Advertisement

Large-Scale Clinical Data Management and Analysis System Based on Cloud Computing

  • Ye Wang
  • Lin Wang
  • Hong Liu
  • Changhai Lei
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

With the exponential increase of Electronic Health Record systems in China, large-scale clinical data management and analysis have become big challenges. This paper depicts a novel system named Clinical Data Managing and Analyzing System, which uses hybrid XML database, and HBase/Hadoop infrastructure to handle big amount of heart disease clinical data analysis online. Using standardized format of Clinical Document Architecture, the system now has integrated more than 50,000 valvular heart disease clinical documents and provided efficient distributed data mining tools as well as data managing tools for doctor users from multi heart clinical centers in six different 3A hospitals of China.

Keywords

CDA EHR Data management Data mining HBase Hadoop 

References

  1. 1.
    Kahn S, Sheshadri V (2008) Medical record privacy and security in a digital environment. IT Prof 10(2):46–52Google Scholar
  2. 2.
    Taylor R (2010) An overview of the hadoop/mapreduce/hbase framework and its current applications in bioinformatics. BMC Bioinformatics 11(12):S1CrossRefGoogle Scholar
  3. 3.
    Sarathy V, Narayan P, Mikkilineni R (2010) Next generation cloud computing architecture: enabling real-time dynamism for shared distributed physical infrastructure. In: 2010 19th IEEE international workshop on enabling technologies: infrastructures for collaborative enterprises (WETICE), June 2010, pp 48–53Google Scholar
  4. 4.
    Wang Z, Wang Y, Tan K-L, Wong L, Agrawal D (2011) ECEO: an efficient cloud epistasis computing model in genome-wide association study. Bioinformatics 27(8):1045–1051Google Scholar
  5. 5.
    Ferńandez-Cardeñosa G, de la Torre-Díez I, López-Coronado M, Rodrigues J (2012) Analysis of cloud-based solutions on EHRs systems in different scenarios. J Med Syst 36:3777–3782. doi:  10.1007/s10916-012-9850-2 Google Scholar
  6. 6.
    Dean J, Ghemawat S (2008) Mapreduce: simplified data processing on large clusters. Commun ACM 51(1):107–113CrossRefGoogle Scholar
  7. 7.
    Dean J, Ghemawat S (2010) Mapreduce: a flexible data processing tool. Commun ACM 53(1):72–77CrossRefGoogle Scholar
  8. 8.
    White T (2010) Hadoop: the definitive guide. Yahoo! Press, New YorkGoogle Scholar
  9. 9.
    Li W-S, Yan J, Yan Y, Zhang J (2010) Xbase: cloud-enabled information appliance for healthcare. In: Proceedings of the 13th international conference on extending database technology, EDBT’10, ACM, New York, USA, pp 675–680Google Scholar
  10. 10.
    Tancer J, Varde AS (2011) The deployment of mml for data analytics over the cloud. In: 2011 IEEE 11th international conference on data mining workshops (ICDMW), Dec 2011, pp 188–195Google Scholar
  11. 11.
    Mohammed S, Servos D, Fiaidhi J, Kamel M, Karray F, Gueaieb W, Khamis A (2011) Developing a secure distributed OSGi cloud computing infrastructure for sharing health records, vol 6752. Springer, Berlin, pp 241–252Google Scholar
  12. 12.
    Chen Y-Y, Lu J-C, Jan J-K (2012) A secure ehr system based on hybrid clouds. J Med Syst 36:3375–3384. doi:  10.1007/s10916-012-98306 Google Scholar
  13. 13.
    Ferranti JM, Clayton Musser R, Kawamoto K, Hammond EW (2006) The clinical document architecture and the continuity of care record: a critical analysis. J Am Med Inform Assoc 13(3):245–252Google Scholar
  14. 14.
    Dolin RH, Alschuler L, Beebe C, Biron PV, Boyer, D Essin SL, Kimber E, Lincoln T, Mattison JE (2001) The hl7 clinical document architecture. J Am Med Inform Assoc 8(6):552–569Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Information CenterSecond Military Medical UniversityShanghaiChina
  2. 2.The 85th Hospital of PLAShanghaiChina

Personalised recommendations