Koufi Vassiliki, Malamateniou Flora, Prentza Adrianna, Vassilacopoulos George
Department of Digital Systems, University of Piraeus, Greece.
Stud Health Technol Inform. 2017;238:147-150.
Emergency medical systems (EMS) are considered to be amongst the most crucial systems as they involve a variety of activities which are performed from the time of a call to an ambulance service till the time of patient's discharge from the emergency department of a hospital. These activities are closely interrelated so that collaboration and coordination becomes a vital issue for patients and for emergency healthcare service performance. The utilization of standard workflow technology in the context of Service Oriented Architecture can provide an appropriate technological infrastructure for defining and automating EMS processes that span organizational boundaries so that to create and empower collaboration and coordination among the participating organizations. In such systems, the utilization of leading-edge analytics tools can prove important as it can facilitate real-time extraction and visualization of useful insights from the mountains of generated data pertaining to emergency case management. This paper presents a framework which provides healthcare professionals with just-in-time insight within and across emergency healthcare processes by performing real-time analysis on process-related data in order to better support decision making and identify potential critical risks that may affect the provision of emergency care to patients.
紧急医疗系统（EMS）被认为是最关键的系统之一，因为它们涉及从呼叫救护车服务之时到患者从医院急诊科出院期间所执行的各种活动。这些活动紧密相关，因此协作与协调对于患者和紧急医疗服务绩效而言都成为至关重要的问题。在面向服务架构的背景下使用标准工作流技术，可以提供一个适当的技术基础设施，用于定义跨越组织边界的EMS流程并使其自动化，从而在参与组织之间创建并加强协作与协调。在这样的系统中，使用前沿分析工具可能很重要，因为它可以促进从与紧急病例管理相关的大量生成数据中实时提取并可视化有用的见解。本文提出了一个框架，该框架通过对与流程相关的数据进行实时分析，为医疗保健专业人员提供紧急医疗流程内部及跨流程的即时见解，以便更好地支持决策制定并识别可能影响向患者提供紧急护理的潜在关键风险。
