Medical service oriented blockchain data credibility evaluation method

In the study of trusted platforms for medical services, many scholars use the tamper-evident property of blockchain and consensus mechanism to ensure the trusted storage and processing of on-chain data, but they ignore the basic and important issue of trustworthiness of blockchain medical data sources, i.e., medical data to be on-chain. The traditional data trustworthiness evaluation method monitors the historical behavior of data subjects, service quality and other characteristics, and then grades the trustworthiness of the data generated by them. However, this evaluation method has great limitations for medical data subjects (patients) who are highly mobile. Therefore, this paper proposes a trustworthiness evaluation method that combines skewed distribution and entropy weight method, classifies medical data and divides multiple evaluation indicators, integrates the weights of each indicator and performs statistical analysis and trustworthiness probability calculation on the indicators, so as to obtain the trustworthiness of the data to be chained and improve the quality of medical services.