The cost-effectiveness of algorithms and artificial intelligence applied in health care: A scoping review research protocol (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Given the rapid digitization of health care and abundance of available data, there is a great interest in how to leverage these advancements into evidence-based practice. Algorithms and artificial intelligence have the potential to improve health care, reduce costs, and contribute to evidence-based practice. An in-depth examination of the available evidence is needed to elucidate the cost-effectiveness of algorithms and AI techniques applied in health care. </sec> <sec> <title>OBJECTIVE</title> The goal of this scoping review will be to map the literature on the cost-effectiveness of algorithms and AI techniques applied in health care. The current review protocol provides an overview of the steps taken to complete the review. </sec> <sec> <title>METHODS</title> The PRISMA-Scoping Review checklist will be used to guide the reporting of the scoping review. Three main concepts include: 1) health care costs; 2) algorithms and AI techniques; and 3) cost-effectiveness analysis. The following databases will be used: PubMed, Scopus, ACM Digital Library, IEEE, Google Scholar, Econlit, OpenGrey, and ProQuest Dissertations and Theses. Two researchers (SA and RHL) will independently screen the titles, abstracts, and full texts, while a third researcher (PS) will negotiate any discrepancies, until consensus is reached. </sec> <sec> <title>RESULTS</title> Article retrieval, data extraction, and interpretation are currently underway. </sec> <sec> <title>CONCLUSIONS</title> Findings from the review may provide invaluable insights on the cost-effectiveness of algorithms and AI techniques applied in health care. Given that health care dollars are scarce, it is important to know which algorithms and AI techniques are worth the upfront investments. As a result, decision-makers will be able to identify which algorithms or AI technique would be of value for their specific context. This review will also identify key knowledge gaps in the literature and will provide next steps for future research. </sec> <sec> <title>CLINICALTRIAL</title> Not applicable - this is a scoping review. </sec>

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