"EMERGing" Electronic Health Record Data Metrics: Insights and Implications for Assessing Residents' Clinical Performance in Emergency Medicine.


Journal

AEM education and training
ISSN: 2472-5390
Titre abrégé: AEM Educ Train
Pays: United States
ID NLM: 101722142

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 04 05 2020
revised: 02 07 2020
accepted: 07 07 2020
entrez: 26 4 2021
pubmed: 27 4 2021
medline: 27 4 2021
Statut: epublish

Résumé

Competency-based medical education requires that residents are provided with frequent opportunities to demonstrate competence as well as receive effective feedback about their clinical performance. To meet this goal, we investigated how data collected by the electronic health record (EHR) might be used to assess emergency medicine (EM) residents' independent and interdependent clinical performance and how such information could be represented in an EM resident report card. Following constructivist grounded theory methodology, individual semistructured interviews were conducted in 2017 with 10 EM faculty and 11 EM residents across all 5 postgraduate years. In addition to open-ended questions, participants were presented with an emerging list of EM practice metrics and asked to comment on how valuable each would be in assessing resident performance. Additionally, we asked participants the extent to which each metric captured independent or interdependent performance. Data collection and analysis were iterative; analysis employed constant comparative inductive methods. Participants refined and eliminated metrics as well as added new metrics specific to the assessment of EM residents (e.g., time between signup and first orders). These clinical practice metrics based on data from our EHR database were organized along a spectrum of independent/interdependent performance. We conclude with discussions about the relationship among these metrics, issues in interpretation, and implications of using EHR for assessment purposes. Our findings document a systematic approach for developing EM resident assessments, based on EHR data, which incorporate the perspectives of both clinical faculty and residents. Our work has important implications for capturing residents' contributions to clinical performances and distinguishing between independent and interdependent metrics in collaborative workplace-based settings.

Identifiants

pubmed: 33898906
doi: 10.1002/aet2.10501
pii: AET210501
pmc: PMC8052996
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e10501

Informations de copyright

© 2020 by the Society for Academic Emergency Medicine.

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Auteurs

Stefanie S Sebok-Syer (SS)

Department of Emergency Medicine at Stanford University School of Medicine Stanford University Palo Alto CA USA.

Lisa Shepherd (L)

Division of Emergency Medicine at Schulich School of Medicine and Dentistry Western University London Ontario Canada.

Allison McConnell (A)

Division of Emergency Medicine at Schulich School of Medicine and Dentistry Western University London Ontario Canada.

Adam M Dukelow (AM)

Division of Emergency Medicine at Schulich School of Medicine and Dentistry Western University London Ontario Canada.

Robert Sedran (R)

Division of Emergency Medicine at Schulich School of Medicine and Dentistry Western University London Ontario Canada.

Lorelei Lingard (L)

Department of Medicine and Faculty of Education and the Centre for Education, Research, and Innovation at Schulich School of Medicine and Dentistry Western University London Ontario Canada.

Classifications MeSH