Profiling Frailty in Older Adults: A Parsimonious Frailty Index from Health Administrative Data

Margherita Silan , University of Padua
Maurizio Nicolaio, , Department of Statistical Sciences, University of Padua
Giovanna Boccuzzo, , Department of Statistical Sciences, University of Padua

Frailty assessment is crucial for stratifying populations and addressing healthcare challenges associated with aging. This study proposes a Frailty Index based on administrative health data that 1) accurately predicts multiple adverse health outcomes, 2) comprises a parsimonious set of variables, 3) aggregates variables without predefined weights, 4) regenerates when applied to different populations, and 5) relies solely on routinely collected administrative data. Using administrative data from a local health authority in Italy, we identified two cohorts of individuals aged 65 years (2016-2018 and 2017-2019). A set of six adverse outcomes (death, emergency room access with highest priority, hospitalization, disability onset, dementia onset, and femur fracture) was selected to define frailty. Variable selection was performed using logistic regression modelling and a forward approach based on partially ordered set (POSET) theory. The final Frailty Index comprised eight variables: age, disability, total number of hospitalizations, mental disorders, neurological diseases, heart failure, kidney failure, and cancer. The Frailty Index performs well or very well for the adverse outcomes (AUC range: 0.749-0.854) except hospitalization (AUC: 0.664). The index captured associations between frailty and chronic diseases, comorbidities, and socioeconomic deprivation. Compared to existing frailty indicators based on administrative data, our proposed Frailty Index stands out for its parsimony, superior predictive performance across multiple outcomes simultaneously, and its ability to regenerate across diverse populations without assuming predefined coefficient values or weights, making it a robust and versatile tool for population health management.

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 Presented in Session P6. Health, Mortality, and Ageing 2