Burnout in Pediatric Emergency Medicine Physicians: A Predictive Model

This study aims to determine the prevalence of and identify predictors associated with burnout in pediatric emergency medicine (PEM) physicians and to construct a predictive model for burnout in this population to stratify risk.

We conducted a cross-sectional electronic survey study among a random sample of board-certified or board-eligible PEM physicians throughout the United States and Canada. Our primary outcome was burnout assessed using the Maslach Burnout Inventory on 3 subscales: emotional exhaustion, depersonalization, and personal accomplishment. We defined burnout as scoring in the high-degree range on any 1 of the 3 subscales. The Maslach Burnout Inventory was followed by questions on personal demographics and work environment. We compared PEM physicians with and without burnout using multivariable logistic regression.

We studied a total of 416 PEM board-certified/eligible physicians (61.3% women; mean age, 45.3 ± 8.8 years). Surveys were initiated by 445 of 749 survey recipients (59.4% response rate). Burnout prevalence measured 49.5% (206/416) in the study cohort, with 34.9% (145/416) of participants scoring in the high-degree range for emotional exhaustion, 33.9% (141/416) for depersonalization, and 20% (83/416) for personal accomplishment. A multivariable model identified 6 independent predictors associated with burnout: 1) lack of appreciation from patients, 2) lack of appreciation from supervisors, 3) perception of an unfair clinical work schedule, 4) dissatisfaction with promotion opportunities, 5) feeling that the electronic medical record detracts from patient care, and 6) working in a nonacademic setting (area under the receiver operating characteristic curve, 0.77). A predictive model demonstrated that physicians with 5 or 6 predictors had an 81% probability of having burnout, whereas those with zero predictors had a 28% probability of burnout.

Burnout is prevalent in PEM physicians. We identified 6 independent predictors for burnout and constructed a scoring system that stratifies probability of burnout. This predictive model may be used to guide organizational strategies that mitigate burnout and improve physician well-being.