 problems, 8 of these were rated as "critical." Usability problems and revision recommendations focus primarily on improving the visual distinguishability of selected inclusion and exclusion criteria, enabling a flexible approach to criteria linking, and enhancing the free-text search. Conclusion Improvement proposals were developed for these user problems which will guide further development and the adaptation of the portal to user needs. This is an important prerequisite for correct and efficient use in everyday clinical work in the future. Results can provide developers of similar systems with a good starting point for interface conceptualizations. The methodological approach/the developed test guideline can serve as a template for similar evaluations.
CRIS-Team WoS Importer:2022-04-29

In Search for Methods to Support Electronic Patient Recruitment in a Multi-ICU Clinical Trial - Diesch, Katharina; Held, Jürgen; Kraus, Stefan; Kunze, Ulrich; Kraska, Detlef; Prokosch, Hans-Ulrich (German Medical Data Sciences: Shaping Change – Creative Solutions for Innovative Medicine, 2019)
Antimycotics are substances to treat fungal infections, a frequent cause of death on intensive care units. It is of great importance to administer such drugs only to patients who actually need them, since the unnecessary application leads to the selection of multiresistent fungi, making future therapy more difficult, and represents a significant financial burden for the health care system. Within the scope of a prospective study, which analyses the premature discontinuation of the administration of unnecessary antifungal drugs, two software platforms for recruitment support were implemented and compared at the University Hospital Erlangen. Besides technical aspects, such as the necessary development time and query runtimes, their usability and user friendliness for the clinical users were compared. We found that the practical identification of patient cohorts is possible both with a full featured business intelligence application and with a low effort approach based on language constructs of the Arden Syntax. Furthermore, this pilot evaluation led to important insights related to the clinical documentation context and data quality issues. A comprehensive analysis of the clinical environment and documentation context is essential for the final decision on the tool to be used.
CRIS-Team Scopus Importer:2019-09-24
Keywords: Antimycotics; Arden Syntax; Clinical Research; Clinical Trial Support; Patient Cohort Identification; Secondary Use

Integrated Data Repository Toolkit (IDRT). A Suite of Programs to Facilitate Health Analytics on Heterogeneous Medical Data - Bauer, C. R. K. D.; Ganslandt, Thomas; Baum, B.; Christoph, Jan; Engel, Igor; Loebe, M.; Mate, Sebastian; Staeubert, S.; Drepper, J.; Prokosch, Hans-Ulrich; Winter, A.; Sax, Ulrich (Methods of Information in Medicine, 2016)
In recent years, research data warehouses moved increasingly into the focus of interest of medical research. Nevertheless, there are only a few center-independent infrastructure solutions available. They aim to provide a consolidated view on medical data from various sources such as clinical trials, electronic health records, epidemiological registries or longitudinal cohorts. The i2b2 framework is a well-established solution for such repositories, but it lacks support for importing and integrating clinical data and metadata.The goal of this project was to develop a platform for easy integration and administration of data from heterogeneous sources, to provide capabilities for linking them to medical terminologies and to allow for transforming and mapping of data streams for user-specific views.A suite of three tools has been developed: the i2b2 Wizard for simplifying administration of i2b2, the IDRT Import and Mapping Tool for loading clinical data from various formats like CSV, SQL, CDISC ODM or biobanks and the IDRT i2b2 Web Client Plugin for advanced export options. The Import and Mapping Tool also includes an ontology editor for rearranging and mapping patient data and structures as well as annotating clinical data with medical terminologies, primarily those used in Germany (ICD-10-GM, OPS, ICD-O, etc.).With the three tools functional, new i2b2-based research projects can be created, populated and customized to researcher's needs in a few hours. Amalgamating data and metadata from different databases can be managed easily. With regards to data privacy a pseudonymization service can be plugged in. Using common ontologies and reference terminologies rather than project-specific ones leads to a consistent understanding of the data semantics.i2b2's promise is to enable clinical researchers to devise and test new hypothesis even without a deep knowledge in statistical programing. The approach presented here has been tested in a number of scenarios with millions of observations and tens of thousands of patients. Initially mostly observant, trained researchers were able to construct new analyses on their own. Early feedback indicates that timely and extensive access to their "own" data is appreciated most, but it is also lowering the barrier for other tasks, for instance checking data quality and completeness (missing data, wrong coding).
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Integrated Data Repository Toolkit: Werkzeuge zur Nachnutzung medizinischer Daten für die Forschung - Ganslandt, Thomas; Sax, U.; Löbe, M.; Drepper, J.; Bauer, C.; Baum, B.; Christoph, Jan; Mate, Sebastian; Quade, M.; Stäubert, S.; Prokosch, Hans-Ulrich (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), 2012)
CRIS-Team Scopus Importer:2021-11-16

Integrating a Secure and Generic Mobile App for Patient Reported Outcome Acquisition into an EHR Infrastructure Based on FHIR Resources - Ploner, Nico; Prokosch, Hans-Ulrich (Digital Personalized Health and Medicine, 2020)
Both patients and physicians of the University Hospital of Erlangen would welcome means of digital data exchange between patients and the hospital. This work presents a system's architecture, FHIR based data model, security measures, and application flow based on patient's smartphones and a public cloud infrastructure to obtain patient reported outcome measures and merge that information with clinical routine data.
CRIS-Team Scopus Importer:2020-07-03
Keywords: FHIR; Mobile Applications; Patient Reported Outcome Measures

Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development - Hinderer, Marc; Boeker, Martin; Wagner, Sebastian A.; Lablans, Martin; Newe, Stephanie; Huelsemann, Jan L.; Neumaier, Michael; Binder, Harald; Renz, Harald; Acker, Till; Prokosch, Hans-Ulrich; Sedlmayr, Martin (BMC Medical Informatics and Decision Making, 2017)
Pharmacogenomic clinical decision support systems (CDSS) have the potential to help overcome some of the barriers for translating pharmacogenomic knowledge into clinical routine. Before developing a prototype it is crucial for developers to know which pharmacogenomic CDSS features and user-system interactions have yet been developed, implemented and tested in previous pharmacogenomic CDSS efforts and if they have been successfully applied. We address this issue by providing an overview of the designs of user-system interactions of recently developed pharmacogenomic CDSS.We searched PubMed for pharmacogenomic CDSS published between January 1, 2012 and November 15, 2016. Thirty-two out of 118 identified articles were summarized and included in the final analysis. We then compared the designs of user-system interactions of the 20 pharmacogenomic CDSS we had identified.Alerts are the most widespread tools for physician-system interactions, but need to be implemented carefully to prevent alert fatigue and avoid liabilities. Pharmacogenomic test results and override reasons stored in the local EHR might help communicate pharmacogenomic information to other internal care providers. Integrating patients into user-system interactions through patient letters and online portals might be crucial for transferring pharmacogenomic data to external health care providers. Inbox messages inform physicians about new pharmacogenomic test results and enable them to request pharmacogenomic consultations. Search engines enable physicians to compare medical treatment options based on a patient's genotype.Within the last 5 years, several pharmacogenomic CDSS have been developed. However, most of the included articles are solely describing prototypes of pharmacogenomic CDSS rather than evaluating them. To support the development of prototypes further evaluation efforts will be necessary. In the future, pharmacogenomic CDSS will likely include prediction models to identify patients who are suitable for preemptive genotyping.
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Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation - Gründner, Julian; Wolf, Nicolas; Tögel, Lars; Haller, Florian; Prokosch, Hans-Ulrich; Christoph, Jan (Journal of Medical Internet Research, 2020)
Background: The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for the identification and evaluation of driver mutations and for defining personalized cancer treatment regimens. The meaningful combination of omics data, ie, pathogenic gene variants and alterations with other patient data, to understand the full picture of malignancy has been challenging.
CRIS-Team WoS Importer:2020-12-11

Integrative bioinformatic analyses of global transcriptome data decipher novel molecular insights into cardiac anti-fibrotic therapies - Fuchs, Maximilian; Kreutzer, Fabian Philipp; Kapsner, Lorenz; Mitzka, Saskia; Just, Annette; Perbellini, Filippo; Terracciano, Cesare M.; Xiao, Ke; Geffers, Robert; Bogdan, Christian; Prokosch, Hans-Ulrich; Fiedler, Jan; et al. (International Journal of Molecular Sciences, 2020)
Integrative bioinformatics is an emerging field in the big data era, offering a steadily increasing number of algorithms and analysis tools. However, for researchers in experimental life sciences it is often difficult to follow and properly apply the bioinformatical methods in order to unravel the complexity and systemic effects of omics data. Here, we present an integrative bioinformatics pipeline to decipher crucial biological insights from global transcriptome profiling data to validate innovative therapeutics. It is available as a web application for an interactive and simplified analysis without the need for programming skills or deep bioinformatics backgroundThe approach was applied to an ex vivo cardiac model treated with natural anti-fibrotic compounds and we obtained new mechanistic insights into their anti-fibrotic action and molecular interplay with miRNAs in cardiac fibrosis. Several gene pathways associated with proliferation, extracellular matrix processes and wound healing were altered, and we could identify micro (mi) RNA-21-5p and miRNA-223-3p as key molecular components related to the anti-fibrotic treatment. Importantlyour pipeline is not restricted to a specific cell type or disease and can be broadly applied to better understand the unprecedented level of complexity in big data research.
CRIS-Team Scopus Importer:2020-07-17
Keywords: Algorithm; Big data; Cardiac fibrosis; Integrative bioinformatics; MiRNAs; Natural compounds; Transcriptomics; Web application

Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study - Schaaf, Jannik; Prokosch, Hans-Ulrich; Boeker, Martin; Schaefer, Johanna; Vasseur, Jessica; Storf, Holger; Sedlmayr, Martin (BMC Medical Informatics and Decision Making, 2020)
BACKGROUND: Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS. METHODS: Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs. An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring's qualitative content analysis approach. RESULTS: A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted. The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs. CONCLUSIONS: This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.
CRIS-Team Scopus Importer:2020-09-25
Keywords: Clinical decision support systems; Computer-assisted diagnosis; Interview; Qualitative research; Rare diseases

Investigating the Capabilities of FHIR Search for Clinical Trial Phenotyping - Gulden, Christian; Mate, Sebastian; Prokosch, Hans-Ulrich; Kraus, Stefan (Studies in health technology and informatics, 2018)
Clinical trials are the foundation of evidence-based medicine and their computerized support has been a recurring theme in medical informatics. One challenging aspect is the representation of eligibility criteria in a machine-readable format to automate the identification of suitable participants. In this study, we investigate the capabilities for expressing trial eligibility criteria via the search functionality specified in HL7 FHIR, an emerging standard for exchanging healthcare information electronically which also defines a set of operations for searching for health record data. Using a randomly sampled subset of 303 eligibility criteria from ClinicalTrials.gov yielded a 34 % success rate in representing them using the FHIR search semantics. While limitations are present, the FHIR search semantics are a viable tool for supporting preliminary trial eligibility assessment.
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IT infrastructure components to support clinical care and translational research projects in a comprehensive cancer center - Prokosch, Hans-Ulrich; Ries, Markus; Beyer, Alexander; Schwenk, Martin; Seggewies, Christof; Köpcke, Felix; Mate, Sebastian; Martin, Marcus; Bärthlein, Barbara; Beckmann, Matthias; Stürzl, Michael; Croner, Roland; et al. (User Centred Networked Health Care, 2011)
This paper presents the concept of an integrated IT infrastructure framework established at the comprehensive cancer center at the University Hospital Erlangen. The framework is based on the single source concept where data from the electronic medical record are reused for clinical and translational research projects. The applicability of the approach is illustrated by two case studies from colon cancer and prostate cancer research projects. © 2011 European Federation for Medical Informatics. All rights reserved.
UnivIS-Import:2015-04-14:Pub.2011.tech.IMMD.infome.itinfr
Keywords: Cancer documentation; Center; Comprehensive cancer; IT infrastructure framework; Single source concept; Translational research

Japanese-German Collaboration on Electronic Health Record Systems - Winter, Alfred; Takabayashi, Katsuhiko; Jahn, Franziska; Kimura, Eizen; Engelbrecht, Rolf; Haux, Reinhold; Honda, Masayuki; Hübner, Ursula H; Inoue, Sozo; Kohl, Christian D; Matsumoto, Takehiro; Matsumura, Yasushi; et al. (Studies in health technology and informatics, 2017)
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Ketos: Clinical decision support and machine learning as a service – A training and deployment platform based on Docker, OMOP-CDM, and FHIR Web Services - Gründner, Julian; Schwachhofer, Thorsten; Sippl, Phillip; Wolf, Nicolas; Erpenbeck, Marcel; Gulden, Christian; Kapsner, Lorenz A.; Zierk, Jakob; Mate, Sebastian; Stürzl, Michael; Croner, Roland; Prokosch, Hans-Ulrich; et al. (PLoS ONE, 2019)
Background and objective To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in this work implements a tool for researchers allowing them to perform statistical analyses and deploy resulting models in a secure environment. Methods The proposed system uses Docker virtualization to provide researchers with reproducible data analysis and development environments, accessible via Jupyter Notebook, to perform statistical analysis and develop, train and deploy models based on standardized input data. The platform is built in a modular fashion and interfaces with web services using the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard to access patient data. In our prototypical implementation we use an OMOP common data model (OMOP-CDM) database. The architecture supports the entire research lifecycle from creating a data analysis environment, retrieving data, and training to final deployment in a hospital setting. Results We evaluated the platform by establishing and deploying an analysis and end user application for hemoglobin reference intervals within the University Hospital Erlangen. To demonstrate the potential of the system to deploy arbitrary models, we loaded a colorectal cancer dataset into an OMOP database and built machine learning models to predict patient outcomes and made them available via a web service. We demonstrated both the integration with FHIR as well as an example end user application. Finally, we integrated the platform with the open source DataSHIELD architecture to allow for distributed privacy preserving data analysis and training across networks of hospitals. Conclusion The KETOS platform takes a novel approach to data analysis, training and deploying decision support models in a hospital or healthcare setting. It does so in a secure and privacy-preserving manner, combining the flexibility of Docker virtualization with the advantages of standardized vocabularies, a widely applied database schema (OMOP-CDM), and a standardized way to exchange medical data (FHIR).
CRIS-Team Scopus Importer:2019-10-11

Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials - Melzer, Georg; Maiwald, Tim; Prokosch, Hans-Ulrich; Ganslandt, Thomas (Applied Clinical Informatics, 2021)
Background Even though clinical trials are indispensable for medical research, they are frequently impaired by delayed or incomplete patient recruitment, resulting in cost overruns or aborted studies. Study protocols based on real-world data with precisely expressed eligibility criteria and realistic cohort estimations are crucial for successful study execution. The increasing availability of routine clinical data in electronic health records (EHRs) provides the opportunity to also support patient recruitment during the prescreening phase. While solutions for electronic recruitment support have been published, to our knowledge, no method for the prioritization of eligibility criteria in this context has been explored. Methods In the context of the Electronic Health Records for Clinical Research (EHR4CR) project, we examined the eligibility criteria of the KATHERINE trial. Criteria were extracted from the study protocol, deduplicated, and decomposed. A paper chart review and data warehouse query were executed to retrieve clinical data for the resulting set of simplified criteria separately from both sources. Criteria were scored according to disease specificity, data availability, and discriminatory power based on their content and the clinical dataset. Results The study protocol contained 35 eligibility criteria, which after simplification yielded 70 atomic criteria. For a cohort of 106 patients with breast cancer and neoadjuvant treatment, 47.9% of data elements were captured through paper chart review, with the data warehouse query yielding 26.9% of data elements. Score application resulted in a prioritized subset of 17 criteria, which yielded a sensitivity of 1.00 and specificity 0.57 on EHR data (paper charts, 1.00 and 0.80) compared with actual recruitment in the trial. Conclusion It is possible to prioritize clinical trial eligibility criteria based on real-world data to optimize prescreening of patients on a selected subset of relevant and available criteria and reduce implementation efforts for recruitment support. The performance could be further improved by increasing EHR data coverage.
CRIS-Team Scopus Importer:2021-01-29
Keywords: clinical trial; data warehousing and data marts; electronic health records and systems; recruitment; secondary use

