Computer model and code sharing practices in healthcare discrete-event simulation: a systematic scoping review

Thomas Monks and Alison Harper

No c4ytf, OSF Preprints from Center for Open Science

Abstract: Objectives: Discrete-event simulation is a widely used computational method in health services and health economic studies. This systematic scoping review investigates to what extent authors share computer models, and audits if sharing adheres to best practice. Data sources: The Web of Science, Scopus, PubMed, and ACM Digital Library databases were searched between 1st January 2019 till 31st December 2022. Eligibility criteria for selecting studies: Cost-effectiveness, Health service research and methodology studies in a health context were included. Data extraction and synthesis: The data extraction and best practice audit were performed by two reviewers. We developed best practice audit criteria based on the Turing Way and other published reproducibility guides. Main outcomes and measures: We measured the proportion of literature that shared models; we report analyses by publication type, year of publication, Covid-19 application; and free and open source versus commercial software. Results: 47 (8.3\%) of the 564 studies included cited a published DES computer model; rising to 9.0\% in 2022. Studies were more likely to share models if they had been developed using free and open source tools. Studies rarely followed best practice when sharing computer models. Conclusions: Although still in the minority, there is evidence that healthcare DES authors are increasingly sharing their computer model artifacts. Although commercial software dominates the DES literature, free and open source software plays a crucial role in sharing. The DES community can adopt many simple best practices to improve the quality of sharing.

Date: 2023-06-05
New Economics Papers: this item is included in nep-hea
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DOI: 10.31219/osf.io/c4ytf

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