Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19146, United States.
McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
J Am Med Inform Assoc. 2024 Oct 1;31(10):2405-2413. doi: 10.1093/jamia/ocae187.
Conduct a scoping review of research studies that describe rule-based clinical decision support (CDS) malfunctions.
In April 2022, we searched three bibliographic databases (MEDLINE, CINAHL, and Embase) for literature referencing CDS malfunctions. We coded the identified malfunctions according to an existing CDS malfunction taxonomy and added new categories for factors not already captured. We also extracted and summarized information related to the CDS system, such as architecture, data source, and data format.
Twenty-eight articles met inclusion criteria, capturing 130 malfunctions. Architectures used included stand-alone systems (eg, web-based calculator), integrated systems (eg, best practices alerts), and service-oriented architectures (eg, distributed systems like SMART or CDS Hooks). No standards-based CDS malfunctions were identified. The "Cause" category of the original taxonomy includes three new types (organizational policy, hardware error, and data source) and two existing causes were expanded to include additional layers. Only 29 malfunctions (22%) described the potential impact of the malfunction on patient care.
While a substantial amount of research on CDS exists, our review indicates there is a limited focus on CDS malfunctions, with even less attention on malfunctions associated with modern delivery architectures such as SMART and CDS Hooks.
CDS malfunctions can and do occur across several different care delivery architectures. To account for advances in health information technology, existing taxonomies of CDS malfunctions must be continually updated. This will be especially important for service-oriented architectures, which connect several disparate systems, and are increasing in use.
对描述基于规则的临床决策支持(CDS)故障的研究进行范围综述。
2022 年 4 月,我们在三个书目数据库(MEDLINE、CINAHL 和 Embase)中搜索了参考 CDS 故障的文献。我们根据现有的 CDS 故障分类法对识别出的故障进行编码,并为尚未捕获的因素添加了新类别。我们还提取并总结了与 CDS 系统相关的信息,例如架构、数据源和数据格式。
28 篇文章符合纳入标准,共捕获 130 个故障。使用的架构包括独立系统(例如,基于网络的计算器)、集成系统(例如,最佳实践警报)和面向服务的架构(例如,分布式系统,如 SMART 或 CDS Hooks)。没有发现基于标准的 CDS 故障。原始分类法的“原因”类别包括三种新类型(组织政策、硬件错误和数据源),并扩展了两个现有原因以包含更多层。只有 29 个故障(22%)描述了故障对患者护理的潜在影响。
虽然关于 CDS 的研究很多,但我们的综述表明,对 CDS 故障的关注有限,对与 SMART 和 CDS Hooks 等现代交付架构相关的故障的关注更少。
CDS 故障可以而且确实会在几个不同的医疗保健交付架构中发生。为了适应健康信息技术的进步,必须不断更新现有的 CDS 故障分类法。这对于面向服务的架构尤其重要,因为面向服务的架构连接了几个不同的系统,并且使用量正在增加。