Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Jul 3, 2025
Open Peer Review Period: Jul 21, 2025 - Sep 15, 2025
Date Accepted: Dec 17, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Development of quality indicators for the correct use of electronic medical records in primary care using: a Delphi-derived method
ABSTRACT
Background:
Used correctly, the electronic medical record (EMR) can support clinical decision making, provide information for research, facilitate coordination of care, reduce medical error, and generate a patient health summary. Studies show large differences in the quality of data in the EMR.
Objective:
The objective of our study was to develop a evidence-based set of electronically extractable quality indicators (QIs), approved by expert consensus, for assessing, from a medical perspective, the good use of EMRs by general practitioners (GPs).
Methods:
A RAND-modified Delphi method was used to develop QIs for use of EMRs. TRIP database and MEDLINE were searched, and a selection of recommendations were filtered using the SMART-principle. A panel was composed of 12 GPs and 6 EMR-developers. The selected recommendations were transformed into QIs as a percentage.
Results:
A combined list of 20 indicators and 30 recommendations was created out of 9 guidelines and 4 review articles. After the consensus round, 20 indicators and 20 recommendations were approved. All 20 recommendations were transformed into QIs. Most of the QIs evaluate the completeness and adequacy of the problem list.
Conclusions:
This study provides a set of 40 EMR-extractable QIs for the correct use of the EMR in primary care. These QIs can be used to map the completeness of the EMRs by setting up an audit and feedback system and can be used to develop specific (computer based) trainings for GPs.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.