R in HEOR modelling for HTA submissions: An assessment

This paper discusses the growing importance of R programming language in Health Economics and Outcomes Research (HEOR) modelling, particularly for Health Technology Assessment (HTA) submissions. The authors highlight the advantages of using R over traditional tools like MS Excel or TreeAge. They emphasise R’s ability to enhance transparency, simplify bug tracking, and enable more complex model structures. 

The paper outlines how R can be integrated throughout the entire model development process, from initial decision-making to final reporting. It mentions various R packages specifically designed for HEOR, such as heemod and darthpack, as well as general-purpose packages that support documentation, testing, and reporting. The authors also note using version control systems and AI tools to optimise the modelling process further. 

The adoption of R by HTA agencies is discussed, focusing on NICE (UK) and ZIN (Netherlands). While these agencies are beginning to accept R-based models, the authors acknowledge that widespread adoption is still limited. They highlight NICE’s pilot program using R for a reusable reference model in advanced renal cell carcinoma, demonstrating the potential for R to improve consistency and efficiency in HTA decision-making. 

The paper concludes by emphasising R’s readiness to become the primary tool for health economics modelling. It notes that R’s versatility and large community support make it well-positioned to adapt to future changes in the HTA landscape, such as increased use of AI and potential shifts towards generalised cost-effectiveness modelling. The authors call for stakeholder collaboration to integrate R into the HEOR field fully. They also offer you Parexel’s expertise in developing R-based health economic models across various therapeutic areas.
 

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