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临床决策支持系统(CDSS)中的警报:文献计量学综述与内容分析

Alerts in Clinical Decision Support Systems (CDSS): A Bibliometric Review and Content Analysis.

作者信息

Chien Shuo-Chen, Chen Ya-Lin, Chien Chia-Hui, Chin Yen-Po, Yoon Chang Ho, Chen Chun-You, Yang Hsuan-Chia, Li Yu-Chuan Jack

机构信息

Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan.

International Center for Health Information and Technology, College of Medical science and Technology, Taipei Medical University, Taipei 110, Taiwan.

出版信息

Healthcare (Basel). 2022 Mar 23;10(4):601. doi: 10.3390/healthcare10040601.

DOI:10.3390/healthcare10040601
PMID:35455779
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9028311/
Abstract

A clinical decision support system (CDSS) informs or generates medical recommendations for healthcare practitioners. An alert is the most common way for a CDSS to interact with practitioners. Research about alerts in CDSS has proliferated over the past ten years. The research trend is ongoing with new emerging terms and focus. Bibliometric analysis is ideal for researchers to understand the research trend and future directions. Influential articles, institutes, countries, authors, and commonly used keywords were analyzed to grasp a comprehensive view on our topic, alerts in CDSS. Articles published between 2011 and 2021 were extracted from the Web of Science database. There were 728 articles included for bibliometric analysis, among which 24 papers were selected for content analysis. Our analysis shows that the research direction has shifted from patient safety to system utility, implying the importance of alert usability to be clinically impactful. Finally, we conclude with future research directions such as the optimization of alert mechanisms and comprehensiveness to enhance alert appropriateness and to reduce alert fatigue.

摘要

临床决策支持系统(CDSS)为医疗从业者提供信息或生成医疗建议。警报是CDSS与从业者交互的最常见方式。在过去十年中,关于CDSS中警报的研究大量涌现。随着新术语和新重点的不断出现,这一研究趋势仍在持续。文献计量分析对于研究人员了解研究趋势和未来方向非常理想。通过分析有影响力的文章、机构、国家、作者以及常用关键词,以全面了解我们的主题——CDSS中的警报。从科学网数据库中提取了2011年至2021年发表的文章。共有728篇文章纳入文献计量分析,其中24篇论文被选作内容分析。我们的分析表明,研究方向已从患者安全转向系统效用,这意味着警报可用性对于产生临床影响的重要性。最后,我们总结了未来的研究方向,如优化警报机制和全面性,以提高警报的适当性并减少警报疲劳。

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A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19).关于用于新型冠状病毒(COVID-19)诊断的深度学习技术的综述
IEEE Access. 2021 Feb 10;9:30551-30572. doi: 10.1109/ACCESS.2021.3058537. eCollection 2021.
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Drugs Real World Outcomes. 2024 Mar;11(1):125-135. doi: 10.1007/s40801-023-00405-y. Epub 2024 Jan 6.
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Exploring concepts and trends in informal caregiver burden: systematic review using citation network and content analysis.探索非正式照料者负担的概念与趋势:运用引文网络和内容分析的系统综述
Aging Clin Exp Res. 2023 Dec;35(12):2873-2885. doi: 10.1007/s40520-023-02582-w. Epub 2023 Nov 1.
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Construction and effectiveness evaluation of a knowledge-based infectious disease monitoring and decision support system.基于知识的传染病监测与决策支持系统的构建与效果评价。
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