Physician Burnout and Timing of Electronic Health Record Use

Abstract

Background Rates of burnout among physicians have been high in recent years. The electronic health record (EHR) is implicated as a major cause of burnout. Objective This article aimed to determine the association between physician burnout and timing of EHR use in an academic internal medicine primary care practice. Methods We conducted an observational cohort study using cross-sectional and retrospective data. Participants included primary care physicians in an academic outpatient general internal medicine practice. Burnout was measured with a single-item question via self-reported survey. EHR time was measured using retrospective automated data routinely captured within the institution's EHR. EHR time was separated into four categories: weekday work-hours in-clinic time, weekday work-hours out-of-clinic time, weekday afterhours time, and weekend/holiday after-hours time. Ordinal regression was used to determine the relationship between burnout and EHR time categories. Results EHR use during in-clinic sessions was related to burnout in both bivariate (odds ratio [OR] = 1.04, 95% confidence interval [CI]: 1.01, 1.06; p = 0.007) and adjusted (OR = 1.07, 95% CI: 1.03, 1.1; p = 0.001) analyses. No significant relationships were found between burnout and after-hours EHR use. Conclusion In this small single-institution study, physician burnout was associated with higher levels of in-clinic EHR use but not after-hours EHR use. Improved understanding of the variability of in-clinic EHR use, and the EHR tasks that are particularly burdensome to physicians, could help lead to interventions that better integrate EHR demands with clinical care and potentially reduce burnout. Further studies including more participants from diverse clinical settings are needed to further understand the relationship between burnout and after-hours EHR use.

Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review

“… 58 , 77 A majority of those studies involved single sites (77.1%) and were affiliated with an academic institution/teaching hospital (80.0%). One third used Epic systems (n = 13), 13 , 22 , 27 , 43 , 53 , 54 , 56 , 57 , 64 , 66 , 69 , 72 , 73 followed by multiple/other/unspecified (n = 12), 14 , 28 , 29 , 52 , 63 , 67 , 68 , 75–79 Cerner (n = 6), 58–60 , 65 , 71 , 74 Allscripts (n = 2), 61 , 62 and Eclipsys (n = 2). 55 , 70 …”

“…Most studies exclusively focused on physicians (n = 25) 13–2942 as compared to nurses (n = 5) 58 , 67 , 76–78 or an interprofessional sample of providers (n = 5). 22 , 55 , 56 , 69 , 73 Clinician specialties were heterogeneous; over half the studies involved single specialties (general [n = 11], 14 , 27 , 52 , 53 , 61 , 62 , 64 , 71–73 , 75 emergency [n = 2], 57 , 79 intensivist [n = 2], 67 , 70 other [(n = 5] 13 , 54 , 56 , 74 , 78 ), while the remaining were multiple subspecialties (n = 13) 9 , 22 , 28 , 43 , 58–60 , 63 , 65 , 66 , 69 , 76 , 77 or unspecified (n = 2). 55 , 68 Across all studies, most involved general medicine (n = 17) 14 , 22 , 27 , 28 , 43 , 52 , 53 , 59–66 , 69 , 71–73 , 75–77 follo...…”

“…While purely qualitative studies were excluded, 5 studies employed mixed methods 28 , 52 , 55 , 61 , 62 (see online Supplementary Table ). Study designs varied, including time-and-motion (TM [n = 5] 28 , 61 , 62 , 67 , 68 ), validation of TM (n = 2), 27 , 70 cohort (n = 15), 13 , 27 , 43 , 54 , 55 , 57 , 59 , 60 , 63 , 64 , 66 , 72 , 74 , 75 , 77 experimental/quasi-experimental (n = 8), 14 , 22 , 29 , 53 , 56 , 58 , 78 , 79 and cross-sectional studies (n = 4). 69 , 71 , 73 , 76 Eight studies evaluated an intervention, 14 , 22 , 52 , 53 , 56 , 58 , 75 , 78 including scribes (n = 3), 14 , 52 , 53 documentation redesign (n = 3), 58 ...…”

“…Qualitative methods employed in the mixed-methods studies involved informal interviews, 62 social network analysis, 55 thematic analysis, 62 focus groups, 52 and self-reported diary. 28 Few studies addressed validity or reliability of measurements in their studies (n = 11) 22 , 52 , 53 , 59 , 60 , 63 , 64 , 67 , 69 , 73 , 78 ; 2 examined interobserver reliability, 28 , 68 2 employed TM approaches to validate novel analytical methods to examine workflow 70 and the use of EHR usage logs to estimate workload, 27 2 examined correlations between self-reported and objective EHR usage log times, 22 , 73 and 1 employed video recording timers to validate EHR usage log times. 58 …”

Perceived Electronic Health Record Usability as a Predictor of Task Load and Burnout Among US Physicians: Mediation Analysis (Preprint)

“…Occupational burnout in physicians is a complex phenomenon with multiple interdependent drivers related to practice efficiency, organizational culture, and personal resilience [1]. In the domain of practice efficiency, there is growing evidence supporting an association between electronic health record (EHR) usability and physician burnout [2][3][4][5][6][7]. Usability is the extent to which technology can be used effectively, efficiently, and satisfactorily based on its design and integration into a specific context of use [8].…”