ArticleFrontiers in public health2024
Confirmation of a measurement model for hospital supply chain resilience.
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. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Rethinking supply chain disruption: a practical resilience framework for IVF laboratory quality management.Journal of assisted reproduction and genetics · 2026Article
- Optimising ICU supply chains: Evidence-based strategies for efficiency, resilience and patient safety-a structured narrative review.BMJ open quality · 2026Review
- Analysis of hospital resilience in public health emergencies using structural equation modeling: based on risk perception, resource preparedness, and team collaboration.Frontiers in public health · 2026Observational
- Stakeholder Perspectives on the Adaptability of Hospital Drug Formularies to Disease Patterns: A Modified Q-Methodology Study in Vietnam.Risk management and healthcare policy · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The hospital supply chain has revealed increasing vulnerabilities and disruptions in the wake of the COVID-19 pandemic, threatening the healthcare services and patient safety. The resilience of hospital supply chains has emerged as a paramount concern within the healthcare system. However, there is a lack of systematic research to develop an instrument tailored to the healthcare industry that is both valid and reliable for measuring hospital supply chain resilience. Therefore, this study aims to construct and validate a comprehensive scale for assessing hospital supply chain resilience, based on dynamic capability theory. Methods: This study followed rigorous scale development steps, starting with a literature review and 15 semi-structured interviews to generate initial items. These items were then refined through expert panel feedback and three rounds of Delphi studies. Using data from 387 hospitals in Province S, mainland China, the scale underwent rigorous testing and validation using structural equation modeling. To ensure the most effective model, five alternative models were examined to determine the most suitable parsimonious model. Results: The study produced a 26-item scale that captures five dimensions of resilience in line with dynamic capability theory: anticipation, adaptation, response, recovery, and learning, all showing satisfactory consistency, reliability and validity. Conclusion: The multi-dimensional scale offers hospital managers a valuable tool to identify areas needing attention and improvement, benchmark resilience against their counterparts, and ultimately strengthen their supply chains against unexpected risks.
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Registered trials
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