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Medical Sports Data Privacy Protection Method Based on Legal Risk Control
Author(s) -
Liqiang Jia,
Wei Fan
Publication year - 2021
Publication title -
journal of healthcare engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 29
eISSN - 2040-2309
pISSN - 2040-2295
DOI - 10.1155/2021/6630429
Subject(s) - standardization , status quo , computer science , harm , control (management) , big data , information privacy , risk analysis (engineering) , information leakage , order (exchange) , computer security , data protection act 1998 , data mining , business , psychology , social psychology , artificial intelligence , economics , market economy , operating system , finance
With the continuous development of computer and network technology, the amount of information storage in medical information system is more and more large, which is prone to the problem of privacy information leakage, resulting in irreparable harm. In order to solve the problem of privacy leakage in the medical environment, a new privacy rating method is proposed according to the actual situation of the medical environment. The big data technology is used to effectively mine, analyze, integrate, and reuse medical data, and a new improved model is proposed. At the same time, the medical information system applying the improved model is designed according to the complex actual needs. The purpose of this paper is to correctly understand the positive role of medical sports big data (BD) research in the medical field and standardize the behavior of medical staff. On the one hand, it can improve the safety awareness of patients and enhance the standardization of medical treatment environment. This paper will analyze the meaning and research status of medical data from the perspective of legal risk control, focus on the status quo and existing problems of medical sports data privacy protection, and put forward positive countermeasures and some practical solutions. The results show that the medical sports information data has certain regularity and particularity, ease to spread, and mining. Hospitals and medical staff should make the areas and items restricted by law clear, standardize their own behaviors, constantly sum up experience, and actively improve and modify relevant measures.

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