Chemkomnerd Nittaya, Pannakkong Warut, Tanantong Tanatorn, Huynh Van-Nam, Karnjana Jessada
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.
BMC Health Serv Res. 2025 Jul 27;25(1):982. doi: 10.1186/s12913-025-13221-7.
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.
目的:可持续的医院运营需要高效的资源管理,以在适应未来挑战的同时维持高质量的患者护理。所提出的框架在设计时有意考虑了可持续发展目标(SDGs),确保情景选择和评估直接支持医疗保健规划中的可持续性、公平性和恢复力。本研究开发了一个情景驱动、基于模拟的优化框架,以加强医院资源规划,确保恢复力和可持续性。通过应对关键的医疗保健情景——老龄化社会、大流行状况以及提高转诊接受率——该框架使医院运营与与公平医疗保健获取和可持续社区相关的可持续发展目标保持一致。 方法:所提出的框架整合了离散事件模拟(DES)和多目标优化,以分析和优化资源分配,以应对不断变化的医疗保健需求。使用真实世界的医院数据、特定情景的患者流模型以及诸如住院时间(LOS)和医生分配等满意度指标来评估系统性能。该框架应用于一家公立医院的案例研究,得出了每种情景所需资源调整的见解。 结果:模拟优化分析揭示了针对不同情景量身定制的关键资源分配策略。在老龄化社会情景中,该模型确定了在维持服务质量的同时容纳不断增加的老年患者数量所需的最佳医生数量和设备数量。大流行情景强调了适应性资源分配的必要性,包括灵活的人员配置和额外的分诊流程,以确保患者安全和运营效率。提高转诊接受率情景展示了战略性资源投资如何能够增加转诊病例的接受率,减少医疗保健差距并改善专科护理的可及性。 结论:本研究提出了一个全面、可适应的框架,使医院能够在优化患者满意度和运营成本的同时,积极为未来的不确定性做好准备。研究结果突出了情景驱动的资源规划在增强医疗保健服务的恢复力、效率和公平性方面的重要性。通过与可持续发展目标3(良好健康与福祉)、可持续发展目标10(减少不平等)和可持续发展目标11(可持续城市和社区)保持一致,该框架支持可持续的医院管理,并为决策者提供可采取行动的策略来改善医疗保健系统。
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