Inclusion of social determinants of health improves sepsis readmission prediction models.

ABSTRACT:

Objective

Sepsis has a high rate of 30-day unplanned readmissions. Predictive modeling has been suggested as a tool to identify high-risk patients. However, existing sepsis readmission models have low predictive value and most predictive factors in such models are not actionable.

Materials and methods

Data from patients enrolled in the AllofUs Research Program cohort from 35 hospitals were used to develop a multicenter validated sepsis-related unplanned readmission model that incorporates clinical and social determinants of health (SDH) to predict 30-day unplanned readmissions. Sepsis cases were identified using concepts represented in the Observational Medical Outcomes Partnership. The dataset included over 60 clinical/laboratory features and over 100 SDH features.

Resul

SUBMITTER: Amrollahi F 

PROVIDER: S-EPMC9196687 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature