Medical big data anti epidemic show the industry difficulties under the new infrastructure tuyere to be solved

category:Finance
 Medical big data anti epidemic show the industry difficulties under the new infrastructure tuyere to be solved


At the same time, with the opening of new infrastructure, medical big data also ushered in new development opportunities.

According to the public information of prospective Industrial Research Institute, medical big data can be widely used in clinical medicine, health management, public health emergency, epidemic prevention and other industrial fields. Measured by the pillar industry of medical big data, it can drive a trillion market scale.

Compared with the cognitive changes before and after the epidemic, medical institutions further recognized the big data, public health management gradually received attention, and the focus of medical treatment was closer to disease prevention.

Chongqing Liangjiang New Area, Guangzhou respiratory health research institute, and Tianpeng big data also jointly build the Tianpeng health care big data and artificial intelligence application innovation platform project. Relying on the construction of national respiratory disease big data center, mature product solutions and landing demonstration have been formed, and relying on the industry status and influence of Guangzhou respiratory health research institute, it has expanded to regional leading hospitals.

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

The construction of big data in the medical field shows the trend of specialization and regionalization. On the one hand, in order to meet the requirements of medical application scenarios for data depth and accuracy, it is necessary to collect and manage data from specialized diseases; on the other hand, in line with the requirements of resource sinking of medical reform, it is necessary to take the construction of regional specialized big data cloud platform as the foundation.

The business model of data realization is still in the exploration stage. The main direction is based on the application of specialized big data and the big health service for specialized patients. At present, the medical big data industry is still in its infancy, and the infrastructure platform construction is just needed by the hospital and the government, occupying the main market share.

On the other hand, there are also many bottlenecks in the development of medical big data. Standardization, diversification, data security and other issues have become the key constraints.

From the government level, it is necessary to gradually reserve medical big data as strategic resources; realize data sharing; the government needs an effective platform and tool for supervision and decision-making; from the hospital level, there are many data sources, heterogeneous and difficult to collect, the standard system of medical big data has not reached the application level, the lack of big data processing and AI technology for post structure and natural language Speech processing can not effectively use big data; from the patient level, medical big data comes from patients and should return to patients, but at present, patients do not get their own data in time and effectively guide health management, there are pain points at the end of patients.

The novel coronavirus infection is also different from others. Some people say that they are suffocating, some say they can not breathe. Some say that the chest is pressed by stones, and how to standardize the data. Of course, there are data from information system, outpatient service and different data. How to collect and standardize these data is the pain point and difficulty.

In addition, novel coronavirus is detected in different and all aspects, data from different sources, tested data, and data such as CT, whether there is a new coronavirus infection, and different data will involve data cleaning, data, useful and useless, and selectively find suitable data. Many data are related to each other, which is data integration.

In addition, the security of medical data is equally important. There are many sources of data. How to protect the privacy of patients and the confidentiality of treatment plans are also important. Of course, there are also data storage problems, some of which are technical problems and some of which are non-technical problems.

Source: responsible editor of 21st century economic report: Yang Bin_ NF4368