Justinia Taghreed, Qattan Weam, Almenhali Ahmed, Abo-Khatwa Abdulaziz, Alharbi Omar, Alharbi Talal
College of Public Health & Health Informatics, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
King Abdullah International Medical Research Center, Jeddah, Saudi Arabia.
Acta Inform Med. 2021 Dec;29(4):248-252. doi: 10.5455/aim.2021.29.248-252.
Clinical decision support systems (CDSS) can enhance patient safety and reduce medication errors by giving physicians alerts while dispensing medications. Physicians inappropriately override these alerts for various reasons, which can possibly lead to medication errors and impact patient safety.
To assess the appropriateness of overridden major medication-related alerts, to investigate the reasons behind inappropriate overriding, and to evaluate if medication errors occur in inappropriately overridden alerts.
A mixed-methods study was conducted.. Quantitative: Retrospective observation to evaluate the appropriateness of major drug-dose related alert overrides. A simple random sample was taken from appropriate and inappropriate overrides and reviewed for medication errors. Qualitative: Semi-Structured Interviews were conducted with ten consultant physicians from various specialties. Interviews were transcribed and coded inductively then analyzed using Thematic Content Analysis.
Out of 1087 alert overrides that were evaluated for appropriateness, 738 were inappropriately overridden (67.89%). In a sample of 283 inappropriate and 92 appropriate overrides; the resulted medication errors were 7 and 0, respectively. Qualitative analysis resulted in three emergent themes; Judgement, Experience & Guidelines, CDSS Issues & Limitations, Physician Behavior & Safety.
The majority of alerts were found to be inappropriately overridden. This can be attributed to physician reliance on their clinical knowledge and medication databases, having the pharmacists' checks, and alert fatigue. CDSS alerts can be improved by making them more prominent and suppressing or descaling unnecessary alerts. The drop-down justification list can be enhanced by adding free text options and relating recommended dosing to disease or specialty.
临床决策支持系统（CDSS）可通过在配药时向医生发出警报来提高患者安全性并减少用药错误。医生会因各种原因不适当地忽略这些警报，这可能导致用药错误并影响患者安全。
评估被忽略的主要用药相关警报的合理性，调查不适当忽略背后的原因，并评估在不适当忽略的警报中是否发生用药错误。
进行了一项混合方法研究。定量研究：进行回顾性观察以评估主要药物剂量相关警报忽略的合理性。从适当和不适当的忽略中抽取简单随机样本，并审查用药错误情况。定性研究：对来自不同专科的十位顾问医生进行半结构化访谈。访谈内容进行转录并进行归纳编码，然后使用主题内容分析法进行分析。
在评估合理性的1087次警报忽略中，有738次被不适当忽略（67.89%）。在283次不适当忽略和92次适当忽略的样本中，分别导致7次和0次用药错误。定性分析产生了三个新出现的主题：判断、经验与指南；CDSS问题与局限性；医生行为与安全。
发现大多数警报被不适当忽略。这可归因于医生对其临床知识和用药数据库的依赖、有药剂师的检查以及警报疲劳。可以通过使CDSS警报更加突出并抑制或减少不必要的警报来改进这些警报。通过添加自由文本选项并将推荐剂量与疾病或专科相关联，可以增强下拉式理由列表。
