Healthcare Utilization and Provider Workload in Collegiate Student Athletes for Acute, Overuse, Time-Loss and Non-Time-Loss Injuries.

Abstract

Context: Limited real-world data demonstrate healthcare provided by collegiate sports medicine teams, across a variety of sports and injury categories that could inform appropriate staffing and workload.

Objective: To describe athletic training (AT) services and physician encounters (PE) for acute and overuse injuries, stratified by gender and time-loss (TL) status.

Design: Descriptive epidemiology.

Setting: Sports medicine facilities at 12 institutions participating in the PAC-12 Health Analytics Program.

Patients or other participants: Division I collegiate student-athletes.

Main outcome measures: Injury counts were associated with AT services and PE. Percentages of cases which received either none or ≥1 AT service and PE were calculated. Descriptive data were provided with confidence intervals, with rates calculated per-injury and per-team-season.

Results: From 27,575 injuries, 266,910 AT services were provided, with 11,988 PE associated across 31 different sports (M 15; W 16) completing 947 team-seasons (M 416; W 531). Almost half of AT services (47.2%) and PE (48.4%) were dedicated to acute-NTL and overuse-TL and -NTL injuries. Percentages of cases receiving any AT services varied by injury category of acute-TL and -NTL and overuse-TL and -NTL (63.9% to 80.1%), while PE ranged from 33% to 59%. When ranking AT services per-injury and per-team-season, the sports with the highest rates were more frequently categorized as low to moderate risk in the Appropriate Medical Coverage of Intercollegiate Athletics, rather than increased risk.

Conclusions: Lower or moderate risk sports demonstrated substantial healthcare utilization in AT service rates per-injury and per-team-season. Additionally, those services were frequently directed at overuse and NTL injuries, rather than predominantly acute-TL. Our findings suggest a potential mismatch between provider workload and historic risk categorization calculated by injury risk and treatments per-injury. These data should inform and update considerations for appropriate staffing levels, differential workload assignments, and alignment with clinical best practices.