Bayesian Modelling of Healthcare Resource Use in Multinational Randomized Clinical Trials
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ORIGINAL RESEARCH ARTICLE
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Bayesian Modelling of Healthcare Resource Use in Multinational Randomized Clinical Trials Aline Gauthier,1 Andrea Manca2 and Susan Anton 3 1 i3 Innovus, Uxbridge, UK 2 Centre for Health Economics, University of York, York, UK 3 Boehringer-Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut, USA
Abstract
Background: Most cost-effectiveness analyses conducted alongside multinational randomized clinical trials (RCT) are carried out applying the unit costs from the country of interest to trial-wide resource use items with the objective of estimating total healthcare costs by treatment group. However, this approach could confound ‘price effects’ with ‘country effects’. An alternative approach is to use multilevel modelling techniques to analyse healthcare resource use (HCRU) from the trial, and obtain country-specific total costs by applying country-specific unit costs to corresponding shrinkage estimates of differential HCRU. Methods: To illustrate the feasibility of this approach, we analysed data from twin multinational RCTs, which enrolled approximately 2000 individuals into three treatment arms for the management of patients with chronic respiratory disease. The models were implemented using Bayesian multilevel models, to reflect the hierarchical structure of the data while controlling for co-variates at the patient and country level. Results: This analysis showed that directly modelling the level of HCRU is a promising approach to facilitate cost-effectiveness analyses conducted alongside multinational RCTs, offering several advantages compared with the modelling of direct costs. Conclusions: It is argued that modelling the level of HCRU within the Bayesian framework avoids confounding the price effects with the country effects and facilitates the estimation of costs for several countries represented in the trial.
Background Multinational randomized clinical trials (RCTs) are increasingly used as a vehicle to conduct economic evaluation,[1] but these analyses
raise a number of methodological challenges, which are not always recognized. Estimation of costs for RCT-based cost-effectiveness analysis (CEA) is frequently carried out by applying the unit costs from the country of interest to each item
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of resource use in the overall trial, with the objective of estimating the total healthcare costs of each strategy being compared.[2] It has been argued that these ‘pooled’ estimates might not be applicable to the jurisdiction of interest, as between-country variation in factors such as clinical practice, availability of healthcare resource and organization of healthcare system are not taken into account, even though such factors might be expected to affect the cost effectiveness of the intervention.[3,4] To address this problem, multilevel modelling (MLM) has been proposed as a method to explicitly quantify between-country variability while adjusting for both patient- and country-specific factors, thus facili
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