Abstract
The complete transfer path pays attention to the synergy among medical institutions, the result of treatment and the temporal sequence. However, the patient’s visiting behavior usually spans many medical institutions. It is not only difficult for inter-agency medical records, examination results and treatment process to be transmitted comprehensively and efficiently, but also difficult to trace the origin of the complete transfer path. This paper proposes a blockchain medical asset model to support the analysis of transfer paths across medical institutions. Firstly, this method establishes a sharing mechanism based on blockchain across medical institutions, and proposes a mapping algorithm between visiting data and blockchain assets. To solve the problem of lack of traceability and reduce the cost of using medical assets, the blockchain is used to transfer the status and inspect structure of diagnosis and treatment process among institutions. Then, aiming at the problem of lack of referral for patient transfer paths, a blockchain based full-chain transfer path analysis method is designed to find the optimal transfer paths for local medical institutions and overcome the bottleneck of the lack of referral for medical institutions transfer paths. Experiments show that the blockchain medical asset model proposed in this paper can cover the whole chain data of transfer, and can meet the needs of cross-medical institutions tracing the complete transfer path. The prediction algorithm used in this model has better performance than other prediction algorithms in mining the optimal path.
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Acknowledgement
This research is supported, in part, by the National Natural Science Foundation, China (No. 61772316); the major Science and Technology Innovation of Shandong Province (No. 2019JZZY010109); the Industrial Experts Program of Spring City; Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR) (NSC-2019-011).
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Yin, Q., Kong, L., Min, X., Feng, S. (2021). Blockchain Medical Asset Model Supporting Analysis of Transfer Path Across Medical Institutions. In: Sun, Y., Liu, D., Liao, H., Fan, H., Gao, L. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2020. Communications in Computer and Information Science, vol 1330. Springer, Singapore. https://doi.org/10.1007/978-981-16-2540-4_22
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