Evidence map›Paper›PMID 41406416›Full record

ArticleJMIR medical education2025

Using Electronic Health Data to Deliver an Adaptive Online Learning Solution to Emergency Trainees: Mixed Methods Pilot Study.

Anna Janssen, Andrew Coggins, James Tadros, Deleana Quinn, Amith Shetty, Tim Shaw

Abstract read
In one paragraph

Article in JMIR medical education, 2025. 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

6 authors.

Anna JanssenFaculty of Medicine and Health, The University of Sydney, Charles Perkins Centre D17, Sydney, 2006, Australia, 61 2 9036 9406.ORCID 0000-0001-6611-9651
Andrew CogginsWestern Sydney Local Health District, Sydney, Australia.ORCID 0000-0002-5652-6920
James TadrosWestern Sydney Local Health District, Sydney, Australia.
Deleana QuinnFaculty of Medicine and Health, The University of Sydney, Charles Perkins Centre D17, Sydney, 2006, Australia, 61 2 9036 9406.ORCID 0000-0001-7479-9319
Amith ShettyNSW Ministry of Health, Sydney, Australia.ORCID 0000-0001-7349-1128
Tim ShawFaculty of Medicine and Health, The University of Sydney, Charles Perkins Centre D17, Sydney, 2006, Australia, 61 2 9036 9406.ORCID 0000-0003-0783-1918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electronic medical records (EMRs) are a potentially rich source of information on an individual's health care providers' clinical activities. These data provide an opportunity to tailor web-based learning for health care providers to align closely with their practice. There is increasing interest in the use of EMR data to understand performance and support continuous and targeted education for health care providers. Objective: This study aims to understand the feasibility and acceptability of harnessing EMR data to adaptively deliver a web-based learning program to early-career physicians. Methods: The intervention consisted of a microlearning program where content was adaptively delivered using an algorithm input with EMR data. The microlearning program content consisted of a library of questions covering topics related to best practice management of common emergency department presentations. Study participants were early-career physicians undergoing training in emergency care. The study design involved 3 design cycles, which iteratively changed aspects of the adaptive algorithm based on an end-of-cycle evaluation to optimize the intervention. At the end of each cycle, an online survey and analysis of learning platform metrics were used to evaluate the feasibility and acceptability of the program. Within each cycle, participants were recruited and enrolled in the adaptive program for 6 weeks, with new cohorts of participants in each cycle. Results: Across each cycle, all 75 participants triggered at least 1 question from their EMR data, with the majority triggering 1 question per week. The majority of participants in the study indicated that the online program was engaging and the content felt aligned with clinical practice. Conclusions: The use of EMR data to deliver an adaptive online learning program for emergency trainees is both feasible and acceptable. However, further research is required on the optimal design of such adaptive solutions to ensure training is closely aligned with clinical practice.

Indexed as

Education, DistanceElectronic Health RecordsEmergency MedicineFemaleHumansInternetMalePilot ProjectsSurveys and Questionnairesacceptabilityadaptive algorithmadaptive programadaptive solutionsclinical activitiesdigital healthelectronic health recordselectronic medical recordsemergency careEMRfeasibilityhealth datahealth informaticshealth professional educationonline learningonline microlearningpilot studypractice analyticstrainee

Identifiers

PMID41406416
PMCPMC12711133

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.