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Bounds on a Trauma Outcome Function via Optimization

Author

Listed:
  • James E. Falk

    (George Washington University, Washington, D.C.)

  • Susan W. Palocsay

    (James Madison University, Harrisonburg, Virginia)

  • William J. Sacco

    (Washington Hospital Center, Washington, D.C.)

  • Wayne S. Copes

    (Washington Hospital Center, Washington, D.C.)

  • Howard R. Champion

    (Washington Hospital Center, Washington, D.C.)

Abstract

One measure of the effectiveness of institutional trauma and burn management based on collected patient data involves the computation of a standard normal Z statistic. A potential weakness of the measure arises from incomplete patient data. In this paper, we apply methods of fractional programming and global optimization to efficiently calculate bounds on the computed effectiveness of an institution. The measure of effectiveness (i.e., the trauma outcome function) is briefly described, the optimization problems associated with its upper and lower bounds are defined and characterized, and appropriate solution procedures are developed. We solve an example problem to illustrate the method.

Suggested Citation

  • James E. Falk & Susan W. Palocsay & William J. Sacco & Wayne S. Copes & Howard R. Champion, 1992. "Bounds on a Trauma Outcome Function via Optimization," Operations Research, INFORMS, vol. 40(1-supplem), pages 86-95, February.
    • Handle: RePEc:inm:oropre:v:40:y:1992:i:1-supplement-1:p:s86-s95
    DOI: 10.1287/opre.40.1.S86
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    Cited by:

    1. Palocsay, Susan W. & Stevens, Scott P. & Brookshire, Robert G. & Sacco, William J. & Copes, Wayne S. & Buckman, Robert F. & Smith, J. Stanley, 1996. "Using neural networks for trauma outcome evaluation," European Journal of Operational Research, Elsevier, vol. 93(2), pages 369-386, September.

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