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Incorporating Patient Travel Times in Decisions about Size and Location of Dialysis Facilities

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  • Moshe Eben-Chaime
  • Joseph S. Pliskin

Abstract

This report demonstrates the power and usefulness of mathematical optimization as a de cision support tool in the medical services industry by presenting an application to dialysis service planning Models to predict the number of dialysis beds in a given region are usually population-based. Dialysis planners and providers have found a need to accommodate sparsely populated regions by making some allowance for patient travel times. A formal approach to incorporating travel times into dialysis planning, based on the formulation and solution of a mixed-integer programming model, is presented The development of a method for dialysis planning serves as a platform to demonstrate the use of integer programming to support decision making Major modeling principles are presented, output interpretation and sensitivity analysis are illustrated by examples; and computational requirements are dis cussed Key words. dialysis need forecasting, population-based model, travel time; math ematical optimization, mixed-integer programming; location, allocation (Med Decis Making 1992;12:44-51)

Suggested Citation

  • Moshe Eben-Chaime & Joseph S. Pliskin, 1992. "Incorporating Patient Travel Times in Decisions about Size and Location of Dialysis Facilities," Medical Decision Making, , vol. 12(1), pages 44-51, February.
    • Handle: RePEc:sae:medema:v:12:y:1992:i:1:p:44-51
    DOI: 10.1177/0272989X9201200108
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    Cited by:

    1. 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.
    2. Klein, Michael G. & Verter, Vedat & Moses, Brian G., 2020. "Designing a rural network of dialysis facilities," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1088-1100.

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