Linking a Consortium-Wide Data Quality Assessment Tool with the MIRACUM Metadata Repository - Kapsner, Lorenz; Mang, Jonathan M.; Mate, Sebastian; Seuchter, Susanne A.; Vengadeswaran, Abishaa; Bathelt, Franziska; Deppenwiese, Noemi; Kadioglu, Dennis; Kraska, Detlef; Prokosch, Hans-Ulrich (Applied Clinical Informatics, 2021)
Background Many research initiatives aim at using data from electronic health records (EHRs) in observational studies. Participating sites of the German Medical Informatics Initiative (MII) established data integration centers to integrate EHR data within research data repositories to support local and federated analyses. To address concerns regarding possible data quality (DQ) issues of hospital routine data compared with data specifically collected for scientific purposes, we have previously presented a data quality assessment (DQA) tool providing a standardized approach to assess DQ of the research data repositories at the MIRACUM consortium's partner sites.
CRIS-Team WoS Importer:2021-09-03

Machine learning in medication prescription: A systematic review - Iancu, Alexa; Leb, Ines; Prokosch, Hans-Ulrich; Rödle, Wolfgang (International Journal of Medical Informatics, 2023)
Background: Medication prescription is a complex process that could benefit from current research and development in machine learning through decision support systems. Particularly pediatricians are forced to prescribe medications “off-label” as children are still underrepresented in clinical studies, which leads to a high risk of an incorrect dose and adverse drug effects. Methods: PubMed, IEEE Xplore and PROSPERO were searched for relevant studies that developed and evaluated well-performing machine learning algorithms following the PRISMA statement. Quality assessment was conducted in accordance with the IJMEDI checklist. Identified studies were reviewed in detail, including the required variables for predicting the correct dose, especially of pediatric medication prescription. Results: The search identified 656 studies, of which 64 were reviewed in detail and 36 met the inclusion criteria. According to the IJMEDI checklist, five studies were considered to be of high quality. 19 of the 36 studies dealt with the active substance warfarin. Overall, machine learning algorithms based on decision trees or regression methods performed superior regarding their predictive power than algorithms based on neural networks, support vector machines or other methods. The use of ensemble methods like bagging or boosting generally enhanced the accuracy of the dose predictions. The required input and output variables of the algorithms were considerably heterogeneous and differ strongly among the respective substance. Conclusions: By using machine learning algorithms, the prescription process could be simplified and dosing correctness could be enhanced. Despite the heterogenous results among the different substances and cases and the lack of pediatric use cases, the identified approaches and required variables can serve as an excellent starting point for further development of algorithms predicting drug doses, particularly for children. Especially the combination of physiologically-based pharmacokinetic models with machine learning algorithms represents a great opportunity to enhance the predictive power and accuracy of the developed algorithms.
CRIS-Team Scopus Importer:2023-11-17
Keywords: Electronic medical records (EMR); Machine Learning (ML); Medication prescription

Machine Learning Models of Post-Intubation Hypoxia During General Anesthesia - Sippl, Philipp; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Münster, Tino; Toddenroth, Dennis (Studies in health technology and informatics, 2017)
Fine-meshed perioperative measurements are offering enormous potential for automatically investigating clinical complications during general anesthesia. In this study, we employed multiple machine learning methods to model perioperative hypoxia and compare their respective capabilities. After exporting and visualizing 620 series of perioperative vital signs, we had ten anesthesiologists annotate the subjective presence and severity of temporary post-intubation oxygen desaturation. We then applied specific clustering and prediction methods on the acquired annotations, and evaluated their performance in comparison to the inter-rater agreement between experts. When reproducing the expert annotations, the sensitivity and specificity of multi-layer neural networks substantially outperformed clustering and simpler threshold-based methods. The achieved performance of our best automated hypoxia models thereby approximately equaled the observed agreement between different medical experts. Furthermore, we deployed our classification methods for processing unlabeled inputs to estimate the incidence of hypoxic episodes in another sizeable patient cohort, which attests to the feasibility of using the approach on a larger scale. We interpret that our machine learning models could be instrumental for computerized observational studies of the clinical determinants of post-intubation oxygen deficiency. Future research might also investigate potential benefits of more advanced preprocessing approaches such as automated feature learning.
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Mapping the Entire Record-An Alternative Approach to Data Access from Medical Logic Modules - Kraus, Stefan; Toddenroth, Dennis; Staudigel, Martin; Rödle, Wolfgang; Unberath, Philipp; Griebel, Lena; Prokosch, Hans-Ulrich; Mate, Sebastian (Applied Clinical Informatics, 2020)
OBJECTIVES: This study aimed to describe an alternative approach for accessing electronic medical records (EMRs) from clinical decision support (CDS) functions based on Arden Syntax Medical Logic Modules, which can be paraphrased as "map the entire record." METHODS: Based on an experimental Arden Syntax processor, we implemented a method to transform patient data from a commercial patient data management system (PDMS) to tree-structured documents termed CDS EMRs. They are encoded in a specific XML format that can be directly transformed to Arden Syntax data types by a mapper natively integrated into the processor. The internal structure of a CDS EMR reflects the tabbed view of an EMR in the graphical user interface of the PDMS. RESULTS: The study resulted in an architecture that provides CDS EMRs in the form of a network service. The approach enables uniform data access from all Medical Logic Modules and requires no mapping parameters except a case number. Measurements within a CDS EMR can be addressed with straightforward path expressions. The approach is in routine use at a German university hospital for more than 2 years. CONCLUSION: This practical approach facilitates the use of CDS functions in the clinical routine at our local hospital. It is transferrable to standard-compliant Arden Syntax processors with moderate effort. Its comprehensibility can also facilitate teaching and development. Moreover, it may lower the entry barrier for the application of the Arden Syntax standard and could therefore promote its dissemination.
CRIS-Team Scopus Importer:2020-05-22

Memorandum "Open Metadata". Open Access to Documentation Forms and Item Catalogs in Healthcare - Dugas, M.; Joeckel, K-H; Friede, T.; Gefeller, Olaf; Kieser, M.; Marschollek, M.; Ammenwerth, E.; Roehrig, R.; Knaup-Gregori, P.; Prokosch, Hans-Ulrich (Methods of Information in Medicine, 2015)
At present, most documentation forms and item catalogs in healthcare are not accessible to the public. This applies to assessment forms of routine patient care as well as case report forms (CRFs) of clinical and epidemiological studies. On behalf of the German chairs for Medical Informatics, Biometry and Epidemiology six recommendations to developers and users of documentation forms in healthcare were developed. Open access to medical documentation forms could substantially improve information systems in healthcare and medical research networks. Therefore these forms should be made available to the scientific community, their use should not be unduly restricted, they should be published in a sustainable way using international standards and sources of documentation forms should be referenced in scientific publications.
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MIRACUM: Medical Informatics in Research and Care in University Medicine - Prokosch, Hans-Ulrich; Acker, Till; Bernarding, Johannes; Binder, Harald; Boeker, Martin; Boerries, Melanie; Daumke, Philipp; Ganslandt, Thomas; Hesser, Juergen; Hoening, Gunther; Neumaier, Michael; Marquardt, Kurt; et al. (Methods of Information in Medicine, 2018)
INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g. OHDSI, PCORnet, eMerge, RD-Connect) MIRACUM is a consortium of academic and hospital partners as well as one industrial partner in eight German cities which have joined forces to create interoperable data integration centres (DIC) and make data within those DIC available for innovative new IT solutions in patient care and medical research. OBJECTIVES: Sharing data shall be supported by common interoperable tools and services, in order to leverage the power of such data for biomedical discovery and moving towards a learning health system. This paper aims at illustrating the major building blocks and concepts which MIRACUM will apply to achieve this goal. GOVERNANCE AND POLICIES: Besides establishing an efficient governance structure within the MIRACUM consortium (based on the steering board, a central administrative office, the general MIRACUM assembly, six working groups and the international scientific advisory board), defining DIC governance rules and data sharing policies, as well as establishing (at each MIRACUM DIC site, but also for MIRACUM in total) use and access committees are major building blocks for the success of such an endeavor. ARCHITECTURAL FRAMEWORK AND METHODOLOGY: The MIRACUM DIC architecture builds on a comprehensive ecosystem of reusable open source tools (MIRACOLIX), which are linkable and interoperable amongst each other, but also with the existing software environment of the MIRACUM hospitals. Efficient data protection measures, considering patient consent, data harmonization and a MIRACUM metadata repository as well as a common data model are major pillars of this framework. The methodological approach for shared data usage relies on a federated querying and analysis concept. USE CASES: MIRACUM aims at proving the value of their DIC with three use cases: IT support for patient recruitment into clinical trials, the development and routine care implementation of a clinico-molecular predictive knowledge tool, and molecular-guided therapy recommendations in molecular tumor boards. RESULTS: Based on the MIRACUM DIC release in the nine months conceptual phase first large scale analysis for stroke and colorectal cancer cohorts have been pursued. DISCUSSION: Beyond all technological challenges successfully applying the MIRACUM tools for the enrichment of our knowledge about diagnostic and therapeutic concepts, thus supporting the concept of a Learning Health System will be crucial for the acceptance and sustainability in the medical community and the MIRACUM university hospitals.
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Mitochondrial DNA copy number is associated with mortality and infections in a large cohort of patients with chronic kidney disease - Fazzini, Federica; Lamina, Claudia; Fendt, Liane; Schultheiss, Ulla T.; Kotsis, Fruzsina; Hicks, Andrew A.; Meiselbach, Heike; Weissensteiner, Hansi; Forer, Lukas; Krane, Vera; Eckardt, Kai-Uwe; Köttgen, Anna; et al. (Kidney International, 2019)
Damage of mitochondrial DNA (mtDNA) with reduction in copy number has been proposed as a biomarker for mitochondrial dysfunction and oxidative stress. Chronic kidney disease (CKD) is associated with increased mortality and risk of cardiovascular disease, but the underlying mechanisms remain incompletely understood. Here we investigated the prognostic role of mtDNA copy number for cause-specific mortality in 4812 patients from the German Chronic Kidney Disease study, an ongoing prospective observational national cohort study of patients with CKD stage G3 and A1-3 or G1-2 with overt proteinuria (A3) at enrollment. MtDNA was quantified in whole blood using a plasmid-normalized PCR-based assay. At baseline, 1235 patients had prevalent cardiovascular disease. These patients had a significantly lower mtDNA copy number than patients without cardiovascular disease (fully-adjusted model: odds ratio 1.03, 95% confidence interval [CI] 1.01-1.05 per 10 mtDNA copies decrease). After four years of follow-up, we observed a significant inverse association between mtDNA copy number and all-cause mortality, adjusted for kidney function and cardiovascular disease risk factors (hazard ratio 1.37, 95% CI 1.09-1.73 for quartile 1 compared to quartiles 2-4). When grouped by causes of death, estimates pointed in the same direction for all causes but in a fully-adjusted model decreased copy numbers were significantly lower only in infection-related death (hazard ratio 1.82, 95% CI 1.08-3.08). A similar association was observed for hospitalizations due to infections in 644 patients (hazard ratio 1.19, 95% CI 1.00-1.42 in the fully-adjusted model). Thus, our data support a role of mitochondrial dysfunction in increased cardiovascular disease and mortality risks as well as susceptibility to infections in patients with CKD.
CRIS-Team Scopus Importer:2019-07-02
Keywords: chronic kidney disease; infections; mitochondrial DNA copy number; mortality

Mobile Technology Affinity in Renal Transplant Recipients - Reber, Sandra Therese; Scheel, J.; Stößel, Lisa; Schieber, Katharina; Jank, S.; Luker, C.; Vitinius, F.; Grundmann, F.; Eckardt, Kai-Uwe; Prokosch, Hans-Ulrich; Erim, Yesim (Transplantation Proceedings, 2018)
Medication nonadherence is a common problem in renal transplant recipients (RTRs). Mobile health approaches to improve medication adherence are a current trend, and several medication adherence apps are available. However, it is unknown whether RTRs use these technologies and to what extent. In the present study, the mobile technology affinity of RTRs was analyzed. We hypothesized significant age differences in mobile technology affinity and that mobile technology affinity is associated with better cognitive functioning as well as higher educational level.A total of 109 RTRs (63% male) participated in the cross-sectional study, with an overall mean age of 51.8 ± 14.2 years. The study included the Technology Experience Questionnaire (TEQ) for the assessment of mobile technology affinity, a cognitive test battery, and sociodemographic data.Overall, 57.4% of the patients used a smartphone or tablet and almost 45% used apps. The TEQ sum score was 20.9 in a possible range from 6 (no affinity to technology) to 30 (very high affinity). Younger patients had significantly higher scores in mobile technology affinity. The only significant gender difference was found in having fun with using electronic devices: Men enjoyed technology more than women did. Mobile technology affinity was positively associated with cognitive functioning and educational level.Young adult patients might profit most from mobile health approaches. Furthermore, high educational level and normal cognitive functioning promote mobile technology affinity. This should be kept in mind when designing mobile technology health (mHealth) interventions for RTRs. For beneficial mHealth interventions, further research on potential barriers and desired technologic features is necessary to adapt apps to patients' needs.
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Moving Towards an EHR Data Quality Framework: The MIRACUM Approach - Kapsner, Lorenz A.; Kampf, Marvin; Seuchter, Susanne A.; Kamdje-Wabo, Gaetan; Gradinger, Tobias; Ganslandt, Thomas; Mate, Sebastian; Gründner, Julian; Kraska, Detlef; Prokosch, Hans-Ulrich (German Medical Data Sciences: Shaping Change – Creative Solutions for Innovative Medicine, 2019)
INTRODUCTION: Data quality (DQ) is an important prerequisite for secondary use of electronic health record (EHR) data in clinical research, particularly with regards to progressing towards a learning health system, one of the MIRACUM consortium's goals. Following the successful integration of the i2b2 research data repository in MIRACUM, we present a standardized and generic DQ framework. STATE OF THE ART: Already established DQ evaluation methods do not cover all of MIRACUM's requirements. CONCEPT: A data quality analysis plan was developed to assess common data quality dimensions for demographic-, condition-, procedure- and department-related variables of MIRACUM's research data repository. IMPLEMENTATION: A data quality analysis (DQA) tool was developed using R scripts packaged in a Docker image with all the necessary dependencies and R libraries for easy distribution. It integrates with the i2b2 data repository at each MIRACUM site, executes an analysis on the data and generates a DQ report. LESSONS LEARNED: Our DQA tool brings the analysis to the data and thus meets the MIRACUM data protection requirements. It evaluates established DQ dimensions of data repositories in a standardized and easily distributable way. This analysis allowed us to reveal and revise inconsistencies in earlier versions of the ETL jobs. The framework is portable, easy to deploy across different sites and even further adaptable to other database schemes. CONCLUSION: The presented framework provides the first step towards a unified, standardized and harmonized EHR DQ assessment in MIRACUM. DQ issues can now be systematically identified by individual hospitals to subsequently implement site- or consortium-wide feedback loops to increase data quality.
CRIS-Team Scopus Importer:2019-09-24
Keywords: clinical research; Data analysis; data quality; electronic health record

Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19 - Le, Trang T.; Gutierrez-Sacristan, Alba; Son, Jiyeon; Hong, Chuan; South, Andrew M.; Beaulieu-Jones, Brett K.; Loh, Ne Hooi Will; Luo, Yuan; Morris, Michele; Ngiam, Kee Yuan; Patel, Lav P.; Samayamuthu, Malarkodi J.; et al. (Scientific Reports, 2021)
Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease.
CRIS-Team Scopus Importer:2021-11-05

NEXT-GENERATION REFERENCE INTERVALS FOR PEDIATRIC HEMATOLOGY - Zierk, Jakob; Hirschmann, J.; Toddenroth, Dennis; Arzideh, F.; Streichert, T.; Haeckel, R.; Prokosch, Hans-Ulrich; Rauh, Manfred; Metzler, Markus (2017)
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Next-generation reference intervals for pediatric hematology - Zierk, Jakob; Hirschmann, Johannes; Toddenroth, Dennis; Arzideh, Farhad; Haeckel, Rainer; Bertram, Alexander; Cario, Holger; Frühwald, Michael C.; Groß, Hans Jürgen; Groening, Arndt; Grützner, Stefanie; Gscheidmeier, Thomas; et al. (Clinical Chemistry and Laboratory Medicine, 2019)
Interpreting hematology analytes in children is challenging due to the extensive changes in hematopoiesis that accompany physiological development and lead to pronounced sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, and limitations in current approaches to laboratory test result displays restrict their use when guiding clinical decisions. We employed an improved data-driven approach to create percentile charts from laboratory data collected during patient care in 10 German centers (9,576,910 samples from 358,292 patients, 412,905-1,278,987 samples per analyte). We demonstrate visualization of hematology test results using percentile charts and z-scores (www.pedref.org/hematology) and assess the potential of percentiles and z-scores to support diagnosis of different hematological diseases. We created percentile charts for hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count and platelet count in girls and boys from birth to 18 years of age. Comparison of pediatricians evaluating complex clinical scenarios using percentile charts versus conventional/tabular representations shows that percentile charts can enhance physician assessment in selected example cases. Age-specific percentiles and z-scores, compared with absolute test results, improve the identification of children with blood count abnormalities and the discrimination between different hematological diseases. The provided reference intervals enable precise assessment of pediatric hematology test results. Representation of test results using percentiles and z-scores facilitates their interpretation and demonstrates the potential of digital approaches to improve clinical decision-making.
CRIS-Team Scopus Importer:2019-05-09
Keywords: hematology; laboratory test result display; pediatric reference intervals

Noncurated Data Lead to Misinterpretation of Treatment Outcomes in Patients With Prostate Cancer After Salvage or Palliative Radiotherapy - Rutzner, Sandra; Ganslandt, Oliver Thomas; Fietkau, Rainer; Prokosch, Hans-Ulrich; Lubgan, Dorota (JCO Clinical Cancer Informatics, 2019)
PURPOSE: Clinical data warehouses (cDWHs) and cancer registry databases have enabled researchers to conduct clinical analytics with structured electronic health record data. However, these secondary electronic health record sources are often limited in scope because they do not capture the clinical information needed to understand complex clinical questions. Thus, we evaluated the effect of additional curation of data. MATERIALS AND METHODS: Clinical data sets of 149 patients with prostate cancer with biochemical recurrence after radical prostatectomy treated with salvage or palliative radiotherapy between 2008 and 2017 from our institutional cDWH and Gießener Tumor Documentation System (GTDS) were linked (data warehouse [DWH] population) for analyzing treatment outcomes. The linked data sets were manually curated (manual postprocessing [MPP], eg, incorporate data from established urologists). The primary outcomes were the impact on data quality of treatment outcomes and the time spent on data curation. RESULTS: We obtained significantly more information on disease progression and patient survival (nonsignificant) when using curated data; the biochemical progression-free survival rate at 5 years for the DWH and DWH plus MPP populations was 63% v 30% (P ≤ .001) and the overall survival rate was 84% v 81% (P = .479), respectively. The median deviation of completeness and the median concordance of clinical data values were 21.47% (range, 55.38%-100%) and 95.00% (range, 63.40%-100%), respectively. We spent 121 hours, 42 minutes on data curation, with most time required for laboratory values, accounting, for a total of 45 hours, 20 minutes (37.26%). CONCLUSION: Our analysis indicates that time-to-event outcomes for patients with prostate cancer cannot be extracted using secondary data sources (cDWH plus GTDS) only. Outcomes data differed between the electronic data (DWH) and the second manual extraction (DWH plus MPP) because of a lack of follow-up data. When using such unique database resources, only baseline characteristics can reliably be extracted.
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On-The-Fly Query Translation Between i2b2 and Samply in the German Biobank Node (GBN) Prototypes - Mate, Sebastian; Vormstein, Patric; Kadioglu, Dennis; Majeed, Raphael W; Lablans, Martin; Prokosch, Hans-Ulrich; Storf, Holger (Studies in health technology and informatics, 2017)
Information retrieval is a major challenge in medical informatics. Various research projects have worked on this task in recent years on an institutional level by developing tools to integrate and retrieve information. However, when it comes down to querying such data across institutions, the challenge persists due to the high heterogeneity of data and differences in software systems. The German Biobank Node (GBN) project faced this challenge when trying to interconnect four biobanks to enable distributed queries for biospecimens. All biobanks had already established integrated data repositories, and some of them were already part of research networks. Instead of developing another software platform, GBN decided to form a bridge between these. This paper describes and discusses a core component from the GBN project, the OmniQuery library, which was implemented to enable on-the-fly query translation between heterogeneous research infrastructures.
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Optimizing R with SparkR on a commodity cluster for biomedical research - Sedlmayr, Martin; Würfl, Tobias; Maier, Christian; Haeberle, Lothar; Fasching, Peter; Prokosch, Hans-Ulrich; Christoph, Jan (Computer Methods and Programs in Biomedicine, 2016)
Medical researchers are challenged today by the enormous amount of data collected in healthcare. Analysis methods such as genome-wide association studies (GWAS) are often computationally intensive and thus require enormous resources to be performed in a reasonable amount of time. While dedicated clusters and public clouds may deliver the desired performance, their use requires upfront financial efforts or anonymous data, which is often not possible for preliminary or occasional tasks. We explored the possibilities to build a private, flexible cluster for processing scripts in R based on commodity, non-dedicated hardware of our department.For this, a GWAS-calculation in R on a single desktop computer, a Message Passing Interface (MPI)-cluster, and a SparkR-cluster were compared with regards to the performance, scalability, quality, and simplicity.The original script had a projected runtime of three years on a single desktop computer. Optimizing the script in R already yielded a significant reduction in computing time (2 weeks). By using R-MPI and SparkR, we were able to parallelize the computation and reduce the time to less than three hours (2.6 h) on already available, standard office computers. While MPI is a proven approach in high-performance clusters, it requires rather static, dedicated nodes. SparkR and its Hadoop siblings allow for a dynamic, elastic environment with automated failure handling. SparkR also scales better with the number of nodes in the cluster than MPI due to optimized data communication.R is a popular environment for clinical data analysis. The new SparkR solution offers elastic resources and allows supporting big data analysis using R even on non-dedicated resources with minimal change to the original code. To unleash the full potential, additional efforts should be invested to customize and improve the algorithms, especially with regards to data distribution.
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Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC - Mate, Sebastian; Kampf, Marvin; Rödle, Wolfgang; Kraus, Stefan; Proynova, Rumyana; Silander, Kaisa; Ebert, Lars; Lablans, Martin; Schüttler, Christina; Knell, Christian; Eklund, Niina; Hummel, Michael; et al. (Applied Clinical Informatics, 2019)
BACKGROUND: High-quality clinical data and biological specimens are key for medical research and personalized medicine. The Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to facilitate access to such biological resources. The accompanying ADOPT BBMRI-ERIC project kick-started BBMRI-ERIC by collecting colorectal cancer data from European biobanks. OBJECTIVES: To transform these data into a common representation, a uniform approach for data integration and harmonization had to be developed. This article describes the design and the implementation of a toolset for this task. METHODS: Based on the semantics of a metadata repository, we developed a lexical bag-of-words matcher, capable of semiautomatically mapping local biobank terms to the central ADOPT BBMRI-ERIC terminology. Its algorithm supports fuzzy matching, utilization of synonyms, and sentiment tagging. To process the anonymized instance data based on these mappings, we also developed a data transformation application. RESULTS: The implementation was used to process the data from 10 European biobanks. The lexical matcher automatically and correctly mapped 78.48% of the 1,492 local biobank terms, and human experts were able to complete the remaining mappings. We used the expert-curated mappings to successfully process 147,608 data records from 3,415 patients. CONCLUSION: A generic harmonization approach was created and successfully used for cross-institutional data harmonization across 10 European biobanks. The software tools were made available as open source.
CRIS-Team Scopus Importer:2019-09-20

Patient Cohort Identification on Time Series Data Using the OMOP Common Data Model - Maier, Christian; Kapsner, Lorenz; Mate, Sebastian; Prokosch, Hans-Ulrich; Kraus, Stefan (Applied Clinical Informatics, 2021)
Background â The identification of patient cohorts for recruiting patients into clinical trials requires an evaluation of study-specific inclusion and exclusion criteria. These criteria are specified depending on corresponding clinical facts. Some of these facts may not be present in the clinical source systems and need to be calculated either in advance or at cohort query runtime (so-called feasibility query). Objectives â We use the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) as the repository for our clinical data. However, Atlas, the graphical user interface of OMOP, does not offer the functionality to perform calculations on facts data. Therefore, we were in search for a different approach. The objective of this study is to investigate whether the Arden Syntax can be used for feasibility queries on the OMOP CDM to enable on-The-fly calculations at query runtime, to eliminate the need to precalculate data elements that are involved with researchers' criteria specification. Methods â We implemented a service that reads the facts from the OMOP repository and provides it in a form which an Arden Syntax Medical Logic Module (MLM) can process. Then, we implemented an MLM that applies the eligibility criteria to every patient data set and outputs the list of eligible cases (i.e., performs the feasibility query). Results â The study resulted in an MLM-based feasibility query that identifies cases of overventilation as an example of how an on-The-fly calculation can be realized. The algorithm is split into two MLMs to provide the reusability of the approach. Conclusion â We found that MLMs are a suitable technology for feasibility queries on the OMOP CDM. Our method of performing on-The-fly calculations can be employed with any OMOP instance and without touching existing infrastructure like the Extract, Transform and Load pipeline. Therefore, we think that it is a well-suited method to perform on-The-fly calculations on OMOP.
CRIS-Team Scopus Importer:2021-02-12
Keywords: Arden Syntax; clinical data; electronic health records; information storage and retrieval; Medical Logic Modules

Patient portals: Objectives, acceptance, and effects on health outcome - A scoping review of reviews - Leb, Ines; Magnin, S.; Prokosch, Hans-Ulrich; Boeker, Martin (Studies in Health Technology and Informatics, 2021)
Patient portals provide patients access to their electronic health record and other functions as secure messaging. For over a decade, more and more patient portals are developed for various settings. The aim of this scoping review of reviews is to systematically search the literature for existing reviews to provide an overview of patient portals' objectives, acceptance and effects on outcome. We followed the PRISMA Statement and its extension for scoping reviews, and searched for articles published in 2011 2021. The 19 included articles were considerably heterogeneous concentrating on health outcome or patient portal facilitators and barriers.
CRIS-Team Scopus Importer:2021-10-22
Keywords: Electronic health record; Patient portal; Personal health record; Systematic review

Patient Recruitment System for Clinical Trials: Mixed Methods Study About Requirements at Ten University Hospitals - Fitzer, Kai; Haeuslschmid, Renate; Blasini, Romina; Altun, Fatma Betül; Hampf, Christopher; Freiesleben, Sherry; Macho, Philipp; Prokosch, Hans-Ulrich; Gulden, Christian (JMIR Medical Informatics, 2022)
Background: Clinical trials are the gold standard for advancing medical knowledge and improving patient outcomes. For their success, an appropriately sized cohort is required. However, patient recruitment remains one of the most challenging aspects of clinical trials. Information technology (IT) support systems-for instance, patient recruitment systems-may help overcome existing challenges and improve recruitment rates, when customized to the user needs and environment. Objective: The goal of our study is to describe the status quo of patient recruitment processes and to identify user requirements for the development of a patient recruitment system. Methods: We conducted a web-based survey with 56 participants as well as semistructured interviews with 33 participants from 10 German university hospitals. Results: We here report the recruitment procedures and challenges of 10 university hospitals. The recruitment process was influenced by diverse factors such as the ward, use of software, and the study inclusion criteria. Overall, clinical staff seemed more involved in patient identification, while the research staff focused on screening tasks. Ad hoc and planned screenings were common. Identifying eligible patients was still associated with significant manual efforts. The recruitment staff used Microsoft Office suite because tailored software were not available. To implement such software, data from disparate sources will need to be made available. We discussed concrete technical challenges concerning patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration, and we contributed to the support of developing a successful system. Conclusions: Identifying eligible patients is still associated with significant manual efforts. To fully make use of the high potential of IT in patient recruitment, many technical and process challenges have to be solved first. We contribute and discuss concrete technical challenges for patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration.
CRIS-Team Scopus Importer:2022-05-20
Keywords: clinical information systems; clinical trial; clinical trial recruitment support system; eHealth; electronic support; interview; patient recruitment system; patient screening; recruitment; requirements; survey; user needs

Perspectives for medical informatics - reusing the electronic medical record for clinical research - Prokosch, Hans-Ulrich; Ganslandt, Thomas (Methods of Information in Medicine, 2009)
Objectives: Even though today most university hospitals have already implemented commercial hospital information systems and started to build up comprehensive electronic medical records, reuse of such data for data warehousing and research purposes is still very rare. Given this situation, the focus of this paper is to present an overview on exemplary projects, which have already tackled this challenge, reflect on current initiatives within the United States of America and the European Union to establish IT infrastructures for clinical and translational research, and draw attention to new challenges in this area. Methods: This paper does not intend to provide a fully comprehensive review on all the issues of clinical routine data reuse. It is based, however, on a presentation of a large variety of historical, but also most recent activities in data warehousing, data retrieval and linking medical informatics with translational research. Results: The article presents an overview of the various international approaches to this issue and illustrates concepts and solutions which have been published, thus giving an impression of activities pursued in this field of medical informatics. Further, problems and open questions, which have also been named in the literature, are presented and three challenges (to establish comprehensive clinical data warehouses, to establish professional IT infrastructure applications supporting clinical trial data capture and to integrate medical record systems and clinical trial databases) related to this area of medical informatics are identified and presented. Conclusions: Translational biomedical research with the aim "to integrate bedside and biology" and to bridge the gap between clinical care and medical research today and in the years to come, provides a large and interesting field for medical informatics researchers. Especially the need for integrating clinical research projects with data repositories built up during documentation of routine clinical care, today still leaves many open questions and research challenges. Consideration of regulatory requirements, data privacy issues, data standards as well as people/organizational issues are prerequisites in order to vanquish existing obstacles. © Schattauer 2009.
UnivIS-Import:2015-03-09:Pub.2009.tech.IMMD.infome.perspe
Keywords: Data warehousing; IT infrastructure for clinical research; Reuse of EMR data; Translational biomedical research

Postponements in Use of Radiotherapy during the first Wave of the COVID-19 Pandemic? An Analysis of Hospital Data - Kapsner, Lorenz; Brunner, T.; Christiansen, H.; Kisser, U.; Mansoorian, Sina; Prokosch, Hans-Ulrich; Seuchter, S.; Vordermark, D.; Medenwald, D. (STRAHLENTHERAPIE UND ONKOLOGIE, 2022)
CRIS-Team WoS Importer:2022-06-03

Predicting Clinical Outcomes in Colorectal Cancer Using Machine Learning - Gründner, Julian; Prokosch, Hans-Ulrich; Stürzl, Michael; Croner, Roland S.; Christoph, Jan; Toddenroth, Dennis (Studies in health technology and informatics, 2018)
Using gene markers and other patient features to predict clinical outcomes plays a vital role in enhancing clinical decision making and improving prognostic accuracy. This work uses a large set of colorectal cancer patient data to train predictive models using machine learning methods such as random forest, general linear model, and neural network for clinically relevant outcomes including disease free survival, survival, radio-chemotherapy response (RCT-R) and relapse. The most successful predictive models were created for dichotomous outcomes like relapse and RCT-R with accuracies of 0.71 and 0.70 on blinded test data respectively. The best prediction models regarding overall survival and disease-free survival had C-Index scores of 0.86 and 0.76 respectively. These models could be used in the future to aid a decision for or against chemotherapy and improve survival prognosis. We propose that future work should focus on creating reusable frameworks and infrastructure for training and delivering predictive models to physicians, so that they could be readily applied to other diseases in practice and be continuously developed integrating new data.
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Proof-of-Concept Integration of Heterogeneous Biobank IT Infrastructures into a Hybrid Biobanking Network - Mate, Sebastian; Kadioglu, Dennis; Majeed, Raphael W; Stöhr, Mark R; Folz, Michael; Vormstein, Patric; Storf, Holger; Brucker, Daniel P; Keune, Dietmar; Zerbe, Norman; Hummel, Michael; Senghas, Karsten; et al. (Studies in health technology and informatics, 2017)
Cross-institutional biobank networks hold the promise of supporting medicine by enabling the exchange of associated samples for research purposes. Various initiatives, such as BBMRI-ERIC and German Biobank Node (GBN), aim to interconnect biobanks for enabling the compilation of joint biomaterial collections. However, building software platforms to facilitate such collaboration is challenging due to the heterogeneity of existing biobank IT infrastructures and the necessary efforts for installing and maintaining additional software components. As a remedy, this paper presents the concept of a hybrid network for interconnecting already existing software components commonly found in biobanks and a proof-of-concept implementation of two prototypes involving four biobanks of the German Biobank Node. Here we demonstrate the successful bridging of two IT systems found in many German biobanks - Samply and i2b2.
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Prospective Assessment of an innovative test for prostate cancer screening using the VITA process model framework - Gantner-Bär, Marion; Meier, Florian; Kolominsky-Rabas, Peter; Djanatliev, Anatoli; Metzger, Armin; Voigt, Wieland; Prokosch, Hans-Ulrich; Sedlmayr, Martin (Studies in health technology and informatics, 2014)
Healthcare innovations are crucial for enhancing patient treatment and a high-quality healthcare system. However, bringing new technologies, methods and procedures into the healthcare market is challenging. Enormous amounts of financial, personnel and organizational resources are required with no upfront certainty for the medical and economic benefit. A new and innovative approach uses interdisciplinary medical, technical and economic expertise to forecast effects of healthcare innovations already at the early research and concept phase of an idea and before major investments are made. A process model framework was developed to operationalize this structured assessment of healthcare innovations. The Visionary Iterative Tailored Approach (VITA) is based on conceptual modeling, simulation and health economics evaluation. Its application for the prospective assessment of an innovative prostate cancer screening is presented.<br
UnivIS-Import:2015-03-09:Pub.2014.tech.IMMD.IMMD7.prospe

