Skip to main content

Can Existing Biomedical Ontologies Be More Useful for EHR and CDS?

  • Conference paper
  • First Online:
Knowledge Representation for Health Care (ProHealth 2016, KR4HC 2016)

Abstract

The interoperability of Electronic Health Records (EHR) and Clinical Decision Support (CDS) systems is a major challenge in the medical informatics field. International initiatives propose the use of ontologies for bridging both types of systems. The next-generation of EHR and CDS systems are supposed to use ontologies, or at least ontologies should be fundamental for enabling their interoperability. This situation makes necessary to analyze if current ontologies are ready for playing such intended role. In this paper we describe and discuss some important issues that need to be solved in order to have optimal ontologies for such a purpose, such as the need for increasing reuse in ontologies, as well as getting axiomatically richer ontologies. We also describe how our recent research results in the areas of ontology enrichment and ontology evaluation may contribute to such a goal.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://www.semantichealthnet.eu.

  2. 2.

    http://www.openehr.org.

  3. 3.

    http://www.iso.org/iso/catalogue_detail.htm?csnumber=40784.

  4. 4.

    http://www.hl7.org/implement/standards/product_brief.cfm?product_id=7.

  5. 5.

    http://informatics.mayo.edu/sharp/index.php/CEMS.

  6. 6.

    https://www.hl7.org/fhir/.

  7. 7.

    http://www.opencimi.org/.

  8. 8.

    http://www.ihtsdo.org/snomed-ct.

  9. 9.

    http://www.semantichealthnet.eu.

  10. 10.

    http://www.semantichealthnet.eu/index.cfm/deliverables.

  11. 11.

    http://www.obofoundry.org/ontology/bfo.html.

  12. 12.

    http://www.obofoundry.org/ontology/ro.html.

  13. 13.

    http://www.obofoundry.org/ontology/iao.html.

  14. 14.

    http://oppl2.sourceforge.net.

  15. 15.

    http://sele.inf.um.es/ontoenrich.

  16. 16.

    http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=35683.

  17. 17.

    http://sele.inf.um.es/oquare.

  18. 18.

    http://www.obofoundry.org/ontology/bfo.html.

  19. 19.

    http://purl.bioontology.org/ontology/BT.

References

  1. Health Level 7.: Arden Syntax for Medical Logic Systems Standard Version 2.6. Ann Arbor, MI: Health Level 7 (2007)

    Google Scholar 

  2. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., et al.: Gene ontology: tool for the unification of biology. Nature Genet. 25(1), 25–29 (2000)

    Article  Google Scholar 

  3. Beale, T.: Archetypes: constraint-based domain models for future-proof information systems. In: OOPSLA 2002 Workshop on Behavioural Semantics, vol. 105 (2002)

    Google Scholar 

  4. Berners-Lee, T., Hendler, J., Lassila, O., et al.: The semantic web. Sci. Am. 284(5), 28–37 (2001)

    Article  Google Scholar 

  5. Bouamrane, M.-M., Rector, A., Hurrell, M.: Using owl ontologies for adaptive patient information modelling and preoperative clinical decision support. Knowl. Inform. Syst. 29(2), 405–418 (2011)

    Article  Google Scholar 

  6. Breasted, J.H.: The Edwin Smith Surgical Papyrus: published in facsimile and hieroglyphic transliteration with translation and commentary in two volumes, vol. 3. Chic. UP (1930)

    Google Scholar 

  7. Chen, R., Corbal, I.: Guideline definition language (gdl). Release 0.9, pp. 1–23 (2013)

    Google Scholar 

  8. Duque-Ramos, A., Fernández-Breis, J.T., Stevens, R., Aussenac-Gilles, R.N., et al.: Oquare: a square-based approach for evaluating the quality of ontologies. J. Res. Pract. Inform. Technol. 43(2), 159 (2011)

    Google Scholar 

  9. Duque-Ramos, A., Quesada-Martínez, M., Iniesta-Moreno, M., Fernández-Breis, J.T., Stevens, R.: Supporting the analysis of ontology evolution processes through the combination of static and dynamic scaling functions in oquare. J. Biomed. Semant. 7(1), 63 (2016)

    Google Scholar 

  10. Farion, K., Michalowski, W., Wilk, S., O’Sullivan, D.M., Rubin, S., Weiss, D.: Clinical decision support system for point of care use: ontology driven design and software implementation. Meth. Inform. Med. 48(4), 381–390 (2009)

