Home Healthcare Clinical Notes Predict Patient Hospitalization and Emergency Department Visits.

ABSTRACT:

Background

About 30% of home healthcare patients are hospitalized or visit an emergency department (ED) during a home healthcare (HHC) episode. Novel data science methods are increasingly used to improve identification of patients at risk for negative outcomes.

Objectives

The aim of the study was to identify patients at heightened risk hospitalization or ED visits using HHC narrative data (clinical notes).

Methods

This study used a large database of HHC visit notes (n = 727,676) documented for 112,237 HHC episodes (89,459 unique patients) by clinicians of the largest nonprofit HHC agency in the United States. Text mining and machine learning algorithms (Naïve Bayes, decision tree, random forest) were implemented to predict patient hospitalization or ED visits using th

SUBMITTER: Topaz M 

PROVIDER: S-EPMC7606545 | biostudies-literature | 2020 Nov/Dec

REPOSITORIES: biostudies-literature