Prototypical clinical trial registry based on fast healthcare interoperability resources (FHIR): Design and implementation study - Gulden, Christian; Blasini, Romina; Nassirian, Azadeh; Stein, Alexandra; Altun, Fatma Betül; Kirchner, Melanie; Prokosch, Hans-Ulrich; Boeker, Martin (JMIR Medical Informatics, 2021)
Background: Clinical trial registries increase transparency in medical research by making information and results of planned, ongoing, and completed studies publicly available. However, the registration of clinical trials remains a time-consuming manual task complicated by the fact that the same studies often need to be registered in different registries with different data entry requirements and interfaces. Objective: This study investigates how Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) may be used as a standardized format for exchanging and storing clinical trial records. Methods: We designed and prototypically implemented an open-source central trial registry containing records from university hospitals, which are automatically exported and updated by local study management systems. Results: We provided an architecture and implementation of a multisite clinical trials registry based on HL7 FHIR as a data storage and exchange format. Conclusions: The results show that FHIR resources establish a harmonized view of study information from heterogeneous sources by enabling automated data exchange between trial centers and central study registries.
CRIS-Team Scopus Importer:2021-02-26
Keywords: Clinical trials; Data sharing; Health information interoperability; HL7 FHIR; Trials registry

Quality Requirements for Electronic Health Record Systems*. A Japanese-German Information Management Perspective - Winter, Alfred; Takabayashi, Katsuhiko; Jahn, Franziska; Kimura, Eizen; Engelbrecht, Rolf; Haux, Reinhold; Honda, Masayuki; Huebner, Ursula H.; Inoue, Sozo; Kohl, Christian D.; Matsumoto, Takehiro; Matsumura, Yasushi; et al. (Methods of Information in Medicine, 2017)
For more than 30 years, there has been close cooperation between Japanese and German scientists with regard to information systems in health care. Collaboration has been formalized by an agreement between the respective scientific associations. Following this agreement, two joint workshops took place to explore the similarities and differences of electronic health record systems (EHRS) against the background of the two national healthcare systems that share many commonalities.To establish a framework and requirements for the quality of EHRS that may also serve as a basis for comparing different EHRS.Donabedian's three dimensions of quality of medical care were adapted to the outcome, process, and structural quality of EHRS and their management. These quality dimensions were proposed before the first workshop of EHRS experts and enriched during the discussions.The Quality Requirements Framework of EHRS (QRF-EHRS) was defined and complemented by requirements for high quality EHRS. The framework integrates three quality dimensions (outcome, process, and structural quality), three layers of information systems (processes and data, applications, and physical tools) and three dimensions of information management (strategic, tactical, and operational information management).Describing and comparing the quality of EHRS is in fact a multidimensional problem as given by the QRF-EHRS framework. This framework will be utilized to compare Japanese and German EHRS, notably those that were presented at the second workshop.
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recruIT: A cloud-native clinical trial recruitment support system based on Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) and the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) - Gulden, Christian; Macho, Philipp; Reinecke, Ines; Strantz, Cosima; Prokosch, Hans-Ulrich; Blasini, Romina (Computers in Biology and Medicine, 2024)
Background: Clinical trials (CTs) are foundational to the advancement of evidence-based medicine and recruiting a sufficient number of participants is one of the crucial steps to their successful conduct. Yet, poor recruitment remains the most frequent reason for premature discontinuation or costly extension of clinical trials. Methods: We designed and implemented a novel, open-source software system to support the recruitment process in clinical trials by generating automatic recruitment recommendations. The development is guided by modern, cloud-native design principles and based on Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) as an interoperability standard with the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) being used as a source of patient data. We evaluated the usability using the system usability scale (SUS) after deploying the application for use by study personnel. Results: The implementation is based on the OMOP CDM as a repository of patient data that is continuously queried for possible trial candidates based on given clinical trial eligibility criteria. A web-based screening list can be used to display the candidates and email notifications about possible new trial participants can be sent automatically. All interactions between services use HL7 FHIR as the communication standard. The system can be installed using standard container technology and supports more sophisticated deployments on Kubernetes clusters. End-users (n = 19) rated the system with a SUS score of 79.9/100. Conclusion: We contribute a novel, open-source implementation to support the patient recruitment process in clinical trials that can be deployed using state-of-the art technologies. According to the SUS score, the system provides good usability.
CRIS-Team Scopus Importer:2024-04-26

RECUR - Establishment of An Automated Digital Registry for Patients with Recurrent Stones in the Upper Urinary Tract - Walther, Tabea; Farin, Erik; Boeker, Martin; Prokosch, Hans-Ulrich; Binder, Harald; Praus, Friederike; Ploner, Nico; Fichtner, Urs Alexander; Horki, Petar; Haeuslschmid, Renate; Seuchter, Susanne; Gratzke, Christian; et al. (Gesundheitswesen, 2021)
Zusammenfassung Nierensteine werden wie Herz-Kreislauf-Erkrankungen und Diabetes mellitus aufgrund ihrer Haufigkeit zu den Volkskrankheiten gezahlt. Erkrankte konnen durch akute Schmerzen, wiederholte Krankenhausaufenthalte und relevante Folgeerkrankungen belastet sein. Daraus folgen auch erhebliche Kosten, die Gesellschaft und Gesundheitssystem tragen mussen. Die Rezidivrate liegt bei 50%. Mit dem Register fur RECurrente URolithiasis (RECUR) sollen bestehenden Evidenzlucken geschlossen werden. Dabei handelt es sich um ein prospektives longitudinales Register, dessen Aufbau und Implementierung vom Bundesministerium fur Bildung und Forschung (BMBF) im Rahmen der Forderung Aufbau modellhafter, patientenbezogener Register fur die Versorgungsforschung" finanziert wird. Es basiert auf der digitalen Infrastruktur der Medizininformatik-Initiative des BMBF. Ziel ist es, moglichst viele Patient*innen der 10 teilnehmenden Kliniken mit mehr als einer Nierenstein-Episode einzuschlie ss en, um neue Erkenntnisse uber Risikofaktoren, Diagnose- und Behandlungsalgorithmen zu erhalten. Im Rahmen des RECUR Projekts sollen neben klinischen Routinedaten auch Patient Reported Outcomes" von Patienten mit rezidivierenden Nierensteinen erhoben werden. Die Erhebung dieser Daten werden fur alle teilnehmenden Standorte in Form von digitalen Fragebogen mithilfe einer Smartphone App durchgefuhrt und mit den medizinischen Daten aus dem Krankenhausinformationssystemen in pseudonymisierter Form zusammengefuhrt. Das RECUR-Register hat durch seinen vollstandig foderierten, digitalen Ansatz einen modellhaften Charakter. Dieser ermoglicht die Rekrutierung vieler Patient*innen, die Erfassung eines breiten Datenspektrums und dessen Aufbereitung bei gleichzeitig geringem Verwaltungs- und Personalaufwand.
CRIS-Team WoS Importer:2021-12-03

Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals During the COVID-19 Lockdown - Kapsner, Lorenz; Kampf, Marvin; Seuchter, Susanne A.; Gründner, Julian; Gulden, Christian; Mate, Sebastian; Mang, Jonathan M.; Schüttler, Christina; Deppenwiese, Noemi; Krause, Linda; Zöller, Daniela; Balig, Julien; et al. (Frontiers in Public Health, 2021)
The COVID-19 pandemic has caused strains on health systems worldwide disrupting routine hospital services for all non-COVID patients. Within this retrospective study, we analyzed inpatient hospital admissions across 18 German university hospitals during the 2020 lockdown period compared to 2018. Patients admitted to hospital between January 1 and May 31, 2020 and the corresponding periods in 2018 and 2019 were included in this study. Data derived from electronic health records were collected and analyzed using the data integration center infrastructure implemented in the university hospitals that are part of the four consortia funded by the German Medical Informatics Initiative. Admissions were grouped and counted by ICD 10 chapters and specific reasons for treatment at each site. Pooled aggregated data were centrally analyzed with descriptive statistics to compare absolute and relative differences between time periods of different years. The results illustrate how care process adoptions depended on the COVID-19 epidemiological situation and the criticality of the disease. Overall inpatient hospital admissions decreased by 35% in weeks 1 to 4 and by 30.3% in weeks 5 to 8 after the lockdown announcement compared to 2018. Even hospital admissions for critical care conditions such as malignant cancer treatments were reduced. We also noted a high reduction of emergency admissions such as myocardial infarction (38.7%), whereas the reduction in stroke admissions was smaller (19.6%). In contrast, we observed a considerable reduction in admissions for non-critical clinical situations, such as hysterectomies for benign tumors (78.8%) and hip replacements due to arthrosis (82.4%). In summary, our study shows that the university hospital admission rates in Germany were substantially reduced following the national COVID-19 lockdown. These included critical care or emergency conditions in which deferral is expected to impair clinical outcomes. Future studies are needed to delineate how appropriate medical care of critically ill patients can be maintained during a pandemic.
CRIS-Team Scopus Importer:2021-02-05
Keywords: COVID-19; Germany; healthcare systems; inpatient hospital admissions; lockdown; medical informatics initiative; pandemic; university hospitals

Reference Interval Estimation from Mixed Distributions using Truncation Points and the Kolmogorov-Smirnov Distance (kosmic) - Zierk, Jakob; Arzideh, Farhad; Kapsner, Lorenz; Prokosch, Hans-Ulrich; Metzler, Markus; Rauh, Manfred (Scientific Reports, 2020)
Appropriate reference intervals are essential when using laboratory test results to guide medical decisions. Conventional approaches for the establishment of reference intervals rely on large samples from healthy and homogenous reference populations. However, this approach is associated with substantial financial and logistic challenges, subject to ethical restrictions in children, and limited in older individuals due to the high prevalence of chronic morbidities and medication. We implemented an indirect method for reference interval estimation, which uses mixed physiological and abnormal test results from clinical information systems, to overcome these restrictions. The algorithm minimizes the difference between an estimated parametrical distribution and a truncated part of the observed distribution, specifically, the Kolmogorov-Smirnov-distance between a hypothetical Gaussian distribution and the observed distribution of test results after Box-Cox-transformation. Simulations of common laboratory tests with increasing proportions of abnormal test results show reliable reference interval estimations even in challenging simulation scenarios, when <20% test results are abnormal. Additionally, reference intervals generated using samples from a university hospital’s laboratory information system, with a gradually increasing proportion of abnormal test results remained stable, even if samples from units with a substantial prevalence of pathologies were included. A high-performance open-source C++ implementation is available at https://gitlab.miracum.org/kosmic.
CRIS-Team Scopus Importer:2020-02-14

refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data - Ammer, Tatjana; Schuetzenmeister, Andre; Prokosch, Hans-Ulrich; Rauh, Manfred; Rank, Christopher M.; Zierk, Jakob (Scientific Reports, 2021)
Reference intervals are essential for the interpretation of laboratory test results in medicine. We propose a novel indirect approach to estimate reference intervals from real-world data as an alternative to direct methods, which require samples from healthy individuals. The presented refineR algorithm separates the non-pathological distribution from the pathological distribution of observed test results using an inverse approach and identifies the model that best explains the non-pathological distribution. To evaluate its performance, we simulated test results from six common laboratory analytes with a varying location and fraction of pathological test results. Estimated reference intervals were compared to the ground truth, an alternative indirect method (kosmic), and the direct method (N = 120 and N = 400 samples). Overall, refineR achieved the lowest mean percentage error of all methods (2.77%). Analyzing the amount of reference intervals within ± 1 total error deviation from the ground truth, refineR (82.5%) was inferior to the direct method with N = 400 samples (90.1%), but outperformed kosmic (70.8%) and the direct method with N = 120 (67.4%). Additionally, reference intervals estimated from pediatric data were comparable to published direct method studies. In conclusion, the refineR algorithm enables precise estimation of reference intervals from real-world data and represents a viable complement to the direct method.
CRIS-Team Scopus Importer:2021-08-27

Regional Differences in Thrombectomy Rates : Secondary use of Billing Codes in the MIRACUM (Medical Informatics for Research and Care in University Medicine) Consortium - Haverkamp, Christian; Ganslandt, Thomas; Horki, Petar; Boeker, Martin; Dörfler, Arnd; Schwab, Stefan; Berkefeld, Joachim; Pfeilschifter, Waltraud; Niesen, Wolf-Dirk; Egger, Karl; Kaps, Manfred; Brockmann, Marc A.; et al. (Clinical Neuroradiology, 2018)
Mechanical thrombectomy, in addition to intravenous (i.v.) thrombolysis is recommended for treatment of acute stroke in patients with large vessel occlusions (LVO) in the anterior circulation up to 6 h after symptom onset. We compared thrombectomy rates of eight university hospitals of the MIRACUM consortium to analyze the implementation of this guideline in clinical routine.Anonymized billing data in a standardized format were loaded into a local i2b2 data warehouse by applying already existing extract, transform and load (ETL) routines. A locally executed uniform SQL (structured query language) query delivered aggregated site data for all inpatients with a discharge diagnosis of ischemic stroke (ICD-10 I63) containing counts for type of acute treatment, type of admission and age groups, which were centrally analyzed with R.From 2014 to 2016, the thrombectomy rate almost doubled from a mean of 4.7% to 9.6%, although significant differences between centers exist (range in 2016: 5.8-17%). The number of drip-and-ship procedures increased in 3 out of 8 centers. There was no evidence for a decrease in thrombectomy rates during weekends/holiday or among patients older than 80 years, but this age group is more likely to receive i.v. recombinant tissue plasminogen activator (rtPA).The observed increase of thrombectomy rates and drip-and-ship procedures without a significant difference between weekdays and weekends or patients of different ages is substantiating a rapid implementation of stroke guidelines within the analyzed neurovascular centers. The prototype of the MIRACUM Data Integration Center already contributes to health services research in Germany.
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Reproducibility in 2023 - An End-to-End Template for Analysis and Manuscript Writing - Mang, Jonathan; Prokosch, Hans-Ulrich; Kapsner, Lorenz (Studies in health technology and informatics, 2023)
Reproducibility imposes some special requirements at different stages of each project, including reproducible workflows for the analysis including to follow best practices regarding code style and to make the creation of the manuscript reproducible as well. Available tools therefore include version control systems such as Git and document creation tools such as Quarto or R Markdown. However, a re-usable project template mapping the entire process from performing the data analysis to finally writing the manuscript in a reproducible manner is yet lacking. This work aims to fill this gap by presenting an open source template for conducting reproducible research projects utilizing a containerized framework for both developing and conducting the analysis and summarizing the results in a manuscript. This template can be used instantly without any customization.
CRIS-Team Scopus Importer:2023-06-02
Keywords: Computer and information sciences; Container; Data sharing; Reproducibility; Template

Requirements analysis for a clinical decision support system aiming at improving the artificial nutrition of critically ill patients - Schüttler, Christina; Hinderer, Marc; Kraus, Stefan; Lang, Anne-Katharina; Prokosch, Hans-Ulrich; Castellanos, Ixchel (German medical data sciences: visions and bridges; proceedings of the 62nd annual meeting of the German Association of Medical Informatics, Biometry and Epidemiology (GMDS e.V.) in Oldenburg - GMDS 2017, 2017)
UnivIS-Import:2018-09-11:Pub.2017.tech.IMMD.infome.requir

