@article{7151118245834e62b2e5d804e926d02c,
title = "Ambulance diversions following public hospital emergency department closures",
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.",
author = "Charleen Hsuan and Hsia, {Renee Y.} and Horwitz, {Jill R.} and Ponce, {Ninez A.} and Thomas Rice and Jack Needleman",
note = "Funding Information: Joint Acknowledgment/Disclosure Statement: This study was supported by fellowships to Hsuan from the Agency for Healthcare Research and Quality R36 Grant (R36HS02424701), the NIH/National Center for Advancing Translational Sciences (NCATS) UCLA CTSI Grant Number TL1TR000121, and a Dissertation Year Fellowship from the University of California, Los Angeles. None of the sponsors were involved in the study design, in the collection, analysis, and interpretation of the data, in the writing of the report, or in the decision to submit the article for publication. The content in this paper does not necessarily represent the official views of the Agency for Healthcare Research and Quality, the National Institutes of Health, or UCLA. The authors thank the National Bureau of Economic Research for providing data. Dr. Hsuan thanks the Penn State Department of Health Policy and Administration. Dr. Horwitz thanks the UCLA School of Law and University of Victoria Department of Economics. Dr. Ponce thanks the UCLA Center for Health Policy Research. Funding Information: ported by fellowships to Hsuan from the Agency for Healthcare Research and Quality R36 Grant (R36HS02424701), the NIH/ National Center for Advancing Translational Sciences (NCATS) UCLA CTSI Grant Number TL1TR000121, and a Dissertation Year Fellowship from the University of California, Los Angeles. None of the sponsors were involved in the study design, in the collection, analysis, and interpretation of the data, in the writing of the report, or in the decision to submit the article for publication. The content in this paper does not necessarily represent the official views of the Agency for Healthcare Research and Quality, the National Institutes of Health, or UCLA. Publisher Copyright: {\textcopyright} Health Research and Educational Trust",
year = "2019",
month = aug,
doi = "10.1111/1475-6773.13147",
language = "English (US)",
volume = "54",
pages = "870--879",
journal = "Health Services Research",
issn = "0017-9124",
publisher = "Wiley-Blackwell",
number = "4",
}