| Literature DB >> 30443472 |
Sen Yang1, Jingyuan Li2, Xiaoyi Tang3, Shuhong Chen4, Ivan Marsic5, Randall S Burd6.
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.Entities:
Keywords: Medical Process Diagnosis; Process Mining; Trauma Resuscitation
Year: 2017 PMID: 30443472 PMCID: PMC6233890
Source DB: PubMed Journal: IEEE Intell Inform Bull