Ohashi Kumiko, Dykes Patricia, McIntosh Kathleen, Buckley Elizabeth, Wien Matt, Kreitzman Kevin, Dumais Michael, Bates David W
General Internal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Stud Health Technol Inform. 2013;192:1102.
Computerized smart infusion pumps have been widely implemented to decrease the rate of intravenous (IV) medication errors in hospitals. However, these devices have not always achieved their potential, and important IV errors still persist. Findings from a previous study [1] that assessed the frequency of IV medication errors and the impact of smart infusion pumps identified major issues related to use of smart infusion pumps in a single facility, but generalizability of these results is uncertain. Additionally, lack of standardized methodology for measuring these errors remains an issue. In this study, we developed an observational tool to capture IV medication errors through iterative participatory design with interdisciplinary experts and then tested the tool by using incident cases regarding smart pump errors. We found that the tool could capture all smart infusion pump errors and is ready for testing for use as standard data collection tool in different hospital settings.
计算机化智能输液泵已在医院广泛应用，以降低静脉（IV）用药错误率。然而，这些设备并未总能发挥其潜力，重要的IV错误仍然存在。先前一项研究[1]评估了IV用药错误的频率以及智能输液泵的影响，该研究确定了单个机构中与智能输液泵使用相关的主要问题，但这些结果的普遍性尚不确定。此外，缺乏测量这些错误的标准化方法仍然是一个问题。在本研究中，我们通过与跨学科专家进行迭代参与式设计，开发了一种观察工具来捕捉IV用药错误，然后通过使用有关智能泵错误的事件案例对该工具进行测试。我们发现该工具可以捕捉所有智能输液泵错误，并准备好在不同医院环境中作为标准数据收集工具进行测试。
