Health Informatics: The Relevance of Open Source and Multilevel Modeling

  • Luciana T. Cavalini
  • Timothy W. Cook
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 365)


Health information features significant spatial-temporal and domain complexities, which brings challenges to the implementation of patient-centered, interoperable and semantically coherent healthcare information systems. This position paper supports the idea that the multilevel modeling approach is essential to ensure interoperability at the semantic level, but true interoperability is only achieved by the adoption of open standards, and open source implementations are needed for promote competition based on software quality. The Multilevel Healthcare Information Modelling (MLHIM) specifications are presented as the fully open source multilevel modeling reference implementation, and best practices for the development of multilevel-based open source healthcare applications are suggested.


Health informatics open source software multilevel modeling 


  1. 1.
    Almeida, F., Oliveira, J., Cruz, J.: Open standards and open source: enabling interoperability. Int. J. Soft. Eng. App. 2(1) (2011), doi:10.5121/ijsea.2011.2101Google Scholar
  2. 2.
    Ammenwerth, E., Shaw, N.: Bad informatics can kill: is evaluation the answer? Methods Inf. Med. 44(1), 1–3 (2005)Google Scholar
  3. 3.
    Barretto, S.A., Warren, J., Goodchild, A., Bird, L., Heard, S., Stumptner, M.: Linking guidelines to Electronic Health Record design for improved chronic disease management. In: AMIA Annu. Symp. Proc., pp. 66–70 (2003)Google Scholar
  4. 4.
    Beale, T., Heard, S.: openEHR Architecture overview. openEHR Foundation, London (2008)Google Scholar
  5. 5.
    Blobel, B.: Comparing concepts for electronic health record architectures. Stud. Health Technol. Inform. 90, 209–214 (2002)Google Scholar
  6. 6.
    Cantiello, J., Cortelyou-Ward, K.H.: The American Recovery and Reinvestment Act: lessons learned from physicians who have gone electronic. Health Care Manag (Frederick) 29(4), 332–338 (2010)Google Scholar
  7. 7.
    Chen, R., Klein, G.: The openEHR Java reference implementation project. Stud. Health Technol. Inform. 129(Pt 1), 58–62 (2007)Google Scholar
  8. 8.
    D’Antoni, A.V., Zipp, G.P., Olson, V.G., Cahill, T.F.: Does the mind map learning strategy facilitate information retrieval and critical thinking in medical students? BMC Med. Educ. 10, 61 (2010)CrossRefGoogle Scholar
  9. 9.
    Dutton, W.: Key enablers for eTransformation? eID, interoperability and open source. Eur. J. ePractice 6, 2 (2009)MathSciNetGoogle Scholar
  10. 10.
    Eccles, M., Mason, J.: How to develop cost-conscious guidelines. Health Technol. Assess. 5(16), 1–69 (2001)Google Scholar
  11. 11.
    Gao, S., Mioc, D., Yi, X., Anton, F., Oldfield, E., Coleman, D.J.: Towards web-based representation and processing of health information. Int. J. Health Geographics 8, 3 (2009)CrossRefGoogle Scholar
  12. 12.
    Garde, S., Chen, R., Leslie, H., Beale, T., McNicoll, I., Heard, S.: Archetype-based knowledge management for semantic interoperability of electronic health records. Stud. Health Technol. Inform. 150, 1007–1011 (2009)Google Scholar
  13. 13.
    Garde, S., Knaup, P., Hovenga, E., Heard, S.: Towards semantic interoperability for electronic health records. Methods Inf. Med. 46(3), 332–343 (2007)Google Scholar
  14. 14.
    Hägglund, M., Scandurra, I., Moström, D., Koch, S.: Bridging the gap: a virtual health record for integrated home care. Int. J. Integr. Care 7, 26 (2007)Google Scholar
  15. 15.
    Hammond, W.E., Bailey, C., Boucher, P., Spohr, M., Whitaker, P.: Connecting information to improve health. Health Aff. (Millwood) 29(2), 284–288 (2010)CrossRefGoogle Scholar
  16. 16.
    Haughton, J.: Look up: the right EHR may be in the cloud. Major advantages include interoperability and flexibility. Health Manag. Technol. 32(2), 52 (2011)Google Scholar
  17. 17.
    Haux, R.: Medical informatics: past, present, future. Int. J. Med. Inform. 79(9), 599–610 (2010)CrossRefGoogle Scholar
  18. 18.
