Evidence map›Paper›PMID 36920981›Full record

ArticlePloS one2023

Association of hospital centrality in inter-hospital patient-sharing networks with patient mortality and length of stay.

Regan W Bergmark, Ginger Jin, Robert S Semco, Marc Santolini, Margaret A Olsen, Amar Dhand

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Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
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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.

Regan W BergmarkCenter for Surgery and Public Health, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America.ORCID 0000-0003-3249-4343
Ginger JinCenter for Surgery and Public Health, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America.
Robert S SemcoCenter for Surgery and Public Health, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America.ORCID 0000-0002-4696-3123
Marc SantoliniUniversité Paris Cité, Inserm, System Engineering and Evolution Dynamics, Paris, France.ORCID 0000-0003-1491-0120
Margaret A OlsenDepartment of Medicine, Division of Infectious Disease, Washington University School of Medicine, St. Louis, MO, United States of America.
Amar DhandNetwork Science Institute, Northeastern University, Boston, MA, United States of America.ORCID 0000-0001-6470-7548

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
NCATS NIH HHS UL1 TR002345
6 · The paper itself

Abstract

objectiveThe interdependence of hospitals is underappreciated in patient outcomes studies. We used a network science approach to foreground this interdependence. Specifically, within two large state-based interhospital networks, we examined the relationship of a hospital's network position with in-hospital mortality and length of stay.

methodsWe constructed interhospital network graphs using data from the Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey for Florida (2014) and California (2011). The exposure of interest was hospital centrality, defined as weighted degree (sum of all ties to a given hospital from other hospitals). The outcomes were in-hospital mortality and length of stay with sub-analyses for four acute medical conditions: pneumonia, heart failure, ischemic stroke, myocardial infarction. We compared outcomes for each quartile of hospital centrality relative to the most central quartile (Q4), independent of patient- and hospital-level characteristics, in this retrospective cross-sectional study.

resultsThe inpatient cohorts had 1,246,169 patients in Florida and 1,415,728 in California. Compared to Florida's central hospitals which had an overall mortality 1.60%, peripheral hospitals had higher in-hospital mortality (1.97%, adjusted OR (95%CI): Q1 1.61 (1.37, 1.89), p<0.001). Hospitals in the middle quartiles had lower in-hospital mortality compared to central hospitals (%, adjusted OR (95% CI): Q2 1.39%, 0.79 (0.70, 0.89), p<0.001; Q3 1.33%, 0.78 (0.70, 0.87), p<0.001). Peripheral hospitals had longer lengths of stay (adjusted incidence rate ratio (95% CI): Q1 2.47 (2.44, 2.50), p<0.001). These findings were replicated in California, and in patients with heart failure and pneumonia in Florida. These results show a u-shaped distribution of outcomes based on hospital network centrality quartile.

conclusionsThe position of hospitals within an inter-hospital network is associated with patient outcomes. Specifically, hospitals located in the peripheral or central positions may be most vulnerable to diminished quality outcomes due to the network. Results should be replicated with deeper clinical data.

Indexed as

Heart FailurePneumoniaCross-Sectional StudiesHospital MortalityHospitalsHumansInpatientsLength of StayRetrospective StudiesUnited States

Identifiers

PMID36920981
PMCPMC10016671

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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.