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Mapping the Landscape of Open Source Health Economic Models: A Systematic Database Review and Analysis: An ISPOR
Raymond H Henderson1, Chris Sampson2, Xavier G L V Pouwels3
1Salutem Insights Ltd, Garryduff, Clough, Portlaoise, Ireland.
Summary
This study mapped 182 unique open-source models (OSMs) in health economics, predominantly hosted on GitHub and built with R. Improving licensing and reporting standards is key to maximizing the impact of these valuable health economic models.
Area of Science:
- Health Economics
- Health Technology Assessment
- Open Science
Background:
- Health economic models are vital for evaluating medical interventions.
- Open-source models (OSMs) improve transparency, efficiency, credibility, and reproducibility in health economics.
Purpose of the Study:
- To systematically review and map the landscape of available open-source models in health economics.
- To identify the platforms, software, application domains, and types of OSMs currently available.
Main Methods:
- A systematic database review was performed, searching eleven databases and OSM repositories.
- Predefined search terms and screening processes were used to identify relevant models.
- Duplicate models were removed to ensure unique identification.
Main Results:
- The review identified 182 unique open-source models (OSMs) from 8664 initial hits.
- GitHub was the primary hosting platform (74%), with R as the predominant software (64%).
- Infectious diseases (29%) and Markov models (49%) were the most common application domains and model types, respectively.
Conclusions:
- A diverse range of OSMs is available in health economics, with a strong presence on GitHub and developed using R.
- Clear licensing and standardized reporting are essential for maximizing the utility of OSMs.
- Future work should refine search strategies and reporting standards to better leverage OSMs for health policy.
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