Predicting Falls and When to Intervene in Older People: A Multilevel Logistical Regression Model and Cost Analysis.

ABSTRACT:

Introduction

Falls are the leading cause of injury in older people. Reducing falls could reduce financial pressures on health services. We carried out this research to develop a falls risk model, using routine primary care and hospital data to identify those at risk of falls, and apply a cost analysis to enable commissioners of health services to identify those in whom savings can be made through referral to a falls prevention service.

Methods

Multilevel logistical regression was performed on routinely collected general practice and hospital data from 74751 over 65's, to produce a risk model for falls. Validation measures were carried out. A cost-analysis was performed to identify at which level of risk it would be cost-effective to refer patients to a falls prevention servi

SUBMITTER: Smith MI 

PROVIDER: S-EPMC4957756 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature