Methods to incorporate patient preferences into medical decision algorithms and models and their quantification, balancing and evaluation: a scoping review protocol.

Abstract

Objective: The objective of this scoping review is to identify and map methods used to incorporate patient preferences into medical algorithms and models as well report on their quantification, balancing, and evaluation in the literature. It will focus on computational methods used for incorporating patient preferences into algorithms and models at an individual level as well as the types of medical algorithms and models where these methods have been applied.

Introduction: Medical algorithms and models are increasingly being used to support clinical and shared decision-making; however, their effectiveness, accuracy, acceptance, and comprehension may be limited if patients' preferences are not considered. To address this issue, it is important to explore methods integrating patient preferences.

Inclusion criteria: This review will investigate patient preferences and their integration into medical algorithms and models for individual-level clinical decision-making. The scoping review will include diverse sources, such as peer-reviewed articles, clinical practice guidelines, gray literature, government reports, guidelines, and expert opinions for a comprehensive investigation of the subject.

Methods: This scoping review will follow JBI methodology. A comprehensive search will be conducted in PubMed, Web of Science, ACM Digital Library, IEEE Xplore, the Cochrane Library, OpenGrey, the National Technical Reports Library, and the first 20 pages of Google Scholar. The search strategy will include keywords related to patient preferences, medical algorithms and models, decision-making, and software tools and frameworks. Data extraction and analysis will be guided by the JBI framework, which includes an explorative and qualitative analysis.

Review registration: Open Science Framework https://osf.io/qg3b5.