Evidence map›Paper›PMID 41366385›Full record

ArticleBMC health services research2025

A systematic model for health systems to prevent and respond to health emergencies in the workplace.

Ali Asghar Farshad, Soudabeh Yarmohammadi, Masoud Motalebi Gh, Narmin Hassanzadeh-Rangi, Mitra Faghihi, Elahe Ezati, Yahya Khosravi

Abstract read
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Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ali Asghar FarshadOccupational Health Research Center, Iran University of Medical Sciences, Tehran, Iran.
Soudabeh YarmohammadiTrauma Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Masoud Motalebi GhOccupational Health Research Center, Iran University of Medical Sciences, Tehran, Iran.
Narmin Hassanzadeh-RangiDepartment of Occupational Health and Safety Engineering, School of Health, Alborz University of Medical Sciences, Karaj, Iran. Narminhasanzadeh@yahoo.com.ORCID http://orcid.org/0000-0001-5829-4417
Mitra FaghihiDepartment of Health Education & Promotion, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Elahe EzatiAsadabad School of Medical Sciences, Asadabad, Iran.
Yahya KhosraviDepartment of Occupational Health and Safety Engineering, School of Health, Alborz University of Medical Sciences, Karaj, Iran. yakhosravi@yahoo.com.ORCID http://orcid.org/0000-0001-6431-308X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a research gap in explaining the health system’s role in responding to pandemics and other health emergencies within a systematic framework. This study aims to present a systematic model for health systems to respond to health emergencies in the workplace, drawing on national and international experiences of the COVID-19 pandemic, with a focus on Iran as a case study.

methodsThis study employed a qualitative, content analysis approach, utilizing a triangulation method to collect and analyze data. Data were gathered through document review and semi-structured interviews, and analyzed using inductive and deductive content analysis techniques. The trustworthiness of the findings was assessed using five criteria, including credibility, transferability, dependability, confirmability, and stability.

resultsThe resulting systematic model consists of 45 subthemes, 22 themes, seven dimensions, and four domains. At the domain and subdomain levels, the health system should, during the planning phase, develop a documented plan that understands the context of workplaces in the health emergency and includes leadership commitment and workplace participation. During the operational phase, the health system should implement measures to control the emergency while providing necessary support. During the checking phase, the health system should evaluate performance in the context of the emergency. In the acting phase, the health system should continuously improve its response based on feedback.

conclusionHealth systems, along with other workplace stakeholders, play a critical role in a systematic feedback loop during health emergencies. The proposed model, customized for specific contexts, can serve as a framework for health systems to respond effectively to workplace health emergencies. Future research should focus on testing the model in diverse settings, with an emphasis on both qualitative and quantitative assessments of its effectiveness and efficiency.

Indexed as

COVID-19EmergenciesPandemicsWorkplaceHumansIranPublic Health InfrastructureQualitative ResearchSARS-CoV-2Working ConditionsEmergency responseHealth policyHealth systemsIranPandemicsPublic healthWorkplace

Identifiers

PMID41366385
PMCPMC12690848

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LicenceCC BY-NC-ND
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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.