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将电子健康融入医疗保健的挑战:对 Donabedian 结构、过程和结果模型的系统文献回顾。

The Challenge of Integrating eHealth Into Health Care: Systematic Literature Review of the Donabedian Model of Structure, Process, and Outcome.

机构信息

Saltro Diagnostic Centre, Utrecht, Netherlands.

National eHealth Living Lab, Leiden University Medical Centre, Leiden, Netherlands.

出版信息

J Med Internet Res. 2021 May 10;23(5):e27180. doi: 10.2196/27180.


DOI:10.2196/27180
PMID:33970123
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8145079/
Abstract

BACKGROUND: Health care organizations are increasingly working with eHealth. However, the integration of eHealth into regular health care is challenging. It requires organizations to change the way they work and their structure and care processes to be adapted to ensure that eHealth supports the attainment of the desired outcomes. OBJECTIVE: The aims of this study are to investigate whether there are identifiable indicators in the structure, process, and outcome categories that are related to the successful integration of eHealth in regular health care, as well as to investigate which indicators of structure and process are related to outcome indicators. METHODS: A systematic literature review was conducted using the Donabedian Structure-Process-Outcome (SPO) framework to identify indicators that are related to the integration of eHealth into health care organizations. Data extraction sheets were designed to provide an overview of the study characteristics, eHealth characteristics, and indicators. The extracted indicators were organized into themes and subthemes of the structure, process, and outcome categories. RESULTS: Eleven studies were included, covering a variety of study designs, diseases, and eHealth tools. All studies identified structure, process, and outcome indicators that were potentially related to the integration of eHealth. The number of indicators found in the structure, process, and outcome categories was 175, 84, and 88, respectively. The themes with the most-noted indicators and their mutual interaction were inner setting (51 indicators, 16 interactions), care receiver (40 indicators, 11 interactions), and technology (38 indicators, 12 interactions)-all within the structure category; health care actions (38 indicators, 15 interactions) within the process category; and efficiency (30 indicators, 15 interactions) within the outcome category. In-depth examination identified four most-reported indicators, namely "deployment of human resources" (n=11), in the inner setting theme within the structure category; "ease of use" (n=16) and "technical issue" (n=10), both in the technology theme within the structure category; and "health logistics" (n=26), in the efficiency theme within the outcome category. CONCLUSIONS: Three principles are important for the successful integration of eHealth into health care. First, the role of the care receiver needs to be incorporated into the organizational structure and daily care process. Second, the technology must be well attuned to the organizational structure and daily care process. Third, the deployment of human resources to the daily care processes needs to be aligned with the desired end results. Not adhering to these points could negatively affect the organization, daily process, or the end results.

摘要

背景:医疗机构越来越多地使用电子健康技术。然而,将电子健康技术融入常规医疗服务具有一定的挑战性。这需要医疗机构改变工作方式以及组织结构和护理流程,以确保电子健康技术能够支持实现预期目标。

目的:本研究旨在探讨在结构、过程和结果类别中是否存在与电子健康技术在常规医疗服务中成功整合相关的可识别指标,以及探讨哪些结构和过程指标与结果指标相关。

方法:采用 Donabedian 结构-过程-结果(SPO)框架进行系统文献回顾,以确定与电子健康技术融入医疗保健组织相关的指标。设计数据提取表以提供研究特征、电子健康技术特征和指标的概述。提取的指标被组织到结构、过程和结果类别中的主题和子主题中。

结果:共纳入 11 项研究,涵盖了各种研究设计、疾病和电子健康技术工具。所有研究均确定了与电子健康技术整合相关的结构、过程和结果指标。在结构、过程和结果类别中发现的指标数量分别为 175、84 和 88。在结构类别中,主题和交互项最多的指标是内部环境(51 个指标,16 个交互项)、护理对象(40 个指标,11 个交互项)和技术(38 个指标,12 个交互项);过程类别中是医疗保健行为(38 个指标,15 个交互项);结果类别中是效率(30 个指标,15 个交互项)。深入研究确定了四个最常报道的指标,即结构类别中内部环境主题下的“人力资源部署”(n=11);结构类别中技术主题下的“易用性”(n=16)和“技术问题”(n=10);结果类别中效率主题下的“健康物流”(n=26)。

结论:成功将电子健康技术融入医疗保健需要遵循三个原则。首先,需要将护理对象的角色融入到组织结构和日常护理流程中。其次,技术必须与组织结构和日常护理流程相协调。第三,将人力资源部署到日常护理流程中需要与预期的最终结果保持一致。不遵守这些原则可能会对组织、日常流程或最终结果产生负面影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/f1498a5d67ef/jmir_v23i5e27180_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/3542b1e80b00/jmir_v23i5e27180_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/114fa64b5091/jmir_v23i5e27180_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/5985e4a65612/jmir_v23i5e27180_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/2a25aa675dea/jmir_v23i5e27180_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/829f34c9a3f8/jmir_v23i5e27180_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/f1498a5d67ef/jmir_v23i5e27180_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/3542b1e80b00/jmir_v23i5e27180_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/114fa64b5091/jmir_v23i5e27180_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/5985e4a65612/jmir_v23i5e27180_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/2a25aa675dea/jmir_v23i5e27180_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/829f34c9a3f8/jmir_v23i5e27180_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faad/8145079/f1498a5d67ef/jmir_v23i5e27180_fig6.jpg

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