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dc.rights.licenseopenen_US
dc.contributor.authorSOROCHYNSKYI, Oleksandr
dc.contributor.authorGUIBERT, Quentin
dc.contributor.authorPLANCHET, Frederic
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorSCHWARZINGER, Michael
dc.date.accessioned2024-08-20T09:24:34Z
dc.date.available2024-08-20T09:24:34Z
dc.date.issued2024-06-03
dc.identifier.issn2227-9091en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/201192
dc.description.abstractEnThe 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.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subject.enHealth indicators
dc.subject.enHealthy life expectancy
dc.subject.enHLE
dc.subject.enDisease-free life expectancy
dc.subject.enSurvival analysis
dc.subject.enCox model
dc.subject.enFrench National Hospital Discharge database
dc.title.enEstimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database
dc.title.alternativeRisksen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.3390/risks12060092en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
bordeaux.journalRisksen_US
bordeaux.volume12en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issue6en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.teamPHARES_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Risks&rft.date=2024-06-03&rft.volume=12&rft.issue=6&rft.eissn=2227-9091&rft.issn=2227-9091&rft.au=SOROCHYNSKYI,%20Oleksandr&GUIBERT,%20Quentin&PLANCHET,%20Frederic&SCHWARZINGER,%20Michael&rft.genre=article


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