Development and Internal Validation of a Risk Prediction Model for Falls Among Older People Using Primary Care Electronic Health Records.

ABSTRACT:

Background

Currently used prediction tools have limited ability to identify community-dwelling older people at high risk for falls. Prediction models utilizing electronic health records (EHRs) provide opportunities but up to now showed limited clinical value as risk stratification tool, because of among others the underestimation of falls prevalence. The aim of this study was to develop a fall prediction model for community-dwelling older people using a combination of structured data and free text of primary care EHRs and to internally validate its predictive performance.

Methods

We used EHR data of individuals aged 65 or older. Age, sex, history of falls, medications, and medical conditions were included as potential predictors. Falls were ascertained from the free text. We

SUBMITTER: Dormosh N 

PROVIDER: S-EPMC9255681 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature