Towards a Pathway-Based Clinical Cancer Registration in Hospital Information Systems

  • Michael HeßEmail author
  • Monika Kaczmarek
  • Ulrich Frank
  • Lars-Erik Podleska
  • Georg Taeger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9485)


The clinical cancer registration constitutes a major source of data used to support the cancer research. However, providing data to cancer registries usually requires additional effort, as the automated extraction of the required data from the already existing clinical documentation is often not possible. In this paper, we show how the conceptual models of clinical pathways (CPs), created using the domain-specific modeling language extended with the data models reconstructed based on the common oncological basic data set, can support a model-based design and development of process-oriented hospital information systems and contribute to enhancing the data-quality and efficiency of clinical cancer registration.


Multi-Perspective Hospital Modeling DSML Cancer registration 


  1. 1.
    Altmann, U., Katz, F.R., Dudeck, J.: A reference model for clinical tumour documentation. In: Hasman, A., Haux, R., et al. (eds.) Ubiquity: Technologies for Better Health in Aging Societies, pp. 139–144. IOS Press, Maastricht (2006)Google Scholar
  2. 2.
    Ammenwerth, E., Spötl, H.P.: The time needed for clinical documentation versus direct patient care. Meth. Inf. Med. 48(1), 84–91 (2009)Google Scholar
  3. 3.
    Benson, T.: Principles of Health Interoperability HL7 and SNOMED, 2nd edn. Springer, London (2012)CrossRefGoogle Scholar
  4. 4.
    Blaser, R., Schnabel, M., et al.: Improving pathway compliance and clinician performance by using information technology. IMJI 76(2–3), 151–156 (2007)Google Scholar
  5. 5.
    Blum, K., Müller, U.: Dokumentationsaufwand im Ärztlichen Dienst der Krankenhäuser. Das Krankenhaus 95(7), 544–548 (2003)Google Scholar
  6. 6.
    Boxwala, A.A., et al.: GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines. J. Biomed. Inform. 37(3), 147–161 (2004)CrossRefGoogle Scholar
  7. 7.
    Breil, B., Dugas, M.: Transferring HIS data to population-based cancer registries. In: Adlassnig, K.P., Blobel, B., Mantas, J., Masic, I. (eds.) Medical Informatics in a United and Healthy Europe, pp. 86–90. IOS Press, Sarajevo (2009)Google Scholar
  8. 8.
    Bundesministerium für Gesundheit: Nationaler Krebsplan. Handlungsfelder, Ziele und Umsetzungsempfehlungen, Berlin (2012)Google Scholar
  9. 9.
    Bundesministerium für Gesundheit: Aktualisierter einheitlicher onkologischer Basisdatensatz der Arbeitsgemeinschaft Deutscher Tumorzentren e. V. (ADT) und der Gesellschaft der epidemiologischen Krebsregister in Deutschland e. V. (GEKID). Bundesanzeiger vom April 28, 2014 (2014)Google Scholar
  10. 10.
    Burwitz, M., Schlieter, H., Esswein, W.: Modeling clinical pathways - design and application of a domain-specific modeling language. In: Alt, R., Franczyk, B. (eds.) Proceedings of Wirtschaftsinformatik 2013, vol. 2, pp. 1325–1339, Leipzig (2013)Google Scholar
  11. 11.
    Chen, P.P.S.: The entity relationship model - toward a unified view of data. ACM Trans. Database Syst. 1(1), 9–36 (1976)CrossRefGoogle Scholar
  12. 12.
    Cuggia, M., Avillach, P., Daniel, C.: Representation of patient data in health information systems and electronic health records. In: Venot, A., Burgun, A., Quantin, C. (eds.) Medical Informatics, e-Health, pp. 65–89. Springer, Paris (2014)CrossRefGoogle Scholar
  13. 13.
