Predicting Workload and Stress on Academic Surgical Services
*Lane Curran1, *Brittany Misercola2, David Clark2, *Julianne Ontengco2, James Whiting2
1Albany Medical College, Albany, NY; 2Maine Medical Center, Portland, ME
Objective: Quantify, relate, and predict workload and personal stress for residents (RES) and advanced practice providers (APP) staffing surgical services
Design: Prospective cohort with collection of daily administrative, electronic medical record (EMR), and paging data, and a validated survey
Setting: Trauma (T) and Vascular (V) surgical services at a New England teaching hospital
Participants: 22 RES and 12 APP working weekdays over 10 months
Main Outcome Measure: Perceived stress measured by daily modified NASA Task Load Index (NASA-TLX), consisting of three questions relating to temporal demands, mental demands, and frustration.
Results: Multiple linear regression models demonstrated that perceived stress measured by NASA-TLX was positively associated with RES vs APP, work hours, orders written, team pages received, and team discharges; NASA-TLX was negatively associated with years of experience, number of APP on team, number of RES on team, and later vs earlier day of week. The strength of these predictors was stronger for APP than for RES. Multivariate models showed no significant independent associations between NASA-TLX and age, sex, time in OR, team census, team admissions, or service (T vs V).
Technical challenges to data collection from each source had to be overcome; daily survey response rates were >50% for the first two months, decreasing thereafter. For census, admissions, notes written, and pages received (especially for APP), T exceeded V; for OR time and orders written, V exceeded T. Work hours (first EMR log-in to last log-out) were similar for T and V.
Conclusions: Objective data can quantify workload and predict perceived stress, especially for APP, and may be used for planning or evaluation of staffing resource distribution among academic surgical services.