English, Article edition: `Lost in Translation': Accounting for Between-Country Differences in the Analysis of Multinational Cost-Effectiveness Data Andrea Manca; Andrew R. Willan

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Physical Description
  • article
Language
  • English

Edition details

Title
  • `Lost in Translation': Accounting for Between-Country Differences in the Analysis of Multinational Cost-Effectiveness Data
Author
  • Andrea Manca
  • Andrew R. Willan
Physical Description
  • article
Notes
  • Cost-effectiveness analysis has gained status over the last 15 years as an important tool for assisting resource allocation decisions in a budget-limited environment such as healthcare. Randomised (multicentre) multinational controlled trials are often the main vehicle for collecting primary patient-level information on resource use, cost and clinical effectiveness associated with alternative treatment strategies. However, trial-wide cost effectiveness results may not be directly applicable to any one of the countries that participate in a multinational trial, requiring some form of additional modelling to customise the results to the country of interest. This article proposes an algorithm to assist with the choice of the appropriate analytical strategy when facing the task of adapting the study results from one country to another. The algorithm considers different scenarios characterised by: (a) whether the country of interest participated in the trial; and (b) whether individual patient-level data (IPD) from the trial are available. The analytical options available range from the use of regression-based techniques to the application of decision-analytic models. Decision models are typically used when the evidence base is available exclusively in summary format whereas regression-based methods are used mainly when the country of interest actively recruited patients into the trial and there is access to IPD (or at least country-specific summary data). Whichever method is used to reflect between-country variability in cost-effectiveness data, it is important to be transparent regarding the assumptions made in the analysis and (where possible) assess their impact on the study results.
  • Clinical-trial-design, Geographical-locations, Pharmacoeconomics
  • RePEc:wkh:phecon:v:24:y:2006:i:11:p:1101-1119
Language
  • English
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