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:10.1109/ACCESS.2019.2939158

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

^*Corresponding author for this work

School of Management

Kaifeng Hospital of Traditional Chinese Medicine
University of Sheffield
Sustainable Development Research Institute for Economy and Society
Yangzhou University

Research output: Contribution to journal › Article › peer-review

31 Citations (Scopus)

Abstract

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.

Original language	English
Article number	8824131
Pages (from-to)	136223-136231
Number of pages	9
Journal	IEEE Access
Volume	7
DOIs	https://doi.org/10.1109/ACCESS.2019.2939158
Publication status	Published - 2019

Keywords

Big data analytics
Electronic health records and impacts
Knowledge-based view

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10.1109/ACCESS.2019.2939158

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title = "Optimizing the electronic health records through big data analytics: A knowledge-based view",

abstract = "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 = "Big data analytics, Electronic health records and impacts, Knowledge-based view",

author = "Caifeng Zhang and Rui Ma and Shiwei Sun and Yujie Li and Yichuan Wang and Zhijun Yan",

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year = "2019",

doi = "10.1109/ACCESS.2019.2939158",

language = "English",

volume = "7",

pages = "136223--136231",

journal = "IEEE Access",

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T2 - A knowledge-based view

AU - Zhang, Caifeng

AU - Ma, Rui

AU - Sun, Shiwei

AU - Li, Yujie

AU - Wang, Yichuan

AU - Yan, Zhijun

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Big data analytics

KW - Electronic health records and impacts

KW - Knowledge-based view

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M3 - Article

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JO - IEEE Access

JF - IEEE Access

M1 - 8824131

ER -

Optimizing the electronic health records through big data analytics: A knowledge-based view

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Keywords

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