Managing Business Process Variability Through Process Mining and Semantic Reasoning: An Application in Healthcare

Detro, Silvana Pereira; Santos, Eduardo Alves Portela; Panetto, Hervé; Loures, Eduardo de Freitas Rocha; Lezoche, Mario

doi:10.1007/978-3-319-65151-4_31

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…For this reason, some authors refer to this type of comparison as a conformance checking or conformance analysis [ 6 , 17 , 19 ]. These studies [ 20 , 21 , 22 ] often include and overlap with a consistent number of papers that aim to identify variants and similarities of pathways within a cohort of patients with similar health conditions [ 23 , 24 , 25 , 26 ].…”

Section: Related Workmentioning

confidence: 99%

Using Unified Modeling Language to Analyze Business Processes in the Delivery of Child Health Services

Pecoraro

Luzi

2022

IJERPH

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Business Process Management (BPM) has been increasingly used in recent years in the healthcare domain to analyze, optimize, harmonize and compare clinical and healthcare processes. The main aim of this methodology is to model the interactions between medical and organizational activities needed to deliver health services, measure their complexity, variability and deviations to improve the quality of care and its efficiency. Among the different tools, languages and notations developed in the decades, UML (Unified Modeling Language) represents a widely adopted technique to model, analyze and compare business processes in healthcare. We adopted its diagrams in the MOCHA project to compare the different ways of organizing, coordinating and delivering child care across 30 EU/EEA countries both from an organization and control-flow perspectives. This paper provides an overview of the main components used to represent the business process using UML diagrams, also highlighting how we customized them to capture the specificity of the healthcare domain taking into account that processes are reconstructed on the basis of country experts’ responses to questionnaires. The benefits of the application of this methodology are demonstrated by providing examples of comparing different aspects of child care.

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Section: Related Workmentioning

confidence: 99%

Using Unified Modeling Language to Analyze Business Processes in the Delivery of Child Health Services

Pecoraro

Luzi

2022

IJERPH

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“…Health processes are mostly classified as ad hoc processes, in the sense that the same treatment can follow different paths by virtue of the patient's response, but also of the discretion of doctors who have the power to deviate from the guidelines on the basis of their knowledge and experience to address specific patient situations (Detro et al, 2017). In this context, it is of crucial importance to have techniques capable of discriminating different behaviors in the same process so that the analyst can study them separately.…”

Section: Variants Analysismentioning

confidence: 99%

“…The ontology, implemented in the OWL description logic, is used for matching the data of a patient with that of other healthy patients, while conformance checking algorithms are used to compare process model of a patient with the process model of healthy patients. Detro et al (2017) proposed a semantic PM framework for selecting the appropriate process variant according with the patient's symptoms by means of ontologies based on known expertise.…”

Section: Event Log Quality Improvementmentioning

confidence: 99%

Process mining applications in the healthcare domain: A comprehensive review

Guzzo

Rullo

Vocaturo

2021

WIREs Data Min & Knowl

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Process mining (PM) is a well-known research area that includes techniques, methodologies, and tools for analyzing processes in a variety of application domains. In the case of healthcare, processes are characterized by high variability in terms of activities, duration, and involved resources (e.g., physicians, nurses, administrators, machineries, etc.). Besides, the multitude of diseases that the patients housed in healthcare facilities suffer from makes medical contexts highly heterogeneous. As a result, understanding and analyzing healthcare processes are certainly not trivial tasks, and administrators and doctors look for tools and methods that can concretely support them in improving the healthcare services they are involved in. In this context, PM has been increasingly used for a wide range of applications as reported in some recent reviews. However, these reviews mainly focus on discussion on applications related to the clinical pathways, while a systematic review of all possible applications is absent. In this article, we selected 172 papers published in the last 10 years, that present applications of PM in the healthcare domain. The objective of this study is to help and guide researchers interested in the medical field to understand the main PM applications in the healthcare, but also to suggest new ways to develop promising and not yet fully investigated applications. Moreover, our study could be of interest for practitioners who are considering applications of PM, who can identify and choose PM algorithms, techniques, tools, methodologies, and approaches, toward what have been the experiences of success.

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“…Technical limitations were identified in 13 papers [28], [23], [51], [46], [41], [27], [44], [45], [32], [33], [37], [48], [55] including limitations in computer processing power, memory usage, bias associated with the mining algorithm, and simplifying the control flow due to computational complexity. There were no studies which reported limitation of team composition, however, 14 studies reported that they had involved clinician(s) to help the team with analysis or verification of results [28], [23], [46], [41], [54], [30], [27], [32], [33], [48], [55], [49], [50], [42].…”

Section: Limitations and Future Workmentioning

confidence: 99%

Process Mining in Cardiology: A Literature Review

Kusuma¹,

Hall²,

Gale³

et al. 2018

IJBBB

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Process mining is a data analytics approach which has shown promising results in healthcare including the potential to improve the management of chronic diseases such as cardiovascular disease (CVD). CVD are one of the leading causes of premature death worldwide. Helping healthcare professionals develop a better understanding of how to improve CVD care pathways may result in better outcomes for patients. This paper describes the opportunities for process mining to support such improvements and provides a summary of process mining studies undertaken in the field of cardiology. The initial search found 1,597 potentially relevant papers which, after a systematic review, identified a final set of 32 relevant studies. These studies were analyzed across five themes: process and data types; research questions; techniques, perspective and tools; methodologies; limitations and suggested future work.

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Managing Business Process Variability Through Process Mining and Semantic Reasoning: An Application in Healthcare

Cited by 7 publications

References 22 publications

Using Unified Modeling Language to Analyze Business Processes in the Delivery of Child Health Services

Using Unified Modeling Language to Analyze Business Processes in the Delivery of Child Health Services

Process mining applications in the healthcare domain: A comprehensive review

Process Mining in Cardiology: A Literature Review

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