BRIGE: Quantitative Model-Based Visualizations of Complex Health Care Processes

这项扩大参与工程研究启动补助金（bridge）赠款为设计和评估可视化提供资金，这些可视化将使卫生保健决策者（包括政策制定者和医院管理者）了解卫生保健工作者和患者如何完成卫生保健过程。决策者将能够使用可视化来更好地选择如何改进医疗保健流程，从而提高流程效率并减少与流程相关的医疗错误。研究人员将使用来自两项研究的现有过程数据来设计可视化。在第一项研究中，研究人员使用眼动追踪技术来记录医护人员如何在使用和不使用条形码技术的情况下验证患者的身份。在第二项研究中，研究人员观察了手术过程，其中一些外科医生睡眠不足。研究者将评估决策者在做出过程改进选择时的注意力分配、对信息的解释和信息的使用，这些选择基于1)汇总统计和图表，2)复杂的数字信息，以及3)不同形式的可视化。如果成功，本研究的结果将提高卫生保健决策者重新设计卫生保健流程的能力。通过微调流程可视化的设计，他们将能够在更短的时间内分析和改进更多的医疗保健流程。通过经验评估他们如何使用可视化，研究将确保可视化易于理解并对决策者有用。这种方法是可扩展的，适合于非医疗保健领域的流程可视化。

This Broadening Participation Research Initiation Grants in Engineering (BRIGE) grant provides funding to design and evaluate visualizations that will allow health care decision makers, including policy makers and hospital administrators, to understand how health care workers and patients complete health care processes. Decision makers will be able to use the visualizations to make better choices about how to improve the health care processes, thereby increasing process efficiency and reducing process-related medical errors. The researcher will design visualizations using existing process data from two studies. In the first study, researchers used eye-tracking technology to document how health care workers verified a patient's identity, with and without barcoding technology. In the second study, researchers observed the surgery process, wherein some surgeons were sleep deprived. The researcher will evaluate decision makers' attention allocation, interpretation of information, and use of information when making process improvement choices based on 1) summary statistics and charts, 2) complex numerical information, and 3) varying forms of the visualizations.If successful, the results of this research will improve health care decision makers' abilities to redesign health care processes. By fine-tuning the design of the process visualizations, they will be able to analyze and improve more health care processes in less time. By empirically evaluating how they use the visualizations, the research will ensure that the visualizations are easy to understand and useful to the decision makers. This approach is scalable and lends itself to visualizing processes in non-health care domains.