Ontological Modelling of a Psychiatric Clinical Practice Guideline

  • Daniel Gorín
  • Malte Meyn
  • Alexander Naumann
  • Miriam Polzer
  • Ulrich Rabenstein
  • Lutz SchröderEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10505)


Clinical practice guidelines (CPGs) serve to transfer results from evidence-based medicine into clinical practice. There is growing interest in clinical decision support systems (CDSS) implementing the guideline recommendations; research on such systems typically considers combinations of workflow languages with knowledge representation formalisms. Here, we report on experience with an OWL-based proof-of-concept implementation of parts of the German S3 guideline for schizophrenia. From the information-technological point of view, the salient feature of our implementation is that it represents the CPG entirely as a logic-based ontology, without resorting, e.g., to rule-based action formalisms or hard-wired workflows to capture clinical pathways. Our current goal is to establish that such an implementation is feasible; long-range benefits we expect from the approach are modularity of CPG implementation, ease of maintenance, and logical unity.


  1. 1.
    Abidi, S., Abidi, S., Hussain, S., Shepherd, M.: Ontology-based modeling of clinical practice guidelines: A clinical decision support system for breast cancer follow-up interventions at primary care settings. In: MEDINFO 2007, pp. 845–849. IOS Press (2007)Google Scholar
  2. 2.
    Abidi, S., Cox, J., Abidi, S., Shepherd, M.: Using OWL ontologies for clinical guidelines based comorbid decision support. In: Hawaii International International Conference on Systems Science, HICSS 2012, pp. 3030–3038. IEEE Comp. Soc. (2012)Google Scholar
  3. 3.
    Beierle, C., Eisele, L., Kern-Isberner, G., Meyer, R.G., Nietzke, M.: Using ontological knowledge about active pharmaceutical ingredients for a decision support system in medical cancer therapy. In: Friedrich, G., Helmert, M., Wotawa, F. (eds.) KI 2016. LNCS, vol. 9904, pp. 119–125. Springer, Cham (2016). doi: 10.1007/978-3-319-46073-4_9 CrossRefGoogle Scholar
  4. 4.
    Bouamrane, M.-M., Rector, A., Hurrell, M.: A hybrid architecture for a preoperative decision support system using a rule engine and a reasoner on a clinical ontology. In: Polleres, A., Swift, T. (eds.) RR 2009. LNCS, vol. 5837, pp. 242–253. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-05082-4_17 CrossRefGoogle Scholar
  5. 5.
    Deutsche Gesellschaft für Psychiatrie, Psychotherapie und Nervenheilkunde (ed.) Behandlungsleitlinie Schizophrenie. In: Gaebel, W., Falkai, P. (eds.) Steinkopff, Darmstadt (2006)Google Scholar
  6. 6.
    Doulaverakis, C., Koutkias, V., Antoniou, G., Kompatsiaris, I.: Applying SPARQL-based inference and ontologies for modelling and execution of clinical practice guidelines: a case study on hypertension management. In: Riaño, D., Lenz, R., Reichert, M. (eds.) KR4HC/ProHealth -2016. LNCS, vol. 10096, pp. 90–107. Springer, Cham (2017). doi: 10.1007/978-3-319-55014-5_6 CrossRefGoogle Scholar
  7. 7.
    Garg, A., Adhikari, N., McDonald, H., Rosas-Arellano, M., Devereaux, P., Beyene, J., Sam, J., Haynes, R.: Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 293, 1223–1238 (2005)CrossRefGoogle Scholar
  8. 8.
    Jafarpour, B., Abidi, S.R., Abidi, S.S.R.: Exploiting semantic web technologies to develop OWL-based clinical practice guideline execution engines. IEEE J. Biomed. Health Inform. 20, 388–398 (2016)CrossRefGoogle Scholar
  9. 9.
    Kashyap, V., Morales, A., Hongsermeier, T.: On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies. In: AMIA Annual Symposium, vol. 2006, pp. 414–418. AMIA (2006)Google Scholar
  10. 10.
    Martin, D., Burstein, M., McDermott, D., McIlraith, S., Paolucci, M., Sycara, K., McGuinness, D., Sirin, E., Srinivasan, N.: Bringing semantics to web services with OWL-S. World Wide Web, WWW 2007 10, 243–277 (2007)Google Scholar
  11. 11.
    Mehdi, A., Rudolph, S., Grimm, S.: Epistemic querying of OWL knowledge bases. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011. LNCS, vol. 6643, pp. 397–409. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-21034-1_27 CrossRefGoogle Scholar
  12. 12.
    Peleg, M.: Computer-interpretable clinical guidelines: a methodological review. J. Biomed. Inform. 46, 44–763 (2013)CrossRefGoogle Scholar
  13. 13.
    Peleg, M., Tu, S., Bury, J., Ciccarese, P., Fox, J., Greenes, R.A., Hall, R., Johnson, P., Jones, N., Kumar, A., Miksch, S., Quaglini, S., Seyfang, A., Shortliffe, E., Stefanelli, M.: Comparing computer-interpretable guideline models: a case-study approach. J. AMIA 10, 52–68 (2003)Google Scholar
  14. 14.
    Rector, A., Rogers, J., Zanstra, P., van der Haring, E.: OpenGALEN: Open source medical terminology and tools. In: AMIA Annual Symposium, p. 982. AMIA (2003)Google Scholar
  15. 15.
    Schulz, S., Stenzhorn, H., Boeker, M., Smith, B.: Strengths and limitations of formal ontologies in the biomedical domain. Rev. Electron. Comun. Inf. Inov. Saude 3, 31–45 (2009)Google Scholar
  16. 16.
    Sesen, M., Banares-Alcántara, R., Fox, J., Kadir, T., Brady, J.: Lung Cancer Assistant: an ontology-driven, online decision support prototype for lung cancer treatment selection. In: OWL: Experiences and Directions Workshop, OWLED 2012 (2012)Google Scholar
  17. 17.
    Sirin, E., Parsia, B.: SPARQL-DL: SPARQL query for OWL-DL. In: OWL: Experiences and Directions, OWLED 2007. CEUR Workshop Proceedings, vol. 258 (2007)Google Scholar
  18. 18.
    Tao, C., Wei, W., Solbrig, H., Savova, G., Chute, C.: CNTRO: A semantic web ontology for temporal relation inferencing in clinical narratives. In: Annual Sympposium on AMIA, pp. 787–791 (2010)Google Scholar
  19. 19.
    Trivedi, M., Kern, J., Grannemann, B., Altshuler, K., Sunderajan, P.: A computerized clinical decision support system as a means of implementing depression guidelines. Psych. Serv. 55, 879–885 (2004)CrossRefGoogle Scholar
  20. 20.
    Ye, Y., Jiang, Z., Diao, X., Yang, D., Du, G.: An ontology-based hierarchical semantic modeling approach to clinical pathway workflows. Comp. Bio. Med. 39, 722–732 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Daniel Gorín
    • 1
  • Malte Meyn
    • 1
  • Alexander Naumann
    • 2
  • Miriam Polzer
    • 1
  • Ulrich Rabenstein
    • 1
  • Lutz Schröder
    • 1
    Email author
  1. 1.Friedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany
  2. 2.Psychiatrische Klinik LüneburgLüneburgGermany

Personalised recommendations