Sustained management of the variability in work hours among anesthesiologists providing patient care in operating rooms and not on call to work late if necessary

Abstract

Study objective: We evaluated a department's long-term (6.5-year) success of achieving an overall and individual incidence of anesthesiologists working late of approximately 20% of days when not on call to work late, if necessary, and providing care in operating rooms. Design: Historical cohort study, January 2014 through September 2020. Setting: Inpatient surgical suite of large teaching hospital. Main results: The percentage of days worked past 5:00 PM was mean (standard deviation) 17.7% (5.0%) of days, 99% confidence interval (CI) 15.0% to 20.4%. There was considerable variability among quarters, the coefficient of variation being 28% (99% CI 20% to 45%). This was caused, in part, by anesthesiologists less often working late during January–March versus July–September (14.0% [4.5%] versus 21.6% [3.2%]; P = 0.0031; N = 7 years each). The N = 67 anesthesiologists not on call differed in their percentages of workdays finishing after 5:00 PM (P < 0.0001). While the mean was 18% (6%), the coefficient of variation was 37% (29% to 49%). There were no significant outliers. In contrast, not only were there differences among anesthesiologists in the relative risks of working late when receiving relief versus when not handing off a case (P < 0.0001), there were outliers. Conclusions: An anesthesia department aiming for a 20% incidence of anesthesiologists having to work late when not on call can achieve this objective, long-term, within a few percent (e.g., 2%). Seasonal variation can contribute to variability among quarters in the overall departmental incidence. Individual anesthesiologists can have variability among themselves, though, and that is caused by large heterogeneity in their relative risks of working late when receiving relief versus when not handing off a case. For departments choosing to provide information to anesthesiologists to increase predictability, factors to consider should include season of the year and the individual anesthesiologist.