    Hudson, D.L.: Cohen ME. Uncertainty and complexity in personal health records. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., pp. 6773–6776 (2010)Google Scholar
  19. 19.
    Hulse, N.C., Rocha, R.A., Del Fiol, G., Bradshaw, R.D., Hanna, T.P., Roemer, L.K.: KAT: A flexible XML-based knowledge authoring environment. J. Am. Med. Inform. Assoc. 12, 418–430 (2005)CrossRefGoogle Scholar
  20. 20.
    Kalra, D., Beale, T., Heard, S.: The openEHR Foundation. Stud. Health Technol. Inform. 115, 153–173 (2005)Google Scholar
  21. 21.
    Kashfi, H.: An openEHR-based clinical decision support system: a case study. Stud. Health Technol. Inform. 150, 348 (2009)Google Scholar
  22. 22.
    Kelley, J.: The interoperability hang-up. When it comes to information exchange, how should precede what. Health Manag. Technol. 32(2), 32–34 (2011)Google Scholar
  23. 23.
    Kohl, C.D., Garde, S., Knaup, P.: Facilitating secondary use of medical data by using openEHR archetypes. Stud. Health Technol. Inform. 160(Pt 2), 1117–1121 (2010)Google Scholar
  24. 24.
    Maldonado, J.A., Moner, D., Bosca, D., Fernandez-Breis, J.T., Angulo, C., Robles, M.: LinkEHR-Ed: a multi-reference model archetype editor based on formal semantics. Int. J. Med. Inform. 78(8), 559–570 (2008)CrossRefGoogle Scholar
  25. 25.
    Martinez-Costa, C., Menarguez-Tortosa, M., Fernandez-Breis, J.T.: An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes. J. Biomed. Inform. 43(5), 736–746 (2010)CrossRefGoogle Scholar
  26. 26.
    Michelsen, L., Pedersen, S.S., Tilma, H.B., Andersen, S.K.: Comparing different approaches to two-level modelling of electronic health records. Stud. Health Technol. Inform. 116, 113–118 (2005)Google Scholar
  27. 27.
    Neeser, A.E.: XML: The open source solution to interoperability. Open Lib. Class J. 1(2) (2009), (accessed on March 6, 2011)
  28. 28.
    Norlin, C., Kerr, L.M., Rocha, R.A.: Using clinical questions to structure the content of a web-based information resource for primary care physicians. In: AMIA Symp. Proc., pp. 482–486 (2009)Google Scholar
  29. 29.
    Paterson, T., Law, A.: An XML transfer schema for exchange of genomic and genetic mapping data: implementation as a web service in a Taverna workflow. BMC Bioinformatics 10, 252 (2009)CrossRefGoogle Scholar
  30. 30.
    Qian, Y., Tchuvatkina, O., Spidlen, J., Wilkinson, P., Gasparetto, M., Jones, A.R., Manion, F.J., Scheuermann, R.H., Sekaly, R.P., Brinkman, R.R.: FuGEFlow: data model and markup language for flow cytometry. BMC Bioinformatics 10, 184 (2009)CrossRefGoogle Scholar
  31. 31.
    Reynolds, C.J., Wyatt, J.C.: Open Source, open standards, and health care information systems. J. Med. Internet Res. 13(1), e24 (2011)CrossRefGoogle Scholar
  32. 32.
    Rinner, C., Janzek-Hawlat, S., Sibinovic, S., Duftschmid, G.: Semantic validation of standard-based electronic health record documents with W3C XML schema. Methods Inf. Med. 49(3), 271–280 (2010)CrossRefGoogle Scholar
  33. 33.
    Seibel, P.N., Krüger, J., Hartmeier, S., Schwarzer, K., Löwenthal, K., Mersch, H., Dandekar, T., Giegerich, R.: XML Schemas for common bioinformatic data types and their application in workflow systems. BMC Bioinformatics 7, 490 (2006)CrossRefGoogle Scholar
  34. 34.
    Sundvall, E., Qamar, R., Nystrom, M., Forss, M., Petersson, H., Karlsson, D., Ahlfeldt, H., Rector, A.: Integration of tools for binding archetypes to SNOMED CT. BMC Med. Inform. Decis. Mak. 8(suppl. 1), S7 (2008)CrossRefGoogle Scholar
  35. 35.
    Yoder, J.W., Balaguer, F., Johnson, R.: Architecture and design of adaptive object-models,
  36. 36.
    Zhao, L., Lee, K.P., Hu, J.: Generating XML Schemas for DICOM structured reporting templates. J. Am. Med. Inform. Assoc. 12, 72–83 (2005)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Luciana T. Cavalini
    • 1
  • Timothy W. Cook
    • 2
  1. 1.Institute of Community HealthFluminense Federal University (UFF)NiteróiBrazil
  2. 2.National Institute of Science and TecnologyMedicine Assisted by Scientific Computing (INCT-MACC)Brazil

Personalised recommendations