Post-Acute Care Data for Predicting Readmission After Ischemic Stroke: A Nationwide Cohort Analysis Using the Minimum Data Set.

ABSTRACT:

Background

Reducing hospital readmissions is a key component of reforms for stroke care. Current readmission prediction models lack accuracy and are limited by data being from only acute hospitalizations. We hypothesized that patient-level factors from a nationwide post-acute care database would improve prediction modeling.

Methods and results

Medicare inpatient claims for the year 2008 that used International Classification of Diseases, Ninth Revision codes were used to identify ischemic stroke patients older than age 65. Unique individuals were linked to comprehensive post-acute care assessments through use of the Minimum Data Set (MDS). Logistic regression was used to construct risk-adjusted readmission models. Covariates were derived from MDS variables. Among 39 178 pati

SUBMITTER: Fehnel CR 

PROVIDER: S-EPMC4599502 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature