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电子健康增强型慢性病护理模式:一种理论推导方法。

The eHealth Enhanced Chronic Care Model: a theory derivation approach.

作者信息

Gee Perry M, Greenwood Deborah A, Paterniti Debora A, Ward Deborah, Miller Lisa M Soederberg

机构信息

School of Nursing, Division of Health Sciences, Idaho State University, Pocatello, ID, United States.

出版信息

J Med Internet Res. 2015 Apr 1;17(4):e86. doi: 10.2196/jmir.4067.

DOI:10.2196/jmir.4067
PMID:25842005
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4398883/
Abstract

BACKGROUND

Chronic illnesses are significant to individuals and costly to society. When systematically implemented, the well-established and tested Chronic Care Model (CCM) is shown to improve health outcomes for people with chronic conditions. Since the development of the original CCM, tremendous information management, communication, and technology advancements have been established. An opportunity exists to improve the time-honored CCM with clinically efficacious eHealth tools.

OBJECTIVE

The first goal of this paper was to review research on eHealth tools that support self-management of chronic disease using the CCM. The second goal was to present a revised model, the eHealth Enhanced Chronic Care Model (eCCM), to show how eHealth tools can be used to increase efficiency of how patients manage their own chronic illnesses.

METHODS

Using Theory Derivation processes, we identified a "parent theory", the Chronic Care Model, and conducted a thorough review of the literature using CINAHL, Medline, OVID, EMBASE PsychINFO, Science Direct, as well as government reports, industry reports, legislation using search terms "CCM or Chronic Care Model" AND "eHealth" or the specific identified components of eHealth. Additionally, "Chronic Illness Self-management support" AND "Technology" AND several identified eHealth tools were also used as search terms. We then used a review of the literature and specific components of the CCM to create the eCCM.

RESULTS

We identified 260 papers at the intersection of technology, chronic disease self-management support, the CCM, and eHealth and organized a high-quality subset (n=95) using the components of CCM, self-management support, delivery system design, clinical decision support, and clinical information systems. In general, results showed that eHealth tools make important contributions to chronic care and the CCM but that the model requires modification in several key areas. Specifically, (1) eHealth education is critical for self-care, (2) eHealth support needs to be placed within the context of community and enhanced with the benefits of the eCommunity or virtual communities, and (3) a complete feedback loop is needed to assure productive technology-based interactions between the patient and provider.

CONCLUSIONS

The revised model, eCCM, offers insight into the role of eHealth tools in self-management support for people with chronic conditions. Additional research and testing of the eCCM are the logical next steps.

摘要

背景

慢性病对个人影响重大,对社会成本高昂。当系统实施时,成熟且经过测试的慢性病护理模式(CCM)已被证明可改善慢性病患者的健康状况。自最初的CCM发展以来,信息管理、沟通和技术取得了巨大进步。利用临床有效的电子健康工具改进历史悠久的CCM存在契机。

目的

本文的首要目标是回顾关于使用CCM支持慢性病自我管理的电子健康工具的研究。第二个目标是提出一个修订模型,即电子健康增强慢性病护理模式(eCCM),以展示电子健康工具如何用于提高患者管理自身慢性病的效率。

方法

使用理论推导过程,我们确定了一个“母理论”,即慢性病护理模式,并使用CINAHL、Medline、OVID、EMBASE、PsychINFO、Science Direct以及政府报告、行业报告、法规等,通过搜索词“CCM或慢性病护理模式”以及“电子健康”或电子健康的特定确定组成部分,对文献进行了全面回顾。此外,“慢性病自我管理支持”以及“技术”和几个确定的电子健康工具也被用作搜索词。然后,我们通过对文献的回顾和CCM的特定组成部分来创建eCCM。

结果

我们在技术、慢性病自我管理支持、CCM和电子健康的交叉点上识别出260篇论文,并使用CCM的组成部分、自我管理支持、服务提供系统设计、临床决策支持和临床信息系统组织了一个高质量子集(n = 95)。总体而言,结果表明电子健康工具对慢性病护理和CCM做出了重要贡献,但该模式在几个关键领域需要改进。具体而言,(1)电子健康教育对自我护理至关重要,(2)电子健康支持需要置于社区背景下,并通过电子社区或虚拟社区的优势加以增强,(3)需要一个完整的反馈回路,以确保患者与提供者之间基于技术的有效互动。

结论

修订后的模型eCCM深入了解了电子健康工具在慢性病患者自我管理支持中的作用。对eCCM进行进一步的研究和测试是合理的下一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09e6/4398883/f87fc58f52d8/jmir_v17i4e86_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09e6/4398883/004b2a2bff16/jmir_v17i4e86_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09e6/4398883/f87fc58f52d8/jmir_v17i4e86_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09e6/4398883/004b2a2bff16/jmir_v17i4e86_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09e6/4398883/f87fc58f52d8/jmir_v17i4e86_fig2.jpg

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