Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case Study

The discipline of process mining has a solid track record of successful applications to the healthcare domain. Within such research space, we conducted a case study related to the Intensive Care Unit (ICU) ward of the Uniklinik Aachen hospital in Germany. The aim of this work is twofold: developing a normative model representing the clinical guidelines for the treatment of COVID-19 patients, and analyzing the adherence of the observed behavior (recorded in the information system of the hospital) to such guidelines. We show that, through conformance checking techniques, it is possible to analyze the care process for COVID-19 patients, highlighting the main deviations from the clinical guidelines. The results provide physicians with useful indications for improving the process and ensuring service quality and patient satisfaction. We share the resulting model as an open-source BPMN file.Comment: 12 pages, 2 figures, 3 tables, 15 reference

Process mining for healthcare: Characteristics and challenges

[EN] Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.This work is partially supported by ANID FONDECYT 1220202, Direccion de Investigacion de la Vicerrectoria de Investigacion de la Pontificia Universidad Catolica de Chile-PUENTE [Grant No. 026/2021] ; and Agencia Nacional de Investigacion y Desarrollo [Grant Nos. ANID-PFCHA/Doctorado Nacional/2019-21190116, ANID-PFCHA/Doctorado Nacional/2020-21201411] . With regard to the co-author Hilda Klasky, this manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE) . The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan)Munoz Gama, J.; Martin, N.; Fernández Llatas, C.; Johnson, OA.; Sepúlveda, M.; Helm, E.; Galvez-Yanjari, V.... (2022). Process mining for healthcare: Characteristics and challenges. Journal of Biomedical Informatics. 127:1-15. https://doi.org/10.1016/j.jbi.2022.10399411512

Process Discovery in Healthcare: The Pisa Hospital Case Study

The aim of this thesis is to provide healthcare organizations with a means to perform and improve business process analysis, in order to obtain a better understanding about their processes. Healthcare processes are highly dynamic, complex, ad-hoc and multidisciplinary. For this reason, performing business process analysis is difficult, time-consuming and costly. Process Mining offers an innovative approach to overcome these problems. In this thesis, a methodology based on Process Mining is developed, that allows hospital managers to obtain detailed process knowledge, based on data stored in the healthcare information systems. The methodology is applied to a case study conducted at Pisa Hospital. The results can help hospital managers make decisions related to capacity planning and resources allocation and for making necessary changes in the process of care

Scientific Ecosystems and Decentralized Orchestartion: A Social Network Analysis of the CINet Conferences

This article addresses the orchestration of scientific ecosystems, which encompass a variety of competing and/or collaborating autonomous actors – including researchers, universities and industrial firms – which aim at developing theory. Scientific ecosystems are a very interesting subject to be studied because some of their features – specifically data building and sharing – are increasingly assuming importance for firms that post-COVID will have to cope with the ‘new normal’, which requires them to experiment on the basis of collectively gathered data in order to accelerate their learning “on the fly”. Specifically, business ecosystems challenged by the ‘new normal’ can leverage on the experience that scientific ecosystems have always had regarding data building and sharing. Considering conferences as decentralized orchestrating moments capable of pulling together dispersed resources/capabilities by ensuring knowledge mobility, and building on a social network analysis of the CINet conferences between 2014 and 2017, we aim at understanding the characteristics of the CINet scientific ecosystem in order to infer how well connected and close its researchers are and how effectively information is shared among them

Blockchain-Driven Process Innovation in Healthcare Ecosystems: a Business Process Management Capabilities Analysis

The Blockchain potential in enabling and boosting business process innovation in the Healthcare industry is a hot topic. However, the realization of such a potential is hampered by two hindrances. First, healthcare business processes are inherently complex. This implies additional difficulties in managing and innovating them. Second, the digitalization trend has entailed relevant changes in the capabilities needed to manage and innovate business processes. Yet, to our best knowledge, such changes have not been empirically investigated to understand context-specific factors in driving digital innovation. Accordingly, this research aims at figuring out which may be the main Business Process Management capabilities needed to carry on Blockchain-driven Healthcare business process innovation. To fill this gap, we developed two exploratory case studies in the healthcare sector – one for probing a case of incremental business process innovation (BPI) and another one for investigating a case of radical BPI. The cases focused on the business process redesign phase of the BPM lifecycle. This working paper illustrates and discusses the preliminary results of the incremental BPI case, which concern an Italian project of Blockchain-driven innovation of the national drug logistics process. The findings suggest that the Process Portfolio Management, Process Data Governance, and Multi-purpose Process Design BPM capabilities should be prioritized. Furthermore, they highlight that a new BPM capability – Process Risk Assessment – may be strongly relevant in the healthcare context. These preliminary results integrate the BPM research stream and provide practitioners with actionable insights

Service Reconfiguration in Healthcare Systems: the Case of a New Focused Hospital Unit

In the last years, hospitals have been pushed to change their services in the final attempt to maximize both care effectiveness and efficiency. In particular, emergent trends are prompting hospitals to reorganize current activities around patients and their diagnoses rather than in discipline focused departments. This research aims to support service reconfiguration by proposing a methodology exploiting the benefits of process mining techniques in the healthcare systems. In order to support decision makers during this process, the method mainly identifies/analyzes the patient flow and estimates the resources necessary for specific classes of patients. A case study also shows evidence deriving from its application to a new Patient-Focused Care Unit

Long-lasting remission in a metastatic hepatocellular carcinoma patient after combined regorafenib therapy and surgery

The therapeutic scenario of systemic treatments for hepatocellular carcinoma (HCC) is rapidly changing. There is much interest in the possibility of combining new therapies with surgery, but clinical data is lacking. We aimed to provide an example of such integration