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护士主导的针对慢性病成年人的远程数字支持:一项无荟萃分析的系统综合研究

Nurse-led remote digital support for adults with chronic conditions: A systematic synthesis without meta-analysis.

作者信息

Kilfoy Alicia, Chu Charlene, Krisnagopal Archanaa, Mcatee Enoch, Baek Sunny, Zworth Mallory, Hwang Kyobin, Park Hyun, Jibb Lindsay

机构信息

Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada.

Division of Hematology/Oncology, Hospital for Sick Children, Toronto, Ontario, Canada.

出版信息

J Clin Nurs. 2025 Mar;34(3):715-736. doi: 10.1111/jocn.17226. Epub 2024 Jun 18.

DOI:10.1111/jocn.17226
PMID:38894583
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11808464/
Abstract

AIM

The systematic review aims to synthesize the literature examining the effectiveness of nurse-led remote digital support on health outcomes in adults with chronic conditions.

BACKGROUND

Adults with chronic diseases have increased rates of mortality and morbidity and use health care resources at a higher intensity than those without chronic conditions-placing strain on the patient, their caregivers and health systems. Nurse-led digital health disease self-management interventions have potential to improve outcomes for patients with chronic conditions by facilitating care in environments other that the hospital setting.

DESIGN AND METHODS

We searched PubMed/MEDLINE, Embase, PsycINFO and Cochrane Central databases from inception to 7 December 2022. We included randomized controlled trials assessing the impact of nurse-led remote digital support interventions compared to usual care on health-related outcomes in adults with chronic illness. The Cochrane risk-of-bias tool was used to assess bias in studies. Outcomes were organized into four categories: self-management, clinical outcomes, health care resource use and satisfaction with care. Results are presented narratively based on statistical significance.

RESULTS

Forty-four papers pertaining to 40 unique studies were included. Interventions most targeted diabetes (n = 11) and cardiovascular disease (n = 8). Websites (n = 10) and mobile applications (n = 10) were the most used digital modalities. Nurses supported patients either in response to incoming patient health data (n = 14), virtual appointment (n = 8), virtual health education (n = 5) or through a combination of these approaches (n = 13). Positive impacts of nurse-led digital chronic disease support were identified in each outcome category. Mobile applications were the most effective digital modality.

CONCLUSION AND RELEVANCE TO CLINICAL PRACTICE

Results show that nurse-led remote digital support interventions significantly improve self-management capacity, clinical health outcomes, health care resource use and satisfaction with care. Such interventions have potential to support overall health for adults with chronic conditions in their home environments.

摘要

目的

本系统评价旨在综合分析有关护士主导的远程数字支持对慢性病成年患者健康结局有效性的文献。

背景

慢性病成年患者的死亡率和发病率有所上升,与无慢性病者相比,他们使用医疗资源的强度更高,这给患者、其照护者及医疗系统带来了压力。护士主导的数字健康疾病自我管理干预措施有潜力通过在医院环境以外的其他环境中促进护理,改善慢性病患者的结局。

设计与方法

我们检索了从数据库建立至2022年12月7日的PubMed/MEDLINE、Embase、PsycINFO和Cochrane Central数据库。我们纳入了评估护士主导的远程数字支持干预措施与常规护理相比,对慢性病成年患者健康相关结局影响的随机对照试验。使用Cochrane偏倚风险工具评估研究中的偏倚。结局分为四类:自我管理、临床结局、医疗资源使用和护理满意度。基于统计学显著性以叙述方式呈现结果。

结果

纳入了与40项独特研究相关的44篇论文。干预措施最常针对糖尿病(n = 11)和心血管疾病(n = 8)。网站(n = 10)和移动应用程序(n = 10)是最常用的数字模式。护士通过响应患者传入的健康数据(n = 14)、虚拟预约(n = 8)、虚拟健康教育(n = 5)或这些方法的组合(n = 13)来支持患者。在每个结局类别中均发现了护士主导的数字慢性病支持的积极影响。移动应用程序是最有效的数字模式。

结论及与临床实践的相关性

结果表明,护士主导的远程数字支持干预措施可显著提高自我管理能力、临床健康结局、医疗资源使用和护理满意度。此类干预措施有潜力在家庭环境中支持慢性病成年患者的整体健康。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/da958ac0da44/JOCN-34-715-g125.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/071eed58699b/JOCN-34-715-g093.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/43d29d79bf5f/JOCN-34-715-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/da958ac0da44/JOCN-34-715-g125.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/071eed58699b/JOCN-34-715-g093.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/43d29d79bf5f/JOCN-34-715-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/432c/11808464/da958ac0da44/JOCN-34-715-g125.jpg

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