Cost-Effectiveness Analysis Using Data from Multinational Trials: The Use of Bivariate Hierarchical Modeling

Andrea Manca, Paul C. Lambert, Mark Sculpher and Nigel Rice
Additional contact information
Andrea Manca: Centre for Health Economics, University of York, UK, am126@york.ac.uk
Paul C. Lambert: Centre for Biostatistics & Genetic Epidemiology, Department of Health Sciences, University of Leicester, UK
Mark Sculpher: Centre for Health Economics, University of York, UK

Medical Decision Making, 2007, vol. 27, issue 4, 471-490

Abstract: Health care cost-effectiveness analysis (CEA) often uses individual patient data (IPD) from multinational randomized controlled trials. Although designed to account for between-patient sampling variability in the clinical and economic data, standard analytical approaches to CEA ignore the presence of between-location variability in the study results. This is a restrictive limitation given that countries often differ in factors that could affect the results of CEAs, such as the availability of health care resources, their unit costs, clinical practice, and patient case mix. The authors advocate the use of Bayesian bivariate hierarchical modeling to analyze multinational cost-effectiveness data. This analytical framework explicitly recognizes that patient-level costs and outcomes are nested within countries. Using real-life data, the authors illustrate how the proposed methods can be applied to obtain (a) more appropriate estimates of overall cost-effectiveness and associated measure of sampling uncertainty compared to standard CEA and (b) country-specific cost-effectiveness estimates that can be used to assess the between-location variability of the study results while controlling for differences in country-specific and patientspecific characteristics. It is demonstrated that results from standard CEA using IPD from multinational trials display a large degree of variability across the 17 countries included in the analysis, producing potentially misleading results. In contrast, ``shrinkage estimates'' obtained from the modeling approach proposed here facilitate the appropriate quantification of country-specific cost-effectiveness estimates while weighting the results based on the level of information available within each country. The authors suggest that the methods presented here represent a general framework for the analysis of economic data collected from different locations.

Keywords: Key words: cost-effectiveness analysis; statistics; generalizability; clinical trials. (Med Decis Making 2007; 27:471—490) (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:27:y:2007:i:4:p:471-490

DOI: 10.1177/0272989X07302132

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