Big data management in healthcare: Adoption challenges and implications |
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| Institution: | 1. Department of Biomedical Engineering, National Cheng Kung University, No.1, University Road, Tainan City 701, Taiwan, ROC;2. Medical Device Innovation Center, National Cheng Kung University, No.138, Shengli Rd., North District, Tainan City 704, Taiwan, ROC;3. Department of Marketing Management, Shu-Te University, No.59, Hengshan Rd., Yanchao, Kaohsiung 824, Taiwan, ROC;4. Department of Information Management, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 804, Taiwan, ROC;1. School of Economic Information Engineering, Southwestern University of Finance and Economics, China;2. Fogelman College of Business & Economics, The University of Memphis, United States;1. School of Communication & Information, Nanyang Technological University, Republic of Singapore;2. UC Business School, University of Canterbury, Christchurch, New Zealand;1. Politécnico do Porto, ISCAP, CEOS.PP, S. Mamede de Infesta, Portugal;2. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal;3. Universidade Atlântica, Barcarena, Portugal;4. Politécnico do Porto, ISCAP, CEOS.PP, S. Mamede de Infesta, Portugal;1. University of Evora, Portugal;2. BGMEA University of Fashion & Technology Dhaka, Bangladesh |
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| Abstract: | The computerized healthcare information system has undergone tremendous advancements in the previous two decades. Medical institutions are paying further attention to the replacement of traditional approaches that can no longer handle the increasing amount of patient data. In recent years, the healthcare information system based on big data has been growing rapidly and is being adapted to medical information to derive important health trends and support timely preventive care. This research aims to evaluate organization-driven barriers in implementing a healthcare information system based on big data. It adopts the analytic network process approach to determine the aspect weight and applies VlseKriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) to conclude a highly appropriate strategy for overcoming such barriers. The proposed model can provide hospital managers with forecasts and implications that facilitate the withdrawal of organizational barriers when adopting the healthcare information system based on big data into their healthcare service system. Results can provide benefits for increasing the effectiveness and quality of the healthcare information system based on big data in the healthcare industry. Therefore, by understanding the sequence of the importance of resistance factors, managers can formulate efficient strategies to solve problems with appropriate priorities. |
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| Keywords: | Healthcare information system Medical big data Organizational barrier Adoption strategy Multiple Criteria Decision Making (MCDM) |
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