TY - JOUR
T1 - Temporal Associations Between EHR-Derived Workload, Burnout, and Errors
T2 - a Prospective Cohort Study
AU - Lou, Sunny S.
AU - Lew, Daphne
AU - Harford, Derek R.
AU - Lu, Chenyang
AU - Evanoff, Bradley A.
AU - Duncan, Jennifer G.
AU - Kannampallil, Thomas
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Society of General Internal Medicine.
PY - 2022/7
Y1 - 2022/7
N2 - Background: The temporal progression and workload-related causal contributors to physician burnout are not well-understood. Objective: To characterize burnout’s time course and evaluate the effect of time-varying workload on burnout and medical errors. Design: Six-month longitudinal cohort study with measurements of burnout, workload, and wrong-patient orders every 4 weeks. Participants: Seventy-five intern physicians in internal medicine, pediatrics, and anesthesiology at a large academic medical center. Main Measures: Burnout was measured using the Professional Fulfillment Index survey. Workload was collected from electronic health record (EHR) audit logs and summarized as follows: total time spent on the EHR, after-hours EHR time, patient load, inbox time, chart review time, note-writing time, and number of orders. Wrong-patient orders were assessed using retract-and-reorder events. Key Results: Seventy-five of 104 interns enrolled (72.1%) in the study. A total of 337 surveys and 8,863,318 EHR-based actions were analyzed. Median burnout score across the cohort across all time points was 1.2 (IQR 0.7–1.7). Individual-level burnout was variable (median monthly change 0.3, IQR 0.1–0.6). In multivariable analysis, increased total EHR time (β=0.121 for an increase from 54.5 h per month (25th percentile) to 123.0 h per month (75th percentile), 95%CI=0.016–0.226), increased patient load (β=0.130 for an increase from 4.9 (25th percentile) to 7.1 (75th percentile) patients per day, 95%CI=0.053–0.207), and increased chart review time (β=0.096 for an increase from 0.39 (25th percentile) to 0.59 (75th percentile) hours per patient per day, 95%CI=0.015–0.177) were associated with an increased burnout score. After adjusting for the total number of ordering sessions, burnout was not statistically associated with an increased rate of wrong-patient orders (rate ratio=1.20, 95%CI=0.76–1.89). Conclusions: Burnout and recovery were associated with recent clinical workload for a cohort of physician trainees, highlighting the elastic nature of burnout. Wellness interventions should focus on strategies to mitigate sustained elevations of work responsibilities.
AB - Background: The temporal progression and workload-related causal contributors to physician burnout are not well-understood. Objective: To characterize burnout’s time course and evaluate the effect of time-varying workload on burnout and medical errors. Design: Six-month longitudinal cohort study with measurements of burnout, workload, and wrong-patient orders every 4 weeks. Participants: Seventy-five intern physicians in internal medicine, pediatrics, and anesthesiology at a large academic medical center. Main Measures: Burnout was measured using the Professional Fulfillment Index survey. Workload was collected from electronic health record (EHR) audit logs and summarized as follows: total time spent on the EHR, after-hours EHR time, patient load, inbox time, chart review time, note-writing time, and number of orders. Wrong-patient orders were assessed using retract-and-reorder events. Key Results: Seventy-five of 104 interns enrolled (72.1%) in the study. A total of 337 surveys and 8,863,318 EHR-based actions were analyzed. Median burnout score across the cohort across all time points was 1.2 (IQR 0.7–1.7). Individual-level burnout was variable (median monthly change 0.3, IQR 0.1–0.6). In multivariable analysis, increased total EHR time (β=0.121 for an increase from 54.5 h per month (25th percentile) to 123.0 h per month (75th percentile), 95%CI=0.016–0.226), increased patient load (β=0.130 for an increase from 4.9 (25th percentile) to 7.1 (75th percentile) patients per day, 95%CI=0.053–0.207), and increased chart review time (β=0.096 for an increase from 0.39 (25th percentile) to 0.59 (75th percentile) hours per patient per day, 95%CI=0.015–0.177) were associated with an increased burnout score. After adjusting for the total number of ordering sessions, burnout was not statistically associated with an increased rate of wrong-patient orders (rate ratio=1.20, 95%CI=0.76–1.89). Conclusions: Burnout and recovery were associated with recent clinical workload for a cohort of physician trainees, highlighting the elastic nature of burnout. Wellness interventions should focus on strategies to mitigate sustained elevations of work responsibilities.
KW - burnout
KW - electronic health record
KW - graduate medical education
KW - physician wellness
KW - workload
UR - http://www.scopus.com/inward/record.url?scp=85130763477&partnerID=8YFLogxK
U2 - 10.1007/s11606-022-07620-3
DO - 10.1007/s11606-022-07620-3
M3 - Article
C2 - 35710654
AN - SCOPUS:85130763477
SN - 0884-8734
VL - 37
SP - 2165
EP - 2172
JO - Journal of general internal medicine
JF - Journal of general internal medicine
IS - 9
ER -