Requirements Analysis for a Clinical Decision Support System Aiming at Improving the Artificial Nutrition of Critically Ill Patients - Schüttler, Christina; Hinderer, Marc; Kraus, Stefan; Lang, Anne-Katharina; Prokosch, Hans-Ulrich; Castellanos, Ixchel (Studies in health technology and informatics, 2017)
Nutrition support is an important aspect regarding the care of critically ill patients. Malnutrition affects the recovery process negatively. However, the impact on the clinical outcome is often underestimated in complex clinical settings due to several factors hindering optimization of nutrition.To identify the requirements for a clinical decision support system that enables the medical staff to improve its patients' nutritional status.A literature review and interviews with two senior physicians were conducted to refine the requirements for the support system as well as to determine the inclusion criteria for a subsequent intervention study.The analysis resulted in: (i) the identification of 4 measurement parameters for the assessment of the nutrition status; (ii) the graphical layout in adherence to the standards-based implementation approach for the creation of multi-patient dashboards; (iii) the definition of the study group. The nutrition dashboard will be implemented and integrated based on the set requirements, followed by an intervention study evaluating the dashboard's efficacy.
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Requirements for a cross-location biobank IT infrastructure : Survey of stakeholder input on the establishment of a biobank network of the German Biobank Alliance (GBA) - Schüttler, Christina; Buschhueter, N.; Doellinger, C.; Ebert, L.; Hummel, M.; Linde, J.; Prokosch, Hans-Ulrich; Proynova, R.; Lablans, M. (Pathologe, 2018)
BACKGROUND: The large number of biobanks within Germany results in a high degree of heterogeneity with regard to the IT components used at the respective locations. Within the German Biobank Alliance (GBA), 13 biobanks implement harmonized processes for the provision of biomaterial and accompanying data. OBJECTIVES: The networking of the individual biobanks and the associated harmonisation of the IT infrastructure should facilitate access to biomaterial and related clinical data. METHODS: For this purpose, the relevant target groups were first identified in order to determine their requirements for IT solutions to be developed in a workshop. RESULTS: Of the seven identified interest groups, three were initially invited to a first round of discussions. The stakeholder input expressed resulted in a catalogue of requirements with regard to IT support for (i) a sample and data request, (ii) the handling of patient consent and inclusion, and (iii) the subsequent evaluation of the sample and data request. CONCLUSIONS: The next step is to design the IT solutions as prototypes based on these requirements. In parallel, further user groups are being surveyed in order to be able to further concretise the specifications for development.
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Resistance to antibacterial therapy in pediatric febrile urinary tract infections—a single-center analysis - Raupach, Thomas; Held, Jürgen; Prokosch, Hans-Ulrich; Rascher, Wolfgang; Zierk, Jakob (Journal of Pediatric Urology, 2019)
Background: Febrile urinary tract infections (UTIs) are common serious bacterial infections in childhood and require early diagnosis and antibacterial therapy. However, considerable uncertainty exists regarding the optimal antibacterial agent for primary treatment of pediatric UTIs. Additionally, patterns of susceptibility and resistance change over time and microbiological in vitro resistance is not necessarily associated with treatment failure. Here, we analyzed uropathogens, their resistance patterns, and response to antibacterial treatment in children with acute pyelonephritis. Methods: We used billing codes (international classification of diseases) to identify all inpatients aged 0–18 years with febrile UTIs in a German university tertiary care center from 2009 until 2018. Microbial results were retrieved from the laboratory information system for all children, and treatment regimen and treatment response were analyzed in a subgroup of children. Results: We identified 907 children with acute pyelonephritis; in 590 cases (65%) an uropathogen was detected. Escherichia coli (60.8%), Enterococcus faecalis (13.2%), Klebsiella pneumoniae (7.0%), Proteus spp. (5.2%), and Pseudomonas aeruginosa (4.2%) were the most common pathogens. 353 of 436 E. coli isolates (81.0%) were susceptible or intermediate to aminopenicillin/β-lactamase-inhibitor (BLI) combinations. We examined 52 cases where E. coli was resistant to initial therapy with aminopenicillin/BLI combinations: Therapy was changed in 35 cases (67%) and left unchanged in 17 cases (33%), and we found no significant differences in C-reactive protein and leucocyte count in blood and urine between both groups after 3 days. Conclusions: We present the spectrum of uropathogens and susceptibility test results in pediatric UTIs in a tertiary care center. Our findings suggest a satisfactory response to first-line therapy with aminopenicillin/BLI combinations.
CRIS-Team Scopus Importer:2019-12-03
Keywords: Antibiotic susceptibility/resistance; Escherichia coli; Febrile urinary tract infections; Pediatrics

RIbench: A Proposed Benchmark for the Standardized Evaluation of Indirect Methods for Reference Interval Estimation - Ammer, Tatjana; Schuetzenmeister, Andre; Prokosch, Hans-Ulrich; Zierk, Jakob; Rank, Christopher M.; Rauh, Manfred (Clinical Chemistry, 2022)
Background Indirect methods leverage real-world data for the estimation of reference intervals. These constitute an active field of research, and several methods have been developed recently. So far, no standardized tool for evaluation and comparison of indirect methods exists. Methods We provide RIbench, a benchmarking suite for quantitative evaluation of any existing or novel indirect method. The benchmark contains simulated test sets for 10 biomarkers mimicking routine measurements of a mixed distribution of non-pathological (reference) values and pathological values. The non-pathological distributions represent 4 common distribution types: normal, skewed, heavily skewed, and skewed-and-shifted. To identify strengths and weaknesses of indirect methods, test sets have varying sample sizes and pathological distributions differ in location, extent of overlap, and fraction. For performance evaluation, we use an overall benchmark score and sub-scores derived from absolute z-score deviations between estimated and true reference limits. We illustrate the application of RIbench by evaluating and comparing the Hoffmann method and 4 modern indirect methods -TML (Truncated-Maximum-Likelihood), kosmic, TMC (Truncated-Minimum-Chi-Square), and refineR- against one another and against a nonparametric direct method (n = 120). Results For the modern indirect methods, pathological fraction and sample size had a strong influence on the results: With a pathological fraction up to 20% and a minimum sample size of 5000, most methods achieved results comparable or superior to the direct method. Conclusions We present RIbench, an open-source R-package, for the systematic evaluation of existing and novel indirect methods. RIbench can serve as a tool for enhancement of indirect methods, improving the estimation of reference intervals.
CRIS-Team WoS Importer:2022-11-04

Samply.MDR - A Metadata Repository and Its Application in Various Research Networks - Kadioglu, Dennis; Breil, Bernhard; Knell, Christian; Lablans, Martin; Mate, Sebastian; Schlue, Danijela; Serve, Hubert; Storf, Holger; Ückert, Frank; Wagner, Thomas; Weingardt, Paul; Prokosch, Hans-Ulrich (Studies in health technology and informatics, 2018)
Collaboration in medical research is becoming common, especially for collecting relevant cases across institutional boundaries. If the data, which is usually very heterogeneously formalized and structured, can be integrated, such a collaboration can facilitate research. An absolute prerequisite for this is an extensive description about the formalization and exact meaning of every data element contained in a dataset. This information is commonly known as metadata. Various research networking projects tackle this challenge with the development of concepts and IT tools. The Samply Metadata Repository (Samply.MDR) is a solution for managing and publishing such metadata in a standardized and reusable way. In this article we present the structure and features of the Samply.MDR as well as its flexible usability by giving an overview about its application in various projects.
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Secure Secondary Use of Clinical Data with Cloud-based NLP Services. Towards a Highly Scalable Research Infrastructure - Christoph, Jan; Griebel, Lena; Leb, Ines; Engel, Igor; Köpcke, Felix; Toddenroth, Dennis; Prokosch, Hans-Ulrich; Laufer, J.; Marquardt, K.; Sedlmayr, Martin (Methods of Information in Medicine, 2015)
The secondary use of clinical data provides large opportunities for clinical and translational research as well as quality assurance projects. For such purposes, it is necessary to provide a flexible and scalable infrastructure that is compliant with privacy requirements. The major goals of the cloud4health project are to define such an architecture, to implement a technical prototype that fulfills these requirements and to evaluate it with three use cases.The architecture provides components for multiple data provider sites such as hospitals to extract free text as well as structured data from local sources and de-identify such data for further anonymous or pseudonymous processing. Free text documentation is analyzed and transformed into structured information by text-mining services, which are provided within a cloud-computing environment. Thus, newly gained annotations can be integrated along with the already available structured data items and the resulting data sets can be uploaded to a central study portal for further analysis.Based on the architecture design, a prototype has been implemented and is under evaluation in three clinical use cases. Data from several hundred patients provided by a University Hospital and a private hospital chain have already been processed.Cloud4health has shown how existing components for secondary use of structured data can be complemented with text-mining in a privacy compliant manner. The cloud-computing paradigm allows a flexible and dynamically adaptable service provision that facilitates the adoption of services by data providers without own investments in respective hardware resources and software tools.
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Shift of radiotherapy use during the first wave of the COVID-19 pandemic? An analysis of German inpatient data - Medenwald, Daniel; Brunner, Thomas; Christiansen, Hans; Kisser, Ulrich; Mansoorian, Sina; Vordermark, Dirk; Prokosch, Hans-Ulrich; Seuchter, Susanne A.; Kapsner, Lorenz (Strahlentherapie und Onkologie, 2022)
Objective: To assess the change in inpatient radiotherapy related to COVID-19 lockdown measures during the first wave of the pandemic in 2020. Methods: We included cases hospitalized between January 1 and August 31, 2018–2020, with a primary ICD-10 diagnosis of C00–C13, C32 (head and neck cancer, HNC) and C53 (cervical cancer, CC). Data collection was conducted within the Medical Informatics Initiative. Outcomes were fractions and admissions. Controlling for decreasing hospital admissions during holidays, calendar weeks of 2018/2019 were aligned to Easter 2020. A lockdown period (LP; 16/03/2020–02/08/2020) and a return-to-normal period (RNP; 04/05/2020–02/08/2020) were defined. The study sample comprised a control (admission 2018/19) and study cohort (admission 2020). We computed weekly incidence and IR ratios from generalized linear mixed models. Results: We included 9365 (CC: 2040, HNC: 7325) inpatient hospital admissions from 14 German university hospitals. For CC, fractions decreased by 19.97% in 2020 compared to 2018/19 in the LP. In the RNP the reduction was 28.57% (p < 0.001 for both periods). LP fractions for HNC increased by 10.38% (RNP: 9.27%; p < 0.001 for both periods). Admissions for CC decreased in both periods (LP: 10.2%, RNP: 22.14%), whereas for HNC, admissions increased (LP: 2.25%, RNP: 1.96%) in 2020. Within LP, for CC, radiotherapy admissions without brachytherapy were reduced by 23.92%, whereas surgery-related admissions increased by 20.48%. For HNC, admissions with radiotherapy increased by 13.84%, while surgery-related admissions decreased by 11.28% in the same period. Conclusion: Related to the COVID-19 lockdown in an inpatient setting, radiotherapy for HNC treatment became a more frequently applied modality, while admissions of CC cases decreased.
CRIS-Team Scopus Importer:2022-01-21
Keywords: Admissions; Covid-19 pandemic; Germany; Lockdown; Radiotherapy

Stakeholder perspectives on the key components of a digital service platform supporting dementia - Digidem Bayern - Reichold, Michael; Dietzel, Nikolas; Karrer, Linda; Grässel, Elmar; Kolominsky-Rabas, Peter; Prokosch, Hans-Ulrich (Studies in Health Technology and Informatics, 2020)
The increasing number of people with dementia and caregiving relatives will require a change in the provision of dementia-related services in the future. Digital technologies are a force for change. The new project digiDEM Bayern with its digital services on a digital platform and a digital patient registry should help to improve the situation for people with dementia and their caregivers especially in rural settings. An online survey among service providers for people with dementia and caregiving relatives in Bavaria was conducted to find out how they assess the current landscape of digital and non-digital service offers for people with dementia and their caregivers. The results of the survey have revealed that there is currently a large gap in the provision of digital services varying between the different categories surveyed. digiDEM Bayern addresses this gap with its digital dementia-related service platform.
CRIS-Team Scopus Importer:2021-04-19
Keywords: Dementia; Digital; Informal caregiver; Platform; Services; Stakeholder

Standards-Based Procedural Phenotyping: The Arden Syntax on i2b2 - Mate, Sebastian; Castellanos, Ixchel; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Kraus, Stefan (Studies in health technology and informatics, 2017)
Phenotyping, or the identification of patient cohorts, is a recurring challenge in medical informatics. While there are open source tools such as i2b2 that address this problem by providing user-friendly querying interfaces, these platforms lack semantic expressiveness to model complex phenotyping algorithms. The Arden Syntax provides procedural programming language construct, designed specifically for medical decision support and knowledge transfer. In this work, we investigate how language constructs of the Arden Syntax can be used for generic phenotyping. We implemented a prototypical tool to integrate i2b2 with an open source Arden execution environment. To demonstrate the applicability of our approach, we used the tool together with an Arden-based phenotyping algorithm to derive statistics about ICU-acquired hypernatremia. Finally, we discuss how the combination of i2b2's user-friendly cohort pre-selection and Arden's procedural expressiveness could benefit phenotyping.
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Strategies for biobank networks : Classification of different approaches for locating samples and an outlook on the future within the BBMRI-ERIC - Lablans, Martin; Kadioglu, Dennis; Mate, Sebastian; Leb, Ines; Prokosch, Hans-Ulrich; Ueckert, Frank (Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2016)
Medical research projects often require more biological material than can be supplied by a single biobank. For this reason, a multitude of strategies support locating potential research partners with matching material without requiring centralization of sample storage.Classification of different strategies for biobank networks, in particular for locating suitable samples. Description of an IT infrastructure combining these strategies.Existing strategies can be classified according to three criteria: (a) granularity of sample data: coarse bank-level data (catalogue) vs. fine-granular sample-level data, (b) location of sample data: central (central search service) vs. decentral storage (federated search services), and (c) level of automation: automatic (query-based, federated search service) vs. semi-automatic (inquiry-based, decentral search). All mentioned search services require data integration. Metadata help to overcome semantic heterogeneity.The "Common Service IT" in BBMRI-ERIC (Biobanking and BioMolecular Resources Research Infrastructure) unites a catalogue, the decentral search and metadata in an integrated platform. As a result, researchers receive versatile tools to search suitable biomaterial, while biobanks retain a high degree of data sovereignty.Despite their differences, the presented strategies for biobank networks do not rule each other out but can complement and even benefit from each other.
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Studies on COVID-19 lethality: Causes and dynamics at German University Hospitals Letalität von Patienten mit COVID-19: Untersuchungen zu Ursachen und Dynamik an deutschen Universitätsklinika - Schüttler, Jürgen; Mang, Jonathan M.; Kapsner, Lorenz; Seuchter, Susanne A.; Binder, Harald; Zöller, Daniela; Kohlbacher, Oliver; Boeker, Martin; Zacharowski, Kai; Rohde, Gernot; Balig, Julien; Kampf, Marvin O.; et al. (Anästhesiologie & Intensivmedizin, 2021)
Background: In the initial phase of the COVID-19 pandemic, a lower incidence and death rate was observed in Germany compared to its neighbouring countries, but some studies showed comparatively high death rates in ventilated COVID-19 patients. Methods: In this retrospective analysis, hospital stays of COVID-19 patients at 14 German university hospitals were analysed. For this purpose, local data integration centres of the German Medical Informatics Initiative (MII) combined their data to present death rates in different subgroups depending on gender, age, length of stay in the intensive care unit, ventilation and in combination with different comorbidities. Results: The total lethality rate in 1,318 COVID-19 patients was 18.8 %. In ventilated cases, the lethality rate was 38.8%. Common comorbidities were renal insufficiency (35.2 %), aplastic and other anaemia (26.0 %) diabetes mellitus (21.1 %). The average length of stay was 18 days, or 28 days in case of ventilated patients. Lethality decreased from 20.7 % to 12.7 % over the observation period. Conclusion: The observed decline in lethality rates may be explained with the continuous optimisation of COVID-19 treatment, increasing experience and improved therapy recommendations. The progress made so far by the MII allows cross-consortium analyses to be carried out just in time to better address the challenges of the COVID-19 pandemic.
CRIS-Team Scopus Importer:2021-06-25
Keywords: COVID-19; Lethality; Medical Informatics Initiative; SARS-CoV-2

Supporting Molecular Tumor Boards in Molecular-Guided Decision-Making - The Current Status of Five German University Hospitals - Hinderer, Marc; Boerries, Melanie; Haller, Florian; Wagner, Sebastian; Sollfrank, Stefanie; Acker, Till; Prokosch, Hans-Ulrich; Christoph, Jan (Studies in health technology and informatics, 2017)
German university hospitals have started to establish molecular tumor boards in order to enable physicians to make molecular-guided decisions.Our aim was to describe the organizational structure and procedures which are currently supporting the molecular tumor boards of five German university hospitals.We conducted semi-structured interviews with experts of five university hospitals between December 2016 and February 2017.We observed heterogeneity in both the organization of genetic testing and the management of the molecular tumor boards among the five hospitals. They used free-text documents in most of their support procedures rather than machine-readable documents.There are three potentialities to support the process from genetic testing to reporting within the molecular tumor boards: (i) standardized pipeline to integrate automated variant calling and annotation; (ii) tools supporting the experts in creating their reports and presentations and (iii) implementing pharmacogenomic CDSS into clinical routine.
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Keywords: Clinical decision-making; Personalized medicine; Pharmacogenetics

