ArticleBMC health services research2025
A scenario-driven simulation approach to sustainable hospital resource management: aging society, pandemic preparedness and referral enhancement.
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. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Interpretable SHAP-based machine learning framework for patient satisfaction prediction: a case study in Thammasat University Hospital.BMC medical informatics and decision making · 2026Article
- Financing Regimes and Case-Mix Complexity in Psychiatric Hospitals Beyond the Pandemic Shock-Insights from a Regional European Healthcare System.Healthcare (Basel, Switzerland) · 2026Article
- Bridging Traditional Modeling and Artificial Intelligence in Measles Epidemiology: Methods, Applications, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Deep learning-based physiological risk stratification in night-shift hospital workers.Scientific reports · 2026Article
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Authors and funding
5 authors.
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Abstract
purposeSustainable hospital operations require efficient resource management to maintain high-quality patient care while adapting to future challenges. The proposed framework was intentionally designed with Sustainable Development Goals (SDGs) in mind, ensuring that scenario selection and evaluation directly support sustainability, equity, and resilience in healthcare planning. This study develops a scenario-driven, simulation-based optimization framework to enhance hospital resource planning, ensuring resilience and sustainability. By addressing critical healthcare scenarios-aging society, pandemic conditions, and referral acceptance enhancement-the framework aligns hospital operations with SDGs related to equitable healthcare access and sustainable communities.
methodsThe proposed framework integrates discrete event simulation (DES) and multi-objective optimization to analyze and optimize resource allocation in response to evolving healthcare demands. Real-world hospital data, scenario-specific patient flow models, and satisfaction metrics-such as length of stay (LOS) and physician assignment-were used to evaluate system performance. The framework was applied to a case study in a public hospital, generating insights into the necessary resource adjustments for each scenario.
resultsSimulation-optimization analysis revealed key resource allocation strategies tailored to different scenarios. In the aging society scenario, the model identified the optimal number of physicians and equipment required to accommodate growing elderly patient volumes while maintaining service quality. The pandemic scenario emphasized the need for adaptive resource allocation, including flexible staffing and additional triage processes to ensure patient safety and operational efficiency. The referral acceptance enhancement scenario demonstrated how strategic resource investment can increase referral case acceptance, reducing healthcare disparities and improving access to specialized care.
conclusionThis study presents a comprehensive, adaptable framework that enables hospitals to proactively prepare for future uncertainties while optimizing patient satisfaction and operational costs. The findings highlight the importance of scenario-driven resource planning in enhancing resilience, efficiency, and equity in healthcare delivery. By aligning with SDG 3 (Good Health and Well-Being), SDG 10 (Reducing Inequalities), and SDG 11 (Sustainable Cities and Communities), the framework supports sustainable hospital management and provides decision-makers with actionable strategies to improve healthcare systems.
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