Risk factors and machine learning model for predicting hospitalization outcomes in geriatric patients with dementia.

ABSTRACT:

Introduction

Geriatric patients with dementia incur higher healthcare costs and longer hospital stays than other geriatric patients. We aimed to identify risk factors for hospitalization outcomes that could be mitigated early to improve outcomes and impact overall quality of life.

Methods

We identified risk factors, that is, demographics, hospital complications, pre-admission, and post-admission risk factors including medical history and comorbidities, affecting hospitalization outcomes determined by hospital stays and discharge dispositions. Over 150 clinical and demographic factors of 15,678 encounters (8407 patients) were retrieved from our institution's data warehouse. We further narrowed them down to twenty factors through feature selection engineering by using analysis

SUBMITTER: Wang X 

PROVIDER: S-EPMC9520763 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature