Related Experiment Video
Updated: Aug 6, 2026

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Development of a population-level frfailty index using Quebec administrative data: a Canadian retrospective study
Hadjer Dahel1,2, David Williamson3,2, Qi Li4
1Université de Montréal Faculté de Pharmacie, Montreal, Canada hadjer.dahel@umontreal.ca.
Objectives:
The objectives of this study were to develop and validate a frailty index in the Quebec health administrative dataset designed to identify frail ICU patients and investigate the effects of frailty on ICU patients' outcomes.DesignWe conducted a retrospective observational study.
Settings:
We used the administrative data of the Centre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-Montréal (CIUSSS-EMTL), which regroups a supra-regional academic hospital and a community centre in Montreal, Quebec. We created a cohort through data linkage of hospital admission summary database, homecare database and in-hospital medication database. We included patients 18 years and older with an index ICU admission between 2016 and 2023 in one of the healthcare centres of CIUSSS-EMTL. The index entry date was defined as the date of the first ICU admission within the study period. We excluded patients under 18 years of age, patients who did not live in the CIUSSS-EMTL territory and patients with invalid public insurance number. The frailty index was created following Rockwood guidelines. Our primary outcome was in-hospital mortality. We performed a multivariable regression to determine the relationship between in-hospital mortality and frailty.
Results:
We created a 30-item frailty index. We included 10 849 patients with a mean age of 67.7 (15.4) years. 20% of patients were frail. Frail patients were older, more likely to have dialysis on admission and to be mechanically ventilated. Frailty was associated with an increased risk of in-hospital mortality (aOR: 1.464 (1.293; 1.659)).
Conclusion:
We created a multidimensional 30-item frailty index. We showed a strong correlation between frailty and mortality. Implementation of this index may help with identifying at-risk populations or evaluating processes of care.

