Plain Language Summary

This research focuses on open source health economic models (OSMs), which are crucial tools for evaluating medical treatments and informing health policies. OSMs are models where the code and calculations are openly accessible, allowing for greater transparency, efficiency, and reproducibility in health economics. The study systematically reviewed various databases to understand the availability and characteristics of these models.

The review found 182 unique OSMs, with the majority hosted on GitHub (74%) and developed using the programming language R (64%). These models are used in various medical fields, most commonly infectious diseases, making up 29% of the models. Other areas include oncology and neurology. Markov models are the most frequent type of model used, accounting for 49% of all models.

The review highlights several key challenges. Many models lack clear licensing, which limits their usability despite being publicly available. Improved documentation and metadata are needed to enhance model discoverability and standardization. Ensuring standardized reporting and licensing is vital to maximize the impact of these models on health policy decisions.

For patients, OSMs can lead to better healthcare interventions by supporting decisions based on transparent and reproducible models. For healthcare decision makers, these models offer a robust resource for making informed policy decisions. Researchers can benefit from the ability to build on existing models, promoting collaboration and reducing redundancy.

The study suggests that future efforts should focus on improving search strategies, enhancing reporting standards, implementing clear licensing, and leveraging OSMs to inform health policy decisions. By addressing these areas, the health economics community can better utilize OSMs to improve healthcare outcomes and policy decisions.

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