A Memory-Based Approach to Reducing Medication Errors

项目总结 尽管进行了广泛的研究，但10%至50%的住院用药实例是 与错误相关联。记忆力减退是用药失误(MAE)的常见原因。 前瞻记忆是指记忆将来必须对其采取行动的信息，是一种常见的记忆方式 护士在给药过程中使用的记忆过程，是潜在的重要来源 内存丢失错误。给药过程中的PM任务出现在护士必须记住执行 未来与药物相关的重要任务，例如记住之前检查交互 进行药物治疗，并记住恢复在药物治疗期间中断的任务 行政管理。在护士管理的高风险、大容量内外科病房中管理PM需求 多达8名患者，每个患者平均每天安排25次药物治疗，特别是 具有挑战性，并可能使护士面临犯下MAE的风险。我们的提案将使用认知心理学- 以PM为重点的方法，在用药过程中确定PM需求。我们将使用 社会技术系统理论用于识别给药过程中PM可能存在的高危时刻 没有社会技术系统的支持，并增加了MAES的可能性。我们还将分析药物治疗 通过住院药物处方到给药周期中的技术生成的数据产生的错误 并使这些数据与PM需求保持一致，以便对用药差错之间的关联提供独特的见解 和首相的要求。我们提出的研究包括以下几个方面：具体目标1：识别和量化护士 PM通过访谈和直接观察在用药过程中的需求。具体目标2： 通过分析住院用药周期中的技术使用数据来识别和量化用药错误(即， 处方、配药、给药和记录)，并根据观察到的PM调整用药错误 要求。在给药期间识别护士的记忆需求提供了一个机会 未来开发记忆辅助设备和健康信息技术以支持PM的工作需要减少MAES。

PROJECT SUMMARY Despite being widely researched, between 10 to 50% of inpatient medication administration instances are associated with errors. Memory lapses are a common cause of medication administration errors (MAE). Prospective memory (PM), which is remembering information that must be acted on in the future, is a frequent memory process used by nurses during medication administration and is a potentially significant source of the memory lapse errors. PM tasks during medication administration arise when nurses must remember to perform important medication-related tasks in the future, such as remembering to check for interactions before administering medication, and remembering to resume tasks that are interrupted during medication administration. Managing PM demands in high-risk, high-volume medical/surgical units in which nurses manage up to eight patients, with each patient being scheduled on average 25 medications per day, is especially challenging, and may leave nurses at risk for committing MAEs. Our proposal will use a cognitive psychology- based approach, with a focus on PM, to identify PM demands during medication administration. We will use sociotechnical systems theory to identify high-risk moments during medication administration where PM may be unsupported by the sociotechnical system and increase the likelihood of MAEs. We will also analyze medication errors through data generated by technologies in the inpatient medication prescription to administration cycle and align these data with PM demands to provide unique insights into the association between medication errors and PM demands. Our proposed research includes the following: Specific Aim 1: Identify and quantify nurse PM demands during medication administration through interviews and direct observations. Specific Aim 2: Identify and quantify medication errors by analyzing technology usage data in the inpatient medication cycle (i.e., prescription, dispensing, administration, and documentation), and align medication errors with observed PM demands. Identifying memory demands of nurses during medication administration presents an opportunity for future work to develop memory aids and health information technology to support PM needs to reduce MAEs.