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实时决策支持中生成新知识的临床决策支持工具的范围综述。

A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time.

机构信息

Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.

NewYork-Presbyterian Hospital, New York, New York, USA.

出版信息

J Am Med Inform Assoc. 2020 Dec 9;27(12):1968-1976. doi: 10.1093/jamia/ocaa200.

Abstract

OBJECTIVE

A growing body of observational data enabled its secondary use to facilitate clinical care for complex cases not covered by the existing evidence. We conducted a scoping review to characterize clinical decision support systems (CDSSs) that generate new knowledge to provide guidance for such cases in real time.

MATERIALS AND METHODS

PubMed, Embase, ProQuest, and IEEE Xplore were searched up to May 2020. The abstracts were screened by 2 reviewers. Full texts of the relevant articles were reviewed by the first author and approved by the second reviewer, accompanied by the screening of articles' references. The details of design, implementation and evaluation of included CDSSs were extracted.

RESULTS

Our search returned 3427 articles, 53 of which describing 25 CDSSs were selected. We identified 8 expert-based and 17 data-driven tools. Sixteen (64%) tools were developed in the United States, with the others mostly in Europe. Most of the tools (n = 16, 64%) were implemented in 1 site, with only 5 being actively used in clinical practice. Patient or quality outcomes were assessed for 3 (18%) CDSSs, 4 (16%) underwent user acceptance or usage testing and 7 (28%) functional testing.

CONCLUSIONS

We found a number of CDSSs that generate new knowledge, although only 1 addressed confounding and bias. Overall, the tools lacked demonstration of their utility. Improvement in clinical and quality outcomes were shown only for a few CDSSs, while the benefits of the others remain unclear. This review suggests a need for a further testing of such CDSSs and, if appropriate, their dissemination.

摘要

目的

越来越多的观察性数据可被二次利用,以帮助临床医生处理现有证据未涵盖的复杂病例。我们进行了一项范围性综述,以描述生成新知识的临床决策支持系统(CDSS),以便实时为这些病例提供指导。

材料和方法

截至 2020 年 5 月,我们检索了 PubMed、Embase、ProQuest 和 IEEE Xplore。由 2 位评审员筛选摘要。由第一作者评审并由第二位评审员批准相关文章全文,同时筛选文章的参考文献。提取纳入的 CDSS 的设计、实施和评估细节。

结果

我们的搜索返回了 3427 篇文章,其中 53 篇描述了 25 个 CDSS 被选中。我们确定了 8 个基于专家的工具和 17 个基于数据的工具。16 个(64%)工具是在美国开发的,其余大多在欧洲。大多数工具(n = 16,64%)在 1 个地点实施,只有 5 个在临床实践中得到积极应用。3 个(18%)CDSS 评估了患者或质量结果,4 个(16%)进行了用户接受度或使用测试,7 个(28%)进行了功能测试。

结论

我们发现了一些生成新知识的 CDSS,尽管只有 1 个解决了混杂和偏倚问题。总体而言,这些工具缺乏实用性的证明。只有少数几个 CDSS 显示出了对临床和质量结果的改善,而其他工具的效果仍不清楚。本综述表明需要进一步测试这些 CDSS,如果合适,还需要进行推广。

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