Monitoring care processes in the gynecologic oncology department

Caron, Filip; Vanthienen, Jan; Vanhaecht, Kris; Limbergen, Erik; Weerdt, Jochen De; Baesens, Bart

doi:10.1016/j.compbiomed.2013.10.015

Cited by 45 publications

(36 citation statements)

References 18 publications

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“…All papers except one [39] discussed the control-flow perspective. Most of the papers (27 of the 37) discussed the performance perspective, but only 5 discussed the organizational perspective [3], [11], [23], [44], [45]. All papers, except two [35], [39], studied discovery from a control-flow perspective.…”

Section: Resultsmentioning

confidence: 99%

“…The methodology followed by the other ten papers [3], [11], [20], [29], [34], [37], [40], [44], [61], [62] was using available plug-ins and/ or functionalities in existing tools to solve the problem in their case study.…”

Section: E Methodologiesmentioning

confidence: 99%

“…Some papers identified data improvements [28]- [30], [36]- [38], [48], [57], [64] in terms of improving data quality, dimensionality, and complexity. A larger number of important technical improvements were identified in 20 papers [3], [21]- [23], [29]- [31], [35], [39]- [41], [44], [48]- [52], [58], [60], [64]. These were to:…”

Section: F Limitations and Future Workmentioning

confidence: 99%

“…Data limitations were identified in ten papers [20], [22], [33], [36], [37], [44], [48], [57], [60] and were mostly related to limited access to the data, data quality problems, attributes not available in the data being extracted, or the dataset available in inappropriate level of details. Technique limitations were identified in 13 papers [3], [21], [28], [31], [35], [38]- [40], [48], [50], [52], [63], [64] specifically if the study undertaken was done by implementing plug-ins/ functionalities available in tools.…”

Section: F Limitations and Future Workmentioning

confidence: 99%

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Process mining in oncology: A literature review

Kurniati

Johnson

Hogg³

et al. 2016

2016 6th International Conference on Information Communication and Management (ICICM)

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Abstract-Process mining, an emerging data analytics method, has been used effectively in various healthcare contexts including oncology, the study of cancer. Cancer is a complex disease with many complicated care requirements and there is an urgent need to improve the cost and clinical effectiveness of cancer care pathways. Process mining of the e-health records of cancer patients may play an important future role and this paper presents a literature review of process mining in oncology as a contribution to this research. The search produced 758 articles which were manually reviewed by title, abstract, and full paper text review to develop the original pool of papers. An in-depth ancestor search was used to gather additional articles from the references of the original pool. These steps resulted in 37 papers. Through a thematic review process, the papers were analysed and five themes emerged. These were: 1) process and data types; 2) research questions; 3) techniques, perspectives and tools; 4) methodologies; 5) limitations and future work. This review can: (i) highlight the potential value of process mining for improving cancer care processes (ii) provide a useful overview of the current work undertaken; (iii) help researchers to choose process mining algorithms, techniques, tools, methodologies and approaches; and (iv) identify research opportunities in this new field of study.

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Section: Resultsmentioning

confidence: 99%

Section: E Methodologiesmentioning

confidence: 99%

Section: F Limitations and Future Workmentioning

confidence: 99%

Section: F Limitations and Future Workmentioning

confidence: 99%

See 2 more Smart Citations

Process mining in oncology: A literature review

Kurniati

Johnson

Hogg³

et al. 2016

2016 6th International Conference on Information Communication and Management (ICICM)

View full text Add to dashboard Cite

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“…Authors indeed recommend the automated creation of a number of related characteristics to be evaluated as affecting factors. Finally, in [16] case data analysis is performed by testing for the existence of particular correlations.…”

Section: Related Workmentioning

confidence: 99%

Discovering Characteristics that Affect Process Control Flow

Delias

Grigori

Mouhoub

et al. 2015

Decision Support Systems IV – Information and Knowledge Management in Decision Processes

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Abstract. In flexible environments like healthcare and customer service, business processes are executed with high variability. Often, this is because cases' characteristics vary. However, it is difficult to correlate process flow with characteristics because characteristics may refer to different perspectives, their number can be real big or even because deep domain knowledge may be required to state hypotheses. The goal of this paper is to propose an effective exploratory tool for discovering the characteristics that are causing the process variation. To this end, we propose a process mining approach. First, we apply a clustering approach based on Latent Class Analysis to identify subtypes of related cases based on the case-wise process characteristics. Then, a process model is discovered for each cluster and through a model similarity step, we are able to recommend the characteristics that mostly diversify the flow. Finally, to validate our methodology, we applied it to both simulated and real datasets.

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