Abstract
Most Markov models are built using basic spreadsheet software, which has drawbacks: analyses are hard to reproduce and lack of transparency, errors are difficult to spot, track and correct, and graphic capabilities are lacking. The R language can overcome these issues through script-based approaches, but programming models is not a simple matter, which has limited its use in this field. Our main objective was to develop a free and open-source R package for Markov models focused on reproducibility and ease of use. We developed an R package to compute the models described in the reference textbook “Decision Modelling for Health Economic Evaluation” by Briggs et al. We aimed to facilitate easy and transparent model writing that ensured security and reproducibility. To facilitate model building, a graphical user interface was developed, allowing output of model scripts for peer review. The finalized package, heemod, and the graphical user interface were made available for free on CRAN, the public and open-source R package repository. We reproduced in a concise and readable format all the results of the analyses described in “Decision Modelling for Health Economic Evaluation”, such as homogeneous and non-homogeneous (with time-varying properties) Markov models, as well as sensitivity and probabilistic uncertainty analysis (where it is possible to specify arbitrary distributions and correlation structures between parameters). This work shows that it is possible to develop complex Markov models easily in the R language without sacrificing transparency, reproducibility or mathematical exactitude. The free and open-source license facilitates code review and improvement of the package by third-party experts. We hope the availability of this package will facilitate the use of script-based approaches to health evaluation modelling and help improve the overall quality and reproducibility of studies in this domain.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.