The Architecture of a Feasibility Query Portal for Distributed COVID-19 Fast Healthcare Interoperability Resources (FHIR) Patient Data Repositories: Design and Implementation Study - Gründner, Julian; Deppenwiese, Noemi; Folz, Michael; Koehler, Thomas; Kroll, Bjoern; Prokosch, Hans-Ulrich; Rosenau, Lorenz; Ruehle, Mathias; Scheidl, Marc-Anton; Schüttler, Christina; Sedlmayr, Brita; Twrdik, Alexander; et al. (JMIR Medical Informatics, 2022)
Background: An essential step in any medical research project after identifying the research question is to determine if there are sufficient patients available for a study and where to find them. Pursuing digital feasibility queries on available patient data registries has proven to be an excellent way of reusing existing real-world data sources. To support multicentric research, these feasibility queries should be designed and implemented to run across multiple sites and securely access local data. Working across hospitals usually involves working with different data formats and vocabularies. Recently, the Fast Healthcare Interoperability Resources (FHIR) standard was developed by Health Level Seven to address this concern and describe patient data in a standardized format. The Medical Informatics Initiative in Germany has committed to this standard and created data integration centers, which convert existing data into the FHIR format at each hospital. This partially solves the interoperability problem; however, a distributed feasibility query platform for the FHIR standard is still missing. Objective: This study described the design and implementation of the components involved in creating a cross-hospital feasibility query platform for researchers based on FHIR resources. This effort was part of a large COVID-19 data exchange platform and was designed to be scalable for a broad range of patient data. Methods: We analyzed and designed the abstract components necessary for a distributed feasibility query. This included a user interface for creating the query, backend with an ontology and terminology service, middleware for query distribution, and FHIR feasibility query execution service. Results: We implemented the components described in the Methods section. The resulting solution was distributed to 33 German university hospitals. The functionality of the comprehensive network infrastructure was demonstrated using a test data set based on the German Corona Consensus Data Set. A performance test using specifically created synthetic data revealed the applicability of our solution to data sets containing millions of FHIR resources. The solution can be easily deployed across hospitals and supports feasibility queries, combining multiple inclusion and exclusion criteria using standard Health Level Seven query languages such as Clinical Quality Language and FHIR Search. Developing a platform based on multiple microservices allowed us to create an extendable platform and support multiple Health Level Seven query languages and middleware components to allow integration with future directions of the Medical Informatics Initiative. Conclusions: We designed and implemented a feasibility platform for distributed feasibility queries, which works directly on FHIR-formatted data and distributed it across 33 university hospitals in Germany. We showed that developing a feasibility platform directly on the FHIR standard is feasible.
CRIS-Team WoS Importer:2022-07-01

The clinical data intelligence project - Sonntag, Daniel; Tresp, Volker; Zillner, Sonja; Hammon, Matthias; Reis, André; Fasching, Peter; Sedlmayr, Martin; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Budde, Clemens; Schmidt, Danilo; Hinrichs, Carl; et al. (Informatik-Spektrum, 2015)
UnivIS-Import:2017-12-18:Pub.2015.tech.IMMD.infome.thecli

The COVID-19 Data Exchange Platform of the German University Medicine - Prokosch, Hans-Ulrich; Bahls, Thomas; Bialke, Martin; Eils, Jürgen; Fegeler, Christian; Gründner, Julian; Haarbrandt, Birger; Hampf, Christopher; Hoffmann, Wolfgang; Hund, Hauke; Kampf, Marvin; Kapsner, Lorenz; et al. (Challenges of Trustable AI and Added-Value on Health, 2022)
COVID-19 has challenged the healthcare systems worldwide. To quickly identify successful diagnostic and therapeutic approaches large data sharing approaches are inevitable. Though organizational clinical data are abundant, many of them are available only in isolated silos and largely inaccessible to external researchers. To overcome and tackle this challenge the university medicine network (comprising all 36 German university hospitals) has been founded in April 2020 to coordinate COVID-19 action plans, diagnostic and therapeutic strategies and collaborative research activities. 13 projects were initiated from which the CODEX project, aiming at the development of a Germany-wide Covid-19 Data Exchange Platform, is presented in this publication. We illustrate the conceptual design, the stepwise development and deployment, first results and the current status.
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The effect object paradigm - a means to support medication safety with clinical decision support - Patapovas, Andrius; Pfistermeister, Barbara; Tarkhov, Aleksey; Terfloth, Lothar; Maas, Renke; Fromm, Martin; Kornhuber, Johannes; Prokosch, Hans-Ulrich; Bürkle, Thomas (Studies in health technology and informatics, 2014)
In many countries, officially approved drug information known as summary of product characteristics (SPC) is mostly available in text form, which cannot be used for Clinical Decision Support Systems (CDSS). It may be essential however to substantiate CDSS advice with such legally binding text snippets. In an attempt to link various drug data sources including SPC towards a CDSS to support medication safety in psychiatric patients we arrived at the notion of an effect object.A requirements analysis revealed data items and data structure which are needed from the patient and from the drug information source for the CDSS functionality. Published drug data modelling approaches were analyzed and found unsuitable. A conceptional database modeling approach using top down and bottom up modeling was performed.The schema based data model implemented within the django framework centered on SPC "effect objects" which comprise all SPC data required for the respective CDSS function such as search for contraindications in the proposed medication. Today six effect objects have been defined for contraindications and warnings, missing indications, adverse effects, drug-drug interactions, dosing and pharmacokinetics.The transformation of SPC data to a database-driven "effect objects" structure permits decoupling between the CDSS functions and different underlying data sources and supports the design of reusable, stable and verified CDSS functions.
EVALuna2:127

The effects of exercise programs on cognition, activities of daily living, and neuropsychiatric symptoms in community-dwelling people with dementia-a systematic review - Steichele, Kathrin; Keefer, Anne; Dietzel, Nikolas; Grässel, Elmar; Prokosch, Hans-Ulrich; Kolominsky-Rabas, Peter (Alzheimer's Research and Therapy, 2022)
Background: The prevalence of dementia is expected to increase dramatically. Due to a lack of pharmacological treatment options for people with dementia, non-pharmacological treatments such as exercise programs have been recommended to improve cognition, activities of daily living, and neuropsychiatric symptoms. However, inconsistent results have been reported across different trials, mainly because of the high heterogeneity of exercise modalities. Thus, this systematic review aims to answer the questions whether exercise programs improve cognition, activities of daily living as well as neuropsychiatric symptoms in community-dwelling people with dementia.
CRIS-Team WoS Importer:2022-08-05

The experience of physicians in pharmacogenomic clinical decision support within eight German university hospitals - Hinderer, Marc; Boeker, Martin; Wagner, Sebastian A.; Binder, Harald; Sckert, Frank; Newe, Stephanie; Huelsemann, Jan L.; Neumaier, Michael; Schade-Brittinger, Carmen; Acker, Till; Prokosch, Hans-Ulrich; Sedlmayr, Brita (Pharmacogenomics, 2017)
The aim of this study was to assess the physicians' attitude, their knowledge and their experience in pharmacogenomic clinical decision support in German hospitals.We conducted an online survey to address physicians of 13 different medical specialties across eight German university hospitals. In total, 564 returned questionnaires were analyzed.The remaining knowledge gap, the uncertainty of test reimbursement and the physicians' lack of awareness of existing pharmacogenomic clinical decision support systems (CDSS) are the major barriers for implementing pharmacogenomic CDSS into German hospitals. Furthermore, pharmacogenomic CDSS are most effective in the form of real-time decision support for internists.Physicians in German hospitals require additional education of both genetics and pharmacogenomics. They need to be provided with access to relevant pharmacogenomic CDSS.
EVALuna2:186

The generic Informed Consent Service gICS®: implementation and benefits of a modular consent software tool to master the challenge of electronic consent management in research - Rau, Henriette; Geidel, Lars; Bialke, Martin; Blumentritt, Arne; Langanke, Martin; Liedtke, Wenke; Pasewald, Sandra; Stahl, Dana; Bahls, Thomas; Maier, Christian; Prokosch, Hans-Ulrich; Hoffmann, Wolfgang (Journal of Translational Medicine, 2020)
BACKGROUND: Defining and protecting participants' rights is the aim of several ethical codices and legal regulations. According to these regulations, the Informed Consent (IC) is an inevitable element of research with human subjects. In the era of "big data medicine", aspects of IC become even more relevant since research becomes more complex rendering compliance with legal and ethical regulations increasingly difficult. METHODS: Based on literature research and practical experiences gathered by the Institute for Community Medicine (ICM), University Medicine Greifswald, requirements for digital consent management systems were identified. RESULTS: To address the requirements, the free-of-charge, open-source software "generic Informed Consent Service" (gICS®) was developed by ICM to provide a tool to facilitate and enhance usage of digital ICs for the international research community covering various scenarios. gICS facilitates IC management based on IC modularisation and supports various workflows within research, including (1) electronic depiction of paper-based consents and (2) fully electronic consents. Numerous projects applied gICS and documented over 336,000 ICs and 2400 withdrawals since 2014. DISCUSSION: Since the consent's content is a prerequisite for securing participants' rights, application of gICS is no guarantee for legal compliance. However, gICS supports fine-granular consents and accommodation of differentiated consent states, which can be directly exchanged between systems, allowing automated data processing. CONCLUSION: gICS simplifies and supports sustained IC management as a major key to successfully conduct studies and build trust in research with human subjects. Therefore, interested researchers are invited to use gICS and provide feedback for further improvements.
CRIS-Team Scopus Importer:2020-08-07
Keywords: Consent management; GDPR; General data protection regulation; Informed consent

The journey to establishing an IT-infrastructure within the German Biobank Alliance - Schüttler, Christina; Prokosch, Hans-Ulrich; Hummel, Michael; Lablans, Martin; Kroll, Björn; Engels, Cäcilia (PLoS ONE, 2021)
Background: Biobanks ensure the long-term storage and accessibility of biospecimens and corresponding data sets. Thus, they form the foundation for many research projects which may contribute to improving medical care. With the establishment of the German Biobank Node and Alliance, expertise in biobanking is bundled and strengthened. An important component within this research infrastructure is the set-up of an information technology (IT) network for allowing feasibility requests across individual biobanks. Objective: We aim to describe relevant aspects that have shaped the journey to interconnect biobanks, to enhance their visibility within the research-community, to harmonize data, and to enable feasibility searches to support access to available data and biosamples. Methods: To achieve this task, we resorted to a wide variety of methods: we ran a requirement analysis, decided on the mode of operation for the federated team of IT-developers and on the development approach itself, took related national and international initiatives into account, and concluded with evaluations of the developed software artefacts and the operation of the entire chain of applications. Results: We drew an IT framework including all heterogeneous data aspects derived from our requirement analysis and developed a comprehensive IT infrastructure. The successful implementation benefited from a smooth interaction of a federated IT team distributed across all participating sites that was even able to manage a major technology change mid-project. Authentication and project management services from associated partners could be integrated and the graphic user interface for an intuitive search tool for biospecimens was designed iteratively. The developed code is open source to ensure sustainability and the local implementation is concluded and functioning. The evaluation of the components was positive. Conclusions: The entire project had given ample opportunity for challenges, predictable and unpredictable-from the mode of operation to changing some of the initial ideas. We learned our lessons concerning personnel, budget planning and technical as well as manual monitoring as well as some requirements arising only during the process of the project. Nevertheless, we can here report a success story of a network infrastructure, highly agile and much easier in local installation than initially anticipated.
CRIS-Team Scopus Importer:2021-10-22

The nephrology eHealth-system of the metropolitan region of Hannover for digitalization of care, establishment of decision support systems and analysis of health care quality - Pape, L.; Schneider, N.; Schleef, T.; Junius-Walker, U.; Haller, H.; Brunkhorst, R.; Hellrung, N.; Prokosch, Hans-Ulrich; Haarbrandt, B.; Marschollek, M.; Schiffer, Mario (BMC Medical Informatics and Decision Making, 2019)
Background: Even though a high demand for sector spanning communication exists, so far no eHealth platform for nephrology is established within Germany. This leads to insufficient communication between medical providers and therefore suboptimal nephrologic care. In addition, Clinical Decision Support Systems have not been used in Nephrology until now. Methods: The aim of NEPHRO-DIGITAL is to create a eHealth platform in the Hannover region that facilitates integrated, cross-sectoral data exchange and includes teleconsultation between outpatient nephrology, primary care, pediatricians and nephrology clinics to reduce communication deficits and prevent data loss, and to enable the creation and implementation of an interoperable clinical decision support system. This system will be based on input data from multiple sources for early identification of patients with cardiovascular comorbidity and progression of renal insufficiency. Especially patients will be able to enter and access their own data. A transfer to a second nephrology center (metropolitan region of Erlangen-Nuremburg) is included in the study to prove feasibility and scalability of the approach. Discussion: A decision support system should lead to earlier therapeutic interventions and thereby improve the prognosis of patients as well as their treatment satisfaction and quality of life. The system will be integrated in the data integration centres of two large German university medicine consortia (HiGHmed (highmed.org) and MIRACUM (miracum.org)). Trial registration: ISRCTN16755335 (09.07.2019).
CRIS-Team Scopus Importer:2019-09-17
Keywords: Clinical decision support system; eHealth; Graft survival; Interoperability; Kidney transplantation; Patient survival; Quality of life

The Patient as Genomic Data Manager - Evaluation of the PROMISE App - Griebel, Lena; Hinderer, Marc; Amr, Ali; Meder, Benjamin; Schweig, Marc; Deuber, Dominic; Egger, Christoph; Kawohl, Claudia; Krämer, Annika; Flade, Isabell; Schröder, Dominique; Prokosch, Hans-Ulrich (Digital Personalized Health and Medicine, 2020)
PROMISE (Personal Medical Safe) was a German research project which aimed to provide the responsibility of genomic data to the patient via a mobile app. The patient should accept or decline study requests to use his/her genomic data via the app. In the evaluation of the app the experiences with mobile health as well as the opinion on being the genomic data manager were measured. Furthermore, the test patients were asked about their opinion and their concerns on the PROMISE app. Most of the 19 test patients were aware of the high sensibility of genomic data and thought that the PROMISE app was a suitable solution. The largest part found it good that they were the responsible data owner. However, several participants also found it important to have a permanent contact person when it comes to questions on inquiries or the app.
CRIS-Team Scopus Importer:2020-07-03
Keywords: genomic sequencing; patient empowerment; Personalized medicine; technology acceptance

The sample locator: A federated search tool for biosamples and associated data in Europe using HL7 FHIR - Engels, Cecilia; Kern, Jori; Dudová, Zdenka; Deppenwiese, Noemi; Kiel, Alexander; Kroll, Björn; Kussel, Tobias; Schüttler, Christina; Tomášik, Radovan; Hummel, Michael; Lablans, Martin; Breu, Martin; et al. (Computers in Biology and Medicine, 2024)
Background: This study outlines the development of a highly interoperable federated IT infrastructure for academic biobanks located at the major university hospital sites across Germany. High-quality biosamples linked to clinical data, stored in biobanks are essential for biomedical research. We aimed to facilitate the findability of these biosamples and their associated data. Networks of biobanks provide access to even larger pools of samples and data even from rare diseases and small disease subgroups. The German Biobank Alliance (GBA) established in 2017 under the umbrella of the German Biobank Node (GBN), has taken on the mission of a federated data discovery service to make biosamples and associated data available to researchers across Germany and Europe. Methods: In this context, we identified the requirements of researchers seeking human biosamples from biobanks and the needs of biobanks for data sovereignty over their samples and data in conjunction with the sample donor's consent. Based on this, we developed a highly interoperable federated IT infrastructure using standards such as Fast Healthcare Interoperability Resources (HL7 FHIR) and Clinical Quality Language (CQL). Results: The infrastructure comprises two major components enabling federated real-time access to biosample metadata, allowing privacy-compliant queries and subsequent project requests. It has been in use since 2019, connecting 16 German academic biobanks, with additional European biobanks joining. In production since 2019 it has run 4941 queries over the span of one year on more than 900,000 biosamples collected from more than 170,000 donors. Conclusion: This infrastructure enhances the visibility and accessibility of biosamples for research, addressing the growing demand for human biosamples and associated data in research. It also underscores the need for improvements in processes beyond IT infrastructure, aiming to advance biomedical research and similar infrastructure development in other fields.
CRIS-Team Scopus Importer:2024-08-16
Keywords: Biobanks; Biomedical research; Biosamples; FAIR data sharing; Feasibility search; Federated system; IT infrastructure; Software tools; Technology development

