Comparing Process Models for Patient Populations: Application in Breast Cancer Care
| Autor: | Marazza, Francesca, Bukhsh, Faiza Allah, Vijlbrief, Onno, Geerdink, Jeroen, Pathak, Shreyasi, van Keulen, Maurice, Seifert, Christin, Di Francescomarino, Chiara, Dijkman, Remco, Zdun, Uwe |
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| Přispěvatelé: | Datamanagement & Biometrics |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
050101 languages & linguistics
Process modeling Computer science Process (engineering) media_common.quotation_subject Medizin Process mining 02 engineering and technology Machine learning computer.software_genre Conformance checking Business process discovery Similarity (psychology) 0202 electrical engineering electronic engineering information engineering 0501 psychology and cognitive sciences Quality (business) media_common business.industry 22/3 OA procedure 05 social sciences Quality control Directed graph Informatik Breast cancer care 020201 artificial intelligence & image processing Process comparison Artificial intelligence business computer |
| Zdroj: | Business Process Management Workshops-BPM 2019 International Workshops, Revised Selected Papers, 496-507 STARTPAGE=496;ENDPAGE=507;TITLE=Business Process Management Workshops-BPM 2019 International Workshops, Revised Selected Papers International Workshop Process-Oriented Data Science for Healthcare 2019 Business Process Management Workshops ISBN: 9783030374525 Business Process Management Workshops |
| Popis: | Processes in organisations such as hospitals, may deviate from intended standard processes, due to unforeseeable events and the complexity of the organisation. For hospitals, the knowledge of actual patient streams for patient populations (e.g., severe or non-severe cases) is important for quality control and improvement. Process discovery from event data in electronic health records can shed light on the patient flows, but their comparison for different populations is cumbersome and time-consuming. In this paper, we present an approach for the automatic comparison of process models extracted from events in electronic health records. Concretely, we propose to compare processes for different patient populations by cross-log conformance checking, and standard graph similarity measures obtained from the directed graph underlying the process model. Results from a case study on breast cancer care show that average fitness and precision of cross-log conformance checks provide good indications of process similarity and therefore can guide the direction of further investigation for process improvement. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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