1.2. Market Sore Spots

There are a lot of sore spots in the healthcare industry itself, such as aging, sub-health and medical resources inequality, which have posed to be a great challenge to the human society. Unfortunately, it is difficult to solve these problems due to many factors, such as the unbalanced allocation of resources, the low level of intelligence of the information system, the information barrier between medical institutions, the high cost of training healthcare workers, etc.

1) Individuals lack of retroactive right, knowing right and access and control right over their own medical data

Medical data are generated from users, but most of the data are stored in medical institutions. Users do not know the medical information, nor can control the information. When a patient sees a doctor, only limited information can be referenced, which often increases the difficulty of clinical decision-making and is not conducive to the patient's disease diagnosis and treatment process.

Moreover, users are not able to enjoy the benefits generated by their own medical data research. In 2005, an American leukemia patient's blood contained a biological mechanism that could cure leukemia. Without prior notification, his treatment medical research institute developed relevant medical techniques by his medical data and benefited billions of dollars. In comparison, the data stored in the blockchain can be traced back by the entire chain. Users have full control right and knowing right about their own data, and can enjoy the benefits brought by the research of the medical data.

2) The data security problems are the major concerns, and it is getting really serious due to the fast growth of medical data, health information and centralized storage methods.

In the typical situation, most of the medical data and health information are stored in a data center, so the data are easily damaged by accidents such as malicious tampering, hacker attacks, natural disasters, etc. With the speeding up of the informatization of medical institutions, the hidden dangers of such centralized storage in data center are increasingly getting higher.

3) It is difficult for medical data, health information to be effectively shared and utilized due to the isolated data islands.

Due to historical reasons, there are information barriers between medical institutions, and their data cannot be communicated with each other. Medical data also cannot be effectively integrated and utilized. When users seek cross-hospital treatment, their medical history is difficult to obtain and retrieve.

Centralized storage also can hinder the efficiency of data research. For security reasons, it needs lengthy procedures for recording and filing users' medical data and for research institutes to transfer these data. However, the distributed storage data of the blockchain not only can ensure the security, but also can real- time transfer the data from the entire network.

Google once detected signs of flu outbreaks in some areas through users' search behaviors, and then it informed the relevant medical institutions to prepare flu drugs in advance. At present, in a typical clinic, a flu-receiving patient will take up to three months to report feedback for any signs and symptoms after diagnosis and observation, which might miss the best prevention and treatment period. The domestic SARS and flu outbreak also exposed the low efficiency and flaws of centralized medical data

4) Contradiction exists between the outburst of personal health management demand and the

effective management of health information.

As the saying goes, "the best doctor helps people to prevent diseases". As people's living standards improve, the demands for better health management also increase. Health management is the premise of disease prevention, and the premise of achieving effective health management is having stable monitoring sources of physiological data. Patients with acute and chronic disease, middle-aged group, seniors, and sub-health people all have high demands for an effective health management system. On the other hand, meanwhile, healthy people also have demands for stable health management.

The problem is that under the current health information management, users' previous medical records can only be accessed when the data are stored at the same hospital. But more diseases are related to the personal's past history and genetic information. The current data management mechanism is unable to establish such an exclusive medical file for a user, let alone using Al to analyze the user's health situation.