Guidance For Reporting Analyses of Metadata on Electronic Health Record Use.

Electronic health record audit log event log measurement metadata

Journal

Journal of the American Medical Informatics Association : JAMIA
ISSN: 1527-974X
Titre abrégé: J Am Med Inform Assoc
Pays: England
ID NLM: 9430800

Informations de publication

Date de publication:
20 Dec 2023
Historique:
received: 20 10 2023
accepted: 18 12 2023
medline: 21 12 2023
pubmed: 21 12 2023
entrez: 20 12 2023
Statut: aheadofprint

Résumé

Research on how people interact with electronic health records (EHRs) increasingly involves the analysis of metadata on EHR use. These metadata can be recorded unobtrusively and capture EHR use at a scale unattainable through direct observation or self-reports. However, there is substantial variation in how metadata on EHR use are recorded, analyzed and described, limiting understanding, replication, and synthesis across studies. In this perspective, we provide guidance to those working with EHR use metadata by describing four common types, how they are recorded, and how they can be aggregated into higher-level measures of EHR use. We also describe guidelines for reporting analyses of EHR use metadata-or measures of EHR use derived from them-to foster clarity, standardization, and reproducibility in this emerging and critical area of research.

Identifiants

pubmed: 38123497
pii: 7484670
doi: 10.1093/jamia/ocad254
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Adam Rule (A)

Information School, University of Wisconsin-Madison, Madison, Wisconsin.

Thomas Kannampallil (T)

Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri.
Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St Louis, Missouri.

Michelle R Hribar (MR)

Office of Data Science and Health Informatics, National Eye Institute, National Institute of Health, Bethesda, Maryland.
Department of Ophthalmology, Casey Eye Institute, and Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon.

Adam C Dziorny (AC)

Department of Pediatrics, University of Rochester School of Medicine, Rochester, New York.

Robert Thombley (R)

Center for Clinical Informatics and Improvement Research, Department of Medicine, University of California, San Francisco, San Francisco, California.

Nate C Apathy (NC)

National Center for Human Factors in Healthcare, MedStar Health Research Institute, Washington, District of Columbia.
Center for Biomedical Informatics, Regenstrief Institute Inc, Indianapolis, Indiana.

Julia Adler-Milstein (J)

Center for Clinical Informatics and Improvement Research, Department of Medicine, University of California, San Francisco, San Francisco, California.

Classifications MeSH