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Analysis of Smart Health Research Context and Development Trend Driven by Big Data

  • Ying Qu
  • Moran Fan
  • Xiaowei Zhang
  • Weige JiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11924)

Abstract

In the context of new healthcare reform in China, smart health has gradually developed into a necessary link for health service. To comb the research context of smart health based on academic achievements and to explore the development priority of the leading research will help to perfect the theoretical studies and practical applications of smart health. Through Python crawler technology, accessed 922 documents as a data source from CNKI; Using word segmentation, statistical techniques, visualization analysis research context; CiteSpace V software is used to analyze the research profile and development priority from the literature sources, cooperation teams and key words. Through the qualitative analysis of research context and the quantitative analysis of the number of different types of literature, it reveals the process of the development of smart health from the theoretical start, idea formation, practical application, technological progress, cross-border cooperation to the final relatively stable. But found some problems such as underutilization of data, lack of informationization of critical illness, low recognition of family health systems, and problems between government and patients. Therefore, we should strengthen the government’s promotion, application stability, hospital data information processing ability, etc. in the development priority. These foreseeability trend and development context will provide new ideas for theoretical research and make up for the deficiencies in practical application.

Keywords

Smart health Research focus Bibliometrics Word cloud visualization Cooccurrence network 

Notes

Acknowledgements

This paper is supported by the Scientific and Technological Research Projects of Colleges and Universities in Hebei Province ‘Research on Risk Knowledge Management of Software Project Driven by Big Data’ (Project No. ZD2017029).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Economics and ManagementHebei University of Science and TechnologyShijiazhuangChina

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