Using phenotypic data from the Electronic Health Record (EHR) to predict discharge.

ABSTRACT:

Background

Timely discharge to post-acute care (PAC) settings, such as skilled nursing facilities, requires early identification of eligible patients. We sought to develop and internally validate a model which predicts a patient's likelihood of requiring PAC based on information obtained in the first 24 h of hospitalization.

Methods

This was a retrospective observational cohort study. We collected clinical data and commonly used nursing assessments from the electronic health record (EHR) for all adult inpatient admissions at our academic tertiary care center from September 1, 2017 to August 1, 2018. We performed a multivariable logistic regression to develop the model from the derivation cohort of the available records. We then evaluated the capability of the model to predic

SUBMITTER: Bhatia MC 

PROVIDER: S-EPMC10334536 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature