Conducting Trial-Based Economic Evaluations Using R: A Tutorial

Trial-based economic evaluations are increasingly being conducted to support healthcare decision-making. When analysing trial-based economic evaluation data, different methodological challenges may be encountered, including (i) missing data, (ii) correlated costs and effects, (iii) baseline imbalanc...

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Bibliographic Details
Published in:PharmacoEconomics 2023-11, Vol.41 (11), p.1403-1413
Main Authors: Ben, Ângela Jornada, van Dongen, Johanna M., El Alili, Mohamed, Esser, Jonas L., Broulíková, Hana Marie, Bosmans, Judith E.
Format: Article
Language:English
Subjects:
Clinical outcomes
Clinical trials
Cost analysis
Decision making
Health Administration
Health Economics
Intervention
Medical research
Medicine
Medicine & Public Health
Missing data
Pharmacoeconomics and Health Outcomes
Practical Application
Public Health
Quality of Life Research
Skewness
Statistical methods
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Summary:Trial-based economic evaluations are increasingly being conducted to support healthcare decision-making. When analysing trial-based economic evaluation data, different methodological challenges may be encountered, including (i) missing data, (ii) correlated costs and effects, (iii) baseline imbalances and (iv) skewness of costs and/or effects. Despite the broad range of methods available to account for these methodological challenges in effectiveness studies, they may not always be directly applicable in trial-based economic evaluations where costs and effects are analysed jointly, and more than one methodological challenge typically needs to be addressed simultaneously. The use of inappropriate methods can bias results and conclusions regarding the cost-effectiveness of healthcare interventions. Eventually, such low-quality evidence can hamper healthcare decision-making, which may in turn result in a waste of already scarce healthcare resources. Therefore, this tutorial aims to provide step-by-step guidance on how to combine appropriate statistical methods for handling the abovementioned methodological challenges using a ready-to-use R script. The theoretical background of the described methods is provided, and their application is illustrated using a simulated trial-based economic evaluation.
ISSN:1170-7690
1179-2027
DOI:10.1007/s40273-023-01301-7