A landmark study by ISPOR uncovers the prevailing use of R and GitHub in the development and distribution of open source health economic models. This research provides a comprehensive overview of the current landscape, highlighting trends and identifying areas for improvement within the field.
Published in the June 2025 issue of Value in Health, the study titled “Mapping the Landscape of Open Source Health Economic Models: A Systematic Database Review and Analysis” offers an in-depth analysis of openly accessible models used in health technology assessments. Authored by a global team of health economics experts, the report emphasizes the role of open source models in enhancing transparency and reproducibility.
Dominance of R and GitHub
The analysis reveals that R, a free software environment for statistical computing, is the preferred platform for building open source health economic models, accounting for 64% of the models reviewed. Additionally, GitHub emerges as the primary host, accommodating 74% of identified models, followed by Zenodo at 11%. This preference underscores the importance of accessible and collaborative tools in the development of health economic assessments.
Application Areas and Modeling Approaches
Infectious disease stands out as the most common application area, representing 29% of the models, with oncology and neurology following at 13% and 9% respectively. Markov models are the predominant modeling approach, utilized in nearly half of the cases (49%). However, the study also identifies that almost 25% of the models lack a clear licensing agreement, posing challenges for their broader use and dissemination.
- R’s dominance suggests a strong preference for its statistical capabilities in health economics.
- The prevalence of GitHub indicates a trend towards centralized, collaborative platforms for model sharing.
- High usage in infectious diseases may reflect ongoing global health priorities.
- Licensing ambiguities could hinder the adoption and adaptation of existing models.
The study advocates for the adoption of open licenses and comprehensive documentation to facilitate the reuse and verification of health economic models. Aligning with frameworks like Sharing Tools and Artifacts for Reusable Simulations (STARS), the authors call for standardized reporting guidelines and metadata standards to enhance model discoverability and reliability.
Enhanced transparency through standardized practices can significantly impact health policy decisions. By leveraging open source models, policymakers can make more informed choices regarding resource allocation and the cost-effectiveness of healthcare interventions. This approach not only fosters collaboration but also ensures that models remain up-to-date and relevant in a rapidly evolving healthcare landscape.
Adopting standardized guidelines will likely lead to higher quality and more functional open source models. Researchers and institutions are encouraged to contribute to repositories with clear licensing and thorough documentation, thereby advancing the field of health economics and outcomes research. This collective effort can drive innovation and improve the accuracy and applicability of health technology assessments worldwide.
The findings from this ISPOR study serve as a crucial roadmap for future developments in health economics modeling. Emphasizing the importance of open source practices, the research provides actionable insights that can enhance the efficiency and effectiveness of health policy decision-making processes.
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