Abstract
In the last years, both clinical evidence and expert consensus have been codified in the form of clinical practice guidelines in order to promote an actual empowerment in the overall quality of care. Even if different solutions have been realized to specify temporal constraints in computerized guidelines, none of them proposes a formal language as the basis of guideline formalism in order to easily and directly support the temporal perspective. In such a direction, this paper proposes a formal approach, which has been seamlessly embedded into a standards-based verifiable guideline model, named GLM-CDS (GuideLine Model for Clinical Decision Support). Such an approach hybridizes the theoretic semantics of ontology and rule languages to specify a variety of temporal constraints according to some time patterns, i.e., task duration, periodicity, deadline, scheduling and time lags. These constraints are then encoded in the form of rules verifiable at run-time during the guideline enactment, in order to support the detection of violations or errors occurred with respect to the temporal perspective. As an example of application of the proposed approach, some temporal constraints have been integrated in GLM-CDS and verified by using a reasoning engine, according to the time patterns identified.
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Anselma, L., Terenziani, P., Montani, S., Bottrighi, A.: Towards a comprehensive treatment of repetitions, periodicity and temporal constraints in clinical guidelines. Artif. Intell. Med. 38(2), 171–195 (2006)
Boxwala, A.A., Peleg, M., Tu, S., Ogunyemi, O., Zeng, Q.T., Wang, D., Patel, V.L., Greenes, R.A., Shortliffe, E.H.: GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines. J. Biomed. Inform. 37(3), 147–161 (2004)
Duftschmid, G., Miksch, S., Gall, W.: Verification of temporal scheduling constraints in clinical practice guidelines. Artif. Intell. Med. 25(2), 93–121 (2002)
Field, M.J., Lohr, K.N.: Guidelines for Clinical Practice: From Development to Use. Institute of Medicine, National Academy Press, Washington, DC (1992)
Fox, J., Johns, N., Rahmanzadeh, A.: Disseminating medical knowledge: the PROforma approach. Artif. Intell. Med. 14, 157–181 (1998)
Iannaccone, M., Esposito, M., De Pietro, G.: A standards-based verifiable guideline model for decision support in clinical applications. In: Process Support and Knowledge Representation in Health Care 8268, pp.143–157 (2013)
Iannaccone, M., Esposito, M.: Formal encoding and verification of temporal constraints in clinical practice guidelines. In: The 8th International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2013), pp. 211–222. Progress & Business Publishers, Krakow (2013)
Isern, D., Moreno, A.: Computer-based execution of clinical guidelines: a review. Int. J. Med. Inform. 77, 787–808 (2008)
Kautz H.A., Ladkin P.B.: Integrating metric and qualitative temporal reasoning. In: Proceedings 9th NationalConference on Artificial Intelligence (AAAI’91). AT&T Bell Laboratories, Murray Hill, NJ, USA. AAAI Press, MenloPark (CA, USA) (1991)
Lanz, A., Weber, B., Reichert, M.: Time patterns for process-aware information systems. Requir. Eng. 1–29 (2012)
Meiri, I.: Combining qualitative and quantitative constraints in temporal reasoning. Artif. Intell. 87, 343–385 (1996)
Minutolo, A., Esposito, M., De Pietro, G.: A Mobile reasoning system for supporting the monitoring of chronic diseases. In: Wireless Mobile Communication and Healthcare, pp. 225–232 (2012)
Scott, I.: What are the most effective strategies for improving quality and safety of health care? Int. Med. J. 39(6), 389–400 (2009)
Seyfang, A., Miksch, S., Marcos, M.: Combining diagnosis and treatment using Asbru. Int. J. Med. Inf. 68(1–3), 49–57 (2002)
Shortliffe, E., Cimino, J.: Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics), Springer, New York, Inc., Secaucus, NJ (2006)
Terenziani P.: Reasoning about time. In: Encyclopedia of Cognitive Science, pp. 869–874. Macmillan Reference Ltd. (2003)
Tu, S.W., Campbell, J.R., Glasgow, J., Nyman, M.A., McClure, R., McClay, J., Parker, C., Hrabak, K.M., Berg, D., Weida, T., Mansfield, J.G., Musen, M.A., Abarbanel, R.M.: The SAGE guideline model: achievements and overview. J. Am. Med. Inform. Assoc. 14, 589–598 (2007)
Tu, S.W., Musen, M.A.: Modeling data and knowledge in the EON guideline architecture. Stud. Health. Technol. Inform. 84(Pt. 1), 280–284 (2001)
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Iannaccone, M., Esposito, M. (2016). Formal Specification of Temporal Constraints in Clinical Practice Guidelines. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_28
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DOI: https://doi.org/10.1007/978-3-319-19090-7_28
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