    Article  Google Scholar 

  11. Fox, J., Johns, N., Rahmanzadeh, A.: Disseminating medical knowledge: the proforma approach. Artif. Intell. Med. 14(1), 157–182 (1998)

    Article  Google Scholar 

  12. Goble, C., Stevens, R.: Stevens.: state of the nation in data integration for bioinformatics. J. Biomed. Inform. 41(5), 687–693 (2008)

    Article  Google Scholar 

  13. Hawkins, M., Ralley, R., Young, J.: A medical panorama: the casebooks project. Book 2.0 4(1–2), 61–69 (2014)

    Google Scholar 

  14. Ingram, D.: The good european health record. In: Laires, M.F., Ladeira, M.F., Christensen, J.P. (eds.) Health in the New Communication Age, pp. 66–74. IOS (1995)

    Google Scholar 

  15. Isern, D., Moreno, A.: Computer-based execution of clinical guidelines: a review. Int. J. Med. Inform. 77(12), 787–808 (2008)

    Article  Google Scholar 

  16. Isern, D., Sánchez, D., Moreno, A.: Ontology-driven execution of clinical guidelines. Comput. Meth. Programs Biomed. 107(2), 122–139 (2012)

    Article  Google Scholar 

  17. Kalra, D., Lewalle, P., Rector, A., Rodrigues, J.M., Stroetmann, K.A., Surjan, G., Ustun, B., Virtanen, M., Zanstra, P.E.: Semantic interoperability for better health and safer healthcare. Research and Deployment Roadmap for Europe. SemanticHEALTH Project Report, Published by the European Commission (2009). http://ec.europa.eu/information_society/ehealth

  18. Martínez-Costa, C., Menárguez-Tortosa, M., Fernández-Breis, J.T., Maldonado, J.A.: A model-driven approach for representing clinical archetypes for semantic web environments. J. Biomed. Inform. 42(1), 150–164 (2009)

    Article  Google Scholar 

  19. Menárguez-Tortosa, M., Fernández-Breis, J.T.: Owl-based reasoning methods for validating archetypes. J. Biomed. Inform. 46(2), 304–317 (2013)

    Article  Google Scholar 

  20. Montero, M.A., Prado, S.: Electronic health record as a knowledge management tool in the scope of health. In: Riaño, D. (ed.) K4HelP 2008. LNCS (LNAI), vol. 5626, pp. 152–166. Springer, Heidelberg (2009). doi:10.1007/978-3-642-03262-2_12

    Chapter  Google Scholar 

  21. Mosa, A.S.M., Yoo, I., Sheets, L.: A systematic review of healthcare applications for smartphones. BMC Med. Inform. Decis. Making 12(1), 1 (2012)

    Article  Google Scholar 

  22. Musen, M.A., Middleton, B., Greenes, R.A.: Clinical decision-support systems. In: Shortliffe, E.H., Cimino, J.J. (eds.) Biomedical Informatics, pp. 643–674. Springer, New York (2014)

    Google Scholar 

  23. Ohno-Machado, L., Gennari, J.H., Murphy, S.N., Jain, N.L., Tu, S.W., Oliver, D.E., Pattison-Gordon, E., Greenes, R.A., Shortliffe, E.H., Barnett, G.O.: The guideline interchange format. J. Am. Med. Inform. Assoc. 5(4), 357–372 (1998)

    Google Scholar 

  24. Peleg, M.: Computer-interpretable clinical guidelines: a methodological review. J. Biomed. inform. 46(4), 744–763 (2013)

    Article  Google Scholar 

  25. Quesada-Martínez, M., Fernández-Breis, J.T., Karlsson, D.: Suggesting missing relations in biomedical ontologies based on lexical regularities. Stud. Health Technol. Inform. 228, 384 (2016)

    Google Scholar 

  26. Quesada-Martínez, M., Fernández-Breis, J.T., Stevens, R.: Lexical characterization and analysis of the BioPortal ontologies. In: Peek, N., Marín Morales, R., Peleg, M. (eds.) AIME 2013. LNCS (LNAI), vol. 7885, pp. 206–215. Springer, Heidelberg (2013). doi:10.1007/978-3-642-38326-7_31

