Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study
Abstract BackgroundPhysician surveys provide indispensable insights into physician experience, but the question of whether responders are representative can limit confidence in conclusions. Ubiquitously collected electronic health record (EHR) use data may improve understandin...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-02-01
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| Series: | JMIR Medical Informatics |
| Online Access: | https://medinform.jmir.org/2025/1/e64722 |
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| Summary: | Abstract
BackgroundPhysician surveys provide indispensable insights into physician experience, but the question of whether responders are representative can limit confidence in conclusions. Ubiquitously collected electronic health record (EHR) use data may improve understanding of the experiences of survey nonresponders in relation to responders, providing clues regarding their well-being.
ObjectiveThe aim of the study was to identify EHR use measures corresponding with physician survey responses and examine methods to estimate population-level survey results among physicians.
MethodsThis longitudinal observational study was conducted from 2019 through 2020 among academic and community primary care physicians. We quantified EHR use using vendor-derived and investigator-derived measures, quantified burnout symptoms using emotional exhaustion and interpersonal disengagement subscales of the Stanford Professional Fulfillment Index, and used an ensemble of response propensity-weighted penalized linear regressions to develop a burnout symptom prediction model.
ResultsAmong 697 surveys from 477 physicians with a response rate of 80.5% (697/866), always responders were similar to nonresponders in gender (204/340, 60% vs 38/66, 58% women; PPPPP
ConclusionsEHR use measures showed limited utility for predicting burnout symptoms but allowed discrimination between responders and nonresponders. These measures may enable qualitative interpretations of the effects of nonresponders and may inform survey response maximization efforts. |
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| ISSN: | 2291-9694 |