Evidence map›Paper›PMID 31142493›Full record

SynthesisBMJ health & care informatics2019

Interventions to improve the use of EMRs in primary health care: a systematic review and meta-analysis.

Noura Hamade, Amanda Terry, Monali Malvankar-Mehta

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMJ health & care informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Observational
  12. Review
  13. Association between evidence-based training and clinician proficiency in electronic health record use.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  14. 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

3 authors.

Noura Hamade
Amanda Terry
Monali Malvankar-Mehta

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic medical record (EMR) adoption in primary care has grown exponentially since their introduction in the 1970s. However, without their proper

objectiveThe purpose of this systematic review was to identify interventions aimed at improving EMR use in primary healthcare settings.

methodsTen online databases were searched to identify studies conducted in primary healthcare settings aimed at implementing interventions to observe the use of EMRs and directly measure the use of EMR functions or outcomes effected by the use of EMR functions.

resultsOf 2098 identified studies, 12 were included in the review. Results showed that interventions focused on the use of EMR functions, including referrals, electronic communication, reminders, use of clinical decision support systems and workflow management support functions, were five times more likely to show improvements in EMR use compared with controls. Interventions focused on data quality were five and a half times more likely to show improvements in EMR use compared with controls.

conclusionsIndividuals in primary healthcare settings aiming to improve EMR use would benefit from implementing interventions focused on EMR feature add-ons such as clinical decision support systems and customised referral templates, and provisions of educational materials, or financial incentives targeted at improving the use of EMR functions and data quality.

Indexed as

Continuity of Patient CareDecision Support Systems, ClinicalPrimary Health CareReminder SystemsElectronic Health RecordsHumansMedical Informaticsbenefits realisationelectronic medical recordshealth information technologiesprimary healthcare

Identifiers

PMID31142493
PMCPMC7062324

What OpenQuestion holds

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LicenceCC BY-NC
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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 OpenQuestion graph.