Identifying Latent Subgroups of High-Risk Patients Using Risk Score Trajectories.

ABSTRACT:

Objective

Many healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and characterize latent subgroups of high-risk patients based on risk score trajectories.

Study design

Observational study of 7289 patients discharged from Veterans Health Administration (VA) hospitals during a 1-week period in November 2012 and categorized in the top 5th percentile of risk for hospitalization.

Methods

Using VA administrative data, we calculated weekly risk scores using the validated Care Assessment Needs model, reflecting the predicted probability of hospitalization. We applied the non-parametric k-means algo

SUBMITTER: Wong ES 

PROVIDER: S-EPMC6258600 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature