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Construction of a Frailty Indicator with Partially Ordered Sets: A Multiple-Outcome Proposal Based on Administrative Healthcare Data

Author

Listed:
  • Margherita Silan

    (Department of Statistical Science)

  • Giada Signorin

    (Department of Statistical Science)

  • Elisa Ferracin

    (Regional Health Service ASL TO3)

  • Elisabetta Listorti

    (Regional Health Service ASL TO3
    Bocconi University)

  • Teresa Spadea

    (Regional Health Service ASL TO3)

  • Giuseppe Costa

    (Regional Health Service ASL TO3)

  • Giovanna Boccuzzo

    (Department of Statistical Science)

Abstract

Given the progressive aging of Italian and European populations, the number of cases with chronic diseases is steeply increasing. This calls for new strategies for health resource management and the implementation of prevention policies. Among chronic patients, frail subjects have special and wider care requirements, along with an increased risk of adverse health outcomes. Thus, their identification is an important step for the Italian National Program for Chronic Diseases. This study aims at constructing an indicator that measures the frailty level of individuals in the population aged over 65 y using administrative healthcare data-flows of the Piedmont region. Following the multidimensional nature of frailty, we adopted a multiple-outcome approach in our proposal. This was done by considering the capacity to predict six unfavorable outcomes: death, urgent unplanned hospitalization, access to the emergency room with red code, avoidable hospitalization, hip fracture, and disability. We identified a parsimonious set of seven explanatory variables that can simultaneously predict the six outcomes we considered. We then assembled them into a unique frailty indicator through the use of a partially ordered set (poset) theory. Our indicator performed well with respect to all the outcomes and was able to describe several individual characteristics that are not directly considered in the computation of the indicator. Thanks to its parsimony and to the use of administrative healthcare data, our indicator allows all the stakeholders involved in the healthcare process, such as Italian Local Health Units, general practitioners, and regional managers, to use it to target frail individuals with better comprehensive healthcare actions.

Suggested Citation

  • Margherita Silan & Giada Signorin & Elisa Ferracin & Elisabetta Listorti & Teresa Spadea & Giuseppe Costa & Giovanna Boccuzzo, 2022. "Construction of a Frailty Indicator with Partially Ordered Sets: A Multiple-Outcome Proposal Based on Administrative Healthcare Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 160(2), pages 989-1017, April.
    • Handle: RePEc:spr:soinre:v:160:y:2022:i:2:d:10.1007_s11205-020-02512-7
    DOI: 10.1007/s11205-020-02512-7
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    References listed on IDEAS

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    1. Tennstedt, Sharon L. & McKinlay, John B., 1994. "Frailty and its consequences: Introduction," Social Science & Medicine, Elsevier, vol. 38(7), pages 863-865, April.
    2. Giulio Caperna & Giovanna Boccuzzo, 2018. "Use of Poset Theory with Big Datasets: A New Proposal Applied to the Analysis of Life Satisfaction in Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 1071-1088, April.
    3. Marco Fattore, 2016. "Partially Ordered Sets and the Measurement of Multidimensional Ordinal Deprivation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(2), pages 835-858, September.
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    1. Sergi Trias-Llimos & Magali Barbieri & Viviana Egidi & Luisa Frova & Francesco Grippo & France Meslé & Marilena Pappagallo & Aline Désesquelles, 2023. "Frailty at death: An examination of multiple causes of death in four low mortality countries in 2017," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(2), pages 13-30.

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