Research on the Blockchain-Based Shared Mechanism for Elderly Chronic Disease Health Records with Traditional Chinese Medicine Characteristics
Year: 2025
Type: conference-paper
Abstract: Taking care of chronic diseases in the elderly has become a major global public health problem. Chinese medicine has its own set of theories and therapeutic advantages, which can provide great help to the management of chronic diseases of the elderly in these aspects of prevention, conditioning and rehabilitation. However, there are a lot of problems in the management of health records of the elderly, such as data fragmentation, information inaccessibility, privacy risk, non-uniform data standards, etc., which affect the efficient sharing of health information among different organizations. In order to solve this problem, some people propose to use blockchain technology to get a health record sharing mechanism for the elderly and chronic diseases, focusing on the Chinese medicine sector. This mechanism wants to establish a multi-party cooperation, highly interconnected health record sharing platform, using blockchain decentralization, tamper-proof, transparent features, seamlessly integrating medical institutions, Chinese medicine diagnosis and treatment data, and achieving collaborative sharing. Doing so not only protects the privacy and security of patients' health information, but also organically combines TCM-specific data such as tongue diagnosis, pulse diagnosis, and medication with medical data through virtual chain technology, effectively solving the problem of cross-chain collaboration between different storage structures. Through system design and case study, the potential of this mechanism is verified - it can enhance the efficiency of health record management for the elderly and chronic diseases, enhance the transparency of data sharing, protect patient privacy, and also promote the development of personalized medicine.
Authors: Yuanci Lyu, Shuyi Xu, Lu Yin, Feifei Chen, Ting Zhou
Institution: Wuhan Donghu University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414182378