Allocation of Scarce Healthcare Resources in a Military Treatment Facility During a Pandemic: A Comparison of Goal Programming and Portfolio Decision Analysis Methods

Abstract

In a pandemic, healthcare decisionmakers face the challenge of allocating critical, but scarce healthcare resources in a dynamic, uncertain environment. Their decisions will not only affect the patients coming to the hospital for treatment, but also the Military Treatment Facility's personnel responsible. The decisionmaker must decide how to allocate these resources to achieve multiple, conflicting objectives under multiple constraints. In response, we propose a methodology for the implementation of both Portfolio Decision Analysis and Goal Programming. The steps of this methodology provide a framework with which the decisionmaker can develop optimal allocation of resources. This framework was then applied to a notional case study using both a linear value function and a piecewise value function to show the effect of non-linear value functions on each method. Complementary analysis was conducted to illustrate insights into the model and the problem itself. This application showed the merits of both models. Both, using the framework provided, allow for as much fidelity as required by the situation. Each model can be updated to account for the dynamic environment or based on analysis performed. The flexibility and adaptability of these models is especially useful in our problem.

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Document Details

Document Type
Technical Report
Publication Date
Mar 25, 2021
Accession Number
AD1135064

Entities

People

  • Donald B. Hale

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Business Administration
  • Case Studies
  • Covid-19
  • Goal Programming
  • Governments
  • Health Care
  • Health Services
  • Hospitals
  • Linear Programming
  • Management Personnel
  • Mathematical Programming
  • Medical Personnel
  • Operations Research
  • Optimization
  • Systems Engineering

Readers

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