Big data management in healthcare: Adoption challenges and implications. (August 2020) - Chen, Peng-Ting; Lin, Chia-Li; Wu, Wan-Ning
Highlights: Barriers to big data development in medical institutions were perceived. A framework of medical big data barriers was constructed. Solid suggestions toward the removal of barriers to big data implementation. 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.