Objective To quantify how stress related to use of health information technology (HIT) predicts burnout among physicians. Methods All 4197 practicing physicians in Rhode Island were surveyed in 2017 on their HIT use. Our main outcome was self-reported burnout. The presence of HIT-related stress was defined by report of at least 1 of the following: poor/marginal time for documentation, moderately high/excessive time spent on the electronic health record (EHR) at home, and agreement that using an EHR adds to daily frustration. We used logistic regression to assess the association between each HIT-related stress measure and burnout, adjusting for respondent demographics, practice characteristics, and the other stress measures. Results Of the 1792 physician respondents (43% response rate), 26% reported burnout. Among EHR users (91%), 70% reported HIT-related stress, with the highest prevalence in primary care-oriented specialties. After adjustment, physicians reporting poor/marginal time for documentation had 2.8 times the odds of burnout (95% CI: 2.0–4.1; P < .0001), compared to those reporting sufficient time. Physicians reporting moderately high/excessive time on EHRs at home had 1.9 times the odds of burnout (95% CI: 1.4–2.8; P < .0001), compared to those with minimal/no EHR use at home. Those who agreed that EHRs add to their daily frustration had 2.4 times the odds of burnout (95% CI: 1.6–3.7; P < .0001), compared to those who disagreed. Conclusion HIT-related stress is measurable, common (about 70% among respondents), specialty-related, and independently predictive of burnout symptoms. Identifying HIT-specific factors associated with burnout may guide healthcare organizations seeking to measure and remediate burnout among their physicians and staff.

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Objective The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data. Materials and Methods We combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics. Results Clinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039). Discussion High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, “patient calls” encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being. Conclusions Our results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.