Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies

Marion S. Rauner (), Walter J. Gutjahr (), Kurt Heidenberger (), Joachim Wagner () and Joseph Pasia ()
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Marion S. Rauner: Department of Innovation and Technology Management, School of Business and Economics, University of Vienna, Vienna, Austria
Walter J. Gutjahr: Department of Statistics and Decision Support Systems, School of Business and Economics, University of Vienna, Vienna, Austria
Kurt Heidenberger: Department of Innovation and Technology Management, School of Business and Economics, University of Vienna, Vienna, Austria
Joachim Wagner: Department of Accounting, School of Business and Economics, University of Vienna, Vienna, Austria
Joseph Pasia: Department of Production and Operations Management, School of Business and Economics, University of Vienna, Vienna, Austria

Operations Research, 2010, vol. 58, issue 5, 1269-1286

Abstract: We present a risk-group oriented chronic disease progression model embedded within a metaheuristic-based optimization of the policy variables. Policy-makers are provided with Pareto-optimal screening schedules for risk groups by considering cost and effectiveness outcomes as well as budget constraints. The quality of the screening technology depends on risk group, disease stage, and time. As the metaheuristic solution technique, we use the Pareto ant colony optimization (P-ACO) algorithm for multiobjective combinatorial optimization problems, which is based on the ant colony optimization paradigm. Our approach is illustrated by a numerical example for breast cancer. For a 10-year time horizon, we provide cost-effective screening schedules for selected annual and total budgets. We then discuss policy implications of 16 mammography screening scenarios varying the screening schedule (annual, biennial, triennial, quadrennial) and the rate of women tested (25%, 50%, 75%, 100%). Due to the model's flexible structure, interventions for multiple chronic diseases can be considered simultaneously.

Keywords: decision analysis; dynamic resource allocation; multicriteria optimization; metaheuristics; health care; chronic disease policy analysis; prevention (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (8)

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