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With the rapid development of healthcare big data and artificial intelligence technology, how to utilize the massive medical data generated based on clinical diagnosis and treatment has become an important issue to be solved in the field of clinical research. Clinical diagnosis and treatment data is an essential part of healthcare big data, and also the main field of healthcare big data research. With the continuous deepening and extensive development of informatization, hospitals have accumulated a large number of patient-centered clinical diagnosis and treatment data. Deeply mining and analyzing these data through big data technology can provide reference for precise diagnosis and treatment, and standardized prevention and control of diseases. However, conducting relevant research still faces many difficulties and blockages, such as the increased risk of data leakage or abuse, and the difficulty in implementing informed consent. To safely, legally and efficiently utilize clinical diagnosis and treatment data to conduct clinical research and fully tap into the value of these precious medical resources, a tertiary hospital in Beijing has built a research big data platform and developed relevant systems to effectively solve the problems of blockages and difficulties in the application of rich clinical resources to clinical research, and improve the service quality of medical institutions and the conversion rate of scientific research achievements. By introducing the key points and management methods in the implementation of clinical research based on the scientific research big data platform, analyzing and exploring the existing problems and improvement measures, this paper aimed to provide theoretical basis and system reference for high-quality and efficient health and medical big data clinical research, inspire and promote the continuous improvement of medical research management, and promote the development of medical and health science and technology innovation.
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Deep integration of healthcare and prevention in public hospitals is not only a basic function played by hospitals in their public health services, but also an inevitable choice to meet the health needs of the people in their life span. The authors analyzed the current situation in healthcare and prevention integration in Wuhan in recent years, focusing on such problems existing in the construction of healthcare and prevention integration in public hospitals, as unclear functional positioning of medical prevention integration in public hospitals, insufficient refinement of healthcare and prevention integration policies, delay in the construction of public health informatization, and poor public health awareness of medical personnel. In view of the above problems, the authors put forward the following improvement suggestions: optimizing the policy environment of healthcare and prevention integration, strengthening the leading role of the hospital management, building a hospital public health big data platform, mobilizing the initiative of clinical technicians, and improving the work identity of hospital public health workers.
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In order to effectively integrate scientific research data resources and improve data utilization, the National Clinical Medical Research Center had built a "3321" -integration big data sharing innovation platform. By providing full support to scientific research, sorting out the distribution mechanism of achievements, and formulating authority management norms, the big data platform had solved the weaknesses in data sharing ability, sharing willingness, and sharing security, giving full play to the effectiveness of the clinical research big data platform. By February 2022, the center had collected more than 1.04 million elderly patients data through the big data platform, as well as carried out 75 scientific research projects, and established 10 large population-based clinical research queues. The big data platform had realized full coverage of major diseases in the field of geriatric diseases, promoted the high-quality construction of the national clinical medical research center, and improved the scientific research and innovation ability of the cooperative units.
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Objective To investigate the epidemiological characteristics of acute myocardial infarction (AMI) in Yichang City in the last 5 years, and to provide a basis for targeted prevention and treatment. Methods The annual estimated percentage was used to evaluate the trend of morbidity and mortality of AMI by using the monitoring data from 2015 to 2019 from the health big data platform of Yichang. Results There were 1 976 new cases of AMI in Yichang from 2015 to 2019, with a crude morbidity of 41.96/100 000, and standardized morbidity of 87.52/100 000. Among them the crude incidence rate in males was 57.69/100 000, and 29.84/100 000 in females. The difference was statistically significant (χ2=15.76, P2=45.65, P<0.001). The morbidity and mortality of males and females were increased with age. Conclusion From 2015 to 2019, the morbidity of AMI in Yichang was at a moderately low level in China, but the mortality was higher than the national average. The morbidity showed an upward trend, with men and elderly people aged ≥60 being more serious. Appropriate intervention measures should be taken for different groups of people to reduce the incidence of AMI.
RESUMO
The paper analyzes the current situation of integration in healthcare industry and the difficulties in the construction of healthcare big data platform,proposes the construction of healthcare big data platform by Cloud P2P network,and the platform framework including the five layers of resource layer,sense/access layer,transfer layer,service layer and application layer.