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A scenario-driven simulation approach to sustainable hospital resource management: aging society, pandemic preparedness and referral enhancement
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Metadata
Document Title
A scenario-driven simulation approach to sustainable hospital resource management: aging society, pandemic preparedness and referral enhancement
Name from Authors Collection
Affiliations
School of Manufacturing Systems and Mechanical Engineering, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12120, Thailand; School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, 923-1211, Japan; Thammasat University Research Unit in Data Innovation and Artificial Intelligence, Thammasat University, Pathum Thani, 12120, Thailand; Department of Computer Science, Faculty of Science and Technology, Thammasat University, Pathum Thani, 12120, Thailand; Intelligent System Research Group, National Electronics and Computer Technology Center (NECTEC), Pathum Thani, Thailand
Type
Article
Source Title
BMC Health Services Research
ISSN
14726963
Year
2025
Volume
25
Issue
1
Open Access
All Open Access; Gold Open Access; Green Open Access
Publisher
BioMed Central Ltd
DOI
10.1186/s12913-025-13221-7
Abstract
Purpose: Sustainable 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. Methods: The 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. Results: Simulation-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. Conclusion: This 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. © The Author(s) 2025.
Keyword
Discrete Event Simulation | Multi-Objective Optimization | Patient Satisfaction | Resource management | Sustainable Healthcare
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Knowledge Taxonomy Level 3
License
CC BY-NC-ND
Rights
Authors
Publication Source
Scopus
Publication Source
Scopus