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Optimal Resource Allocation in Community Hypertension Programs

Author

Listed:
  • Albert L. Nichols

    (Harvard University)

  • Milton C. Weinstein

    (Harvard University)

Abstract

This paper presents a simple model to guide the efficient allocation of resources in community programs to detect and treat hypertension. We model such programs as n-component series systems, where each stage must function in sequence in order for the system as a whole to operate. The model differs from standard series reliability models in that, if a component fails, costs at subsequent stages are not incurred. This "pay-as-you-go" aspect implies that widespread screening is inefficient, and that resources could be better spent ensuring continued treatment of identified hypertensives. Calculations based on actual programs suggest that an optimal allocation of a fixed budget could increase significantly the number of hypertensives controlled, by about 40 percent in our example. This conclusion is robust under all but the most pessimistic assumptions.

Suggested Citation

  • Albert L. Nichols & Milton C. Weinstein, 1978. "Optimal Resource Allocation in Community Hypertension Programs," Management Science, INFORMS, vol. 24(14), pages 1526-1537, October.
    • Handle: RePEc:inm:ormnsc:v:24:y:1978:i:14:p:1526-1537
    DOI: 10.1287/mnsc.24.14.1526
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    Citations

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    Cited by:

    1. Rochelle P. Walensky & Milton C. Weinstein & Heather E. Smith & Kenneth A. Freedberg & A. David Paltiel, 2005. "Optimal Allocation of Testing Dollars: The Example of HIV Counseling, Testing, and Referral," Medical Decision Making, , vol. 25(3), pages 321-329, May.
    2. Heidenberger, Kurt, 1996. "Dynamic project selection and funding under risk: A decision tree based MILP approach," European Journal of Operational Research, Elsevier, vol. 95(2), pages 284-298, December.
    3. Tinglong Dai & Kelly Gleason & Chao‐Wei Hwang & Patricia Davidson, 2021. "Heart analytics: Analytical modeling of cardiovascular care," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 30-43, February.
    4. Zanakis, Stelios H. & Mandakovic, Tomislav & Gupta, Sushil K. & Sahay, Sundeep & Hong, Sungwan, 1995. "A review of program evaluation and fund allocation methods within the service and government sectors," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 59-79, March.
    5. Marion S. Rauner & Walter J. Gutjahr & Kurt Heidenberger & Joachim Wagner & Joseph Pasia, 2010. "Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies," Operations Research, INFORMS, vol. 58(5), pages 1269-1286, October.

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