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利用大数据估算新西兰的痴呆症患病率:一项观察性研究方案。

Using Big Data to Estimate Dementia Prevalence in New Zealand: Protocol for an Observational Study.

作者信息

Rivera-Rodriguez Claudia, Cheung Gary, Cullum Sarah

机构信息

Department of Statistics, University of Auckland, Auckland, New Zealand.

Department of Psychological Medicine, University of Auckland, Auckland, New Zealand.

出版信息

JMIR Res Protoc. 2021 Jan 6;10(1):e20225. doi: 10.2196/20225.

Abstract

BACKGROUND

Dementia describes a cluster of symptoms that includes memory loss; difficulties with thinking, problem solving, or language; and functional impairment. Dementia can be caused by a number of neurodegenerative diseases, such as Alzheimer disease and cerebrovascular disease. Currently in New Zealand, most of the systematically collected and detailed information on dementia is obtained through a suite of International Residential Assessment Instrument (interRAI) assessments, including the home care, contact assessment, and long-term care facility versions. These versions of interRAI are standardized comprehensive geriatric assessments. Patients are referred to have an interRAI assessment by the Needs Assessment and Service Coordination (NASC) services after a series of screening processes. Previous estimates of the prevalence and costs of dementia in New Zealand have been based on international studies with different populations and health and social care systems. This new local knowledge will have implications for estimating the demographic distribution and socioeconomic impact of dementia in New Zealand.

OBJECTIVE

This study investigates the prevalence of dementia, risk factors for dementia, and drivers of the informal cost of dementia among people registered in the NASC database in New Zealand.

METHODS

This study aims to analyze secondary data routinely collected by the NASC and interRAI (home care and contact assessment versions) databases between July 1, 2014, and July 1, 2019, in New Zealand. The databases will be linked to produce an integrated data set, which will be used to (1) investigate the sociodemographic and clinical risk factors associated with dementia and other neurological conditions, (2) estimate the prevalence of dementia using weighting methods for complex samples, and (3) identify the cost of informal care per client (in number of hours of care provided by unpaid carers) and the drivers of such costs. We will use design-based survey methods for the estimation of prevalence and generalized estimating equations for regression models and correlated and longitudinal data.

RESULTS

The results will provide much needed statistics regarding dementia prevalence and risk factors and the cost of informal care for people living with dementia in New Zealand. Potential health inequities for different ethnic groups will be highlighted, which can then be used by decision makers to inform the development of policy and practice.

CONCLUSIONS

As of November 2020, there were no dementia prevalence studies or studies on informal care costs of dementia using national data from New Zealand. All existing studies have used data from other populations with substantially different demographic distributions. This study will give insight into the actual prevalence, risk factors, and informal care costs of dementia for the population with support needs in New Zealand. It will provide valuable information to improve health outcomes and better inform policy and planning.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/20225.

摘要

背景

痴呆症描述了一系列症状,包括记忆力丧失;思维、解决问题或语言方面的困难;以及功能障碍。痴呆症可能由多种神经退行性疾病引起,如阿尔茨海默病和脑血管疾病。目前在新西兰,大部分系统收集的关于痴呆症的详细信息是通过一套国际居民评估工具(interRAI)评估获得的,包括家庭护理、接触评估和长期护理机构版本。这些interRAI版本是标准化的综合老年评估。患者在经过一系列筛查流程后,由需求评估与服务协调(NASC)服务机构转介进行interRAI评估。此前对新西兰痴呆症患病率和成本的估计是基于针对不同人群以及健康和社会护理系统的国际研究。这一全新的本地知识将对估计新西兰痴呆症的人口分布和社会经济影响产生影响。

目的

本研究调查新西兰NASC数据库中登记人员的痴呆症患病率、痴呆症风险因素以及痴呆症非正式护理成本的驱动因素。

方法

本研究旨在分析2014年7月1日至2019年7月1日期间新西兰NASC和interRAI(家庭护理和接触评估版本)数据库常规收集的二手数据。这些数据库将进行关联以生成一个综合数据集,该数据集将用于:(1)调查与痴呆症和其他神经系统疾病相关的社会人口统计学和临床风险因素;(2)使用复杂样本加权方法估计痴呆症患病率;(3)确定每位客户的非正式护理成本(以无薪护理人员提供的护理小时数计)以及此类成本的驱动因素。我们将使用基于设计的调查方法来估计患病率,并使用广义估计方程来构建回归模型以及处理相关和纵向数据。

结果

研究结果将提供新西兰痴呆症患病率、风险因素以及痴呆症患者非正式护理成本等急需的统计数据。不同种族群体潜在的健康不平等问题将得到凸显,决策者可据此为政策制定和实践提供参考。

结论

截至2020年11月,新西兰尚无使用本国数据进行的痴呆症患病率研究或痴呆症非正式护理成本研究。所有现有研究均使用了来自其他人口结构差异较大的群体的数据。本研究将深入了解新西兰有支持需求人群的痴呆症实际患病率、风险因素和非正式护理成本。它将提供有价值的信息,以改善健康结果,并为政策制定和规划提供更充分的依据。

国际注册报告识别码(IRRID):DERR1-10.2196/20225。

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