Visualization of Similar Patients in a Clinical Decision Support System for Rare Diseases - A Focus Group Study

Sedlmayr M, Schaaf J, Sedlmayr M, Prokosch HU, Tegtbauer N, Kadioglu D, Schaefer J, Boeker M, Storf H (2021)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2021

Publisher: IOS Press

Edited Volumes: German Medical Data Sciences: Bringing Data to Life

Series: Studies in Health Technology and Informatics

Book Volume: 278

Pages Range: 49-57

ISBN: 978-1-64368-176-4

DOI: 10.3233/SHTI210050

Abstract

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.

Authors with CRIS profile

Martin Sedlmayr Lehrstuhl für Medizinische Informatik Hans-Ulrich Prokosch Lehrstuhl für Medizinische Informatik

Involved external institutions

Universitätsklinikum Frankfurt am Main (KGU) DE Germany (DE) Albert-Ludwigs-Universität Freiburg DE Germany (DE) Technische Universität Dresden DE Germany (DE)

How to cite

APA:

Sedlmayr, M., Schaaf, J., Sedlmayr, M., Prokosch, H.-U., Tegtbauer, N., Kadioglu, D.,... Storf, H. (2021). Visualization of Similar Patients in a Clinical Decision Support System for Rare Diseases - A Focus Group Study. In Rainer Röhrig, Tim Beißbarth, Werner Brannath, Hans-Ulrich Prokosch, Irene Schmidtmann, Susanne Stolpe, Antonia Zapf (Eds.), German Medical Data Sciences: Bringing Data to Life. (pp. 49-57). IOS Press.

MLA:

Sedlmayr, Martin, et al. "Visualization of Similar Patients in a Clinical Decision Support System for Rare Diseases - A Focus Group Study." German Medical Data Sciences: Bringing Data to Life. Ed. Rainer Röhrig, Tim Beißbarth, Werner Brannath, Hans-Ulrich Prokosch, Irene Schmidtmann, Susanne Stolpe, Antonia Zapf, IOS Press, 2021. 49-57.

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