Process Mining for Trauma Resuscitation.

Sen Yang, Jingyuan Li, Xiaoyi Tang, Shuhong Chen, Ivan Marsic, Randall S Burd
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Abstract

We present our process mining system for analyzing the trauma resuscitation process to improve medical team performance and patient outcomes. Our system has four main parts: trauma resuscitation process model discovery, process model enhancement (or repair), process deviation analysis, and process recommendation. We developed novel algorithms to address the technical challenges for each problem. We validated our system on real-world trauma resuscitation data from the Children's National Medical Center (CNMC), a level 1 trauma center. Our results show our system's capability of supporting complex medical processes. Our approaches were also implemented in an interactive visual analytic tool.

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创伤复苏过程挖掘。
我们提出了我们的过程挖掘系统,用于分析创伤复苏过程,以提高医疗团队的绩效和患者的结果。我们的系统有四个主要部分:创伤复苏过程模型发现、过程模型增强(或修复)、过程偏差分析和过程推荐。我们开发了新的算法来解决每个问题的技术挑战。我们根据国家儿童医疗中心(CNMC)一级创伤中心的真实创伤复苏数据验证了我们的系统。我们的结果显示了我们的系统支持复杂医疗过程的能力。我们的方法也在交互式视觉分析工具中实现。
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Process Mining for Trauma Resuscitation. Computer Science in the Information Age
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