Process mining can help acquire insightful knowledge and heighten the system's performance. In this study, we surveyed the trajectories of 1050 sepsis patients in a regional hospital in the Netherlands from the registration to the discharge phase. Based on this real-world case study, the event log comprises events and activities related to the emergency ward, admission to hospital wards, and discharge enriched with data from lab experiments and triage checklists. At first, we aim to discover this process through Heuristics Miner (HM) and Inductive Miner (IM) methods. Then, we analyze a systematic process model based on organizational information and knowledge. Besides, we address conformance checking given medical guidelines for these patients and monitor the related flows on the systematic process model. The results show that HM and IM are inadequate in identifying the relevant process. However, using a systematic process model based on expert knowledge and organizational information resulted in an average fitness of 97.8%, a simplicity of 77.7%, and a generalization of 80.2%. The analyses demonstrate that process mining can shed light on the patient flow in the hospital and inspect the day-to-day clinical performance versus medical guidelines. Also, the process models obtained by the HM and IM methods cannot provide a concrete comprehension of the process structure for stakeholders compared to the systematic process model. The implications of our findings include the potential for process mining to improve the quality of healthcare services, optimize resource allocation, and reduce costs. Our study also highlights the importance of considering expert knowledge and organizational information in developing effective process models.

翻译：过程挖掘有助于获取深刻洞见并提升系统性能。本研究追踪了荷兰某地区医院1050名脓毒症患者从入院登记到出院阶段的轨迹。基于这一真实世界案例研究，事件日志包含急诊科、住院部及出院相关事件与活动，并补充了实验室检测数据和分诊检查清单信息。我们首先通过启发式挖掘器（HM）和归纳挖掘器（IM）方法发现该过程，随后基于组织信息与知识构建系统化过程模型。此外，我们根据医疗指南对这些患者进行一致性检验，并在系统化过程模型上监测相关流程。结果表明，HM和IM方法在识别相关过程方面存在不足。然而，基于专家知识和组织信息的系统化过程模型实现了97.8%的平均拟合度、77.7%的简约度以及80.2%的泛化度。分析显示，过程挖掘能揭示医院患者流动情况，并对照医疗指南评估日常临床绩效。同时，与系统化过程模型相比，HM和IM方法获得的过程模型无法为利益相关者提供对过程结构的具象理解。本研究的启示包括过程挖掘在提升医疗服务质量、优化资源配置及降低成本方面的潜力，同时强调了在开发有效过程模型时需重视专家知识与组织信息。