Advertisement

IT-Architecture Development Approach in Implementing BI-Systems in Medicine

  • Oksana Yu. Iliashenko
  • Victoria M. Iliashenko
  • Alisa DubgornEmail author
Conference paper
First Online:
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 95)

Abstract

One of the main key aspect of management in medical organizations is information support by different analytical systems. For this reason, the number of medical organizations that decide on the implementation of Business Intelligence class systems increases. BI-system allows for the data operational monitoring on the medical organizations management, simplifies the entire process of forming analytical reports in the company. BI system is the most complete source of information on current activities at medical organizations. The BI-system implementation at an enterprise involves the modernization of the business processes system, services architecture, the development of IT architecture and information exchange model. One of the important tasks in the information and analytical system implementation is its integration into the existing architectural solution at the enterprise. This paper provides the development of a medical organization’s IT architecture and a corresponding information exchange model when solving problems of integrating BI system into the general IT architecture of an enterprise.

Keywords

Business intelligence BI BI-system IT architecture Medicine 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

The reported study was funded by RFBR according to the research project № 19-010-00579.

References

  1. 1.
    Ariyachandra, T., Watson, H.J.: Key factor in selecting a data warehouse architecture. Bus. Intell. J. 10(2), 19–26 (2005)Google Scholar
  2. 2.
    Ariyachandra, T., Watson, H.J.: Which data warehouse architecture is most successful. Bus. Intell. J. 11(1), 4–6 (2006)Google Scholar
  3. 3.
    Devlin, B.A., Murphy, P.T.: An architecture for a business and information system. IBM Syst. J. 27(1), 60–80 (1988)CrossRefGoogle Scholar
  4. 4.
    Iliashenko, O.Yu., Levina, A.I., Dubgorn, A.: Using business intelligence technologies for evaluation of road network organization. In: Proceedings of the 30th IBIMA 2017, pp. 2144–2155 (2017)Google Scholar
  5. 5.
    Ilin, I., Iliashenko, O.Yu., Levina, A.: Reengineering of high-tech and specialized medical care delivery process for telemedicine system implementation. In: Proceedings of the 29th International Business Information Management Association Conference IBIMA, pp. 1822–1831 (2017)Google Scholar
  6. 6.
    Inmon, W.H.: DW 2.0 Architecture for the Next Generation of Data Warehousing. Morgan-Kaufman, Burlington (2008)Google Scholar
  7. 7.
    Inmon, B.: Data Lake Architecture: Designing the Data Lake and Avoiding the Garbage Dump. Technics Publications, Basking Ridge (2016)Google Scholar
  8. 8.
    Yuen-Reed, G., Mojsilović, A.: The role of big data and analytics in health payer transformation to consumer-centricity. In: Weaver, C., Ball, M., Kim, G., Kiel, J. (eds.) Healthcare Information Management Systems Cases, Strategies, and Solutions, 4th edn, pp. 399–420. Springer, Cham (2016)CrossRefGoogle Scholar
  9. 9.
    Cresswell, K.M., Sheikh, A.: Key Advances in Clinical InformaticsTransforming Health Care Through Health Information Technology. Academic Press, Cambridge (2017).  https://doi.org/10.1016/b978-0-12-809523-2.00002-9. Accessed 1 May 2019CrossRefGoogle Scholar
  10. 10.
    Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd edn. Wiley, Indianapolis (2013)Google Scholar
  11. 11.
    Kroenke, D.M., Auer, D.J., Yoder, R.C., Vandenberg, S.L.: Database Processing: Fundamentals, Design, and Implementation, 15th edn. Pearson, New York (2018)Google Scholar
  12. 12.
    Kroenke, D.M., Auer, D.J., Vandenberg, S.L., Yoder, R.C.: Database Concepts. Pearson, New York (2017)Google Scholar
  13. 13.
    Lankhorst, M.: Enterprise Architecture at Work: Modelling, Communication, Analysis, 4th edn. Springer, Heidelberg (2017)CrossRefGoogle Scholar
  14. 14.
    Lepekhin, A.A., Borremans, A.D., Iliashenko, O.Yu.: Design and implementation of IT services as part of the “Smart City” concept. In: MATEC Web of Conferences, International Science Conference on Business Technologies for Sustainable Urban Development, SPbWOSCE 2017, 13 June 2018, vol. 170 (2018). Paper number 01029Google Scholar
  15. 15.
    Liya, W., Barash, G., Barash, G., Bartolii, C.: A service-oriented architecture for business intelligence. In: IEEE International Conference on Service-Oriented Computing and Applications (SOCA 2007), pp. 279–285 (2007)Google Scholar
  16. 16.
    Official website of the company OPENGROUP. TOGAF Standart. https://www.opengroup.org/. Accessed 18 Jan 2019
  17. 17.
    Official website of the company Netrika. https://netrika.ru/. Accessed 1 May 2019
  18. 18.
    Troyansky, O., Gibson, T., Leichtweis, C.: QlikView Your Business. An Expert Guide to Business Discovery with QlikView and Qlik Sens. Wiley, Hoboken (2015)CrossRefGoogle Scholar
  19. 19.
    Schaffner, J., Jacobs, D., Eckart, B., Brunnert, J., Zeier, A.: Towards enterprise software as a service in the cloud. In: Proceedings of the 2nd IEEE Workshop on Information and Software as Services (WISS), pp. 52–59 (2010)Google Scholar
  20. 20.
    Liu, T., Shen, A., Hu, X., Tong, G., Gu, W.: The application of collaborative business intelligence technology in the hospital SPD logistics management model. Iran. J. Public Health 46(6), 744–754 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Oksana Yu. Iliashenko
    • 1
  • Victoria M. Iliashenko
    • 1
  • Alisa Dubgorn
    • 1
    Email author
  1. 1.Peter the Great St. Petersburg Polytechnic UniversitySaint PetersburgRussia

Personalised recommendations

Cite paper

Buy options