Understanding Physician Work and Well-being Through Social Network Modeling Using Electronic Health Record Data: a Cohort Study
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11606_2021_Article_7351.pdf
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Author(s)
Escribe, Célia
Eisenstat, Stephanie A.
Palamara, Kerri
O’Donnell, Walter J.
Wasfy, Jason H.
Lehrhoff, Sara R.
Bravard, Marjory A.
Levi, Retsef
del Carmen, Marcela G.
Date Issued
January 28, 2022
Publisher
Springer International Publishing
Citation
Escribe, Célia, Eisenstat, Stephanie A., Palamara, Kerri, O’Donnell, Walter J., Wasfy, Jason H. et al. 2022. "Understanding Physician Work and Well-being Through Social Network Modeling Using Electronic Health Record Data: a Cohort Study."
Version
Final published version
Abstract
Abstract
Background
Understanding association between factors related to clinical work environment and well-being can inform strategies to improve physicians’ work experience.
Objective
To model and quantify what drivers of work composition, team structure, and dynamics are associated with well-being.
Design
Utilizing social network modeling, this cohort study of physicians in an academic health center examined inbasket messaging data from 2018 to 2019 to identify work composition, team structure, and dynamics features. Indicators from a survey in 2019 were used as dependent variables to identify factors predictive of well-being.
Participants
EHR data available for 188 physicians and their care teams from 18 primary care practices; survey data available for 163/188 physicians.
Main Measures
Area under the receiver operating characteristic curve (AUC) of logistic regression models to predict well-being dependent variables was assessed out-of-sample.
Key Results
The mean AUC of the model for the dependent variables of emotional exhaustion, vigor, and professional fulfillment was, respectively, 0.665 (SD 0.085), 0.700 (SD 0.082), and 0.669 (SD 0.082). Predictors associated with decreased well-being included physician centrality within support team (OR 3.90, 95% CI 1.28–11.97, P=0.01) and share of messages related to scheduling (OR 1.10, 95% CI 1.03–1.17, P=0.003). Predictors associated with increased well-being included higher number of medical assistants within close support team (OR 0.91, 95% CI 0.83–0.99, P=0.05), nurse-centered message writing practices (OR 0.89, 95% CI 0.83–0.95, P=0.001), and share of messages related to ambiguous diagnosis (OR 0.92, 95% CI 0.87–0.98, P=0.01).
Conclusions
Through integration of EHR data with social network modeling, the analysis highlights new characteristics of care team structure and dynamics that are associated with physician well-being. This quantitative methodology can be utilized to assess in a refined data-driven way the impact of organizational changes to improve well-being through optimizing team dynamics and work composition.
MIT Department
Massachusetts Institute of Technology. Operations Research Center
Sloan School of Management
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DOI of Published Version
https://doi.org/10.1007/s11606-021-07351-x
