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Sustainability 2015, 7(3), 2730-2744; doi:10.3390/su7032730

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

1
Center for Integrated Facility Engineering, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA
2
Sustainable Design and Project Management Programs, University of California, Berkeley, CA 94305, USA
3
Department of Public Health Sciences, Queen's University, Kingston, ON K7L3N6, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 7 January 2015 / Revised: 24 February 2015 / Accepted: 28 February 2015 / Published: 6 March 2015
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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. View Full-Text
Keywords: aging population; senior health; healthcare sustainability; Geographic Information System (GIS); hospital site selection; decision framework aging population; senior health; healthcare sustainability; Geographic Information System (GIS); hospital site selection; decision framework
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kim, J.I.; Senaratna, D.M.; Ruza, J.; Kam, C.; Ng, S. Feasibility Study on an Evidence-Based Decision-Support System for Hospital Site Selection for an Aging Population. Sustainability 2015, 7, 2730-2744.

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