Advertisement

A Novel Generic Clinical Reference Process Model for Event-Based Process Times Measurement

  • Eva Gattnar
  • Okan Ekinci
  • Vesselin Detschew
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 97)

Abstract

In recent years, performance measurement has become an important element of efficiency improvement projects in many organizations. Thereby, process-based measures are used to evaluate the process efficiency and quality. In health care, such measures are often neither commonly defined nor standardized. Therefore we present a novel approach for standardized clinical quality metrics measurement by means of a newly developed clinical reference process model and generic Key Performance Indicators (KPIs). We use both for a comprehensive description of the complete clinical patient-centered process in hospital. Our approach fulfils performance measurement requirements particularly in the field of time-critical diseases like heart attack and stroke.

Keywords

performance measurement process monitoring key performance indicators clinical process model event-driven process chain 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Gattnar, E., Ekinci, O., Detschew, V.: Event-based Workflow Analysis in Healthcare. In: Proceedings of the 9th International Workshop on Modeling, Simulation, Verification and Validation of Enterprise Information Systems (MSVVEIS 2011), In Conjunction with the 13th International Conference on Enterprise Information Systems (ICEIS 2011), pp. 61–70 (2011)Google Scholar
  2. 2.
    Birdsell, J.M., Hayden, K.A., Lewis, S.: Performance Measurement in Healthcare: Part II. Healthcare Policy 2(1), 57–78 (2006)Google Scholar
  3. 3.
    Ghattas, J., Peleg, M., Soffer, P., Denekamp, Y.: Learning the Context of a Clinical Process. In: Proceedings of the Business Process Management Workshops (Prohealth 2009), pp. 545–556 (2009)Google Scholar
  4. 4.
    Deutsche Gesellschaft für Kardiologie, http://www.dgk.org
  5. 5.
    American Heart Association, http://www.americanheart.org
  6. 6.
    Kahla-Witzsch, H.A.: Interprofessionelles Qualitätsmanagement als unverzichtbare Grundlage für eine erfolgreiche Pfadarbeit. In: Hellmann, W. (ed.) Praxis Klinischer Pfade: Viele Wege führen zum Ziel, Ecomed, Landsberg/Lech (2003)Google Scholar
  7. 7.
    Kahla-Witzsch, H.A., Geisinger, T.: Clinical Pathways in der Krankenhauspraxis, Kohlhammer, Stuttgart (2004)Google Scholar
  8. 8.
    Keller, G., Nüttgens, G., Scheer, A.-W.: Semantische Prozeßmodellierung auf der Grundlage Ereignisgesteuerter Prozeßketten (EPK), Veröffentlichungen des Instituts für Wirtschaftsinformatik (IWi), Universität des Saarlandes, Heft 89, Saarbrücken (1992)Google Scholar
  9. 9.
    Fettke, P., Loos, P.: Perspectives on Reference Modeling. In: Fettke, P., Loos, P. (eds.) Reference Modeling for Business Systems Analysis. Idea Group Publishing Inc., London (2007)CrossRefGoogle Scholar
  10. 10.
    Status Quo Prozessmanagement 2010/2011: BPM expo, http://www.bpm-expo.com
  11. 11.
    vom Brocke, J.: Referenzmodellierung: Gestaltung und Verteilung von Konstruktionsprozessen. Logos Verlag, Berlin (2003)Google Scholar
  12. 12.
    Sarshar, K., Dominitzki, P., Loos, P.: Einsatz von Ereignisgesteuerten Prozessketten zur Modellierung von Prozessen in der Krankenhausdomäne. In: EPK 2005: Geschäftsprozessmanagement mit Ereignisgesteuerten Prozessketten, Proc., 4. Workshop der Gesellschaft für Informatik e.V (GI), Hamburg, pp. 97–116 (2005)Google Scholar
  13. 13.
    Davis, R.: Business Process Modelling with ARIS. Springer, London (2001)CrossRefGoogle Scholar
  14. 14.
