When did the concept of healthcare big data emerge?
Early on, big data in healthcare was not a separate industry, but more of an "element" of the industry. In the late 1990s, old information technology vendors, including Neusoft, Weining Health, and Wanda Information, established a foothold in public hospitals, laying the foundation for the development of medical big data in China.
After more than a decade of exploration, the domestic medical big data industry chain has been initially formed. The policy of regulation and integration of medical big data has been gradually promoted, and the industry has also seen the emergence of startups that store, mine, analyze, and apply medical big data. But overall, the development of medical big data in China is not fast.
This is partly due to the fact that the total amount of big data in China is large, but the quality is low, decentralized, and incomplete; on the other hand, due to the highly policy-driven nature of the healthcare industry, the state's pace of control over big data in healthcare is still relatively conservative.
Everyone's Health has made an inventory of domestic enterprises in the field of medical big data, and found that these enterprises present three major characteristics, and in the blue sea of medical big data, there is still a "gold mine" that needs to be mined.
According to the medical big data industry chain, EEU big health will be sorted into three dimensions: the basic layer, technology layer and application layer. The foundation layer is responsible for data collection and conversion, the technology layer focuses on data storage, processing, cleaning and analysis, and the application layer focuses on the scenario application of data value mining.
In the inventory of Yeeo Big Health, there are some enterprises such as Tencent, UW Genetics and other enterprises in the three dimensions are covered, there are also, for example, Bozhi medical cloud and other enterprises focus on medical big data part of the link.
From the perspective of the above three dimensions, the difference in enterprise scale is more obvious. The base layer is mostly concentrated in listed companies, and most of them are medical devices and medical information technology companies. As most of the newly established startups in recent years have not spent much time on data precipitation, this behavior is even contrary to the direction of its commercialization, so the "supply side" of healthcare big data is concentrated in the HIT vendors connected to the physical hospitals, and medical devices, especially smart wearable devices.
Looking at the technology layer, most of the companies are providing services in the form of healthcare technology solutions. This type of company is usually first based on a certain type of disease, and AI technology and data processing and analysis capabilities as a technical barrier, the service covers medical institutions, pharmaceutical companies, insurance and other major players. The difference is that the segmentation and scope covered by each company varies. Interestingly, none of the companies in the technology tier have high financing rounds, with 23 of the 33 in Series B and below, and only 3 listed companies.
This phenomenon is mitigated in the application tier, but the volume divergence of companies is still evident. In the application layer statistics of 34 enterprises, B round and below companies occupy 50%, however, the table appears a lot of listed companies. This on the one hand reflects the listed companies medical gradually began to notice the medical big data this piece of "fat meat", on the other hand, also inevitably exacerbated the degree of competition in the medical big data application layer.
Obviously, compared to the application of AI in medical diagnostic aids or Internet healthcare, medical big data is far from reaching the node of the outbreak, compared to other industries, the degree of application is not as mature as retail, finance and other industries. But according to IDC Digital's predictions, by 2020 the amount of healthcare data will reach 40 trillion GB, 30 times more than in 2010.
This is a potential gold mine, so what are the application scenarios for big data in the healthcare industry? Yeeo Big Health has summarized six directions.
1, big data + medical research and development.
In the initial application, medical big data in the shortening of the R & D cycle, reduce R & D costs, processing patient data, simulation of the disease model, etc. have excellent performance, which gives the entrants to enhance a lot of confidence.
2. Big data + clinical decision making. In the structure of the information construction of medical institutions, medical big data can play a good supporting role in clinical decision-making. Currently, medical big data is used more in assisting clinical precision medicine, disease risk prediction, such as calculating the probability of disease and time nodes before a patient has a certain symptom, so as to carry out early intervention in the clinic.
3. Big data + Internet healthcare. There have been industry participants who have said that the core content of Internet + healthcare is big data. In this scenario, companies are more likely to combine big data with Internet hospitals, pension, health management and residents' electronic health records, and assist the government in regional health information management.
4. Big data + medical insurance.
In addition to helping health insurance accurate service, accurate management and scientific decision-making, in health insurance, big data also has a huge space to play in, for example, the design of single-disease, DRGs, and other payment standards, improve drug data and unified standards, and improve the health insurance intelligent monitoring system.
5, big data + health management.
Health Management This fire is not accompanied by the rise of big data and burned up, but accurately, big data so that the "accurate health management" began to become a generation of the industry Netflix, which players, including Miao-Health, health benefits, and other companies. The players include companies such as Wonderful Health and Healthy Benefits. Today, big data health management is based more on EHR (electronic health record) and EMR (electronic medical record) organization.
6, big data + intelligent diagnosis. Medical imaging and auxiliary diagnostic segmentation application is one of the most mature landing scenarios of medical big data, but for the current AI + medical enterprises more distressing thing is that, on the one hand, the magnitude of the data is not large enough, on the other hand, the data silo situation is serious, which is a big constraint on its development. But in any case, big data + intelligent diagnosis is still widely viewed by the industry. In the commercialization of landing, the pace of these enterprises is also relatively fast.
Overall, there are many application scenarios for medical big data, but the degree of application is mostly in the middle or even weak; in the above table of nearly a hundred medical big data enterprises, there are only Ding Xiangyuan, micro-medicine, zero kryptonite, and Si Di stepped into the ranks of the unicorn; in addition to this, there are only a handful of new capitals focusing on medical big data in the country.
This series of status quo actually shows that medical big data is a blue ocean, and under the blue ocean lies a huge commercial value.
In recent years, as China's medical demand rises, medical institutions, pharmaceutical companies, insurance companies are constantly looking for new opportunities for industrial upgrading, and the development of medical and health big data is like a crackerjack. The EEU Big Health Channel has planned a series of interviews and selected reports on medical data, focusing on the disruption and change brought by big data to each link of the medical industry chain.
If you have a recommendation for a company, please contact Mr. Guo Mingzi, the head of EEI Big Health Channel (WeChat: Lelion8742390).