Development of an electronic health record-based Human Immunodeficiency Virus (HIV) risk prediction model for women, incorporating social determinants of health.

ABSTRACT:

Background

Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying women who could benefit from PrEP remains a challenge. This study developed a women-specific model to predict HIV risk within a year using electronic health record (EHR) data and social determinants of health (SDoH).

Methods

We conducted a case-control study using EHR and claims data from a centralized patient repository in the Southeastern United States (OneFlorida+). The dataset was split into 60% training, 30% testing, and 10% calibration. Five-fold cross-validation was applied for hyperparameter tuning. Contextual-level SDoH were linked to EHR/claim data. Various machine learning (ML) methods were tested, and Shapley Additive

SUBMITTER: Liu Y 

PROVIDER: S-EPMC12219962 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature