Morelock Skip G, Kirk Jeffrey D
Collin College School of Nursing McKinney Texas.
Independent statistician.
Nurs Open. 2019 Jun 17;6(3):1197-1204. doi: 10.1002/nop2.319. eCollection 2019 Jul.
This study sought to identify patterns of medication errors with respect to shifts, day of week, unit involved, severity, medication class and cause of errors and to propose possible solutions.
This was a retrospective explorative study using a database containing 605 medication events from two medical centres. Variables assessed include medication type, the error severity, and time the medication was ordered, the unit that the error occurred on and the day of the week of the errors.
Simple percentages were used to report the results, and point-biserial correlation was employed to test for significant differences between the day and night shifts.
There were no statistically significant findings when comparing event severity against the a.m. or p.m. shifts. The medication classes with the most errors were antibiotics, and the most common reason cited for errors was dose omission. The most commonly reported severity level was a 2 which requires increased patient monitoring.
本研究旨在确定与班次、一周中的日期、涉及的科室、严重程度、药物类别及错误原因相关的用药错误模式,并提出可能的解决方案。
这是一项回顾性探索性研究,使用了一个包含来自两个医疗中心的605起用药事件的数据库。评估的变量包括药物类型、错误严重程度、用药医嘱时间、错误发生的科室以及错误发生的星期几。
使用简单百分比报告结果,并采用点二列相关分析来检验日班和夜班之间的显著差异。
将事件严重程度与上午或下午班次进行比较时,未发现具有统计学意义的结果。错误最多的药物类别是抗生素,最常见的错误原因是漏服剂量。最常报告的严重程度级别为2级,这需要加强对患者的监测。