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Record W2167017002 · doi:10.1377/hlthaff.2013.1203

California Emergency Department Closures Are Associated With Increased Inpatient Mortality At Nearby Hospitals

2014· article· en· W2167017002 on OpenAlexaboutno aff
Charles Y. Liu, Tanja Srebotnjak, Renee Y. Hsia

Bibliographic record

VenueHealth Affairs · 2014
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsEmergency departmentMedicineOddsQuarter (Canadian coin)DemographyEmergency medicineClosure (psychology)Odds ratioMedical emergencyFamily medicineGerontologyGeographyLogistic regressionNursingPolitical science

Abstract

fetched live from OpenAlex

Between 1996 and 2009 the annual number of emergency department (ED) visits in the United States increased by 51 percent while the number of EDs nationwide decreased by 6 percent, which placed unprecedented strain on the nation's EDs. To investigate the effects of an ED's closing on surrounding communities, we identified all ED closures in California during the period 1999-2010 and examined their association with inpatient mortality rates at nearby hospitals. We found that one-quarter of hospital admissions in this period occurred near an ED closure and that these admissions had 5 percent higher odds of inpatient mortality than admissions not occurring near a closure. This association persisted whether we considered ED closures as affecting all future nearby admissions or only those occurring in the subsequent two years. These results suggest that ED closures have ripple effects on patient outcomes that should be considered when health systems and policy makers decide how to regulate ED closures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.290
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2014
Admission routes1
Has abstractyes

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