Personal health revolution in the age of data "cure" large data

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It giants flock to public health care

In Victor Maire Schoenberg's Big Data age, there are two cases where the combination of big data and public health is impressive:

Mr. Jobs, who died 8 years after his cancer, almost created a miracle in the history of pancreatic cancer. Mr. Jobs was reported to have paid a large amount of money during this period to obtain his own data document, including the entire genetic code. By doing so, doctors can use the specific genetic makeup of joe and large data to administer the desired effect and adjust the medical plan.

If the case is individual, then a case of group value is Google's successful prediction of a flu outbreak. A few weeks before the 2009 swine flu outbreak, Google's observations, analysis and modelling of people's online search records showed that their forecasts were 97% more relevant to official data and judged more timely than the CDC.

From personal health management to public health management, large numbers of changes in personal care and valuable early-warning capabilities are attracting the IT giants to "marry" with medical care. For example, in China, search giant Baidu's move in this regard is worth the future development reference.

On the one hand, Baidu released large data engine, will open cloud, data Factory, Baidu brain three components, including the core of large data to open up, to achieve data mining all walks of life, the use of "Data Factory" and "Baidu Brain" analysis of data, output analysis for their own and partners to provide solutions. In February 2014, the Beijing Health Planning Institute said that the system will combine the qualified information of the medical and health institutions, the access information of the resources with Baidu's powerful network search ability, background information screening and filtration technology, in order to make public emergencies, epidemic outbreaks, health service industry development, Analysis and early warning are provided in the fields of population flow, which is the basis for scientific decision-making.

On the other hand, to create a "soft and hard cloud" combination of intelligent health care mobile platform, records of people's daily life style, such as daily exercise and exercise time, sleep amount, sedentary time, height, blood pressure, these quantified data with a long time and trend, will become an important basis for the analysis of the disease.

With large data technology, we can imagine such a medical scenario from production data, to mining, managing, analyzing information, and ultimately providing solutions. If millions of people suffer from heart disease every year in the world, large data can find common denominator from these people and realize early treatment early warning. From a health standpoint, early prevention will greatly improve people's ability to fight disease. From the perspective of insurance companies, it can also greatly reduce the rate of payment.

What is the spark of big data and health?

Using "black box" to express the theory of large data meaning is very image-the problem from a port into the middle is a collection of thousands of data "black box", after a computer engineering "purification", "drill", useful information from another port.

There is no doubt that when big health passes through the "black box" of large data, it combines the great thrust of "breaking the Tradition" and "The Future of Wisdom". The combination of the two produces some of the brightest sparks worth paying attention to.

The first spark is the ability to exert force in the whole process of a person's state of health, and prediction is the core point. Health care is highly "personalized" and must be individualized. The big data here is that one is based on predictive personal health management, which is the most common application area for wearable devices and health apps, and the other is the monitoring, evaluation, rehabilitation and nursing of individual patients.

The second spark is that large data is the platform of different systems to "get through the tool", so that the flow of information more carefree. These system platforms include hospital doctors, patients or sub-health people, pharmaceutical companies, regulatory departments and so on. To break the traditional medical treatment, patients only have to communicate with doctors in the passive situation.

The third spark is that the medical model is changed, and health management and treatment will break the space constraints. The use of large data, future inspection results, etc. can be analyzed by intelligent machines. A global study shows that tele-monitoring after discharge can reduce the patient's medical expenses by 42%, and the doctor's time interval will be extended by 71%.

But we also need to see more real challenges in the digital process of health care management. The medical professional barrier brought by the complicated and professional information in health care is the first challenge. This is also the resolution target of the "slow data" era after large data. Large data companies need to be combined more closely with practitioners in the healthcare industry to discover the value of large volumes of data.

Second, the existing fragmentation of medical information. Even in Beijing at the same level of hospitals, the patient's diagnosis and treatment information can not be shared, not to mention the whole country. Hospital internal information, in most hospitals or singles alone in the situation, a few such as Peking University People's Hospital, Beijing Union Hospital consciously build a medical large data information platform. There is no unified, normative platform, the future of data integration is bound to face problems, "black box" function will be affected. This is also mentioned in Beijing Wei planning and Baidu Cooperation is an important inducement, only through the unified large data engine platform to achieve unified data management, to achieve greater value of the release.