Evidence map›Paper›PMID 39903710›Full record

ArticlePloS one2025

Data-driven insights into interhospital care fragmentation: Implications for health policy and equity among older adults.

Somayeh Ghazalbash, Manaf Zargoush, Vedat Verter, Dan Perri

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Somayeh GhazalbashManagement Analytics, Smith School of Business, Queen's University, Kingston, Ontario, Canada.
Manaf ZargoushHealth Policy and Management, DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada.ORCID 0000-0002-5052-4828
Vedat VerterManagement Analytics, Smith School of Business, Queen's University, Kingston, Ontario, Canada.ORCID 0000-0002-4628-9618
Dan PerriDivision of Gastroenterology and Critical Care Medicine, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo determine factors leading to interhospital care fragmentation (ICF); evaluate how ICF affects rehospitalization costs, length of stays (LOS), and delayed discharge; and analyze ICF disparity among equity-seeking groups. MATERIALS AND

methodsWe used a 13-year retrospective cohort of older adults (65+) in Ontario, Canada. Utilizing multivariable logistic regression, we identified characteristics associated with ICF and determined its association with outcomes.

resultsDischarge to facilities except home and homecare and travel distance were the strongest risk factors for ICF. Patients were less likely to experience ICF if they were older, frail, or had multiple comorbidities. ICF was strongly associated with an increase in the daily costs of readmission. Moreover, the risks of a prolonged LOS after ICF and delayed discharge were higher among returning surgical patients. The rural residency was a source of health inequality.

conclusionsICF exacerbates health disparities and worsens patient outcomes. Our study identified several risk factors associated with ICF, some of which are controllable, paving the way for interventions to mitigate this issue. To promote health equity and reduce adverse outcomes, policymakers should focus on policies for reducing care discontinuity, particularly addressing the controllable risk factors.

Indexed as

Health EquityHealth PolicyAgedAged, 80 and overFemaleHumansLength of StayMaleOntarioPatient DischargePatient ReadmissionRetrospective StudiesRisk Factors

Identifiers

PMID39903710
PMCPMC11793756

What OpenQuestion holds

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Registered trials

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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.