    de Bleser, L., Depreitere, R., Waele, K.D., Vanhaecht, K., Vlayen, J., Sermeus, W.: Defining pathways. J. Nurs. Manage. 14(7), 553–563 (2006)CrossRefGoogle Scholar
  14. 14.
    Drucker, P.F.: Managing in the Next Society. Butterworth-Heinemann, Oxford (2002)Google Scholar
  15. 15.
    Dumas, M., Rosa, M.L., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  16. 16.
    Färber, M., Jablonski, S., Schneider, T.: A Comprehensive Modeling Language for Clinical Processes. In: Hein, A., Thoben, W., Appelrath, H.J., Jensch, P. (eds.) European Conference on eHealth 2007, Proceedings of the ECEH 2007, pp. 77–88. Gesellschaft für Informatik e. V., Oldenburg (2007)Google Scholar
  17. 17.
    Field, M.J., Lohr, K.N.: Clinical Practice Guidelines: Directions for a New Program. The National Academies Press, Washington (DC) (1990)Google Scholar
  18. 18.
    Frank, U.: Memo organisation modelling language (2): Focus on business processes. ICB Research Report 49, University of Duisburg-Essen (2011)Google Scholar
  19. 19.
    Frank, U.: Some guidelines for the conception of domain-specific modelling languages. In: Nüttgens, M., Thomas, O., Weber, B. (eds.) Proceedings of EMISA 4th International Workshop. LNI, vol. 190, pp. 93–106. GI, Bonn (2011)Google Scholar
  20. 20.
    Frank, U.: The MEMO Meta Modelling Language (MML) and Language Architecture. 2nd edn. ICB-Research Report 43, University of Duisburg-Essen (2011)Google Scholar
  21. 21.
    Frank, U.: Domain-specific modeling languages: requirements analysis and design guidelines. In: Reinhartz-Berger, I., Sturm, A., Clark, T., Cohen, S., Bettin, J. (eds.) Domain Engineering, pp. 133–157. Springer, Berlin (2013)CrossRefGoogle Scholar
  22. 22.
    Gooch, P., Roudsari, A.: Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems. JAMIA 18, 738–748 (2011)Google Scholar
  23. 23.
    Haier, J.: Datenmanagement in integrierten Krebszentren: Harmonisierung der Strukturen erforderlich. Deutsches Ärzteblatt 106(21), A-1040–A-1043 (2009)Google Scholar
  24. 24.
    Heß, M.: Towards a domain-specific method for multi-perspective hospital modelling – motivation and requirements. In: vom Brocke, J., Hekkala, R., Ram, S., Rossi, M. (eds.) DESRIST 2013. LNCS, vol. 7939, pp. 369–385. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  25. 25.
    Heß, M., Kaczmarek, M., Frank, U., Podleska, L., Taeger, G.: Towards a DSML for clinical pathways in the realm of multi-perspective hospital modelling. In: Becker, J., vom Brocke, J., de Marco, M. (eds.) Proceedings of 23rd ECIS, Münster (2015)Google Scholar
  26. 26.
    Heß, M., Podleska, L., Täger, G.: Vision einer integrierten Tumordokumentation (Poster). In: 20 Informationstagung Tumordokumentation, Lübeck (2013)Google Scholar
  27. 27.
    Heß, M., Schlieter, H., Täger, G.: Modellierung komplexer Entscheidungssituationen in Prozessmodellen - Anwendung am Beispiel der Tumorklassifikation bei Weichteilsarkomen. In: Thomas, O., Nüttgens, M. (eds.) Dienstleistungsmodellierung 2012, pp. 268–290. Springer Gabler, Wiesbaden (2012)Google Scholar
  28. 28.
    HL7-Benutzergruppe in Deutschland e. V.: Implementierungsleitfaden Übermittlung von onkologischen Daten mittels HL7 CDA R2. Technical report, Köln (2011)Google Scholar
  29. 29.
    Katalinic, A., Richter, A., et al.: Krebsregistrierung im europäischen und nichteuropäischen Ausland. Der Onkologe 19(12), 1025–1036 (2013)CrossRefGoogle Scholar
  30. 30.
    Klinkhammer-Schalke, M., Hentschel, S., et al.: Einheitlicher onkologischer Basisdatensatz der ADT/GEKID (Stand: 12.02.2014). ADT und GEKID (2014)Google Scholar