    Gattnar, E., Ekinci, O.: Qualitätsmanagement im Krankenhaus – Konzepte, Rahmenbedingungen und Standards. In: Podium der Wirtschaft, Recht & Soziales, Band, vol. 21, pp. 67–130 (2011)Google Scholar
  15. 15.
    Lenz, R., Reichert, M.: IT support for healthcare processes – premises, challenges, perspectives. Data & Knowledge Engineering 61, 39–58 (2007)CrossRefGoogle Scholar
  16. 16.
    Anyanwu, K., Sheth, A., Cardoso, J., Miller, J., Kochut, K.: Healthcare Enterprise Process Development and Integration. Journal of Research and Practice in Information Technology 35(2), 364–376 (2003)Google Scholar
  17. 17.
    Dadam, P., Reichert, M., Rinderle-Ma, S.: Prozessmanagementsysteme – Nur ein wenig Flexibilität wird nicht reichen. Informatik Spektrum 34(4) (2011)Google Scholar
  18. 18.
    Becker, J., Fischer, R., Janiesch, C.: Optimizing U.S. Health Care Processes - A Case Study in Business Process Management. In: Proceedings of the 13th Americas Conference on Information Systems, AMCIS 2007 (2007)Google Scholar
  19. 19.
    Gattnar, E., Ekinci, O., Detschew, V.: Clinical Process Modeling and Performance Measurement in Hospitals. In: Proceedings of the AQuSerM 2011: 5th International Workshop on Advances in Quality of Service Management - In conjunction with the 15th IEEE International Enterprise Computing Conference (IEEE EDOC 2011), pp. 132–140. IEEE Computer Society Press (2011)Google Scholar
  20. 20.
    Gattnar, E., Ekinci, O., Detschew, V.: Interoperable Process Monitoring using Clinical IT-Standards and Healthcare Information Systems. In: Proceedings of the IADIS International Conferences Informatics 2011, Wireless Applications and Computing 2011, Telecommunications, Networks and Systems 2011, pp. 59–66 (2011)Google Scholar
  21. 21.
    Rubin, H., Pronovost, P., Diette, G.: The advantages and disadvantages of process-based measures of health care quality. International Journal for Quality in Health Care 13(6), 469–474 (2001)CrossRefGoogle Scholar
  22. 22.
    zur Mühlen, M., Rosemann, M.: Workflow-based process monitoring and controlling-—technical and organizational issues. In: Sprague, R. (ed.) Proceedings of the 33rd Hawaii International Conference on System Science (HICSS-33), pp. 1–10. IEEE Computer Society Press (2000)Google Scholar
  23. 23.
    Aalst, W.M.P.: Business Alignment: Using Process Mining as a Tool for Delta Analysis. Requirements Engineering 10(3), 198–211 (2005)CrossRefGoogle Scholar
  24. 24.
    Aalst, W.M.P., et al.: Workflow mining: A survey of issues and approaches. Data & Knowledge Engineering 47(2), 237–267 (2003)CrossRefGoogle Scholar
  25. 25.
    van der Aalst, W.M.P., ter Hofstede, A.H.M., Weske, M.: Business Process Management: a Survey. In: van der Aalst, W.M.P., ter Hofstede, A.H.M., Weske, M. (eds.) BPM 2003. LNCS, vol. 2678, pp. 1–12. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  26. 26.
    Winter, A., Haux, R.: A Three Level graph-based Model for the Management of Computer-Supported Hospital Information Systems. Methods of Information in Medicine 34(4), 378–396 (1995)Google Scholar
  27. 27.
    Buchauer, A., et al.: 3LGM: Method and Tool to support the management of heterogeneous hospital information systems. In: Computers in Medicine, Polish Society of Medical Informatics, pp. 72–82 (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Eva Gattnar
    • 1
    • 2
  • Okan Ekinci
    • 1
  • Vesselin Detschew
    • 2
  1. 1.Clinical Competence Center Cardiology, Siemens HealthcareErlangenGermany
  2. 2.Institute of Biomedical Engineering and InformaticsIlmenau Technical UniversityIlmenauGermany

Personalised recommendations