    Chapter  Google Scholar 

  27. Quesada-Martínez, M., Fernández-Breis, J.T., Stevens, R.: Lexical characterisation of bio-ontologies by the inspection of regularities in labels. Curr. Bioinform. 10(2), 165–176 (2015)

    Article  Google Scholar 

  28. Rector, A., Iannone, L.: Lexically suggest, logically define: quality assurance of the use of qualifiers and expected results of post-coordination in snomed ct. J. Biomed. Inform. 45(2), 199–209 (2012)

    Article  Google Scholar 

  29. Rector, A.L., Johnson, P.D., Tu, S., Wroe, C., Rogers, J.: Interface of inference models with concept and medical record models. In: Quaglini, S., Barahona, P., Andreassen, S. (eds.) AIME 2001. LNCS (LNAI), vol. 2101, pp. 314–323. Springer, Heidelberg (2001). doi:10.1007/3-540-48229-6_43

    Chapter  Google Scholar 

  30. Schober, D., Tudose, I., Svatek, V., Boeker, M.: Ontocheck: verifying ontology naming conventions and metadata completeness in protégé 4. J. Biomed. Semant. 3(2), 1 (2012)

    Google Scholar 

  31. Shahar, Y., Young, O., Shalom, E., Galperin, M., Mayaffit, A., Moskovitch, R., Hessing, A.: A framework for a distributed, hybrid, multiple-ontology clinical-guideline library, and automated guideline-support tools. J. Biomed. Inform. 37(5), 325–344 (2004)

    Article  Google Scholar 

  32. Sherman, R.: Computer system clears up errors, lets nurses get back to nursing: a progress report from children’s hospital, Akron, Ohio. Hosp. Top. 43(10), 44–46 (1965)

    Article  Google Scholar 

  33. Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., Goldberg, L.J., Eilbeck, K., Ireland, A., Mungall, C.J., et al.: The obo foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnol. 25(11), 1251–1255 (2007)

    Article  Google Scholar 

  34. Tao, C., Jiang, G., Oniki, T.A., Freimuth, R.R., Zhu, Q., Sharma, D., Pathak, J., Huff, S.M., Chute, C.G.: A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data. J. Am. Med. Inform. Assoc. 20(3), 554–562 (2013)

    Article  Google Scholar 

  35. Third, A.: Hidden semantics: what can we learn from the names in an ontology? In: Proceedings of the Seventh International Natural Language Generation Conference, pp. 67–75. Association for Computational Linguistics (2012)

    Google Scholar 

  36. Tu, S.W., Eriksson, H., Gennari, J.H., Shahar, Y., Musen, M.A.: Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of protege-ii to protocol-based decision support. Artif. Intell. Med. 7(3), 257–289 (1995)

    Article  Google Scholar 

  37. Warner, H.R., Toronto, A.F., Veasey, L.G., Stephenson, R.: A mathematical approach to medical diagnosis: application to congenital heart disease. Jama 177(3), 177–183 (1961)

    Article  Google Scholar 

  38. Wilk, S., Michalowski, W., Michalowski, M., Farion, K., Hing, M.M., Mohapatra, S.: Mitigation of adverse interactions in pairs of clinical practice guidelines using constraint logic programming. J. Biomed. Inform. 46(2), 341–353 (2013)

    Article  Google Scholar 

  39. Wright, A., Sittig, D.F.: A four-phase model of the evolution of clinical decision support architectures. Int. J. Med. Inform. 77(10), 641–649 (2008)

    Article  Google Scholar 

  40. Yao, W., Kumar, A.: Conflexflow: Integrating flexible clinical pathways into clinical decision support systems using context and rules. Decis. Support Syst. 55(2), 499–515 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

This work has been partially funded by to the Spanish Ministry of Economy and Competitiveness, the FEDER Programme and by the Fundación Séneca through grants TIN2014-53749-C2-2-R and 19371/PI/14.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jesualdo Tomás Fernández-Breis .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Fernández-Breis, J.T., Quesada-Martínez, M., Duque-Ramos, A. (2017). Can Existing Biomedical Ontologies Be More Useful for EHR and CDS?. In: Riaño, D., Lenz, R., Reichert, M. (eds) Knowledge Representation for Health Care. ProHealth KR4HC 2016 2016. Lecture Notes in Computer Science(), vol 10096. Springer, Cham. https://doi.org/10.1007/978-3-319-55014-5_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-55014-5_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55013-8

  • Online ISBN: 978-3-319-55014-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics