Abstract
The ageing population imposes increasing pressure on healthcare systems, requiring more extensive care for older people and early identification of frail individuals to\r\nreduce the risk of adverse health events. The aim of this work is to develop an indicator to\r\nassess the frailty level of each individual using the administrative health database of ULSS6\r\nEuganea, an Italian healthcare local authority. Given the multidimensional nature of frailty,\r\na multi-outcome approach has been adopted, considering six outcomes: death, emergency\r\nroom visits with a red code, hip fracture, hospitalization, disability, and dementia. After\r\nselecting a subgroup of frailty determinants for each adverse event using gradient boosting\r\napproach, six classification rules were estimated through outcome-specific logistic regression\r\nmodels. The frailty indicator was created by combining these classification rules, weighted\r\naccording to their individual predictive capacity. The indicator shows good performance\r\nacross all outcomes and allows for the use of different subgroups of frailty determinants specific to each outcome, including the subject’s gender, a factor excluded in other indicators\r\nalready known in the literature.
| Lingua originale | Inglese |
|---|---|
| Titolo della pubblicazione ospite | IES 2025 - Innovation & Society: Statistics and Data Science for Evaluation and Quality. BOOK OF SHORT PAPERS |
| Editore | Coop. Libraria Editrice Università di Padova |
| Pagine | 147-154 |
| Numero di pagine | 8 |
| ISBN (stampa) | 978 88 5495 849 4 |
| Stato di pubblicazione | Pubblicato - 2025 |
Keywords
- Social frailty
- health care
- older adults
- Europe