Journal of Medical Systems

, Volume 36, Issue 4, pp 2203–2212 | Cite as

Ontology-Based Clinical Pathways with Semantic Rules

  • Zhen Hu
  • Jing-Song LiEmail author
  • Tian-Shu Zhou
  • Hai-Yan Yu
  • Muneou Suzuki
  • Kenji Araki


Clinical Pathways (CP) enhance the quality of patient care, and are thus important in health management. However, there is a need to address the challenge of adaptation of treatment procedures in CP—that is, the treatment schemes must be re-modified once the clinical status and other care conditions of patients in the healthcare setting change, which happen frequently. In addition, the widespread and frequent use of Electronic Medical Records (EMR) implies an increasing need to combine CP with other healthcare information systems, especially EMR, in order to greatly improve healthcare quality and efficiency. This study proposed an ontology-based method to model CP: ontology was used to model CP domain terms; Semantic Web Rule language was used to model domain rules. In this way, the CP could reason over the rules, knowledge, and information collected, and provides automated error checking for the next steps of the treatment in runtime, which is adaptive to treatment procedures. To evaluate our method, we built a Lobectomia Pulmonalis CP and realized it based on an EMR system.


Clinical pathways Ontology Semantic rules EMR 



This research is supported by the Fundamental Research Funds for the Central Universities and by National High-tech R&D Program (No. 2009AA045300).


  1. 1.
    Rotter, T., Kinsman, L., James, E. L., Machotta, A., Gothe, H., Willis, J., Snow, P., and Kugler, J., Clinical pathways: Effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane Database Syst. Rev. 2010, Issue 3. Art. No.: CD006632. doi: 10.1002/14651858.CD006632.pub2.
  2. 2.
    Cheal, J., Development and implementation of a clinical pathway programme in an acute care general hospital in Singapore. Int. J. Qual. Health Care 12:403–412, 2000.CrossRefGoogle Scholar
  3. 3.
    Loeb, M., Carusone, S., Goeree, R., Walter, S., Brazil, K., Krueger, P., Simor, A., Moss, L., and Marrie, T., Effect of a clinical pathway to reduce hospitalizations in nursing home residents with Pneumonia. J. Am. Assoc. 295(21):2503–2510, 2006.CrossRefGoogle Scholar
  4. 4.
    Madan, A. K., Speck, K. E., Ternovits, C. A., and Tichansky, D. S., Outcome of a clinical pathway for discharge within 48 hours after laparoscopic gastric bypass. Am. J. Surg. 192(3):399–402, 2006.CrossRefGoogle Scholar
  5. 5.
    Hauck, L. D., Adler, L. M., and Mulla, Z. D., Clinical pathways care improves outcomes among patients hospitalized for community-acquired pneumonis. Ann. Epidemiol. 14:669–675, 2000.CrossRefGoogle Scholar
  6. 6.
    Alexandrou, D., Xenikoudakis, F., and Mentzas, G., SEMPATH: Semantic adaptive and personalized clinical pathways. Int. Conf. eHealth Telemed. Soc. Med.:36–41, 2009.Google Scholar
  7. 7.
    Abidi, S., and Chen, H., Adaptable personalized care planning via a semantic web framework. 20th International congress of the European federation of medical informatics. Ios Press, Maastricht, 2006.Google Scholar
  8. 8.
    Okada, O., Ohboshi, N., Kuroda, T., Nagase, K., and Yoshihara, H., Electronic clinical path system based on semistructured data model using personal digital assistant for onsite Access. J. Med. Syst. 29(4):379–389, 2005.CrossRefGoogle Scholar
  9. 9.
    Okada, O., Ohboshi, N., Kuroda, T., Nagase, K., and Yoshihara, H., Clinical pathways modeling in XML for a web-based benchmark test system for medicine. J. Med. Syst. 29(5):539–553, 2005.CrossRefGoogle Scholar
  10. 10.
    Ye, Y., Jiang, Z., Diao, X., Yang, D., and Gu, G., An ontology-based hierarchical semantic modeling approach to clinical pathway workflows. Comput. Biol. Med. 39:722–732, 2009.CrossRefGoogle Scholar
  11. 11.
    Li, J., Zhang, X., Chu, J., Suzuki, M., and Araki, K., Design and development of EMR supporting medical process management. J. Med. Syst., 2010. AcceptedGoogle Scholar
  12. 12.
    Chu, S., and Cesnik, B., Improving clinical pathway design: Lessons learned from a computerized prototype. Int. J. Med. Inform. 51:1–11, 1998.CrossRefGoogle Scholar
  13. 13.
    Lee, C. S., and Wang, M. H., Ontology-based intelligent healthcare agent and its application to respiratory waveform recognition. Expert Syst. Appl. 33:606–619, 2007.CrossRefGoogle Scholar
  14. 14.
    O’Connor, M. J., Shankar, R. D., Parrish, D. B., and Das, A. K., Knowledge-data integration for temporal reasoning in a clinical trial system. Int. J. Med. Inform., Volume 78, Supplement 1, MedInfo 2007, April 2009, Pages S77–S85, ISSN 1386–5056. doi:10.1016/j.ijmedinf.2008.07.013.
  15. 15.
    Argüello, M., and Des, J., Clinical practice guidelines: A case study of combining OWL-S, OWL, and SWRL. Appl. Innov. Intell. Syst. XV 2:19–32, 2008. doi: 10.1007/978-1-84800-086-5_2.CrossRefGoogle Scholar
  16. 16.
    Chi, Y., Rule-based ontological knowledge base for monitoring partners across supply networks. Expert Syst. Appl. 37:1400–1407, 2010.CrossRefGoogle Scholar
  17. 17.
    OWL Web Ontology Language Reference, Last date visited: 2010-1-10.
  18. 18.
    SWRL Semantic Web Rule Language, Last date visited: 2010-1-10.
  19. 19.
    Uschold, M., and Jasper, R., A framework for understanding and classifying ontology application. Procedings of the IJCAI-99 workshop in Ontologies and problem-solving methods. Sweden, 1999.Google Scholar
  20. 20.
    Atkinson-Abutridy, J. A., A domain-independent approach to discourse-level knowledge discovery from texts. Lect. Notes Comput. Sci. 3533:470–479, 2005.CrossRefGoogle Scholar
  21. 21.
    Abidi, S. R., A concept framework for ontology based automating and merging of clinical pathways of comorbidities. Knowledge management for health care procedures. Lect. Notes Comput. Sci. 5626(2009):55–66, 2009. doi: 10.1007/978-3-642-03262-2_5.CrossRefGoogle Scholar
  22. 22.
    Uschold, M., and Gruninger, M., Ontologies: Principles, methods and applications. Knowl. Eng. Rev. 11:93–155, 1996.CrossRefGoogle Scholar
  23. 23.
    National Referral Guidelines, Last date visited: 2011-01-10.
  24. 24.
    O’Connor, M. J., Tu, S. W., Nyulas, C. I., Das, A. K., and Musen, M. A., Querying the semantic web with SWRL. Advances in rule interchange and applications. Lect. Notes Comput. Sci. 4824(2007):155–159, 2007. doi: 10.1007/978-3-540-75975-1_13.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Zhen Hu
    • 1
  • Jing-Song Li
    • 1
    Email author
  • Tian-Shu Zhou
    • 1
  • Hai-Yan Yu
    • 1
  • Muneou Suzuki
    • 2
  • Kenji Araki
    • 2
  1. 1.Healthcare Informatics Engineering Research CenterZhejiang UniversityHangzhouChina
  2. 2.Department of Medical InformaticsMiyazaki University HospitalMiyazakiJapan

Personalised recommendations