Rules to Identify Persons with Frailty in Administrative Health Databases

Can J Aging. 2017 Dec;36(4):514-521. doi: 10.1017/S0714980817000393. Epub 2017 Oct 4.

Abstract

This study sought to develop frailty "identification rules" using population-based health administrative data that can be readily applied across jurisdictions for living and deceased persons. Three frailty identification rules were developed based on accepted definitions of frailty, markers of service utilization, and expert consultation, and were limited to variables within two common population-based administrative health databases: hospital discharge abstracts and physician claims data. These rules were used to identify persons with frailty from both decedent and living populations across five Canadian provinces. Participants included persons who had died and were aged 66 years or older at the time of death (British Columbia, Alberta, Ontario, Quebec, and Nova Scotia) and living persons 65 years or older (British Columbia, Alberta, Ontario, and Quebec). Descriptive statistics were computed for persons identified using each rule. The proportion of persons identified as frail ranged from 58.2-78.1 per cent (decedents) and 5.1-14.7 per cent (living persons).

Keywords: administrative health data; aging; algorithm; algorithme; données administratives sur la santé; fragilité; frailty; identification; vieillissment.

MeSH terms

  • Accidental Falls / statistics & numerical data
  • Aged
  • Aged, 80 and over
  • Canada / epidemiology
  • Cognitive Dysfunction / epidemiology
  • Databases, Factual
  • Frail Elderly / statistics & numerical data*
  • Frailty / epidemiology*
  • Frailty / physiopathology*
  • Geriatric Assessment*
  • Humans
  • Long-Term Care / statistics & numerical data
  • Palliative Care / statistics & numerical data
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Population Surveillance