Nephrology and Kidney Transplant Research Center, Urmia University of Medical Sciences, Urmia, Iran.
Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran.
BMC Med Inform Decis Mak. 2020 Aug 20;20(1):196. doi: 10.1186/s12911-020-01196-w.
Drug-laboratory (lab) interactions (DLIs) are a common source of preventable medication errors. Clinical decision support systems (CDSSs) are promising tools to decrease such errors by improving prescription quality in terms of lab values. However, alert fatigue counteracts their impact. We aimed to develop a novel user-friendly, evidence-based, clinical context-aware CDSS to alert nephrologists about DLIs clinically important lab values in prescriptions of kidney recipients.
For the most frequently prescribed medications identified by a prospective cross-sectional study in a kidney transplant clinic, DLI-rules were extracted using main pharmacology references and clinical inputs from clinicians. A CDSS was then developed linking a computerized prescription system and lab records. The system performance was tested using data of both fictitious and real patients. The "Questionnaire for User Interface Satisfaction" was used to measure user satisfaction of the human-computer interface.
Among 27 study medications, 17 needed adjustments regarding renal function, 15 required considerations based on hepatic function, 8 had drug-pregnancy interactions, and 13 required baselines or follow-up lab monitoring. Using IF & THEN rules and the contents of associated alert, a DLI-alerting CDSS was designed. To avoid alert fatigue, the alert appearance was considered as interruptive only when medications with serious risks were contraindicated or needed to be discontinued or adjusted. Other alerts appeared in a non-interruptive mode with visual clues on the prescription window for easy, intuitive notice. When the system was used for real 100 patients, it correctly detected 260 DLIs and displayed 249 monitoring, seven hepatic, four pregnancy, and none renal alerts. The system delivered patient-specific recommendations based on individual lab values in real-time. Clinicians were highly satisfied with the usability of the system.
To our knowledge, this is the first study of a comprehensive DLI-CDSS for kidney transplant care. By alerting on considerations in renal and hepatic dysfunctions, maternal and fetal toxicity, or required lab monitoring, this system can potentially improve medication safety in kidney recipients. Our experience provides a strong foundation for designing specialized systems to promote individualized transplant follow-up care.
药物-实验室（lab）相互作用（DLIs）是可预防药物错误的常见来源。临床决策支持系统（CDSS）是一种有前途的工具，可以通过提高实验室值方面的处方质量来减少此类错误。然而，警报疲劳会抵消其影响。我们旨在开发一种新颖的、用户友好的、基于证据的、临床上下文感知的 CDSS，以便提醒肾病学家注意肾移植受者处方中临床重要的实验室值的 DLIs。
对于在肾脏移植诊所进行的前瞻性横断面研究中确定的最常开处方药物，使用主要药理学参考文献和临床医生的临床输入提取 DLI 规则。然后，开发了一个链接计算机化处方系统和实验室记录的 CDSS。使用虚构和真实患者的数据测试系统性能。使用“用户界面满意度调查问卷”来衡量人机界面的用户满意度。
在 27 种研究药物中，有 17 种需要根据肾功能进行调整，15 种需要根据肝功能进行考虑，8 种有药物-妊娠相互作用，13 种需要基线或后续实验室监测。使用 IF 和 THEN 规则以及相关警报的内容，设计了一个 DLI 警报 CDSS。为了避免警报疲劳，仅当存在严重风险的药物被禁忌或需要停止或调整时，警报的出现才被认为是中断的。其他警报以非中断模式出现，在处方窗口上有视觉提示，便于直观注意。当系统用于 100 名真实患者时，它正确检测到 260 个 DLI，并显示 249 个监测、7 个肝脏、4 个妊娠和 0 个肾脏警报。该系统根据个体实验室值实时提供患者特定的建议。临床医生对系统的可用性非常满意。
据我们所知，这是第一项针对肾脏移植护理的全面 DLI-CDSS 的研究。通过提醒肾功能和肝功能障碍、母体和胎儿毒性或所需的实验室监测，该系统有可能提高肾移植受者的药物安全性。我们的经验为设计专门的系统以促进个体化移植随访护理提供了坚实的基础。
