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Feasibility Study on an Evidence-Based Decision-Support System for Hospital Site Selection for an Aging Population

Author

Listed:
  • Jung In Kim

    (Center for Integrated Facility Engineering, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA)

  • Devini Manouri Senaratna

    (Center for Integrated Facility Engineering, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA)

  • Jacobo Ruza

    (Sustainable Design and Project Management Programs, University of California, Berkeley, CA 94305, USA)

  • Calvin Kam

    (Center for Integrated Facility Engineering, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA)

  • Sandy Ng

    (Department of Public Health Sciences, Queen's University, Kingston, ON K7L3N6, Canada)

Abstract

An aging population has significant, dynamic and complex healthcare needs. Meeting such needs in a sustainable manner requires the capability to prioritize and project multiple relevant criteria (e.g., dynamic population health, treatment preferences, resources, technological changes and location of facilities). Most current decision-making processes for urban hospital site selection rely on a combination of experience and statistical data, yet they lack robustness and trending capabilities. This leads to tremendous efficiency implications, as it is not uncommon for hospitals to have a lifespan of more than 100 years after they are built. Our research team has developed an evidence-based decision-support system, enhanced with a Geographic Information System (GIS), that has the potential to overcome these limitations. This paper presents a feasibility demonstration of our framework through a retrospective case study of hospital site selection in Dallas, Texas, demonstrating its positive value in providing a foundation for informed healthcare resource allocation in the context of an aging population.

Suggested Citation

  • Jung In Kim & Devini Manouri Senaratna & Jacobo Ruza & Calvin Kam & Sandy Ng, 2015. "Feasibility Study on an Evidence-Based Decision-Support System for Hospital Site Selection for an Aging Population," Sustainability, MDPI, vol. 7(3), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:3:p:2730-2744:d:46464
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    References listed on IDEAS

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    Cited by:

    1. Dell’Ovo, Marta & Capolongo, Stefano & Oppio, Alessandra, 2018. "Combining spatial analysis with MCDA for the siting of healthcare facilities," Land Use Policy, Elsevier, vol. 76(C), pages 634-644.
    2. Gang Du & Chuanwang Sun, 2015. "Location Planning Problem of Service Centers for Sustainable Home Healthcare: Evidence from the Empirical Analysis of Shanghai," Sustainability, MDPI, vol. 7(12), pages 1-21, November.
    3. Ashraf Balabel & Mamdooh Alwetaishi, 2021. "Toward Sustainable Healthcare Facilities: An Initiative for Development of “Mostadam-HCF” Rating System in Saudi Arabia," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
    4. Caprioli, Caterina & Bottero, Marta, 2021. "Addressing complex challenges in transformations and planning: A fuzzy spatial multicriteria analysis for identifying suitable locations for urban infrastructures," Land Use Policy, Elsevier, vol. 102(C).
    5. Khaled Yousef Almansi & Abdul Rashid Mohamed Shariff & Bahareh Kalantar & Ahmad Fikri Abdullah & Sharifah Norkhadijah Syed Ismail & Naonori Ueda, 2022. "Performance Evaluation of Hospital Site Suitability Using Multilayer Perceptron (MLP) and Analytical Hierarchy Process (AHP) Models in Malacca, Malaysia," Sustainability, MDPI, vol. 14(7), pages 1-36, March.
    6. Jing Luo & Guangping Chen & Chang Li & Bingyan Xia & Xuan Sun & Siyun Chen, 2018. "Use of an E2SFCA Method to Measure and Analyse Spatial Accessibility to Medical Services for Elderly People in Wuhan, China," IJERPH, MDPI, vol. 15(7), pages 1-17, July.
    7. R. Krishankumar & K. S. Ravichandran & J. Premaladha & Samarjit Kar & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2018. "A Decision Framework under a Linguistic Hesitant Fuzzy Set for Solving Multi-Criteria Group Decision Making Problems," Sustainability, MDPI, vol. 10(8), pages 1-21, July.

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