The Status Quo of Rare Diseases Centres for the Development of a Clinical Decision Support System - A Cross-Sectional Study - Schaaf, Jannik; Sedlmayr, Martin; Prokosch, Hans-Ulrich; Ganslandt, Thomas; Schade-Brittinger, Carmen; von Wagner, Michael; Kadioglu, Dennis; Schubert, Katharina; Lee-Kirsch, Min Ae; Kraemer, Bernhard K.; Winner, Beate; Mueller, Tobias; et al. (dHealth 2020 – Biomedical Informatics for Health and Care, 2020)
Clinical decision support systems (CDSS) help to improve the diagnostics and treatment of rare diseases (RD). As one of four funded consortia of the Medical Informatics Initiative supported by the Federal Ministry of Education and Research (BMBF, Germany), MIRACUM develops a clinical decision support system (CDSS) for RD based on distributed data of ten university hospitals. The CDSS will be developed at the Rare Diseases Centres (RDC) of the MIRACUM consortium. Since it is essential to deliver decision support at the right time and place in the clinician's workflow, this study aimed to capture relevant information of the RDCs regarding patient admission and diagnostic process. Additionally, we investigated how patient documentation and digitalisation is performed at the centres. Therefore, we conducted a cross-sectional survey involving experts in the RDs domain to capture relevant information for the further development of a CDSS in RD. For each centre, one expert on RDs participated in the study (n=8). The survey identified several challenges regarding the reuse of patient data, e.g. the paper-based documentation of a patientâĂŹs medical history and coding of diagnoses using ICD-10. However, we noticed a relevant use of current software diagnosis support and a similarly performed diagnostic process in all RDC. Further studies are needed to get more detailed insights and to define specific requirements.
CRIS-Team Scopus Importer:2020-07-10
Keywords: clinical decision support; quantitative analysis; rare diseases

Time Tracking of Standard Ultrasound Examinations in Pediatric Hospitals and Pediatric Medical Practices - A Multicenter Study by the Pediatric Section of the German Society of Ultrasound in Medicine (DEGUM) - Regensburger, Adrian; Knieling, Ferdinand; Feldkamp, Axel; Rascher, Wolfgang; Diesch, Katharina; Wölfle, Joachim; Prokosch, Hans-Ulrich; Jüngert, Jörg M. (Ultraschall in der Medizin, 2019)
PURPOSE: Ultrasonography is the primary imaging modality in pediatrics but still lacks sufficient reimbursement in Germany. In this multicenter study, national data for the duration of standard ultrasound in pediatrics were systematically documented in order to specify the actual time required. MATERIALS AND METHODS: N = 10 hospitals (N = 5 university hospitals, N = 5 non-university hospitals) and N = 3 medical practices in Germany recorded the entire process of an ultrasound examination in a special protocol developed by the Pediatric Section of the DEGUM. The duration of each of seven single steps during ultrasonography (from data input to final discussion of the results) of different organ systems was logged. RESULTS: In total, N = 2118 examinations from different organ systems were recorded. N = 10 organ systems were examined frequently (> 30 times). The total duration of an ultrasound examination was statistically significantly longer in hospitals compared to medical practices (median (IQR) 27 min. (18-38) vs. 12 min. (9-17), p < 0.001). The "hands-on" patient time was approximately one half of the total required time in both settings (49.9 % vs. 48.9 %). Ultrasonography of the abdomen and brain lasted longer in university hospitals than in non-university hospitals (p < 0.001, and p = 0.04, respectively). Cooperation and age did not uniformly correlate with the total duration. CONCLUSION: This study provides novel comprehensive national data for the duration of standardized ultrasound examinations of children and adolescents in Germany. These data are essential for a further evaluation of the economic costs and should support better remuneration in the future.
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Towards a Bavarian Oncology Real World Data Research Platform - Ziegler, Jasmin; Gründner, Julian; Rosenau, Lorenz; Erpenbeck, Marcel; Prokosch, Hans-Ulrich; Deppenwiese, Noemi (German Medical Data Sciences 2023 – Science. Close to People, 2023)
INTRODUCTION: In the last decade numerous real-world data networks have been established in order to leverage the value of data from electronic health records for medical research. In Germany, a nation-wide network based on electronic health record data from all German university hospitals has been established within the Medical Informatics Initiative (MII) and recently opened for researcherst' access through the German Portal for Medical Research Data (FDPG). In Bavaria, the six university hospitals have joined forces within the Bavarian Cancer Research Center (BZKF). The oncology departments aim at establishing a federated observational research network based on the framework of the MII/FDPG and extending it with a clear focus on oncological clinical data, imaging data and molecular high throughput analysis data. METHODS: We describe necessary adaptions and extensions of existing MII components with the goal of establishing a Bavarian oncology real world data research platform with its first use case of performing federated feasibility queries on clinical oncology data. RESULTS: We share insights from developing a feasibility platform prototype and presenting it to end users. Our main discovery was that oncological data is characterized by a higher degree of interdependence and complexity compared to the MII core dataset that is already integrated into the FDPG. DISCUSSION: The significance of our work lies in the requirements we formulated for extending already existing MII components to match oncology specific data and to meet oncology researchers needs while simultaneously transferring back our results and experiences into further developments within the MII.
CRIS-Team Scopus Importer:2023-09-22
Keywords: ADT/GEKID; federated feasibility queries; FHIR; oncology

Towards a Computable Data Corpus of Temporal Correlations between Drug Administration and Lab Value Changes - Newe, Axel; Wimmer, Stefan; Neubert, Antje; Becker, Linda; Prokosch, Hans-Ulrich; Beckmann, Matthias; Fietkau, Rainer; Forster, Christian; Neurath, Markus; Schett, Georg; Ganslandt, Thomas (PLoS ONE, 2015)
Background The analysis of electronic health records for an automated detection of adverse drug reactions is an approach to solve the problems that arise from traditional methods like spontaneous reporting or manual chart review. Algorithms addressing this task should be modeled on the criteria for a standardized case causality assessment defined by the World Health Organization. One of these criteria is the temporal relationship between drug intake and the occurrence of a reaction or a laboratory test abnormality. Appropriate data that would allow for developing or validating related algorithms is not publicly available, though. Methods In order to provide such data, retrospective routine data of drug administrations and temporally corresponding laboratory observations from a university clinic were extracted, transformed and evaluated by experts in terms of a reasonable time relationship between drug administration and lab value alteration. Result The result is a data corpus of 400 episodes of normalized laboratory parameter values in temporal context with drug administrations. Each episode has been manually classified whether it contains data that might indicate a temporal correlation between the drug administration and the change of the lab value course, whether such a change is not observable or whether a decision between those two options is not possible due to the data. In addition, each episode has been assigned a concordance value which indicates how difficult it is to assess. This is the first open data corpus of a computable ground truth of temporal correlations between drug administration and lab value alterations. Discussion The main purpose of this data corpus is the provision of data for further research and the provision of a ground truth which allows for comparing the outcome of other assessments of this data with the outcome of assessments made by human experts. It can serve as a contribution towards systematic, computerized ADR detection in retrospective data. With this lab value curve data as a basis, algorithms for detecting temporal relationships can be developed, and with the classification made by human experts, these algorithms can immediately be validated. Due to the normalization of the lab value data, it allows for a generic approach rather than for specific or solitary drug/lab value combination

Towards a FHIR-Based Data Model for Coronary Angiography Observations - Holweg, Florian; Achenbach, Stephan; Deppenwiese, Noemi; Gaede, Luise; Prokosch, Hans-Ulrich (Healthcare of the Future 2022, 2022)
Coronary heart disease is among the most frequent causes of death globally. Thus, our research project aims to develop prognostic models, to predict the risk of spontaneous myocardial infarctions based on a combination of clinical parameters and image data sets (invasive coronary angiograms). To train such models we use data from more than 30,000 coronary angiograms acquired at the cardiology department of Erlangen University Hospital. To linking such proprietary data with additional clinical parameters and to harmonize it for future cross-hospital federated machine learning approaches we defined a mapping for coronary angiography based on the symptom/ clinical phenotype HL7® FHIR® module of the German medical informatics initiative. In this paper we describe the final design of the coronary angiography information model and our mapping approach to ICD-10 and SNOMED CT. From the database we use a subset of 15 required values patient characteristics to create the HL7® FHIR® resource.
CRIS-Team Scopus Importer:2022-05-27
Keywords: coronary angiography; data model; HL7 FHIR; SNOMED CT

Towards a National Portal for Medical Research Data (FDPG): Vision, Status, and Lessons Learned - Prokosch, Hans-Ulrich; Gebhardt, Marie; Gründner, Julian; Kleinert, Philip; Buckow, Karoline; Rosenau, Lorenz; Semler, Sebastian C. (Caring is Sharing – Exploiting the Value in Data for Health and Innovation, 2023)
Harmonizing medical data sharing frameworks is challenging. Data collection and formats follow local solutions in individual hospitals; thus, interoperability is not guaranteed. The German Medical Informatics Initiative (MII) aims to provide a Germany-wide, federated, large-scale data sharing network. In the last five years, numerous efforts have been successfully completed to implement the regulatory framework and software components for securely interacting with decentralized and centralized data sharing processes. 31 German university hospitals have today established local data integration centers that are connected to the central German Portal for Medical Research Data (FDPG). Here, we present milestones and associated major achievements of various MII working groups and subprojects which led to the current status. Further, we describe major obstacles and the lessons learned during its routine application in the last six months.
CRIS-Team Scopus Importer:2023-06-02
Keywords: federated data network; Large scale data sharing; real world data

Towards a smart object network for clinical services. - Sedlmayr, Martin; Becker, Andreas; Münch, Ulli; Meier, Fritz; Prokosch, Hans-Ulrich; Ganslandt, Thomas (Annual Symposium proceedings, 2009)
Radio Frequency Identification (RFID) technology has become prevalent in logistics to support and optimize processes and numerous projects investigate its opportunities and challenges in the clinical context. However, most approaches are focused on one specific application using only a few possibilities of the technology. We describe the development of a smart object network to serve as a generic platform for various clinical services. Based on two disparate scenarios - tracking medical devices and transfusion safety - the architecture, implementation issues and prospects of such a platform are discussed.
CRIS-Team Scopus Importer:2021-11-16

Towards Implementation of OMOP in a German University Hospital Consortium - Maier, Carolin; Lang, L.; Storf, H.; Vormstein, P.; Bieber, R.; Bernarding, J.; Herrmann, T.; Haverkamp, C.; Horki, P.; Laufer, J.; Berger, F.; Hoening, G.; et al. (Applied Clinical Informatics, 2018)
In 2015, the German Federal Ministry of Education and Research initiated a large data integration and data sharing research initiative to improve the reuse of data from patient care and translational research. The Observational Medical Outcomes Partnership (OMOP) common data model and the Observational Health Data Sciences and Informatics (OHDSI) tools could be used as a core element in this initiative for harmonizing the terminologies used as well as facilitating the federation of research analyses across institutions. To realize an OMOP/OHDSI-based pilot implementation within a consortium of eight German university hospitals, evaluate the applicability to support data harmonization and sharing among them, and identify potential enhancement requirements. The vocabularies and terminological mapping required for importing the fact data were prepared, and the process for importing the data from the source files was designed. For eight German university hospitals, a virtual machine preconfigured with the OMOP database and the OHDSI tools as well as the jobs to import the data and conduct the analysis was provided. Last, a federated/distributed query to test the approach was executed. While the mapping of ICD-10 German Modification succeeded with a rate of 98.8% of all terms for diagnoses, the procedures could not be mapped and hence an extension to the OMOP standard terminologies had to be made.Overall, the data of 3 million inpatients with approximately 26 million conditions, 21 million procedures, and 23 million observations have been imported.A federated query to identify a cohort of colorectal cancer patients was successfully executed and yielded 16,701 patient cases visualized in a Sunburst plot. OMOP/OHDSI is a viable open source solution for data integration in a German research consortium. Once the terminology problems can be solved, researchers can build on an active community for further development.
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Two Years of tranSMART in a University Hospital for Translational Research and Education - Christoph, Jan; Knell, Christian; Naschberger, Elisabeth; Stürzl, Michael; Maier, Christian; Prokosch, Hans-Ulrich; Sedlmayr, Martin (Studies in health technology and informatics, 2017)
For translational research, software platforms such as tranSMART with an integrated view of both clinical and omics data have gained more and more attention in the last years.We wanted to examine the success and failures of tranSMART in the fields of translational research and education by looking at the examples of six use cases at our hospital. We wanted to point out suitable scenarios and user groups as well as still existing challenges and limitations.We sum up the experience we made with our use cases with a focus on lessons learned.tranSMART was successfully established by a bottom-up approach at our university hospital and has been running for more than two years now. It has been used in four translational research projects as well as in education in the context of lectures and bachelor/master theses.tranSMART can be a very useful tool for translational research and education. But it should be used with both care and statistical knowledge to avoid wrong conclusions. Some technical constraints, especially for data modeling, still limit many applications. Version control and data provenance are remaining challenges.
EVALuna2:187

Two years of tranSMART in a university hospital for translational research and education - Christoph, Jan; Knell, Christian; Naschberger, Elisabeth; Stürzl, Michael; Maier, Christian; Prokosch, Hans-Ulrich; Sedlmayr, Martin (Health informatics meets eHealth: Digital insight information-driven health & care; proceedings of the 11th eHealth2017 Conference, 2017)
UnivIS-Import:2018-09-11:Pub.2017.tech.IMMD.infome.twoyea
Keywords: Biomedical research; Medical education; Research personnel; Translational medical research

Usability and Suitability of the Omics-Integrating Analysis Platform tranSMART for Translational Research and Education - Christoph, Jan; Knell, Christian; Boßerhoff, Anja Katrin; Naschberger, Elisabeth; Stürzl, Michael; Rübner, Matthias; Seuß, Hannes; Ruh, Manuel; Prokosch, Hans-Ulrich; Sedlmayr, Brita (Applied Clinical Informatics, 2017)
Platforms like tranSMART assist researchers in analyzing clinical and corresponding omics data. Usability is an important, yet often overlooked, factor affecting the adoption and meaningful use. Analyses on the specific needs of translational researchers and considerations about the application of such platforms for education are rare. The aim of this study was to test whether tranSMART can be used in education and how well medical students and professional researchers can handle it; to identify which kind of translational researchers-in terms of skills, experienced limitations, and available data-can take advantage of tranSMART; and to evaluate the usability and to generate recommendations for improvements. An online-based test has been done by medical students (N = 109) and researchers (N = 26). The test comprised 13 tasks in the context of four typical research scenarios based on experimental and clinical data. A web questionnaire was provided to identify both the needs and the conditions of research as well as to evaluate the system's usability based on the "System Usability Scale" (SUS). Students and researchers were able to handle tranSMART well and coped with most scenarios: cohort identification, data exploration, hypothesis generation, and hypothesis validation were answered with a rate of correctness between 82 and 100%. Of the total, 72.2% of the teaching researchers considered tranSMART suitable for their lessons and 84.6% of the researchers considered the platform useful for their daily work; 65.4% of the researchers named the nonavailability of a platform like tranSMART as a restriction on their research. The usability was rated "acceptable" with a SUS of 70.8. tranSMART is potentially suitable for education purposes and fits most of the needs of translational researchers. Improvements are needed on the presentation of analysis results and on the guidance of users through the analysis, especially to ensure the compliance of the analysis with the requirements of statistical testing.
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Usability evaluation of an offline electronic data capture app in a prospective multicenter dementia registry (digidem bayern): Mixed method study - Reichold, Michael; Heß, Miriam; Kolominsky-Rabas, Peter; Grässel, Elmar; Prokosch, Hans-Ulrich (JMIR Formative Research, 2021)
Background: Digital registries have been shown to provide an efficient way of gaining a better understanding of the clinical complexity and long-term progression of diseases. The paperless method of electronic data capture (EDC) during a patient interview saves both time and resources. In the prospective multicenter project "Digital Dementia Registry Bavaria (digiDEM Bayern)," interviews are also performed on site in rural areas with unreliable internet connectivity. It must be ensured that EDC can still be performed in such a context and that there is no need to fall back on paper-based questionnaires. In addition to a web-based data collection solution, the EDC system REDCap (Research Electronic Data Capture) offers the option to collect data offline via an app and to synchronize it afterward. Objective: The aim of this study was to evaluate the usability of the REDCap app as an offline EDC option for a lay user group and to examine the necessary technology acceptance of using mobile devices for data collection. The feasibility of the app-based offline data collection in the digiDEM Bayern dementia registry project was then evaluated before going live. Methods: An exploratory mixed method design was employed in the form of an on-site usability test with the "Thinking Aloud" method combined with an online questionnaire including the System Usability Scale (SUS). The acceptance of mobile devices for data collection was surveyed based on five categories of the technology acceptance model. Results: Using the "Thinking Aloud" method, usability issues were identified and solutions were accordingly derived. Evaluation of the REDCap app resulted in a SUS score of 74, which represents "good" usability. After evaluating the technology acceptance questionnaire, it can be concluded that the lay user group is open to mobile devices as interview tools. Conclusions: The usability evaluation results show that a lay user group generally agree that data collecting partners in the digiDEM project can handle the REDCap app well. The usability evaluation provided statements about positive aspects and could also identify usability issues relating to the REDCap app. In addition, the current technology acceptance in the sample showed that heterogeneous groups of different ages with diverse experiences in handling mobile devices are also ready for the use of app-based EDC systems. Based on these results, it can be assumed that the offline use of an app-based EDC system on mobile devices is a viable solution for collecting data in a decentralized registry-based research project.
CRIS-Team Scopus Importer:2021-11-19
Keywords: Dementia; Digital health; Electronic data collection; Evaluation; Mobile app; Mobile device; Offline; Registry; Usability; Usability testing

