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可视化仪表盘对医疗质量和临床医生满意度的影响:综合文献综述

The Impact of Visualization Dashboards on Quality of Care and Clinician Satisfaction: Integrative Literature Review.

作者信息

Khairat Saif Sherif, Dukkipati Aniesha, Lauria Heather Alico, Bice Thomas, Travers Debbie, Carson Shannon S

机构信息

University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

出版信息

JMIR Hum Factors. 2018 May 31;5(2):e22. doi: 10.2196/humanfactors.9328.

DOI:10.2196/humanfactors.9328
PMID:29853440
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6002673/
Abstract

BACKGROUND

Intensive Care Units (ICUs) in the United States admit more than 5.7 million people each year. The ICU level of care helps people with life-threatening illness or injuries and involves close, constant attention by a team of specially-trained health care providers. Delay between condition onset and implementation of necessary interventions can dramatically impact the prognosis of patients with life-threatening diagnoses. Evidence supports a connection between information overload and medical errors. A tool that improves display and retrieval of key clinical information has great potential to benefit patient outcomes. The purpose of this review is to synthesize research on the use of visualization dashboards in health care.

OBJECTIVE

The purpose of conducting this literature review is to synthesize previous research on the use of dashboards visualizing electronic health record information for health care providers. A review of the existing literature on this subject can be used to identify gaps in prior research and to inform further research efforts on this topic. Ultimately, this evidence can be used to guide the development, testing, and implementation of a new solution to optimize the visualization of clinical information, reduce clinician cognitive overload, and improve patient outcomes.

METHODS

Articles were included if they addressed the development, testing, implementation, or use of a visualization dashboard solution in a health care setting. An initial search was conducted of literature on dashboards only in the intensive care unit setting, but there were not many articles found that met the inclusion criteria. A secondary follow-up search was conducted to broaden the results to any health care setting. The initial and follow-up searches returned a total of 17 articles that were analyzed for this literature review.

RESULTS

Visualization dashboard solutions decrease time spent on data gathering, difficulty of data gathering process, cognitive load, time to task completion, errors, and improve situation awareness, compliance with evidence-based safety guidelines, usability, and navigation.

CONCLUSIONS

Researchers can build on the findings, strengths, and limitations of the work identified in this literature review to bolster development, testing, and implementation of novel visualization dashboard solutions. Due to the relatively few studies conducted in this area, there is plenty of room for researchers to test their solutions and add significantly to the field of knowledge on this subject.

摘要

背景

美国重症监护病房(ICU)每年收治超过570万人。ICU的护理水平有助于救治患有危及生命疾病或受伤的患者,且需要一组经过专门培训的医疗服务提供者进行密切、持续的关注。从病情发作到实施必要干预措施之间的延迟会极大地影响患有危及生命诊断的患者的预后。有证据支持信息过载与医疗差错之间存在关联。一种能够改善关键临床信息的显示和检索的工具具有极大潜力可使患者受益。本综述的目的是综合关于可视化仪表盘在医疗保健中应用的研究。

目的

进行本综述的目的是综合先前关于使用仪表盘为医疗服务提供者可视化电子健康记录信息的研究。对该主题的现有文献进行综述可用于识别先前研究中的差距,并为该主题的进一步研究工作提供信息。最终,这些证据可用于指导新解决方案的开发、测试和实施,以优化临床信息的可视化、减少临床医生的认知过载并改善患者预后。

方法

如果文章涉及可视化仪表盘解决方案在医疗保健环境中的开发、测试、实施或使用,则将其纳入。最初仅对重症监护病房环境中关于仪表盘的文献进行了搜索,但发现符合纳入标准的文章不多。随后进行了二次跟进搜索,以将结果扩展到任何医疗保健环境。最初和跟进搜索总共返回了17篇文章用于本次文献综述分析。

结果

可视化仪表盘解决方案减少了数据收集所花费的时间、数据收集过程的难度、认知负荷、任务完成时间、差错,并提高了态势感知、对循证安全指南的依从性、可用性和导航性。

结论

研究人员可以基于本综述中确定的工作的发现、优势和局限性,来加强新型可视化仪表盘解决方案的开发、测试和实施。由于该领域进行的研究相对较少,研究人员有很大空间来测试他们的解决方案,并显著增加该主题的知识领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/1f6a0efea238/humanfactors_v5i2e22_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/fd71a50e205e/humanfactors_v5i2e22_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/f65ad58c12ed/humanfactors_v5i2e22_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/2bd8e647bbed/humanfactors_v5i2e22_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/08186075c927/humanfactors_v5i2e22_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/1f6a0efea238/humanfactors_v5i2e22_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/fd71a50e205e/humanfactors_v5i2e22_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/f65ad58c12ed/humanfactors_v5i2e22_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/2bd8e647bbed/humanfactors_v5i2e22_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/08186075c927/humanfactors_v5i2e22_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21c0/6002673/1f6a0efea238/humanfactors_v5i2e22_fig5.jpg

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