老年人体弱对医疗需求的影响:模拟人口动态模型,为服务规划提供信息。

Bronagh Walsh, Carole Fogg, Tracey England, Sally Brailsford, Paul Roderick, Scott Harris, Simon Fraser, Andrew Clegg, Simon de Lusignan, Shihua Zhu, Francesca Lambert, Abigail Barkham, Harnish Patel, Vivienne Windle
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引用次数: 0

摘要

背景:随着人口老龄化,体弱和相关的医疗保健需求也在增加。为体弱老年人规划和委托提供服务所需的证据很少。我们需要准确了解不同程度体弱的发生率和流行率,以及对健康结果、服务使用和人口成本的影响:研究设计与方法:研究设计:一项回顾性观察研究,利用英格兰和威尔士初级和二级医疗保健的常规数据建立统计模型,为模拟(系统动力学)建模提供信息。在英格兰汉普郡开展的利益相关者参与活动为建模提供了信息。数据来源包括皇家全科医师学院研究和监控中心数据库以及安全匿名信息链接数据库。我们使用电子虚弱指数工具估算了老龄化队列中人群的虚弱患病率、发病率和进展情况,并计算了相关的服务使用情况和成本。通过多态模型和广义线性模型探讨了虚弱与结果、服务使用和成本之间的关系。研究结果为系统动力学仿真模型原型的开发提供了依据,该模型用于探索虚弱对人口的影响以及未来 10 年内的各种情况。模拟模型的人口预测与安全匿名信息链接的回顾性数据进行了外部验证:皇家全科医师学院研究和监测中心的样本包括 2006 年至 2017 年间年龄在 50 岁以上的初级保健人群的开放队列(约 210 万人)。数据与医院病例统计数据和国家统计局死亡数据相关联。从安全匿名信息链接中生成了一个可比的验证数据集:电子虚弱指数得分每年计算一次,并分为适合、轻度、中度和严重虚弱类别。其他变量包括年龄、性别、多重贫困指数得分、种族和城市/农村:结果:虚弱转变、死亡率、住院率、急诊就诊率、全科医生就诊率和费用:研究结果:50-64 岁的人群中已经存在体弱现象。虚弱发生率为每 1000 人年 47 例。体弱患病率从 26.5%(2006 年)增至 38.9%(2017 年)。年龄较大、贫困程度较高、女性、亚裔和城市地区可独立预测虚弱的发生和发展;在 50-64 岁的 "健康 "人群中,4.8% 的人在一年内经历了向较高虚弱状态的转变,而在 75-84 岁的人群中,这一比例为 21.4%。个人医疗费用会随着虚弱程度的增加而增加,但轻度和中度虚弱人群由于人数较多,总体费用较高。模拟预测显示,2017 年至 2027 年期间,虚弱程度将增加 7.1%,从 41.5%增至 48.7%,相关费用将在 11 年内增加 58 亿英镑(英格兰):模拟建模表明,体弱患病率以及相关的服务使用和成本在未来将继续上升。情景分析表明,降低发病率和减缓病情发展,尤其是在 65 岁之前,有可能大幅减少未来的服务使用量和成本,但减少体弱老年人的意外入院次数影响不大。研究成果将整理成一个调试工具包,其中包括与虚弱相关的需求驱动因素指南和模拟模型输出结果:本研究已注册为 NCT04139278 www.clinicaltrials.gov.Funding:该奖项由国家健康与护理研究所(NIHR)的健康与社会护理服务研究计划(NIHR award ref:16/116/43)资助,全文发表于《健康与社会护理服务研究》(Health and Social Care Delivery Research)第12卷第44期。如需了解更多奖项信息,请访问 NIHR Funding and Awards 网站。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning.

Background: As populations age, frailty and the associated demand for health care increase. Evidence needed to inform planning and commissioning of services for older people living with frailty is scarce. Accurate information on incidence and prevalence of different levels of frailty and the consequences for health outcomes, service use and costs at population level is needed.

Objectives: To explore the incidence, prevalence, progression and impact of frailty within an ageing general practice population and model the dynamics of frailty-related healthcare demand, outcomes and costs, to inform the development of guidelines and tools to facilitate commissioning and service development.

Study design and methods: A retrospective observational study with statistical modelling to inform simulation (system dynamics) modelling using routine data from primary and secondary health care in England and Wales. Modelling was informed by stakeholder engagement events conducted in Hampshire, England. Data sources included the Royal College of General Practitioners Research and Surveillance Centre databank, and the Secure Anonymised Information Linkage Databank. Population prevalence, incidence and progression of frailty within an ageing cohort were estimated using the electronic Frailty Index tool, and associated service use and costs were calculated. Association of frailty with outcomes, service use and costs was explored with multistate and generalised linear models. Results informed development of a prototype system dynamics simulation model, exploring population impact of frailty and future scenarios over a 10-year time frame. Simulation model population projections were externally validated against retrospective data from Secure Anonymised Information Linkage.

Study population: The Royal College of General Practitioners Research and Surveillance Centre sample comprised an open cohort of the primary care population aged 50 + between 2006 and 2017 (approx. 2.1 million people). Data were linked to Hospital Episode Statistics data and Office for National Statistics death data. A comparable validation data set from Secure Anonymised Information Linkage was generated.

Baseline measures: Electronic Frailty Index score calculated annually and stratified into Fit, Mild, Moderate and Severe frailty categories. Other variables included age, sex, Index of Multiple Deprivation score, ethnicity and Urban/rural.

Outcomes: Frailty transitions, mortality, hospitalisations, emergency department attendances, general practitioner visits and costs.

Findings: Frailty is already present in people aged 50-64. Frailty incidence was 47 cases per 1000 person-years. Frailty prevalence increased from 26.5% (2006) to 38.9% (2017). Older age, higher deprivation, female sex, Asian ethnicity and urban location independently predict frailty onset and progression; 4.8% of 'fit' people aged 50-64 years experienced a transition to a higher frailty state in a year, compared to 21.4% aged 75-84. Individual healthcare use rises with frailty severity, but Mild and Moderate frailty groups have higher overall costs due to larger population numbers. Simulation projections indicate frailty will increase by 7.1%, from 41.5% to 48.7% between 2017 and 2027, and associated costs will rise by £5.8 billion (in England) over an 11-year period.

Conclusions: Simulation modelling indicates that frailty prevalence and associated service use and costs will continue to rise in the future. Scenario analysis indicates reduction of incidence and slowing of progression, particularly before the age of 65, has potential to substantially reduce future service use and costs, but reducing unplanned admissions in frail older people has a more modest impact. Study outputs will be collated into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and simulation model outputs.

Study registration: This study is registered as NCT04139278 www.clinicaltrials.gov.

Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/116/43) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 44. See the NIHR Funding and Awards website for further award information.

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