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Time-Tradeoff Utilities for Identifying and Evaluating a Minimum Data Set for Time-Critical Biosurveillance

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  • Jason N. Doctor

    (Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, jdoctor@usc.edu, Department of Clinical Pharmacy and Pharmaceutical Economics and Policy, University of Southern California, Los Angeles, Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

  • Janet G. Baseman

    (Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

  • William B. Lober

    (Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

  • Jac Davies

    (Inland Northwest Health Services, Spokane Washington, Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

  • John Kobayashi

    (Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

  • Bryant T. Karras

    (Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

  • Sherrilynne Fuller

    (Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Center for Public Health Informatics, School of Public Health & Community Medicine, Seattle, Washington)

Abstract

Background. Researchers and policy makers are interested in identifying, implementing, and evaluating a national minimum data set for biosurveillance. However, work remains to be done to establish methods for measuring the value of such data. Purpose. The purpose of this article is to establish and evaluate a method for measuring the utility of biosurveillance data. Method. The authors derive an expected utility model in which the value of data may be determined by trading data relevance for time delay in receiving data. In a sample of 23 disease surveillance practitioners, the authors test if such tradeoffs are sensitive to the types of data elements involved (chief complaint v. emergency department [ED] log of visit) and proportional changes to the time horizon needed for receiving data (24 v. 48 h). In addition, they evaluate the logical error rate: the proportion of responses that scored less relevant data as having higher utility. Results. Utilities of chief complaints were significantly higher than ED log of visit, F(1, 21)= 5.60, P

Suggested Citation

  • Jason N. Doctor & Janet G. Baseman & William B. Lober & Jac Davies & John Kobayashi & Bryant T. Karras & Sherrilynne Fuller, 2008. "Time-Tradeoff Utilities for Identifying and Evaluating a Minimum Data Set for Time-Critical Biosurveillance," Medical Decision Making, , vol. 28(3), pages 351-358, May.
    • Handle: RePEc:sae:medema:v:28:y:2008:i:3:p:351-358
    DOI: 10.1177/0272989X08317011
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    References listed on IDEAS

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    1. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834, September.
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