Extensions of Health Economic Evaluations in R for Microsoft Excel Users: A Tutorial for Incorporating Heterogeneity and Conducting Value of Information Analyses

Nichola R. Naylor (), Jack Williams, Nathan Green, Felicity Lamrock and Andrew Briggs
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Nichola R. Naylor: London School of Hygiene & Tropical Medicine
Jack Williams: London School of Hygiene & Tropical Medicine
Nathan Green: University College London
Felicity Lamrock: Queen’s University Belfast
Andrew Briggs: London School of Hygiene & Tropical Medicine

PharmacoEconomics, 2023, vol. 41, issue 1, No 3, 32 pages

Abstract: Abstract Advanced health economic analysis techniques currently performed in Microsoft Excel, such as incorporating heterogeneity, time-dependent transitions and a value of information analysis, can be easily transferred to R. Often the outputs of survival analyses (such as Weibull regression models) will estimate the impacts of correlated patient characteristics on patient outcomes, and are utilised directly as inputs for health economic decision models. This tutorial provides a step-by-step guide of how to conduct such analyses with a Markov model developed in R, and offers a comparison with established analyses performed in Microsoft Excel. This is done through the conversion of a previously published Microsoft Excel case study of a hip replacement surgery cost-effectiveness model. We hope that this paper can act as a facilitator in switching decision models from Microsoft Excel to R for complex health economic analyses, providing open-access code and data, suitable for future adaptation.

Date: 2023
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DOI: 10.1007/s40273-022-01203-0

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