Incorporating patient travel times in decisions about size and location of dialysis facilities.
This report demonstrates the power and usefulness of mathematical optimization as a decision 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 discussed.
Eben-Chaime
M
M
Department of Industrial Engineering and Management, Ben-Gurion University, Negev, Beer-Sheva, Israel.
Pliskin
J S
JS
D000554:Ambulatory Care Facilities / Q000191:economics / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D005544:Forecasting; D017048:Health Care Costs; D006276:Health Facility Size / Q000592:standards*; D006301:Health Services Needs and Demand / Q000639:trends; D006801:Humans; D011365:Professional Practice Location / Q000592:standards*; D012040:Regional Health Planning / Q000592:standards*; D006435:Renal Dialysis / Q000191:economics / Q000706:statistics & numerical data*; D013997:Time Factors; D014195:Travel