Prediction of rehospitalization and mortality risks for skilled nursing facilities using a dimension reduction approach.

ABSTRACT:

Background

Hospitals are incentivized to reduce rehospitalization rates, creating an emphasis on skilled nursing facilities (SNFs) for post-hospital discharge. How rehospitalization rates vary depending on patient and SNF characteristics is not well understood, in part because these characteristics are high-dimensional. We sought to estimate rehospitalization and mortality risks by patient and skilled nursing facility (SNF) leveraging high-dimensional characteristics.

Methods

Using 1,060,337 discharges from 13,708 SNFs of Medicare patients residing or visiting a provider in Wisconsin, Iowa, and Illinois, factor analysis was performed to reduce the number of patient and SNF characteristics. K-means clustering was applied to SNF factors to categorize SNFs into groups. Rehospit

SUBMITTER: David Gomez JC 

PROVIDER: S-EPMC10304328 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature