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Design of a multi-site multi-state clinical trial of home monitoring of chronic disease in the community in Australia

机译:澳大利亚社区慢性病家庭监测的多站点多州临床试验设计

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Background Telehealth services based on at-home monitoring of vital signs and the administration of clinical questionnaires are being increasingly used to manage chronic disease in the community, but few statistically robust studies are available in Australia to evaluate a wide range of health and socio-economic outcomes. The objectives of this study are to use robust statistical methods to research the impact of at home telemonitoring on health care outcomes, acceptability of telemonitoring to patients, carers and clinicians and to identify workplace cultural factors and capacity for organisational change management that will impact on large scale national deployment of telehealth services. Additionally, to develop advanced modelling and data analytics tools to risk stratify patients on a daily basis to automatically identify exacerbations of their chronic conditions. Methods/Design A clinical trial is proposed at five locations in five states and territories along the Eastern Seaboard of Australia. Each site will have 25 Test patients and 50 case matched control patients. All participants will be selected based on clinical criteria of at least two hospitalisations in the previous year or four or more admissions over the last five years for a range of one or more chronic conditions. Control patients are matched according to age, sex, major diagnosis and their Socio-Economic Indexes for Areas (SEIFA). The Trial Design is an Intervention control study based on the Before-After-Control-Impact (BACI) design. Discussion Our preliminary data indicates that most outcome variables before and after the intervention are not stationary, and accordingly we model this behaviour using linear mixed-effects (lme) models which can flexibly model within-group correlation often present in longitudinal data with repeated measures. We expect reduced incidence of unscheduled hospitalisation as well as improvement in the management of chronically ill patients, leading to better and more cost effective care. Advanced data analytics together with clinical decision support will allow telehealth to be deployed in very large numbers nationally without placing an excessive workload on the monitoring facility or the patient's own clinicians. Trial registration Registered with Australian New Zealand Clinical Trial Registry on 1st April 2013. Trial ID: ACTRN12613000635?763
机译:背景技术基于生命特征的在家监测和临床问卷管理的远程医疗服务正越来越多地用于社区中的慢性病管理,但是澳大利亚很少有统计上可靠的研究来评估广泛的健康和社会经济状况。结果。这项研究的目的是使用强大的统计方法来研究家庭远程监护对医疗保健结果的影响,远程监护对患者,护理人员和临床医生的可接受性,并确定会影响大型企业的工作场所文化因素和组织变革管理能力扩大全国范围内的远程医疗服务部署。此外,开发先进的建模和数据分析工具以对患者进行每日风险分层,以自动识别其慢性病的恶化情况。方法/设计拟在澳大利亚东部沿海的五个州和地区的五个位置进行一项临床试验。每个站点将有25位测试患者和50位匹配的对照患者。将根据前一年至少两次住院的临床标准,或过去五年中针对一处或多处慢性病范围的四次或以上入院的临床标准选择所有参与者。对照患者根据年龄,性别,主要诊断及其所在地区的社会经济指标(SEIFA)进行匹配。试验设计是一项基于干预后控制影响(BACI)设计的干预控制研究。讨论我们的初步数据表明,干预前后大多数结果变量都不稳定,因此我们使用线性混合效应(lme)模型对该行为进行建模,该模型可以灵活地模拟纵向数据中经常重复进行的组内相关性。我们希望减少计划外住院的发生率,并改善慢性病患者的管理,从而带来更好,更具成本效益的护理。先进的数据分析和临床决策支持将使远程医疗在全国范围内大量部署,而不会给监视设施或患者自己的临床医生带来过多的工作量。试验注册于2013年4月1日在澳大利亚新西兰临床试验注册中心注册。试验编号:ACTRN12613000635?763

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