Evidence map›Paper›PMID 39917519›Full record

ArticleFrontiers in public health2024

Models of community hospitals and state of research in high-income countries: a scoping review.

Min Hui Tan, Sharna Si Ying Seah, Xin Yi Seah, Simone Teo, Jeremy Leow, Lian Leng Low

Abstract readScoping Review
In one paragraph

Article in Frontiers in public health, 2024. 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
–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

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

6 authors.

Min Hui TanSingHealth Community Hospitals, Singapore, Singapore.
Sharna Si Ying SeahSingHealth Community Hospitals, Singapore, Singapore.
Xin Yi SeahSingHealth Community Hospitals, Singapore, Singapore.
Simone TeoSingHealth Community Hospitals, Singapore, Singapore.
Jeremy LeowSingHealth Community Hospitals, Singapore, Singapore.
Lian Leng LowSingHealth Community Hospitals, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Existing literature have not reviewed the growing spectrum of care models in Community Hospitals (CH) along with the scope of research. We fill this gap by reviewing CHs models in high-income countries. Methods: We conducted a scoping review according to Arksey & O'Malley's framework. We searched for articles published between January 2016 to April 2024 in EMBASE, PubMed, and Scopus. Additional studies were identified through snowballing. Results: 470 studies were included in the review. CHs models in 22 countries were categorized based on healthcare services provided and target patient populations. CHs in 18 countries were found to provide COVID-19 services. CHs in eight countries primarily provide post-acute and rehabilitative services. 40 articles were extracted to synthesize research themes in CHs providing post-acute care. Majority focused on assessing the healthcare needs of patient populations. Other domains include program efficacy, research and educational needs of staff, clinical guidelines reviews, and the community's role in supporting CHs. Conclusion: CHs evolve to meet changing healthcare needs and understanding the state of CHs research would inform potential research directions. Future studies could explore the relationship between post-acute settings and the community, and strategies to enhance staff capability and address barriers to conducting research in post-acute settings.

Indexed as

COVID-19Developed CountriesHospitals, CommunityDelivery of Health CareHumanscommunity hospitalsmodels of carepost-acute careresearchscoping review

Identifiers

PMID39917519
PMCPMC11799244

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.