Claims-Based Machine Learning Classifier of Modified Rankin Scale in Acute Ischemic Stroke.

ABSTRACT:

Background

We developed a classifier to infer acute ischemic stroke severity from Medicare claims using the modified Rankin Scale at discharge. The classifier can be used to improve stroke outcomes research and support the development of national surveillance tools.

Methods

This multistate study included all participating centers in the Paul Coverdell National Acute Stroke Program database from 9 US states. This database was linked to Medicare data sets for patients hospitalized with acute ischemic stroke, employing demographics, admission details, and diagnosis codes to create unique patient matches. We included Medicare beneficiaries aged 65 and older who were hospitalized for an initial acute ischemic stroke from January 2018 to December 2020. Using Lasso-penalized logist

SUBMITTER: Habib M 

PROVIDER: S-EPMC12684556 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature