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Mathematical programming for the efficient allocation of health care resources.

A A Stinnett1, A D Paltiel

  • 1Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA. stinnett@fas.harvard.edu

Journal of Health Economics
|September 4, 1996
PubMed
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This study presents a flexible mathematical programming framework for efficient health care resource allocation. It overcomes previous restrictive assumptions, allowing for complex factors like indivisibility and ethical considerations.

Area of Science:

  • Health economics
  • Operations research
  • Public health policy

Background:

  • Previous health care resource allocation models used restrictive assumptions.
  • Efficiently allocating limited health care resources under budget constraints is a significant challenge.

Purpose of the Study:

  • To develop a general mathematical programming framework for health care resource allocation.
  • To accommodate complex factors often ignored in prior models.
  • To integrate ethical considerations into resource allocation decisions.

Main Methods:

  • Utilized established optimization techniques.
  • Developed a general mathematical programming framework.
  • Incorporated methods for handling returns to scale, indivisibility, and program interdependence.

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  • Integrated ethical constraints, including the cost of equity.

    • Main Results:

    • Demonstrated that a general mathematical programming framework can handle complex allocation scenarios.
    • Showcased the ability to incorporate detailed information on returns to scale and indivisibility.
    • Provided methods for including ethical considerations and quantifying the cost of equity.

    Conclusions:

    • The proposed framework offers a more comprehensive and flexible approach to health care resource allocation.
    • This method allows for more realistic and ethically sound decision-making in resource allocation.
    • The framework can lead to more efficient and equitable distribution of health care resources.