Ambulance diversions following public hospital emergency department closures

Health Serv Res. 2019 Aug;54(4):870-879. doi: 10.1111/1475-6773.13147. Epub 2019 Apr 2.

Abstract

Objective: To examine whether hospitals are more likely to temporarily close their emergency departments (EDs) to ambulances (through ambulance diversions) if neighboring diverting hospitals are public vs private.

Data sources/study setting: Ambulance diversion logs for California hospitals, discharge data, and hospital characteristics data from California's Office of Statewide Health Planning and Development and the American Hospital Association (2007).

Study design: We match public and private (nonprofit or for-profit) hospitals by distance and size. We use random-effects models examining diversion probability and timing of private hospitals following diversions by neighboring public vs matched private hospitals.

Data collection/extraction methods: N/A.

Principal findings: Hospitals are 3.6 percent more likely to declare diversions if neighboring diverting hospitals are public vs private (P < 0.001). Hospitals declaring diversions have lower ED occupancy (P < 0.001) after neighboring public (vs private) hospitals divert. Hospitals have 4.2 percent shorter diversions if neighboring diverting hospitals are public vs private (P < 0.001). When the neighboring hospital ends its diversion first, hospitals terminate diversions 4.2 percent sooner if the neighboring hospital is public vs private (P = 0.022).

Conclusions: Sample hospitals respond differently to diversions by neighboring public (vs private) hospitals, suggesting that these hospitals might be strategically declaring ambulance diversions to avoid treating low-paying patients served by public hospitals.

Keywords: access to care; ambulance diversion; emergency department.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ambulance Diversion / statistics & numerical data*
  • Bed Occupancy / statistics & numerical data
  • California
  • Emergency Service, Hospital / statistics & numerical data*
  • Hospital Bed Capacity / statistics & numerical data
  • Hospitals, Private / statistics & numerical data*
  • Hospitals, Public / statistics & numerical data*
  • Humans
  • Probability
  • Residence Characteristics
  • Socioeconomic Factors
  • Time Factors