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Specialty care single and multi-period location–allocation models within the Veterans Health Administration

Listed author(s):
  • Benneyan, James C.
  • Musdal, Hande
  • Ceyhan, Mehmet Erkan
  • Shiner, Brian
  • Watts, Bradley V.
Registered author(s):

    Optimal location of specialty care services within any healthcare network is increasingly important for balancing costs, access to care, and patient-centeredness. Typical long-range planning efforts attempt to address a myriad of quantitative and qualitative issues, including within-network access within reasonable travel distances, space capacity constraints, costs, politics, and community commitments. To help inform these decisions, single and multi-period mathematical integer programs were developed that minimize total procedure, travel, non-coverage, and start-up costs to increase network capacity subject to access constraints. These models have been used to help the Veterans Health Administration (VHA) explore relationships and tradeoffs between costs, coverage, service location, and capacity and to inform larger strategic planning discussions. Results indicate significant opportunity to simultaneously reduce total cost, reduce total travel distances, and increase within-network access, the latter being linked to better care continuity and outcomes. An application to planning short and long-term sleep apnea care across the VHA New England integrated network, for example, produced 10–15% improvements in each performance measure. As an example of further insight provided by these analyses, most optimal solutions increase the amount of outside-network care, contrary to current trends and policies to reduce external referrals.

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    Article provided by Elsevier in its journal Socio-Economic Planning Sciences.

    Volume (Year): 46 (2012)
    Issue (Month): 2 ()
    Pages: 136-148

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    Handle: RePEc:eee:soceps:v:46:y:2012:i:2:p:136-148
    DOI: 10.1016/j.seps.2011.12.005
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    1. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    2. Harper, P. R. & Shahani, A. K. & Gallagher, J. E. & Bowie, C., 2005. "Planning health services with explicit geographical considerations: a stochastic location-allocation approach," Omega, Elsevier, vol. 33(2), pages 141-152, April.
    3. Murray Côté & Siddhartha Syam & W. Vogel & Diane Cowper, 2007. "A mixed integer programming model to locate traumatic brain injury treatment units in the Department of Veterans Affairs: a case study," Health Care Management Science, Springer, vol. 10(3), pages 253-267, September.
    4. Melachrinoudis, Emanuel & Min, Hokey, 2000. "The dynamic relocation and phase-out of a hybrid, two-echelon plant/warehousing facility: A multiple objective approach," European Journal of Operational Research, Elsevier, vol. 123(1), pages 1-15, May.
    5. Maria Bruni & Domenico Conforti & Nicola Sicilia & Sandro Trotta, 2006. "A new organ transplantation location–allocation policy: a case study of Italy," Health Care Management Science, Springer, vol. 9(2), pages 125-142, May.
    6. Aboolian, Robert & Sun, Yi & Koehler, Gary J., 2009. "A location-allocation problem for a web services provider in a competitive market," European Journal of Operational Research, Elsevier, vol. 194(1), pages 64-77, April.
    7. Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
    8. Syam, Siddhartha S. & Côté, Murray J., 2010. "A location-allocation model for service providers with application to not-for-profit health care organizations," Omega, Elsevier, vol. 38(3-4), pages 157-166, June.
    9. Murray, Alan T., 2001. "Strategic analysis of public transport coverage," Socio-Economic Planning Sciences, Elsevier, vol. 35(3), pages 175-188, September.
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