Who is coming in? Evaluation of physician performance within multi-physician emergency departments

This study aimed to examine how physician performance metrics are affected by the speed of other attendings (co-attendings) concurrently staffing the ED.

A retrospective study was conducted using patient data from two EDs between January-2018 and February-2020. Machine learning was used to predict patient length of stay (LOS) conditional on being assigned a physician of average speed, using patient- and departmental-level variables. A physician's patients' actual LOSs were compared to the model's predictions to calculate a measurement of that physician's speed. Linear regression models were employed to assess how physician performance changed based on the measured speed of the concurrent ED co-attendings, on outcomes including patient LOS, patients treated per hour, imaging utilization, admission rates, and 72-h ED revisits.

Eighty physicians and 212,902 ED visits were included. Overall, patients assigned to the fastest physicians have a 17.8 % [13.5 %, 22.0 %] shorter LOS compared to average-speed attendings. When the fastest physicians work alongside the fastest co-attendings, their LOS benefit is reduced to 14.9 %, representing a 2.9 % [0.2 %, 5.6 %] longer LOS than when working without the fastest co-attendings. Similarly, the fastest physicians see 0.21 [0.13, 0.28] more patients per hour compared to average attendings, but this benefit decreases to 0.13 [0.09, 0.17] more patients per hour when the fastest co-attendings are present, reflecting a reduction of 0.08 [0.04, 0.11] patients per hour. The fastest physicians order 0.18 [0.13, 0.23] fewer imaging tests per patient than average-speed attendings; however, this reduction diminishes by 0.05 [0.04, 0.07] imaging tests per patient when the fastest co-attendings are present. Our model found effects of similar magnitudes but in the opposite direction when the slowest co-attendings are present. The speed of co-attendings had no significant association on the attending admission rate or 72-h revisit rate. Additionally, compared to the average attending team speed, slower attending teams, over an 8 h shift, experienced increased waiting room volume by 6.4 % [4.5 %, 8.4 %] while there was no difference when staffed by the fastest attending teams (-1.2 % [-3.2 %,0.7 %]).

In this exploratory analysis, physicians have slower throughput and order more imaging when faster co-attendings are present, and faster throughput with less imaging ordered when slower co-attendings are present. Administrators might consider these relationships and balancing attending speeds, particularly at the extremes (slowest and fastest), when designing staffing models as a potential strategy to enhance ED operational efficiency. What is already known on this topic: ED throughput is known to be dependent on multiple factors however physician behavior is commonly modeled as single attendings working in the ED.

This study examines the association between attending and co-attending speed on physician performance and finds that physicians become faster when a slow co-attending is present and slow down when a fast co-attending is present. How this study might affect research, practice or policy: Physician behavior does not exist in isolation and how an entire ED is staffed may have implications for throughput.