Evidence map›Paper›PMID 40857292›Full record

ArticlePloS one2025

Computational modeling and analysis of medical resource shortages in hospital alliance: A simulation-driven approach.

Zhenkun Gan, Zhengtang Fu, Peiwu Dong, Yanbing Ju, Yajun Shen

Expression of concernAbstract 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. It carries an expression of concern. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Zhenkun GanSchool of Economics, Beijing Institute of Technology, Beijing, China.
Zhengtang FuSchool of Environment, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0001-5670-3379
Peiwu DongSchool of Economics, Beijing Institute of Technology, Beijing, China.
Yanbing JuSchool of Management, Beijing Institute of Technology, Beijing, China.
Yajun ShenSchool of Economics, Beijing Institute of Technology, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hospital alliances, as an innovative model of hospital management, are dedicated to achieving resource sharing across the entire healthcare network. During the COVID-19 pandemic in China, these alliances played a pivotal role in combating the outbreak. However, a significant challenge emerged: the difficulty in accurately quantifying medical resource shortages at individual hospitals hindered the efficient allocation of these critical resources. To address this issue, this study proposes an integrated urgent medical resource evaluation model designed to scientifically assess the urgency of medical resource needs within the alliance. Methodologically, the model innovatively combines the SEIR system dynamics model, complex network analysis, and entropy-weighted TOPSIS to construct a multi-dimensional evaluation framework. A case study has been conducted to validate the effectiveness of the proposed methodology. Contrary to conventional expectations, the findings reveal that small-scale hospitals exhibit higher medical resource urgency compared to their large-scale counterparts within the alliance. Based on these results, we recommend that policymakers prioritize addressing medical resource shortages in small-scale hospitals during pandemics.

Indexed as

Computer SimulationCOVID-19Health ResourcesHospitalsChinaHospital AdministrationHumansPandemicsSARS-CoV-2

Identifiers

PMID40857292
PMCPMC12380337

What OpenQuestion holds

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LicenceCC BY
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.