Mining post-surgical care processes in breast cancer patients

Chiudinelli, Lorenzo; Dagliati, Arianna; Tibollo, Valentina; Albasini, Sara; Geifman, Nophar; Peek, Niels; Holmes, John H.; Corsi, Fabio; Bellazzi, Riccardo; Sacchi, Lucia

doi:10.1016/j.artmed.2020.101855

Cited by 20 publications

(24 citation statements)

References 22 publications

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“…The insights can be used to identify treatment patterns with low mortality rates or patterns which require a closer follow-up [11]. An alternative approach to handle the complexity of healthcare processes is proposed in Chiudinelli et al [24].…”

Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

“…They use topic modeling to synthesize the large number of detailed activities taking place during a particular hospital visit to generate an more high-level overview of the post-surgical treatment processes for breast cancer patients [24]. While the prior illustrations focus on clinical processes in which patients are directly involved, Forsberg et al [53] study the use of a picture archiving and communication system by radiologists using process mining.…”

Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

“…An example of preliminary work in this direction is Vroling [54], where the impact of deviations from the clinical guidelines for colon cancer treatment on patient survival is studied [33,54]. Similarly, Chiudinelli et al [24] study the survival probability of breast cancer patients based on their post-surgery treatment process. Relating improvement initiatives inspired by process mining to positive clinical effects will demonstrate that patients can also benefit from process mining.…”

Section: Establish a Standardized Terminology To Support Process Mining In Healthcare (Rc-1)mentioning

confidence: 99%

“…To obtain a control-flow model from an event log, a multitude of discovery algorithms have been developed, of which an overview is provided in De Weerdt et al [21] and Augusto et al [22]. Specific control-flow discovery algorithms for clinical processes have also been proposed in literature [23,24]. Despite the predominant research focus on controlflow, some methods also allow for mining, for instance, resource-related models such as social networks [25,26], resource profiles [27], resource roles [28,29] and work prioritization patterns [30].…”

Section: Introduction To Process Mining In Healthcarementioning

confidence: 99%

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Recommendations for enhancing the usability and understandability of process mining in healthcare

Martin

Weerdt

Fernández-Llatas

et al. 2020

Artificial Intelligence in Medicine

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Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process analysis is required, which can be based on real-life process execution data captured by health information systems. Process mining is a research field that focuses on the development of techniques to extract process-related insights from process execution data, providing valuable and previously unknown information to instigate evidence-based process improvement in healthcare. However, despite the potential of process mining, its uptake in healthcare organizations outside case studies in a research context is rather limited. This observation was the starting point for an international brainstorm seminar. Based on the seminar's outcomes and with the ambition to stimulate a more widespread use of process mining in healthcare, this paper formulates recommendations to enhance the usability and understandability of process mining in healthcare. These recommendations are mainly targeted towards process mining researchers and the community to consider when developing a new research agenda for process mining in healthcare. Moreover, a limited number of recommendations are directed towards healthcare organizations and health information systems vendors, when shaping an environment to enable the continuous use of process mining.

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Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

Section: Establish a Standardized Terminology To Support Process Mining In Healthcare (Rc-1)mentioning

confidence: 99%

Section: Introduction To Process Mining In Healthcarementioning

confidence: 99%

See 2 more Smart Citations

Recommendations for enhancing the usability and understandability of process mining in healthcare

Martin

Weerdt

Fernández-Llatas

et al. 2020

Artificial Intelligence in Medicine

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“…Chiudinelli et al. [ 22 ] analyze data extracted from some 3000 electronic health records and describe a care flow mining algorithm to define the most frequent patterns of care. The results allow drawing electronic temporal phenotypes which describe well-characterized pathology classes across the studied population, and provide the surgeons with relevant help in care delivery.…”

mentioning

confidence: 99%

Artificial intelligence (AI) in breast cancer care - Leveraging multidisciplinary skills to improve care

et al. 2021

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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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Mining post-surgical care processes in breast cancer patients

Cited by 20 publications

References 22 publications

Recommendations for enhancing the usability and understandability of process mining in healthcare

Recommendations for enhancing the usability and understandability of process mining in healthcare

Artificial intelligence (AI) in breast cancer care - Leveraging multidisciplinary skills to improve care

Process mining applications in the healthcare domain: A comprehensive review

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