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Prioritizing Healthcare Interventions: A Comparison of Multicriteria Decision Analysis and Cost-Effectiveness Analysis

Published:September 23, 2021DOI:https://doi.org/10.1016/j.jval.2021.08.008

      Highlights

      • Multicriteria decision analysis (MCDA) and cost-effectiveness analysis (CEA) are commonly used methods to aggregate value preferences to inform economic evaluations in healthcare. The relative merits of these different methods are being increasingly debated, but little empirical evidence is available to provide direct evidence of their relative performance.
      • This study directly compares the application of MCDA and CEA methods to a common research question: the prioritization of nonsurgical management options for knee osteoarthritis. We identify systematic differences between the 2 approaches in the aggregation of value criteria, particularly on the criteria of cost and risks of harm, and several considerations for the design of MCDA studies: treatment of opportunity cost, framing effects, and value models used to aggregate preference criteria.
      • These findings highlight the need for careful consideration of the design and interpretation of MCDA models in healthcare decision making. We support recent recommendations that cost should not be considered as part of the value model in MCDA studies. The appropriateness of value models chosen to aggregate MCDA preference criteria should be carefully evaluated. CEA based on expected value may fail to capture the stakeholders’ preferences for risk aversion.

      Abstract

      Objectives

      To investigate the extent to which stated preferences for treatment criteria elicited using multicriteria decision analysis (MCDA) methods are consistent with the trade-offs (implicitly) applied in cost-effectiveness analysis (CEA), and the impact of any differences on the prioritization of treatments.

      Methods

      We used existing MCDA and CEA models developed to evaluate interventions for knee osteoarthritis in the New Zealand population. We established equivalent input parameters for each model, for the criteria “treatment effectiveness,” “cost,” “risk of serious harms,” and “risk of mild-to-moderate harms” across a comprehensive range of (hypothetical) interventions to produce a complete ranking of interventions from each model. We evaluated the consistency of these rankings between the 2 models and investigated any systematic differences between the (implied) weight placed on each criterion in determining rankings.

      Results

      There was an overall moderate-to-strong correlation in intervention rankings between the MCDA and CEA models (Spearman correlation coefficient = 0.51). Nevertheless, there were systematic differences in the evaluation of trade-offs between intervention attributes and the resulting weights placed on each criterion. The CEA model placed lower weights on risks of harm and much greater weight on cost (at all accepted levels of willingness-to-pay per quality-adjusted life-year than did respondents to the MCDA survey.

      Conclusions

      MCDA and CEA approaches to inform intervention prioritization may give systematically different results, even when considering the same criteria and input data. These differences should be considered when designing and interpreting such studies to inform treatment prioritization decisions.

      Keywords

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