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药物相关计算机决策支持系统(CDSS):使其成为临床医生的伙伴!

Medication related computerized decision support system (CDSS): make it a clinicians' partner!

作者信息

Marcilly Romaric, Leroy Nicolas, Luyckx Michel, Pelayo Sylvia, Riccioli Costanza, Beuscart-Zéphir Marie-Catherine

机构信息

INSERM CIC-IT, Lille, CHU Lille; UDSL EA 2694; Univ Lille Nord de France; F-59000 Lille, France.

出版信息

Stud Health Technol Inform. 2011;166:84-94.

Abstract

Medication related Computerized Decision Support System (CDSS) are known to have a positive impact on Adverse Drug Events (ADE) prevention but they face acceptance problems due to over alerting and usability issues. We present here a Human factors approach to the design of these Clinical Decision Support (CDS) functions and to their integration into different Electronic Health Record (EHR) / Computerized Physicians Order Entry (CPOE) systems, so that the resulting CDSS corresponds to the users needs and fits clinical workflows and cognitive processes. We used ethnographic observations completed with semi-structured interviews to analyse existing work situations and work processes. These were then described in detail using the SHEL (Software, Hardware, Environment & Liveware) formalism, which enables a structured description of the work system and provides an appropriate classification of human errors potentially leading to ADEs. We then propose a Unified Modelling Language (UML) model supporting the characterization by the CDSS of the drug monitoring and clinical context of patients at risk of ADE. This model combines the status of the lab test orders on the one hand with the validity and normality of the lab results on the other hand. This makes the system able to catch the context of the monitoring of the drugs through their corresponding lab tests and lab results (e.g. kalemia for potassium) and also part of the context of the clinical status of the patient (actual lab values, but also diseases and other pathologies that are identified as potential causes of the ADE e.g. renal insufficiency and potassium). We show that making the system able to catch the monitoring and clinical contexts opens interesting opportunities for the design of the CDS information content and display mode. Implementing this model would allow the CDSS to take into account the actions already engaged by the healthcare team and to adapt the information delivered to the monitoring and clinical context, thus making the CDSS a partner to the clinicians, nurses and pharmacists.

摘要

药物相关的计算机化决策支持系统(CDSS)已知对预防药物不良事件(ADE)有积极影响,但由于过度警报和可用性问题,它们面临接受度方面的问题。我们在此提出一种人因方法,用于设计这些临床决策支持(CDS)功能并将其集成到不同的电子健康记录(EHR)/计算机化医师医嘱录入(CPOE)系统中,以使最终的CDSS符合用户需求并适应临床工作流程和认知过程。我们使用民族志观察并辅以半结构化访谈来分析现有的工作情况和工作流程。然后使用SHEL(软件、硬件、环境和人件)形式主义对这些情况进行详细描述,这能够对工作系统进行结构化描述,并对可能导致ADE的人为错误进行适当分类。然后,我们提出一个统一建模语言(UML)模型,支持CDSS对有ADE风险患者的药物监测和临床背景进行特征描述。该模型一方面结合实验室检查订单的状态,另一方面结合实验室结果的有效性和正常性。这使得系统能够通过相应的实验室检查和实验室结果(例如血钾用于监测钾)捕捉药物监测的背景,也能捕捉患者临床状态背景的一部分(实际实验室值,以及被确定为ADE潜在原因的疾病和其他病理情况,例如肾功能不全和钾)。我们表明,使系统能够捕捉监测和临床背景为CDS信息内容和显示模式的设计带来了有趣的机会。实施该模型将使CDSS能够考虑医疗团队已经采取的行动,并根据监测和临床背景调整所提供的信息,从而使CDSS成为临床医生、护士和药剂师的合作伙伴。

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