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Journal of Medical Systems

, 38:104 | Cite as

Cloud-Based Hospital Information System as a Service for Grassroots Healthcare Institutions

  • Qin Yao
  • Xiong Han
  • Xi-Kun Ma
  • Yi-Feng Xue
  • Yi-Jun Chen
  • Jing-Song LiEmail author
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement

Abstract

Grassroots healthcare institutions (GHIs) are the smallest administrative levels of medical institutions, where most patients access health services. The latest report from the National Bureau of Statistics of China showed that 96.04 % of 950,297 medical institutions in China were at the grassroots level in 2012, including county-level hospitals, township central hospitals, community health service centers, and rural clinics. In developing countries, these institutions are facing challenges involving a shortage of funds and talent, inconsistent medical standards, inefficient information sharing, and difficulties in management during the adoption of health information technologies (HIT). Because of the necessity and gravity for GHIs, our aim is to provide hospital information services for GHIs using Cloud computing technologies and service modes. In this medical scenario, the computing resources are pooled by means of a Cloud-based Virtual Desktop Infrastructure (VDI) to serve multiple GHIs, with different hospital information systems dynamically assigned and reassigned according to demand. This paper is concerned with establishing a Cloud-based Hospital Information Service Center to provide hospital information software as a service (HI-SaaS) with the aim of providing GHIs with an attractive and high-performance medical information service. Compared with individually establishing all hospital information systems, this approach is more cost-effective and affordable for GHIs and does not compromise HIT performance.

Keywords

Cloud computing Cloud-based hospital information service Software as a service Cloud-based medical service delivery 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation (Grant No. 61173127), National High-tech R&D Program (No. 2013AA041201), and the Zhejiang University Top Disciplinary Partnership Program.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Qin Yao
    • 1
  • Xiong Han
    • 2
  • Xi-Kun Ma
    • 3
  • Yi-Feng Xue
    • 4
  • Yi-Jun Chen
    • 5
  • Jing-Song Li
    • 1
    Email author
  1. 1.EMR and Intelligent Expert System Engineering Research Center, Key Laboratory of Bio-medical Engineering, Ministry of Education, College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouChina
  2. 2.Health Information Management Center, Joint Logistic Department of Nanjing Military CommandNanjingChina
  3. 3.Department InformationNanjing General Hospital of Nanjing Military CommandNanjingChina
  4. 4.Department InformationThe 454th Hospital of People’s Liberation ArmyNanjingChina
  5. 5.Department InformationThe 101th Hospital of People’s Liberation ArmyWuxiChina

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