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Declarative Guideline Conformance Checking of Clinical Treatments: A Case Study

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Business Process Management Workshops (BPM 2022)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 460))

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Abstract

Conformance checking is a process mining technique that allows verifying the conformance of process instances to a given model. Thus, this technique is predestined to be used in the medical context for the comparison of treatment cases with clinical guidelines. However, medical processes are highly variable, highly dynamic, and complex. This makes the use of imperative conformance checking approaches in the medical domain difficult. Studies show that declarative approaches can better address these characteristics. However, none of the approaches has yet gained practical acceptance. Another challenge are alignments, which usually do not add any value from a medical point of view. For this reason, we investigate in a case study the usability of the HL7 standard Arden Syntax for declarative, rule-based conformance checking and the use of manually modeled alignments. Using the approach, it was possible to check the conformance of treatment cases and create medically meaningful alignments for large parts of a medical guideline.

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Notes

  1. 1.

    https://www.awmf.org.

  2. 2.

    https://www.gekid.de/adt-gekid-basisdatensatz.

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Acknowledgments

The research is partially funded by the German Federal Ministry of Education and Research (BMBF) in the project DaTreFo under the funding code 16KIS1644.

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Correspondence to Joscha Grüger , Tobias Geyer , Stephan A. Braun or Ralph Bergmann .

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Grüger, J., Geyer, T., Kuhn, M., Braun, S.A., Bergmann, R. (2023). Declarative Guideline Conformance Checking of Clinical Treatments: A Case Study. In: Cabanillas, C., Garmann-Johnsen, N.F., Koschmider, A. (eds) Business Process Management Workshops. BPM 2022. Lecture Notes in Business Information Processing, vol 460. Springer, Cham. https://doi.org/10.1007/978-3-031-25383-6_20

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  • DOI: https://doi.org/10.1007/978-3-031-25383-6_20

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  • Online ISBN: 978-3-031-25383-6

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