Availability of Structured Data Elements in Electronic Health Records for Supporting Patient Recruitment in Clinical Trials.

Vass A, Reinecke I, Boeker M, Prokosch HU, Gulden C (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Studies in health technology and informatics IOS Press; 1999

Book Volume: 290

Pages Range: 130-134

DOI: 10.3233/SHTI220046

Abstract

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.

Authors with CRIS profile

Hans-Ulrich Prokosch Lehrstuhl für Medizinische Informatik Christian Gulden Lehrstuhl für Medizinische Informatik

Involved external institutions

Universitätsmedizin Greifswald / Universitätsklinikum Greifswald DE Germany (DE) Universitätsklinikum Carl Gustav Carus Dresden DE Germany (DE) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Vass, A., Reinecke, I., Boeker, M., Prokosch, H.-U., & Gulden, C. (2022). Availability of Structured Data Elements in Electronic Health Records for Supporting Patient Recruitment in Clinical Trials. Studies in health technology and informatics, 290, 130-134. https://doi.org/10.3233/SHTI220046

MLA:

Vass, Albert, et al. "Availability of Structured Data Elements in Electronic Health Records for Supporting Patient Recruitment in Clinical Trials." Studies in health technology and informatics 290 (2022): 130-134.

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