  31. 31.
    Krogstie, J.: Model-Based Development and Evolution of Information Systems. A Quality Approach. Springer, London (2012)CrossRefGoogle Scholar
  32. 32.
    Lenz, R., Blaser, R., et al.: IT support for clinical pathways - lessons learned. Int. J. Med. Inform. 76(Suppl. 3), S397–S402 (2007)CrossRefGoogle Scholar
  33. 33.
    Meiler, C.: Modellierung Planung und Ausführung Klinischer Pfade. ibidem-Verlag, Stuttgart (2005) Google Scholar
  34. 34.
    Oken, M.M., Creech, R.H., Torney, D.C., Horton, J., Davis, T.E., McFadden, E.T., Carbone, P.P.: Toxicity and response criteria of the eastern cooperative oncology group. Am. J. Clin. Oncol. 5, 649–655 (1982)CrossRefGoogle Scholar
  35. 35.
    Österle, H., Becker, J., Frank, U., et al.: Memorandum on design-oriented information systems research. EJIS 20, 7–10 (2011)Google Scholar
  36. 36.
    Peleg, M.: Computer-interpretable clinical guidelines: a methodological review. J. Biomed. Inform. 46(4), 744–763 (2013)CrossRefGoogle Scholar
  37. 37.
    Reichert, M.: What BPM technology can do for healthcare process support. In: Peleg, M., Lavrač, N., Combi, C. (eds.) AIME 2011. LNCS, vol. 6747, pp. 2–13. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  38. 38.
    Riaño, D.: A systematic analysis of medical decisions: how to store knowledge and experience in decision tables. In: Riaño, D., ten Teije, A., Miksch, S. (eds.) KR4HC 2011. LNCS, vol. 6924, pp. 23–36. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  39. 39.
    Rotter, T., Kinsman, L., et al.: Clinical pathways: effects on professional practice, patient outcomes, length of stay and hospital costs (review). Cochrane Database Syst. Rev., 7(3) (2010)Google Scholar
  40. 40.
    Med. Decis. Making, Society for medical decision making: proposal for clinical algorithm standards. 12(2), 149–154 (1992)Google Scholar
  41. 41.
    Stephens, F.O., Aigner, K.R.: Basics of Oncology. Springer, Berlin (2009)Google Scholar
  42. 42.
    Sutton, D., Taylor, P., Earle, K.: Evaluation of proforma as a language for implementing medical guidelines in a practical context. BMC Med. Inform. Decis. Making 6, 1–11 (2006)CrossRefGoogle Scholar
  43. 43.
    Tu, S., Campbell, J.R., Glasgow, J., Nyman, M.A., McClure, R., et al.: The sage guideline model: achievements and overview. JAMIA 14(5), 589–598 (2007)Google Scholar
  44. 44.
    Vos, L., et al.: Towards an organisation-wide process-oriented organisation of care: a literature review. Implementation Sci. 6(8), 1–14 (2011)Google Scholar
  45. 45.
    Wakamiya, S., Yamauchi, K.: What are the standard functions of electronic clinical pathways? Int. J. Med. Inform. 78(8), 543–550 (2009)CrossRefGoogle Scholar
  46. 46.
    Warmer, J.B., Kleppe, A.G.: The Object Constraint Language : Getting Your Models Ready for MDA, 2nd edn. Addison-Wesley, Boston (2003) Google Scholar
  47. 47.
    Winter, A., Haux, R., Ammenwerth, E., Brigl, B., Hellrung, N., Jahn, F.: Health Information Systems. Architectures and Strategies, 2nd edn. Springer, London (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Michael Heß
    • 1
    Email author
  • Monika Kaczmarek
    • 1
  • Ulrich Frank
    • 1
  • Lars-Erik Podleska
    • 2
  • Georg Taeger
    • 2
  1. 1.Research Group Information Systems and Enterprise ModelingUniversity of Duisburg-EssenEssenGermany
  2. 2.Division of Sarcoma Surgery, Department of General-, Visceral- and Transplant Surgery, West German Cancer Center, University Hospital University of Duisburg-EssenEssenGermany

Personalised recommendations