Evidence map›Paper›PMID 41553117›Full record

ArticleJMIR medical informatics2026

Development of Quality Indicators for the Correct Use of Electronic Medical Records in Primary Care: Modified Delphi Study.

Rico Paridaens, Steve Van den Bulck, Michel De Jonghe, Benjamin Fauquert, Liesbeth Meel, Willem Raat, Bert Vaes

Abstract read
In one paragraph

Article in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rico ParidaensAcademisch Centrum voor Huisartsgeneeskunde, Katholieke Universiteit Leuven (KU Leuven), Leuven, Flanders, Belgium.ORCID 0009-0004-6647-7060
Steve Van den BulckAcademisch Centrum voor Huisartsgeneeskunde, Katholieke Universiteit Leuven (KU Leuven), Leuven, Flanders, Belgium.ORCID 0000-0003-0744-3923
Michel De JongheCentre Académique de Médecine Générale, Université catholique de Louvain, Leuven, Belgium.ORCID 0009-0002-6959-2254
Benjamin FauquertUnité de Recherche en Soins Primaires, Vrije Universiteit Brussel, Brussels, Belgium.ORCID 0000-0003-2841-3715
Liesbeth MeelBelgian Centre for Evidence-Based Medicine (CEBAM), Leuven, Belgium.ORCID 0009-0007-1831-5624
Willem RaatAcademisch Centrum voor Huisartsgeneeskunde, Katholieke Universiteit Leuven (KU Leuven), Leuven, Flanders, Belgium.ORCID 0000-0002-9591-3974
Bert VaesAcademisch Centrum voor Huisartsgeneeskunde, Katholieke Universiteit Leuven (KU Leuven), Leuven, Flanders, Belgium.ORCID 0000-0001-5244-1930

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhen used correctly, electronic medical records (EMRs) can support clinical decision-making, provide information for research, facilitate coordination of care, reduce medical errors, and generate patient health summaries. Studies have reported large differences in the quality of EMR data.

objectiveOur study aimed to develop an evidence-based set of electronically extractable quality indicators (QIs) approved by expert consensus to assess the good use of EMRs by general practitioners (GPs) from a medical perspective.

methodsThe RAND-modified Delphi method was used in this study. The TRIP and MEDLINE databases were searched, and a selection of recommendations was filtered using the specific, measurable, assignable, realistic, and time-bound principles. The panel comprised 12 GPs and 6 EMR developers. The selected recommendations were transformed into QIs as percentages.

resultsA combined list of 20 indicators and 30 recommendations was created from 9 guidelines and 4 review articles. After the consensus round, 20 (100%) indicators and 20 (67%) recommendations were approved by the panel. All 20 recommendations were transformed into QIs. Most (16, 40%) QIs evaluated the completeness and adequacy of the problem list.

conclusionsThis study provided a set of 40 EMR-extractable QIs for the correct use of EMRs in primary care. These QIs can be used to map the completeness of EMRs by setting up an audit and feedback system, and to develop specific (computer-based) training for GPs.

Indexed as

Electronic Health RecordsPrimary Health CareQuality Indicators, Health CareDelphi TechniqueHumansDelphi methodelectronic audit and feedbackelectronic medical recordsprimary carequality assessment

Identifiers

PMID41553117
PMCPMC12865340

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.