Reporting of Fairness Metrics in Clinical Risk Prediction Models Used for Precision Health: Scoping Review.

ABSTRACT:

Background

Clinical risk prediction models integrated into digitized health care informatics systems hold promise for personalized primary prevention and care, a core goal of precision health. Fairness metrics are important tools for evaluating potential disparities across sensitive features, such as sex and race or ethnicity, in the field of prediction modeling. However, fairness metric usage in clinical risk prediction models remains infrequent, sporadic, and rarely empirically evaluated.

Objective

We seek to assess the uptake of fairness metrics in clinical risk prediction modeling through an empirical evaluation of popular prediction models for 2 diseases, 1 chronic and 1 infectious disease.

Methods

We conducted a scoping literature review in November 2023 of rece

SUBMITTER: Rountree L 

PROVIDER: S-EPMC11966066 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature