Using Indoor Location System Data to Enhance the Quality of Healthcare Event Logs: Opportunities and Challenges

Martin, Niels

doi:10.1007/978-3-030-11641-5_18

Cited by 11 publications

(7 citation statements)

References 23 publications

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“…With the aim of avoiding the “spaghetti‐like” effect on process discovery tasks, the same authors (Alharbi et al, 2018) proposed an event abstraction method according to which the event log is enriched with HMM‐derived states, so as to remodel the healthcare processes as state transitions. Martin (2018) showed how indoor location system (ILS) data can be used to attenuate data quality issues present in the event logs extracted from a HIS. In particular, he proposed various ways of cross‐referencing data from an ILS and an HIS.…”

Section: Literature Discussionmentioning

confidence: 99%

“…Locations are determined by means of wireless technologies as radio frequency identification (RFID) tags, integrated in patient identification bands or staff cards, and antennas which are deployed in the hospital's departments. RTLS data have been used for PM to collect patients' movements (Araghi et al, 2019(Araghi et al, , 2020Araghi, Fontaili, et al, 2018;Araghi, Fontanili, et al, 2018;Fern andez-Llatas et al, 2013;Martinez-Millana et al, 2019), to mine the workflow of medical equipments (Liu et al, 2014), to study a surgical process (Fernandez-Llatas et al, 2015), and to enhance event logs extracted from a HIS (Fernandez-Llatas et al, 2021;Martin, 2018).…”

Section: Healthcare Datamentioning

confidence: 99%

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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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Section: Literature Discussionmentioning

confidence: 99%

Section: Healthcare Datamentioning

confidence: 99%

Process mining applications in the healthcare domain: A comprehensive review

Guzzo

Rullo

Vocaturo

2021

WIREs Data Min & Knowl

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“…While the preceding examples highlight the potential of process mining in healthcare, some applications also cannot reach their full potential. Even though deficient aspects of an application are typically not explicitly articulated in published work, practical experience learns that the availability of reliable data is a key challenge in healthcare [61,62,63]. For instance, a process mining analysis at an emergency department focusing on a particular pathology was rescoped because it was impossible to distinguish patients with this condition in the event log.…”

Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

“…In recent years, there has been an uptake in research on data quality within the process mining field. Literature focuses on the identification of data quality issues [2,126,127,61,128], and the mitigation of one or more of these issues using a particular heuristic [61,128,129,62,130,131,132].…”

Section: Take Into Account Healthcare Specificities During Technique Development (Rc-5)mentioning

confidence: 99%

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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“…Recently, the application of Indoor Localization Systems (ILS) and Process Mining is proposed in several research works to address such issues and to improve the outcome of patient pathways (Kamel Boulos and Berry, 2012;Martin, 2019;Rojas et al, 2017b;Martinez-Millana et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations

Araghi

Fontanili

Lamine

et al. 2020

Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies

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The application of indoor localization and process mining emerges as an intriguing tool for the researchers to address the structural issues related to the patient pathways inside healthcare organizations. However, there is a major gap in the literature. This is related to the lack of enough attention to the interpretation of location data. Therefore, as a contribution, this article presents the DIAG meta-model and relevant location data interpretation rules. This model-driven approach has been realized in the context of the R-IOSUITE application and it supports the further analyses by the process mining methods.

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Using Indoor Location System Data to Enhance the Quality of Healthcare Event Logs: Opportunities and Challenges

Cited by 11 publications

References 23 publications

Process mining applications in the healthcare domain: A comprehensive review

Process mining applications in the healthcare domain: A comprehensive review

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

Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations

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