Social Indicators Research

, Volume 146, Issue 3, pp 757–782 | Cite as

Quantifying Frailty in Older People at an Italian Local Health Unit: A Proposal Based on Partially Ordered Sets

  • Margherita Silan
  • Giulio Caperna
  • Giovanna BoccuzzoEmail author
Original Research


Population aging, which is common in developed countries, highlights issues related to the health and social assistance of frail individuals. The Italian Chronic Disease Program launched by the Ministry of Health proposes the implementation of tools that stratify the population based on health and care needs and enhances the integration of existing administrative health data flows. This work has its roots in the need to identify frail individuals conveyed by an Italian Local Health Unit (LHU) of the Veneto region and organize an efficient service of care and prevention. We propose an indicator of frailty, computed using the poset approach, comprising only eight variables available in administrative health data at the LHU level. The proposed indicator associates a value of frailty between 0 and 1 to every individual of the population aged 65 years and older, thereby allowing stratification of the population by the risk level. By validating and analyzing the frailty indicator, we show that this approach provides an effective stratification of older people.


Frailty indicator Administrative healthcare data Poset theory Measurement Aging Chronic disease 



The Authors thank Dott. Armando Olivieri and Dott. Luca Benacchio (Local Health Unit 15 “Alta Padovana”—today Local Health Unit 6 “Euganea”—of the Veneto region) for their useful suggestions. The data used for the research are part of the administrative datasets of Local Health Unit 15. They have been managed following a formal agreement between Local Health Unit 15 and the Department of Statistical Science of the University of Padova.


This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Statistical ScienceUniversity of PaduaPaduaItaly

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