根据法国医院出院数据库的临床数据估算无病预期寿命

IF 2 Q2 BUSINESS, FINANCE
Risks Pub Date : 2024-06-03 DOI:10.3390/risks12060092
Oleksandr Sorochynskyi, Quentin Guibert, Frédéric Planchet, Michaël Schwarzinger
{"title":"根据法国医院出院数据库的临床数据估算无病预期寿命","authors":"Oleksandr Sorochynskyi, Quentin Guibert, Frédéric Planchet, Michaël Schwarzinger","doi":"10.3390/risks12060092","DOIUrl":null,"url":null,"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.","PeriodicalId":21282,"journal":{"name":"Risks","volume":"23 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database\",\"authors\":\"Oleksandr Sorochynskyi, Quentin Guibert, Frédéric Planchet, Michaël Schwarzinger\",\"doi\":\"10.3390/risks12060092\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":21282,\"journal\":{\"name\":\"Risks\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Risks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/risks12060092\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/risks12060092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

摘要

制定健康指标来衡量健康预期寿命(HLE)是一个活跃的研究领域,旨在总结人口的健康状况。尽管许多健康指标已作为公共卫生评估的关键指标出现在文献中,但进行评估的方法和数据在性质和质量上存在很大差异。传统上,健康数据的收集依赖于人口调查。然而,这些研究通常规模有限,只能涵盖一小部分具有代表性的人口。这种局限性使得我们必须分别估算发病率和死亡率,从而大大限制了可用的分析方法。在本文中,我们利用法国国家医院出院数据库的提取物来定义健康指标。我们的分析重点是由此产生的无病预期寿命(Dis-FLE)指标,该指标根据 2008-2013 年期间法国每位住院患者的住院轨迹提供见解。通过这项研究,我们说明了采用大型临床数据集作为更可靠的健康指标基础的优缺点。我们阐明了此类数据为更全面地了解人口健康状况所提供的机会。特别是,我们估算了与性别、酗酒、烟草消费和肥胖以及地理位置相关的年龄危险率。同时,我们还深入探讨了采用这种数据驱动方法时所面临的挑战和局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Risks
Risks Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)
CiteScore
3.80
自引率
22.70%
发文量
205
审稿时长
11 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信