Medical Big Data Epidemic Prevention "New Infrastructure" Outlet Difficult To Be Solved

In the fight against the new crown pneumonia epidemic, the value of medical data is highlighted, but there are still many problems to be solved in order to give full play to its value and function.

? ? ? The establishment of an epidemic prevention system for infectious diseases such as scientific research, diagnosis and treatment, prevention and control can be covered by hospitals and communities at all levels, and grid management should be carried out. The disease screening, prevention and control and patient management will be lowered to the grass-roots level. Epidemic surveillance and analysis, virus traceability, prevention and control, resource allocation and other public health and epidemic prevention systems will directly affect the epidemic prevention effect; and the major risks for public health will be judged. Evaluation, decision making, prevention and control research can control the epidemic from the source.

The new crown pneumonia epidemic is a respiratory disease, respiratory diseases due to high incidence, heavy burden of disease, health threats to the population and so on, has become an important issue of global health care and public health.

? ? ? Zhong Nanshan, director of the Chinese Academy of engineering and director of the National Center for respiratory diseases clinical medical research, told reporters including the twenty-first Century economic report that China has achieved some achievements in the prevention and treatment of the new crown pneumonia. The epidemic was basically controlled at the end of February this year and early March. This is mainly based on the guiding ideology of prevention. Artificial intelligence has also played an important role in the prevention, control and treatment of new crown pneumonia.

For example, he pointed out that the authoritative articles published in the lancet magazine predicted that the highest number of patients in China had reached 170 thousand, while their team used artificial intelligence to predict, and the positive and negative factors such as government intervention and Spring Festival abortion were added to the analysis. The model prediction should be 60 thousand to 70 thousand people, which is very close to the real data.

Big data for medical treatment

After the outbreak, the importance of medical data has been improved. At the same time, with the curtain opening of the new infrastructure, medical big data also ushered in new development opportunities.

According to the open Industry Research Institute, medical data can be widely used in clinical medicine, health management, public health emergency, epidemic prevention and other industrial fields. The calculation of the pillar industry of medical data can drive trillions of market scale.

The outline of "healthy China 2030" clearly defined the development of health industry as one of the five tasks of building "healthy China", and put forward the strategic goal of developing the health industry into a pillar industry of the national economy. In 2020, the total scale of health services reached 8 trillion, reaching 16 trillion in 2030, and GDP accounted for more than 10% in the whole year.

The new infrastructure projects will become the growth point in the future, the degree of medical informatization will be increased, and the new capital construction mode will gradually take shape. The state will intensify the construction of hospital information in electronic medical records, smart hospitals and DRG, involving new models such as medical consortium and new County medical and health service system. The acceptance of big data by medical institutions is gradually improving.

Compared with the cognitive changes before and after the outbreak, the medical institutions recognized the big data, and the public health management was gradually taken seriously.

Lu Guanglin, chairman of Guangzhou Tian Peng Computer Technology Co., Ltd., told the twenty-first Century economic news reporter that the revelation of this epidemic to the medical big data industry focuses on the construction of big medical data, breaking all kinds of policies and trade barriers, helping the government and hospitals to make decisions, and effectively helping the health care workers and patients to carry out digital health management.

Chongqing Liangjiang New Area, Guangzhou respiratory health research institute, and Tian Peng big data also jointly build Tian Peng health care big data and AI application innovation platform project. Relying on the construction of national respiratory disease data center, a mature product solution and landing demonstration has been formed. Relying on the industry status and influence of Guangzhou Institute of respiratory health, the development of regional leading hospitals is expanding.

We will provide professional support from the leading hospitals, cut through the respiratory field, and jointly push forward the infrastructure construction of the medical data center, forming a comprehensive application of clinical, scientific research, public health emergency, infectious disease prevention, and gradually developing data operations for the government, hospitals and patients.

The medical big data industry is still in its infancy. The construction of the basic platform is just needed by hospitals and government, occupying the main market share.

The construction of big data in the medical field shows specialization and regionalization. On the one hand, in order to meet the requirements of data depth and accuracy in medical application scenarios, data acquisition and management should be carried out from specialist diseases. On the other hand, in line with the requirements for resource subsidence in medical reform, it is necessary to build a regional specialist data cloud platform.

Medical big data will play an important role in the field of public health. Based on the integration of medical, public opinion, disease control, emergency, public safety, telecommunications and other data, the existing problem of medical prevention and split is changed, and preventive preventive and epidemic based on medical data and integrated emergency infrastructure are established. The state will focus on building a new generation of public health emergency and epidemic prevention platform.

The business model of data realisation is still in the exploratory stage. The application of specialist data and the major health services for specialist patients are the main directions. At present, the medical big data industry is still in its infancy. The construction of the basic platform is just needed by hospitals and government, occupying the main market share.

Industry pain points and difficulties to be solved

On the other hand, big data also have many bottlenecks. Standardization, diversification, data security and other issues have become the key to restricting development.

? ? From the government level, we need to gradually take the big data as a strategic resource to reserve; we need to achieve data sharing; the government needs effective regulatory and decision-making platforms and tools; from the hospital level, there are many heterogeneous data sources, the standard system construction of medical big data has not reached the application level level, the lack of big data processing and AI technology for post structured and natural language. Word processing can not effectively make use of big data; from the patient level, medical data come from patients, and should be returned to patients. But at present, patients can not get their own data timely and effectively guide health management, and there is pain point in the patient's side.

Zheng Jinping, deputy director of the Guangzhou Institute of respiratory health and deputy director of the national respiratory disease clinical medical research center, analyzed the difficulties and pain points of the medical big data industry in twenty-first Century, including the data authenticity and possibility. If the data is not true, or the data in question can not be seen in time, this data is invalid or not sufficient and effective data. This is the source of data.

There is also the problem of data standardization. The same diseases, such as dyspnea, such as new coronavirus infection, pneumonia patients, dyspnea description are different. Some people say that gas is suffocating. Some say that they can not breathe. Some people say that there is stone pressure on the chest and how to standardize the data. Of course, there are data from the information system, from the outpatient and different data, how to collect and standardize, this is pain points and difficulties.

In addition, the problem of data diversification, data from different and various aspects, tested data, checking data, such as CT, testing lymphocytes, whether there is a new coronavirus infection, and having different data, involves how to clean up data, what data is useful, what is useless, and selectively finds suitable data. The connection of numerous data and correlation is the integration of data.

In addition, medical data security issues are equally important, data sources are numerous, how to protect patients' privacy and protect the confidentiality of treatment protocols. Of course, data storage problems also exist, some of them are technical problems, others are non technical problems.

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