Evidence map›Paper›PMID 38832581›Full record

ArticleJMIR medical informatics2024

Addressing Hospital Overwhelm During the COVID-19 Pandemic by Using a Primary Health Care-Based Integrated Health System: Modeling Study.

Jiaoling Huang, Ying Qian, Yuge Yan, Hong Liang, Laijun Zhao

Abstract read
In one paragraph

Article in JMIR medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

5 authors.

Jiaoling HuangSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID http://orcid.org/0000-0003-1975-3937
Ying QianBusiness School, University of Shanghai for Science and Technology, Shanghai, China.ORCID http://orcid.org/0000-0002-1995-9153
Yuge YanSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID http://orcid.org/0009-0005-7255-8753
Hong LiangSchool of Social Development and Public Policy, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0008-5802-2786
Laijun ZhaoBusiness School, University of Shanghai for Science and Technology, Shanghai, China.ORCID http://orcid.org/0000-0003-0081-4576

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: After strict COVID-19-related restrictions were lifted, health systems globally were overwhelmed. Much has been discussed about how health systems could better prepare for future pandemics; however, primary health care (PHC) has been largely ignored. Objective: We aimed to investigate what combined policies PHC could apply to strengthen the health care system via a bottom-up approach, so as to better respond to a public health emergency. Methods: We developed a system dynamics model to replicate Shanghai's response when COVID-19-related restrictions were lifted. We then simulated an alternative PHC-based integrated health system and tested the following three interventions: first contact in PHC with telemedicine services, recommendation to secondary care, and return to PHC for recovery. Results: The simulation results showed that each selected intervention could alleviate hospital overwhelm. Increasing the rate of first contact in PHC with telemedicine increased hospital bed availability by 6% to 12% and reduced the cumulative number of deaths by 35%. More precise recommendations had a limited impact on hospital overwhelm (<1%), but the simulation results showed that underrecommendation (rate: 80%) would result in a 19% increase in cumulative deaths. Increasing the rate of return to PHC from 5% to 20% improved hospital bed availability by 6% to 16% and reduced the cumulative number of deaths by 46%. Moreover, combining all 3 interventions had a multiplier effect; bed availability increased by 683%, and the cumulative number of deaths dropped by 75%. Conclusions: Rather than focusing on the allocation of medical resources in secondary care, we determined that an optimal PHC-based integrated strategy would be to have a 60% rate of first contact in PHC, a 110% recommendation rate, and a 20% rate of return to PHC. This could increase health system resilience during public health emergencies.

Indexed as

bedbedsdeathdeathsdevelopdevelopmenthealth systemhealth systemshospitalhospital overwhelmhospitalsintegratedmanagementmodelmodeling studymortalityoverwhelmpandemicpolicy mixprimary careprimary health careserviceservicessimulationsimulations

Identifiers

PMID38832581
PMCPMC11185287

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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.