Capacity Constraints and Cost-Effectiveness: A Discrete Event Simulation for Drug-Eluting Stents

Beate Jahn, Karl Peter Pfeiffer, Engelbert Theurl, Jean-Eric Tarride and Ron Goeree
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Beate Jahn: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Information Systems and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria and the Department of Medical Statistics Informatics and Health Economics, Innsbruck Medical University, Innsbruck, Austria, beate.jahn@umit.at
Karl Peter Pfeiffer: Department of Medical Statistics Informatics and Health Economics, Medical University of Innsbruck, Innsbruck, Austria
Engelbert Theurl: Department of Public Finance, Leopold-Franzens-University of Innsbruck, Innsbruck, Austria
Jean-Eric Tarride: Programs for Assessment of Technology in Health (PATH) Research Institute, the Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
Ron Goeree: Programs for Assessment of Technology in Health (PATH) Research Institute, the Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada

Medical Decision Making, 2010, vol. 30, issue 1, 16-28

Abstract: Background. Waiting times for access to care, for example, for diagnostic imaging or surgery, are a highly relevant issue in health care. Waiting or deferred treatment caused by limited resource capacities can affect treatment success, quality of life, and costs. However, when treatment alternatives are compared in economic models, often unrestricted availability of resources is assumed, and dynamic changes in waiting lines remain unconsidered. The objective of this study was to evaluate the impact of potential real-world capacity restrictions and implied waiting lines on cost-effectiveness results and additional model outcomes. Methods. A case study of drug-eluting and bare-metal stent treatment illustrates the effect of hypothetical capacity limitations of daily stenting procedures. Therefore, a decision-analytic model which allows for explicitly defined resource capacities and dynamic waiting lines was built using discrete event simulation. Cost-effectiveness, utilization, waiting time, and budgetary impact of alternative treatment scenarios are analyzed under the assumption of limited and unlimited resource capacities. Results. The compared treatment allocation scenarios in the case study demonstrate that the additional cost for waiting increases the average treatment cost per patient. The different scenarios have different impacts on waiting lines because of the number of repeated interventions. Additionally, this effect leads to changes in cost-effectiveness results for the hypothetical capacity limit. Explicitly modeled capacities allow for further analysis of capacity utilization, waiting lines, and budgetary impact. Conclusion. Our model shows that neglected limited capacities can cause wrong cost-effectiveness results. Therefore, capacities should be explicitly included in decision-analytic models if there is evidence of scarcity.

Keywords: health economic evaluation; cost-effectiveness analysis; modeling technology; discrete event simulation; capacities; limited resources. (Med Decis Making 2010; 30:16—28) (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:30:y:2010:i:1:p:16-28

DOI: 10.1177/0272989X09336075

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