Characteristics of smart health ecosystems that support self-care among people with heart failure: A scoping review (Preprint)

Q2 Medicine
R. Nourse, Elton H Lobo, Jenna McVicar, F. Kensing, S. Islam, L. Kayser, R. Maddison
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引用次数: 0

Abstract

BACKGROUND People with heart failure are supported by healthcare providers who follow clinical guidelines, and they are also encouraged to participate in self-care behaviors. However, the management of heart failure is complex. Innovative solutions are required to support healthcare providers with decision-making and to support people with heart failure to sustain appropriate self-care behaviors. In recent years, more sophisticated technologies have emerged within healthcare practice. These technologies use data collection, intelligent data processing, and communication to enable new models of healthcare, such as smart health ecosystems, to assist diagnosis and treatment of conditions, support patients in managing a condition, and monitor patients to support disease prevention. Currently, there is little information about the behavioral and technical characteristics of smart health ecosystems for people with heart failure. OBJECTIVE We aimed to identify and describe the characteristics of smart health ecosystems that support self-care for people with heart failure. METHODS We conducted a scoping review using the Joanna Briggs Institute (JBI) methodology. Searches of MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, and ACM Digital Library databases were searched from January 2008 to September 2021. The search strategy focused on studies that described smart health ecosystems to support self-care among people with heart failure. Two reviewers screened studies at the title and abstract level, and full text then extracted relevant data from the included full texts. RESULTS After removing duplicates, 1543 articles were screened, and 34 articles were identified, representing 13 interventions. Articles represented study designs from different stages of the e-health development cycle; conceptual and planning (n=6), development and usability (n=14), pilot/feasibility (n=2), effectiveness testing (n=9), implementation (n=1), all phases (n=2). They collected data from the end user with sensors and questionnaires and used tailoring to provide personalized support. Interventions supported heart failure self-care behaviors using 34 different behavior change techniques (BCTs), which were facilitated by a combination of 8 intervention features; automated feedback, monitoring (integrated and manual input), presentation of data, education, reminders, communication with a healthcare provider and psychological support. Furthermore, features to support healthcare providers included the presentation of data, alarms, and alerts, communication with the end user, remote care plan modification, health record integration, and communication with other members of the care team. CONCLUSIONS This scoping review identified that there are few reports of smart health ecosystems to support self-care among people with heart failure, and those that have been reported do not provide comprehensive support across all domains of self-care. Further research on implementation and effectiveness is required. This review outlines the behavioral and technical components of the identified interventions; this information can be used as a starting point for designing and testing future smart health ecosystem interventions.
支持心力衰竭患者自我保健的智能健康生态系统的特征:范围审查(预印本)
背景:心力衰竭患者得到遵循临床指南的医疗保健提供者的支持,并鼓励他们参与自我保健行为。然而,心力衰竭的治疗是复杂的。需要创新的解决方案来支持医疗保健提供者做出决策,并支持心力衰竭患者维持适当的自我护理行为。近年来,在医疗保健实践中出现了更复杂的技术。这些技术利用数据收集、智能数据处理和通信来实现智能健康生态系统等新的医疗模式,以协助疾病的诊断和治疗,支持患者管理疾病,并监测患者以支持疾病预防。目前,关于心力衰竭患者智能健康生态系统的行为和技术特征的信息很少。我们旨在识别和描述支持心力衰竭患者自我护理的智能健康生态系统的特征。方法我们使用乔安娜布里格斯研究所(JBI)的方法进行了范围审查。检索自2008年1月至2021年9月的MEDLINE、Embase、CINAHL、PsycINFO、IEEE explore和ACM数字图书馆数据库。搜索策略侧重于描述智能健康生态系统的研究,以支持心力衰竭患者的自我保健。两位审稿人在标题和摘要层面筛选研究,然后从纳入的全文中提取相关数据。结果:剔除重复后,共筛选1543篇文章,鉴定出34篇,代表13项干预措施。文章代表了电子卫生发展周期不同阶段的研究设计;概念和计划(n=6),开发和可用性(n=14),试点/可行性(n=2),有效性测试(n=9),实施(n=1),所有阶段(n=2)。他们通过传感器和问卷从最终用户那里收集数据,并使用定制方法提供个性化支持。使用34种不同的行为改变技术(bct)支持心力衰竭自我护理行为的干预,这些干预由8种干预特征的组合促进;自动反馈、监控(集成和手动输入)、数据表示、教育、提醒、与医疗保健提供者的通信以及心理支持。此外,支持医疗保健提供者的功能还包括数据的表示、警报和警报、与最终用户的通信、远程护理计划修改、健康记录集成以及与护理团队的其他成员的通信。结论:本综述发现,很少有关于智能健康生态系统支持心力衰竭患者自我护理的报道,而那些已经报道的智能健康生态系统并没有为所有领域的自我护理提供全面的支持。需要进一步研究执行情况和有效性。本综述概述了已确定干预措施的行为和技术组成部分;这些信息可作为设计和测试未来智能卫生生态系统干预措施的起点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR Cardio
JMIR Cardio Computer Science-Computer Science Applications
CiteScore
3.50
自引率
0.00%
发文量
25
审稿时长
12 weeks
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