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

Oleksandr Sorochynskyi (), Quentin Guibert, Frédéric Planchet and Michaël Schwarzinger
Additional contact information
Oleksandr Sorochynskyi: Laboratoire SAF EA2429, Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, University of Lyon, 69366 Lyon, 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
Michaël Schwarzinger: Department of Prevention, Bordeaux University Hospital, 33000 Bordeaux, France

Risks, 2024, vol. 12, issue 6, 1-25

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.

Keywords: health indicators; healthy life expectancy; HLE; disease-free life expectancy; survival analysis; cox model; French National Hospital Discharge database (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/12/6/92/pdf (application/pdf)
https://www.mdpi.com/2227-9091/12/6/92/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:12:y:2024:i:6:p:92-:d:1407687

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().