User-centered design of a mobile medication management - Sedlmayr, Brita; Schöffler, Jennifer; Prokosch, Hans-Ulrich; Sedlmayr, Martin (Informatics For Health & Social Care, 2019)
Background: The use of a nationwide medication plan has been promoted as an effective strategy to improve patient safety in Germany. However, the medication plan only exists as a paper-based version, which is related to several problems, that could be circumvented by an electronic alternative. Objective: The main objective of this study was to report on the development of a mobile interface concept to support the management of medication information. Methods: The human-centered design (UCD) process was chosen. First the context of use was analyzed, and personas and an interaction concept were designed. Next, a paper prototype was developed and evaluated by experts. Based on those results, a medium-fidelity prototype was created and assessed by seven end-users who performed a thinking-aloud test in combination with a questionnaire based on the System Usability Scale (SUS). Results: Initially for one persona/user type, an interface design concept was developed, which received an average SUS-Score of 92.1 in the user test. Usability problems have been solved so that the design concept could be fixed for a future implementation. Contribution: The approach of the UCD process and the methods involved can be applied by other researchers as a framework for the development of similar applications.
CRIS-Team Scopus Importer:2019-05-02
Keywords: Evaluation studies; medical informatics application; mobile health; user–computer interface

User-Centered Development of an Online Platform for Drug Dosing Recommendations in Pediatrics - Rödle, Wolfgang; Wimmer, Stefan; Zahn, Julia; Prokosch, Hans-Ulrich; Hinkes, Bernward; Neubert, Antje; Rascher, Wolfgang; Kraus, Stefan; Toddenroth, Dennis; Sedlmayr, Brita (Applied Clinical Informatics, 2019)
Background Drug therapy in pediatric patients is a complex process. Children are subject to continuous growth and variation in drug-metabolizing enzyme activity, requiring continuous adaption of dosages. In Germany, currently no publicly available database exists that provides evidence-based information on drug dosages in pediatrics. For local drug dosing support, a prototype database has been developed within the Children's Hospital, Erlangen. A user-centered development process was initiated to establish an online platform for evidence-based dosing recommendations, as well as pharmacological and pharmaceutical drug information in pediatrics. Objectives The objectives of the study were to survey the demand for such a platform and to assess the usability of the different versions of the developed system. Methods The developed prototype was evaluated in a pluralistic walkthrough with prospective end users. After a redesign, the second prototype of the online platform underwent an online usability testing based on a tailored questionnaire and the System Usability Scale (SUS) (n = 12). Results Eleven of 12 participants expressed a demand for an online platform for pediatric dosing recommendations. The majority of the participants requested the integration of extended features, such as drug-drug interaction alerts, or information on adverse effects, pharmacokinetics, and pharmacodynamics. Particularly noteworthy is the demand for an online calculator; 5 of a total of 15 participants explicitly requested a calculator for dosages (based on age, weight, body surface) and glomerular filtration rate. The usability of the second prototype was rated good to excellent with a median SUS of 81.25. Conclusion Local domain experts demand an online platform for pediatric dosing recommendations. The application of the user-centered design approach enabled the development of a prototype suitable for practical use. Multiple additional required functionalities have been identified, whereby the importance of an online calculator for patient-individual dosing recommendations was particularly emphasized.
CRIS-Team Scopus Importer:2019-08-20
Keywords: computer-assisted; decision support techniques; drug therapy; knowledge bases; online systems; pediatric dosages

Using Arden Syntax for the generation of intelligent intensive care discharge letters - Kraus, Stefan; Castellanos, Ixchel; Albermann, Matthias; Schüttler, Christina; Prokosch, Hans-Ulrich; Staudigel, Martin; Toddenroth, Dennis (Exploring complexity in health: an interdisciplinary systems approach; proceedings of MIE 2016 at HEC2016, 2016)
UnivIS-Import:2017-12-18:Pub.2016.tech.IMMD.infome.usinga

Using Arden Syntax for the Generation of Intelligent Intensive Care Discharge Letters - Kraus, Stefan; Castellanos, Ixchel; Albermann, Matthias; Schüttler, Christina; Prokosch, Hans-Ulrich; Staudigel, Martin; Toddenroth, Dennis (Studies in health technology and informatics, 2016)
Discharge letters are an important means of communication between physicians and nurses from intensive care units and their colleagues from normal wards. The patient data management system (PDMS) used at our local intensive care units provides an export tool to create discharge letters by inserting data items from electronic medical records into predefined templates. Local intensivists criticized the limitations of this tool regarding the identification and the further processing of clinically relevant data items for a flexible creation of discharge letters. As our PDMS supports Arden Syntax, and the demanded functionalities are well within the scope of this standard, we set out to investigate the suitability of Arden Syntax for the generation of discharge letters. To provide an easy-to-understand facility for integrating data items into document templates, we created an Arden Syntax interface function which replaces the names of previously defined variables with their content in a way that permits arbitrary custom formatting by clinical users. Our approach facilitates the creation of flexible text sections by conditional statements, as well as the integration of arbitrary HTML code and dynamically generated graphs. The resulting prototype enables clinical users to apply the full set of Arden Syntax language constructs to identify and process relevant data items in a way that far exceeds the capabilities of the PDMS export tool. The generation of discharge letters is an uncommon area of application for Arden Syntax, considerably differing from its original purpose. However, we found our prototype well suited for this task and plan to evaluate it in clinical production after the next major release change of our PDMS.
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Using Arden Syntax Medical Logic Modules to reduce overutilization of laboratory tests for detection of bacterial infections-Success or failure? - Castellanos, Ixchel; Kraus, Stefan; Toddenroth, Dennis; Prokosch, Hans-Ulrich; Bürkle, Thomas (Artificial Intelligence in Medicine, 2015)
Bacterial infections frequently cause prolonged intensive care unit (ICU) stays. Repeated measurements of the procalcitonin (PCT) biomarker are typically used for early detection and follow up of bacterial infections and sepsis, but those PCT measurements are costly. To avoid overutilization, we developed and evaluated a clinical decision support system (CDSS) in Arden Syntax which computes necessary and preventable PCT orders.The CDSS implements a rule set based on the latest PCT value, the time period since this measurement, and the PCT trend scenario. We assessed the CDSS effects on the daily rate of ordered PCT tests within a prospective study having two ON and two OFF phases in a surgical ICU. In addition, we performed interviews with the participating physicians to investigate their experience with the CDSS advice.Prior to the deployment of the CDSS, 22% of the performed PCT tests were potentially preventable according to the rule set. During the first ON phase the daily rate of ordered PCT tests per patient decreased significantly from 0.807 to 0.662. In subsequent OFF, ON and OFF phases, however, PCT utilization reached again daily rates of 0.733, 0.803, and 0.792, respectively. The interviews demonstrated that the physicians were aware of the problem of PCT overutilization, which they primarily attributed to acute time constraints. The responders assumed that the majority of preventable measurements are indiscriminately ordered for patients during longer ICU stays.We observed an 18% reduction of PCT tests within the first four weeks of CDSS support in the investigated ICU. This reduction may have been influenced by raised awareness of the overutilization problem; the extent of this influence cannot be determined in our study design. No reduction of PCT tests could be observed during the second ON phase. The physician interviews indicated that time critical ICU situations can prevent extensive reflection about the necessity of individual tests. In order to achieve an enduring effect on PCT utilization, we will have to proceed to electronic order entry.
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Using Health Information Resources for People With Cognitive Impairment (digiDEM Bayern): Registry-Based Cohort Study - Weidinger, Florian; Dietzel, Nikolas; Grässel, Elmar; Prokosch, Hans-Ulrich; Kolominsky-Rabas, Peter (JMIR Formative Research, 2025)
Background: Dementia is a growing global health challenge with significant economic and social implications. Underdiagnosis of dementia is prevalent due to a lack of knowledge and understanding among the general population. Enhancing dementia literacy through improved health information–seeking behavior is crucial for the self-determined management of the disease by those affected. Understanding the relationship between dementia literacy, health information–seeking behavior, and the use of various information sources among individuals with cognitive impairment is of high importance in this context. Objective: The aim of this study was to analyze the relevance of different sources of health information from the perspective of people with cognitive impairment, while also evaluating differences based on age, gender, and disease progression. Methods: This study is part of the ongoing project “Digital Dementia Registry Bavaria – digiDEM Bayern.” The Digital Dementia Registry Bavaria is a multicenter, prospective, longitudinal register study in Bavaria, Germany. People with cognitive impairment rated several information sources by using Likert scales with the values unimportant (1) to very important (5). Data were analyzed descriptively, and multiple 2-sample, 2-tailed t tests were used to evaluate differences by cognitive status and gender and using multiple one-way ANOVA to evaluate differences by age group. Results: Data of 924 people with cognitive impairment (531 with dementia, 393 with mild cognitive impairment) were evaluated. The most relevant health information sources were “Personal visit to a medical professional” (mean 3.9, SD 1.1) and “Family / Friends” (mean 3.9, SD 1.2). “Internet” was 1 of the 2 lowest-rated information sources by people with cognitive impairment (mean 1.6, SD 1.1), with nearly three-quarters (684/924, 74%) of the participants rating the source as unimportant. The age-specific analyses showed significant differences for the sources “Internet” (F2,921=61.23; P<.001), “Courses / Lectures” (F2,921=18.88; P<.001), and “Family / Friends” (F2,921=6.27; P=.002) for the 3 defined age groups. There were several significant differences between people with mild cognitive impairment and dementia whereby the first group evaluated most sources higher, such as “Internet” (mean difference=0.6; t640=7.52; P<.001). The only sources rated higher by the dementia group were “TV / Radio” and “Family / Friends,” with none of them showing significant differences. Gender-specific analyses showed women with cognitive impairment valuing every evaluated source higher than men apart from “Internet” (mean difference=0.4; t685=4.97; P<.001). Conclusions: To enhance health and dementia literacy, the best way to communicate health information to people with cognitive impairment is through interpersonal contact with medical professionals and their friends and family. Slight changes in valuation should be considered as the medical condition progresses, along with variations by age and gender. In particular, the evaluation and use of the internet are dependent on these factors. Further research is needed to capture potential changes in the valuation of the internet as a health information source.
CRIS-Team Scopus Importer:2025-01-31
Keywords: cognitive impairment; dementia; digiDEM; Digital Dementia Registry Bavaria; health information; health information–seeking behavior; information sources; mild cognitive impairment

Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery - Kapsner, Lorenz; Feißt, Manuel; Purbojo, Ariawan; Prokosch, Hans-Ulrich; Ganslandt, Thomas; Dittrich, Sven; Mang, Jonathan M.; Wällisch, Wolfgang (Diagnostics, 2024)
Background: The objective of this IRB-approved retrospective monocentric study was to identify risk factors for mortality after surgery for congenital heart defects (CHDs) in pediatric patients using machine learning (ML). CHD belongs to the most common congenital malformations, and remains the leading mortality cause from birth defects. Methods: The most recent available hospital encounter for each patient with an age <18 years hospitalized for CHD-related cardiac surgery between the years 2011 and 2020 was included in this study. The cohort consisted of 1302 eligible patients (mean age [SD]: 402.92 [±562.31] days), who were categorized into four disease groups. A random survival forest (RSF) and the ‘eXtreme Gradient Boosting’ algorithm (XGB) were applied to model mortality (incidence: 5.6% [n = 73 events]). All models were then applied to predict the outcome in an independent holdout test dataset (40% of the cohort). Results: RSF and XGB achieved average C-indices of 0.85 (±0.01) and 0.79 (±0.03), respectively. Feature importance was assessed with ‘SHapley Additive exPlanations’ (SHAP) and ‘Time-dependent explanations of machine learning survival models’ (SurvSHAP(t)), both of which revealed high importance of the maximum values of serum creatinine observed within 72 h post-surgery for both ML methods. Conclusions: ML methods, along with model explainability tools, can reveal interesting insights into mortality risk after surgery for CHD. The proposed analytical workflow can serve as a blueprint for translating the analysis into a federated setting that builds upon the infrastructure of the German Medical Informatics Initiative.
CRIS-Team Scopus Importer:2024-12-06
Keywords: congenital heart defects (CHDs); eXtreme Gradient Boosting (XGB); feature importance; machine learning (ML); mortality; random survival forest (RSF); risk factors

Visualization of Similar Patients in a Clinical Decision Support System for Rare Diseases - A Focus Group Study - Sedlmayr, Martin; Schaaf, Jannik; Sedlmayr, Martin; Prokosch, Hans-Ulrich; Tegtbauer, Niels; Kadioglu, Dennis; Schaefer, Johanna; Boeker, Martin; Storf, Holger (German Medical Data Sciences: Bringing Data to Life, 2021)
The diagnosis of patients with rare diseases is often delayed. A Clinical Decision Support System using similarity analysis of patient-based data may have the potential to support the diagnosis of patients with rare diseases. This qualitative study has the objective to investigate how the result of a patient similarity analysis should be presented to a physician to enable diagnosis support. We conducted a focus group with physicians practicing in rare diseases as well as medical informatics researchers. To prepare the focus group, a literature search was performed to check the current state of research regarding visualization of similar patients. We then created software-mockups for the presentation of these visualization methods for the discussion within the focus group. Two persons took independently field notes for data collection of the focus group. A questionnaire was distributed to the participants to rate the visualization methods. The results show that four visualization methods are promising for the visualization of similar patients: "Patient on demand table", "Criteria selection", "Time-Series chart" and "Patient timeline. "Patient on demand table" shows a direct comparison of patient characteristics, whereas "Criteria selection" allows the selection of different patient criteria to get deeper insights into the data. The "Time-Series chart" shows the time course of clinical parameters (e.g. blood pressure) whereas a "Patient timeline" indicates which time events exist for a patient (e.g. several symptoms on different dates). In the future, we will develop a software-prototype of the Clinical Decision Support System to include the visualization methods and evaluate the clinical usage.
CRIS-Team Scopus Importer:2021-06-11
Keywords: Clinical Decision Support; Rare Diseases; Requirements analysis

Web-based data collection yielded an additional response bias - but had no direct effect on outcome scales - Mayr, Andreas; Gefeller, Olaf; Prokosch, Hans-Ulrich; Pirkl, Anna; Fröhlich, Antje; de Zwaan, Matina (Journal of Clinical Epidemiology, 2012)
Objective: To assess and to evaluate possible effects arising from Web-based data collection on the results of a study. Study Design and Setting: We analyzed participants of the German Weight Control Registry (GWCR) of whom 328 chose to use Web-based questionnaires and 139 preferred to participate via a traditional postal survey. Furthermore, we included data of 212 individuals sampled independently from the general population who fulfilled the study's inclusion criteria - giving us the chance to differentiate between response bias (concerning Web-based data collection) and general selection bias (concerning participation in the GWCR). Results: In addition to selection bias (GWCR participants are overall better educated, more likely to live in a partnership, more often female, and older than the general population), we also found a substantial response bias: Participants using the Internet were younger, better educated, and more often male compared with participants preferring the paper-and-pencil version. However, after adjusting for these differences, we found no additional direct effect of Web-based data collection on any of the outcome variables. Conclusion: Web-based epidemiologic studies still do not attract the same participants as postal surveys, even in highly industrialized countries. However, after adjusting for this bias, the same results can be expected. © 2012 Elsevier Inc. All rights reserved.
UnivIS-Import:2015-04-14:Pub.2012.tech.IMMD.infome.webbas
Keywords: Bias; Data collection; Epidemiologic methods; Internet; Questionnaires; Registries