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Estimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database

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  • Oleksandr Sorochynskyi

    (Laboratoire SAF EA2429, Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, University of Lyon, 69366 Lyon, France
    Prim’Act Actuarial Consulting Firm, 42 Avenue de la Grande Armée, 75017 Paris, France)

  • Quentin Guibert

    (CEREMADE, Université Paris-Dauphine, Université PSL, CNRS, 75016 Paris, France)

  • Frédéric Planchet

    (Laboratoire SAF EA2429, Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, University of Lyon, 69366 Lyon, France
    Prim’Act Actuarial Consulting Firm, 42 Avenue de la Grande Armée, 75017 Paris, France)

  • Michaël Schwarzinger

    (Department of Prevention, Bordeaux University Hospital, 33000 Bordeaux, France
    University of Bordeaux, INSERM, BPH, U1219, I-Prev/PHARES, Certified Team under Ligue Contre le Cancer, CIC 1401, 33000 Bordeaux, France)

Abstract

The development of health indicators to measure healthy life expectancy (HLE) is an active field of research aimed at summarizing the health of a population. Although many health indicators have emerged in the literature as critical metrics in public health assessments, the methods and data to conduct this evaluation vary considerably in nature and quality. Traditionally, health data collection relies on population surveys. However, these studies, typically of limited size, encompass only a small yet representative segment of the population. This limitation can necessitate the separate estimation of incidence and mortality rates, significantly restricting the available analysis methods. In this article, we leverage an extract from the French National Hospital Discharge database to define health indicators. Our analysis focuses on the resulting Disease-Free Life Expectancy (Dis-FLE) indicator, which provides insights based on the hospital trajectory of each patient admitted to hospital in France during 2008–2013. Through this research, we illustrate the advantages and disadvantages of employing large clinical datasets as the foundation for more robust health indicators. We shed light on the opportunities that such data offer for a more comprehensive understanding of the health status of a population. In particular, we estimate age-dependent hazard rates associated with sex, alcohol abuse, tobacco consumption, and obesity, as well as geographic location. Simultaneously, we delve into the challenges and limitations that arise when adopting such a data-driven approach.

Suggested Citation

  • Oleksandr Sorochynskyi & Quentin Guibert & Frédéric Planchet & Michaël Schwarzinger, 2024. "Estimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database," Risks, MDPI, vol. 12(6), pages 1-25, June.
  • Handle: RePEc:gam:jrisks:v:12:y:2024:i:6:p:92-:d:1407687
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    References listed on IDEAS

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    1. Wim Peersman & Dirk Cambier & Jan Maeseneer & Sara Willems, 2012. "Gender, educational and age differences in meanings that underlie global self-rated health," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(3), pages 513-523, June.
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