Innovation Resistance and Resource Allocation Strategy of Medical Information Digitalization

Wei-Chih Lu, I-Ching Tsai, Kuan-Chung Wang, Te-Ai Tang, Kuan-Chen Li, Ya-Ci Ke and Peng-Ting Chen
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Wei-Chih Lu: Department of Biomedical Engineering, National Cheng Kung University, No. 1 University Road, Tainan City 701, Taiwan
I-Ching Tsai: Department of Biomedical Engineering, National Cheng Kung University, No. 1 University Road, Tainan City 701, Taiwan
Kuan-Chung Wang: Department of Biomedical Engineering, National Cheng Kung University, No. 1 University Road, Tainan City 701, Taiwan
Te-Ai Tang: International Institute of Medical Device Innovation, National Cheng Kung University, No. 1 University Road, Tainan City 701, Taiwan
Kuan-Chen Li: Department of Business Administration, National Kaohsiung University of Science and Technology, No. 58 Shenzhong Rd., Yanchao District, Kaohsiung City 82444, Taiwan
Ya-Ci Ke: Department of Business Administration, National Kaohsiung University of Science and Technology, No. 58 Shenzhong Rd., Yanchao District, Kaohsiung City 82444, Taiwan
Peng-Ting Chen: Department of Biomedical Engineering, National Cheng Kung University, No. 1 University Road, Tainan City 701, Taiwan

Sustainability, 2021, vol. 13, issue 14, 1-20

Abstract: Healthcare industries are facing an enormous flow of medical records due to the progression of information technology and the trend of digital transformation. Thus, medical information digitalization is a huge digital dataset that can be utilized to benefit healthcare systems and patients. While many studies focus on the application of the digitalized medical information in the healthcare field, only a few mentioned its resistance. The theoretical background depicts a comprehensive overview of medical information digitalization and the barriers in previous literature. This study emphasized the interaction of medical information digitalization barriers and applies the importance-resistance analysis model (IRA) to identify the resistant factors overcoming strategy. It also clarifies the pathway to eliminating the innovation resistance and reveals the interaction of medical information digitalization barriers. The acquisition, management, and application of medical information digitalization are the key foundation of medical technology innovation, digital transformation, and the application of artificial intelligence. This work can reduce the limitation of a narrow healthcare context. This study helps healthcare industries to clarify and solve barriers and realizes the innovation and application of medical information digitalization. In the long term, the results provide a basis for the future development direction of medical information digitalization and affect the medical industry.

Keywords: medical information digitalization; innovation resistance; artificial intelligence; healthcare technological innovation; resource allocation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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