Aversano Lerina, Iammarino Martina, Madau Antonella, Pirlo Giuseppe, Semeraro Gianfranco
Department of Agricultural Science, Food, Natural Resources and Engineering, University of Foggia, Foggia, Italy.
Department of Information Science and Technology, Pegaso University, Naples, Italy.
PeerJ Comput Sci. 2025 Jan 28;11:e2613. doi: 10.7717/peerj-cs.2613. eCollection 2025.
Process mining applications in healthcare is a field widely investigated in the last years. Its diffusion is driven by increasing digitalization and the availability of large quantities of clinical data, enabling hospitals, clinics, and other healthcare organizations to optimize workflows, reduce operational costs, and improve asset management. The importance of process mining lies in its potential to identify inefficiencies in processes, standardize clinical practices, support evidence-based decisions and, in general, improve the quality of care provided. The article aims to systematically review the research landscape in the field of process mining in healthcare, providing an in-depth understanding of how process mining is applied in healthcare. It contributes to the existing literature by highlighting the following aspects: the specific research topics covered (i), the extent of use of various process mining algorithms in different healthcare applications, showing their adaptability and effectiveness in specific contexts (ii), and, finally, the types and characteristics of data employed in these studies, highlighting the needs and challenges related to data in healthcare process mining (iii). Through this systematic literature review, the article can support researchers in identifying the most valuable research topic to be explored by the scientific community working on process mining in healthcare. To achieve this goal, several articles focusing on the algorithms and data employed were selected and analyzed. The final discussion highlights current research gaps, suggesting future areas of investigation, and identifies critical issues and vulnerabilities of existing process mining applications in healthcare.
医疗保健领域的流程挖掘应用是近年来得到广泛研究的一个领域。其普及得益于数字化程度的不断提高以及大量临床数据的可得性，这使得医院、诊所及其他医疗保健组织能够优化工作流程、降低运营成本并改善资产管理。流程挖掘的重要性在于其有潜力识别流程中的低效率之处、规范临床实践、支持基于证据的决策，并总体上提高所提供护理的质量。本文旨在系统地综述医疗保健领域流程挖掘的研究现状，深入了解流程挖掘在医疗保健中的应用方式。它通过突出以下几个方面为现有文献做出贡献：所涵盖的具体研究主题（i）、各种流程挖掘算法在不同医疗保健应用中的使用程度，展示其在特定背景下的适应性和有效性（ii），以及最后，这些研究中所使用数据的类型和特征，突出医疗保健流程挖掘中与数据相关的需求和挑战（iii）。通过这种系统的文献综述，本文可以帮助研究人员确定医疗保健领域从事流程挖掘的科学界最有价值的研究主题。为实现这一目标，选取并分析了几篇关注所使用算法和数据的文章。最后的讨论突出了当前的研究差距，提出了未来的研究领域，并确定了现有医疗保健流程挖掘应用中的关键问题和弱点。
