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Conformance Verification of Clinical Guidelines in Presence of Computerized and Human-Enhanced Processes

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Foundations of Biomedical Knowledge Representation

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9521))

Abstract

Clinical Guidelines (CGs) capture medical evidence and describe standardized high quality health processes. Their adoption increases the quality of the service offered by health departments, with direct advantage for treated patients. However, their application in real cases is often tempered by a number of factors like the context, the specific case itself, administrative processes, and the involved personnel. In this chapter we analyse the issues related to the problem of representing CGs in a formal way, and to reason about the differences between what is prescribed by CGs, and what is observed during their application/execution. Our approach is based on a general, abstract framework that should be flexible enough to cope with the raised issues. Possible technical solutions are also presented and their limits discussed.

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Notes

  1. 1.

    See http://www.openclinical.org/clinicalpathways.html.

  2. 2.

    http://www.openclinical.org/clinicalpathways.html.

  3. 3.

    NICE, http://www.nice.org.uk.

  4. 4.

    CG56: http://www.nice.org.uk/nicemedia/live/11836/36257/36257.pdf.

  5. 5.

    This is the typical approach followed in BPM, where the process is split into procedural and declarative fragments, or (macro)activities can be expanded by following a declarative or procedural approach (see for example the ad-hoc subprocess construct in BPMN).

  6. 6.

    http://www.jboss.org/drools/.

  7. 7.

    Notice that, even though the techniques in [15, 16] are presented as “a-posteriori” techniques, they could be considered as “a-priori” technique, because they work on the CG model, not on its real enactments.

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Acknowledgments

The approaches presented in this paper are the result of discussions and collaborations with many colleagues. In particular, we would like to thank Davide Sottara, Emory Fry, Paolo Terenziani, Alessio Bottrighi, and Stefania Montani. spara This work has been partially supported by the Health Sciences and Technologies - Interdepartmental Center for Industrial Research (HST-ICIR) - University of Bologna, by the DEIS Depict Project, and by the EU FP7 IP project Optique (Scalable End-user Access to Big Data), grant agreement n. FP7-318338.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Bologna, Bologna, Italy

    Stefano Bragaglia, Federico Chesani & Paola Mello

  2. KRDB Research Centre, Free University of Bozen-Bolzano, Bolzano, Italy

    Marco Montali

Authors
  1. Stefano Bragaglia
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  2. Federico Chesani
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  3. Paola Mello
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  4. Marco Montali
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Corresponding author

Correspondence to Federico Chesani .

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Editors and Affiliations

  1. Inst. for Computing and Inf. Sciences, Radboud University, Nijmegen, The Netherlands

    Arjen Hommersom

  2. Inst. for Computing and Inf. Sciences, Radboud University, Nijmegen, Gelderland, The Netherlands

    Peter J.F. Lucas

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Bragaglia, S., Chesani, F., Mello, P., Montali, M. (2015). Conformance Verification of Clinical Guidelines in Presence of Computerized and Human-Enhanced Processes. In: Hommersom, A., Lucas, P. (eds) Foundations of Biomedical Knowledge Representation. Lecture Notes in Computer Science(), vol 9521. Springer, Cham. https://doi.org/10.1007/978-3-319-28007-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-28007-3_6

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