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A Decision-Making Tool for a Regional Network of Clinical Laboratories

Author

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  • Jose L. Andrade-Pineda

    (School of Engineering, University of Seville, Seville 41092, Spain)

  • Pedro L. Gonzalez-R

    (School of Engineering, University of Seville, Seville 41092, Spain)

  • Jose M. Framinan

    (School of Engineering, University of Seville, Seville 41092, Spain)

Abstract

For healthcare systems that operate in large, geographically dispersed areas, the quality of the services provided requires the effective management of a complex transportation problem. We present a decision support system to help healthcare managers improve the delivery of biological samples collected from patients in hospitals and outpatient clinics to laboratories that perform tests on them. We develop an optimization model for supporting strategic decisions on the transport of samples and the assignment of work in a large healthcare network with geographically dispersed hospitals, clinics, and testing laboratories. We embed our model in a Web-based tool to provide planners with interactive functions, enabling them to explore solutions and interactively access data to facilitate the analysis of what-if scenarios. The tool proved invaluable in helping the Andalusian Healthcare System obtain significant improvements in efficiency, quality of service, and outsourcing costs.

Suggested Citation

  • Jose L. Andrade-Pineda & Pedro L. Gonzalez-R & Jose M. Framinan, 2013. "A Decision-Making Tool for a Regional Network of Clinical Laboratories," Interfaces, INFORMS, vol. 43(4), pages 360-372, August.
    • Handle: RePEc:inm:orinte:v:43:y:2013:i:4:p:360-372
    DOI: 10.1287/inte.2013.0688
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    References listed on IDEAS

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    1. Angel Marín & Esteve Codina, 2008. "Network design: taxi planning," Annals of Operations Research, Springer, vol. 157(1), pages 135-151, January.
    2. Cohn, Amy & Davey, Melinda & Schkade, Lisa & Siegel, Amanda & Wong, Caris, 2008. "Network design and flow problems with cross-arc costs," European Journal of Operational Research, Elsevier, vol. 189(3), pages 890-901, September.
    3. Amy Cohn & Sarah Root & Alex Wang & Douglas Mohr, 2007. "Integration of the Load-Matching and Routing Problem with Equipment Balancing for Small Package Carriers," Transportation Science, INFORMS, vol. 41(2), pages 238-252, May.
    4. Yan, Shangyao & Chen, Shin-Chin & Chen, Chia-Hung, 2006. "Air cargo fleet routing and timetable setting with multiple on-time demands," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(5), pages 409-430, September.
    5. Martin Durbin & Karla Hoffman, 2008. "OR PRACTICE---The Dance of the Thirty-Ton Trucks: Dispatching and Scheduling in a Dynamic Environment," Operations Research, INFORMS, vol. 56(1), pages 3-19, February.
    6. Andreatta, G. & Lulli, G., 2008. "A multi-period TSP with stochastic regular and urgent demands," European Journal of Operational Research, Elsevier, vol. 185(1), pages 122-132, February.
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    Cited by:

    1. Jose L. Andrade-Pineda & David Canca & Pedro L. Gonzalez-R, 2017. "On modelling non-linear quantity discounts in a supplier selection problem by mixed linear integer optimization," Annals of Operations Research, Springer, vol. 258(2), pages 301-346, November.

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