Evidence map›Paper›PMID 30941753›Full record

ArticleHealth services research2019

Ambulance diversions following public hospital emergency department closures.

Charleen Hsuan, Renee Y Hsia, Jill R Horwitz, Ninez A Ponce, Thomas Rice, Jack Needleman

Open access · greenAbstract read
In one paragraph

Article in Health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Charleen HsuanDepartment of Health Policy and Administration, Penn State University, University Park, Pennsylvania.ORCID 0000-0001-8720-2323
Renee Y HsiaDepartment of Emergency Medicine, University of California, San Francisco, Zuckerberg San Francisco General Hospital, San Francisco, California.ORCID 0000-0001-9819-6926
Jill R HorwitzSchool of Law, University of California, Los Angeles, Los Angeles, California.
Ninez A PonceFielding School of Public Health, Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, California.ORCID 0000-0001-5151-6718
Thomas RiceFielding School of Public Health, Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, California.
Jack NeedlemanFielding School of Public Health, Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, California.ORCID 0000-0002-2875-0589
Los Angeles County Department of Public Health · USPennsylvania State University · USSan Francisco General Hospital · USUniversity of California, Los Angeles · US

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
UCLA Clinical and Translational Science InstituteTL1TR000121 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$2.7M
Agency for Healthcare Research and Quality R36HS024247-01NCATS NIH HHS TL1 TR000121NCATS NIH HHS UCLA CTSI #TL1TR000121NCATS NIH HHS UL1 TR002014University of California, Los Angeles
6 · The paper itself

Abstract

objectiveTo 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

settingAmbulance 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

designWe 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

methodsN/A. PRINCIPAL

findingsHospitals 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).

conclusionsSample 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.

Indexed as

Ambulance DiversionBed OccupancyCaliforniaEmergency Service, HospitalHospital Bed CapacityHospitals, PrivateHospitals, PublicHumansProbabilityResidence CharacteristicsSocioeconomic FactorsTime Factorsaccess to careambulance diversionemergency department

Identifiers

PMID30941753
PMCPMC6606538
OpenAlexW2927674455

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.