Modeling Hourly Resident Productivity in the Emergency Department.

Joseph, Joshua W, Daniel J Henning, Connie S Strouse, David T Chiu, Larry A Nathanson, and Leon D Sanchez. 2017. “Modeling Hourly Resident Productivity in the Emergency Department.”. Annals of Emergency Medicine 70 (2): 185-190.e6.

Abstract

STUDY OBJECTIVE: Resident productivity, defined as new patients per hour, carries important implications for emergency department operations. In high-volume academic centers, essential staffing decisions can be made on the assumption that residents see patients at a static rate. However, it is unclear whether this model mirrors reality; previous studies have not rigorously examined whether productivity changes over time. We examine residents' productivity across shifts to determine whether it remained consistent.

METHODS: This was a retrospective cohort study conducted in an urban academic hospital with a 3-year emergency medicine training program in which residents acquire patients ad libitum throughout their shift. Time stamps of all patient encounters were automatically logged. A linear mixed model was constructed to predict productivity per shift hour.

RESULTS: A total of 14,364 8- and 9-hour shifts were worked by 75 residents between July 1, 2010, and June 20, 2015. This comprised 6,127 (42.7%) postgraduate year (PGY) 1 shifts, 7,236 (50.4%) PGY-2 shifts, and 998 (6.9%) PGY-3 nonsupervisory shifts (Table 1). Overall, residents treated a mean of 10.1 patients per shift (SD 3.2), with most patients at Emergency Severity Index level 3 or more acute (93.8%). In the initial hour, residents treated a mean of 2.14 patients (SD 1.2), and every subsequent hour was associated with a significant decrease, with the largest in the second, third, and final hours.

CONCLUSION: Emergency medicine resident productivity during a single shift follows a reliable pattern that decreases significantly hourly, a pattern preserved across PGY years and types of shifts. This suggests that resident productivity is a dynamic process, which should be considered in staffing decisions and studied further.

Last updated on 09/06/2024
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