IEEE Access (Jan 2019)

Optimizing the Electronic Health Records Through Big Data Analytics: A Knowledge-Based View

  • Caifeng Zhang,
  • Rui Ma,
  • Shiwei Sun,
  • Yujie Li,
  • Yichuan Wang,
  • Zhijun Yan

DOI
https://doi.org/10.1109/ACCESS.2019.2939158
Journal volume & issue
Vol. 7
pp. 136223 – 136231

Abstract

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Many hospitals are suffering from ineffective use of big data analytics with electronic health records (EHRs) to generate high quality insights for their clinical practices. Organizational learning has been a key role in improving the use of big data analytics with EHRs. Drawing on the knowledge-based view and big data lifecycle, we investigate how the three modes of knowledge can achieve meaningful use of big data analytics with EHRs. To test the associations in the proposed research model, we surveyed 580 nurses of a large hospital in China in 2019. Structural equation modelling was used to examine relationships between knowledge mode of EHRs and meaningful use of EHRs. The results reveal that know-what about EHRs utilization, know-how EHRs storage and utilization, and know-why storage and utilization can improve nurses' meaningful use of big data analytics with EHRs. This study contributes to the existing digital health and big data literature by exploring the proper adaptation of analytical tools to EHRs from the different knowledge mode in order to shape meaningful use of big data analytics with EHRs.

Keywords