Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development.
Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development.
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DOI：
10.1186/s12911-017-0480-y
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发表时间：
2017-06-06
影响因子：
3.5
通讯作者：
Sedlmayr M
中科院分区：
文献类型：
--
作者：
Hinderer M;Boeker M;Wagner SA;Lablans M;Newe S;Hülsemann JL;Neumaier M;Binder H;Renz H;Acker T;Prokosch HU;Sedlmayr M
药物基因组学临床决策支持系统(CDSS)具有帮助克服将药物基因组学知识转化为临床常规知识的一些障碍的潜力。在开发原型之前，至关重要的是开发人员要知道在以前的药物基因组CDSS工作中还开发、实现和测试了哪些药物基因组CDSS功能和用户-系统交互，以及它们是否已经成功应用。我们通过提供最近开发的药物基因组CDSS的用户-系统交互设计的概述来解决这个问题。计算机检索PubMed 2012年1月1日至2016年11月15日发表的药物基因组CDSS。对118篇已确定的文章中的32篇进行了总结，并纳入了最终分析。然后，我们比较了我们已经确定的20个药物基因组CDSS的用户-系统交互设计。警报是医生-系统交互最广泛的工具，但需要谨慎实施，以防止警报疲劳和避免责任。存储在当地EHR中的药物基因组测试结果和替代原因可能有助于将药物基因组信息传达给其他内部护理提供者。通过患者信函和在线门户将患者整合到用户系统交互中，对于将药物基因组数据传输到外部医疗保健提供者可能是至关重要的。收件箱消息通知医生新的药物基因组测试结果，并使他们能够请求药物基因组咨询。搜索引擎使医生能够根据患者的基因型别比较医疗方案。在过去的5年里，已经开发了几个药物基因组CDSS。然而，大多数收录的文章仅描述了药物基因组CDSS的原型，而没有对它们进行评估。为了支持原型的开发，将需要进一步的评价工作。在未来，药物基因组CDSS可能会包括预测模型，以识别适合先发制人基因分型的患者。本文的在线版本(doi：10.1186/s12911-0170480-y)包含补充材料，授权用户可以使用。
Pharmacogenomic clinical decision support systems (CDSS) have the potential to help overcome some of the barriers for translating pharmacogenomic knowledge into clinical routine. Before developing a prototype it is crucial for developers to know which pharmacogenomic CDSS features and user-system interactions have yet been developed, implemented and tested in previous pharmacogenomic CDSS efforts and if they have been successfully applied. We address this issue by providing an overview of the designs of user-system interactions of recently developed pharmacogenomic CDSS. We searched PubMed for pharmacogenomic CDSS published between January 1, 2012 and November 15, 2016. Thirty-two out of 118 identified articles were summarized and included in the final analysis. We then compared the designs of user-system interactions of the 20 pharmacogenomic CDSS we had identified. Alerts are the most widespread tools for physician-system interactions, but need to be implemented carefully to prevent alert fatigue and avoid liabilities. Pharmacogenomic test results and override reasons stored in the local EHR might help communicate pharmacogenomic information to other internal care providers. Integrating patients into user-system interactions through patient letters and online portals might be crucial for transferring pharmacogenomic data to external health care providers. Inbox messages inform physicians about new pharmacogenomic test results and enable them to request pharmacogenomic consultations. Search engines enable physicians to compare medical treatment options based on a patient’s genotype. Within the last 5 years, several pharmacogenomic CDSS have been developed. However, most of the included articles are solely describing prototypes of pharmacogenomic CDSS rather than evaluating them. To support the development of prototypes further evaluation efforts will be necessary. In the future, pharmacogenomic CDSS will likely include prediction models to identify patients who are suitable for preemptive genotyping. The online version of this article (doi:10.1186/s12911-017-0480-y) contains supplementary material, which is available to authorized users.