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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| Format: | Article |
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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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| author | Daniel Tawfik Tait D Shanafelt Mohsen Bayati Jochen Profit |
| author_facet | Daniel Tawfik Tait D Shanafelt Mohsen Bayati Jochen Profit |
| author_sort | Daniel Tawfik |
| collection | DOAJ |
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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. |
| format | Article |
| id | doaj-art-1e001bc162174bf2b3e26e8ef2ad4407 |
| institution | Kabale University |
| issn | 2291-9694 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Medical Informatics |
| spelling | doaj-art-1e001bc162174bf2b3e26e8ef2ad44072025-02-11T21:31:47ZengJMIR PublicationsJMIR Medical Informatics2291-96942025-02-0113e64722e6472210.2196/64722Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational StudyDaniel Tawfikhttp://orcid.org/0000-0003-2901-2737Tait D Shanafelthttp://orcid.org/0000-0002-7106-5202Mohsen Bayatihttp://orcid.org/0000-0002-7280-912XJochen Profithttp://orcid.org/0000-0002-3782-9248 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.https://medinform.jmir.org/2025/1/e64722 |
| spellingShingle | Daniel Tawfik Tait D Shanafelt Mohsen Bayati Jochen Profit Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study JMIR Medical Informatics |
| title | Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study |
| title_full | Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study |
| title_fullStr | Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study |
| title_full_unstemmed | Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study |
| title_short | Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational Study |
| title_sort | electronic health record use patterns among well being survey responders and nonresponders longitudinal observational study |
| url | https://medinform.jmir.org/2025/1/e64722 |
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