Asiainfo Ding Tao: Big Data makes medicine smarter

2014 Zhongguancun Large Data day on December 11, 2014 in Zhongguancun, the General Assembly to "aggregate data assets, promote industrial innovation" as the theme, to explore data asset management and transformation, large data depth technology and industry data application innovation and ecological system construction and so on key issues. The Conference also carries on the question of the demand and practice of the departments in charge of the government, the finance, the operators and so on to realize the path of transformation and industry innovation through the management and operation of data assets.

In the afternoon of the government's @big data forum, Ding Tao, a senior advisor to the Business Consulting Department of Trust and Enterprise, brought a keynote speech on "Big data to make medical smarter", interpreting large data from an application perspective. The following is the full text of Ding Tao's speech:

Ding Tao: Thanks for the general introduction of my package, I looked at it, we still have a lot of people sitting here, I believe that the people sitting here must be concerned about medical care and health care, so today I share the main from the application point of view, just now the leaders may from different angles on the big data to do some of their own interpretation, I mainly from the point of view of the application of large data to do some reading.

Let's take a look at this headline is big data to make medical smarter there is a picture below, is a villain holding a question mark, holding an exclamation point to push down the question mark, that is, the first exclamation point represents our confidence in large data, I believe that large data in the future will certainly be in the medical field in more areas to play a role, The question mark represents our current in this initial stage, we let the big data play the role of this road, will face more problems, maybe we will use our confidence, exclamation point for our confidence, step by step to solve our problems. This is my basic view on large data.

Then my share is mainly composed of four parts, one is background analysis, industry focus, the second to see what we have in this industry some of the events, the third is our wisdom in the field of medical research, and finally we briefly mention the topic of data transformation.

The background is that first look at the medical services and expenses of our country, this piece of people mainly look at 2013 years of this situation, In terms of the number of visits to the doctor has reached 5.4 times, the number of the national average, the number of Beijing has not been taken out, the number of Beijing is probably about 7.5 times per capita, this is not related to the environment in Beijing, not to say more. Then look at the hospital patients outpatient and hospitalization costs, this one outpatient fee is 2.06 million, per capita hospitalization costs is more than 7,400 yuan, the cost is quite high. Nationally, the total cost of our health is 3 trillion, which accounts for 5.57% of GDP, and this is a pretty high percentage. Look at our future health risks, this is an aging society as we all know, this will become more and more serious, our elderly people will be more and more, and a Ministry of Health statistics, that is the number of Chinese diagnosed with chronic disease population? More than 260 million people, some of them are high blood pressure, obesity, this number is very large, so that is, because these chronic diseases accounted for 85% of the death rate, and this trend towards the rejuvenation of the population, the proportion of Chinese urban white-collar sub-health is also very high, 76%, this piece of words, It's a health risk figure for our population, the number of our medical-sensitive people, this is 330 million to 603 million, and we're going to lose 550 billion dollars between 2005 and 2015, which is a data. Because today our subject is big data, so many of today's films are using data to speak.

And then look at the health of our IT people, many of you are engaged in IT industry is also more concerned about this, the first overtime is normal, this is a Shanghai company to do, that is, we have more than 70% of the programmers are working overtime, of which 5.7% of the programmers work more than 70 hours a week, another increase in the income, We work overtime tired leg weak, but we do not get the money hand weak, from this efficiency, we actually increase the working hours 21%, income only increased by 5.2%. Which means that there are five major diseases plaguing us, like sudden death, chronic fatigue, cervical spondylosis, sudden death of this piece we all know, early also looked at some data, including many of our large IT companies, such as Baidu, Huawei, like Jinshan, do not know whether these colleagues, there is indeed a sudden death phenomenon, Luckily we did not. In other words, the Shanghai Academy of Social Sciences also has a statistics, that is, the IT industry died in the entire death of the industry is the lowest average age, only 37.9 years old, as we it people, we should understand that income and health is not proportional to, we are busy to pay attention to our own health.

Back to the medical system. Look at the problems we face, from three angles, from the patient's point of view, the doctor is difficult, expensive, medical disorder is everyone knows the problem, there are three long a short, is that we wait for a long time, long queues, and outpatient time is short. In addition, from the point of view of the Doctor's Hospital, the efficiency of his quality cost growth is very fast, and the efficiency is not so high. From the Government's point of view, there is no basis for government regulation, a lot of local governments also found that he also knew there is fraud, there is a hospital sick people reported behavior, but this behavior he has no basis, you have no way to find out, health reform is difficult, now we are entering the deep water, more and more difficult, additional subsidies, There may be many aspects to the root causes of these problems, here are some, not particularly comprehensive, but some of the focus we can focus on, like our medical resources shortage and uneven development, in addition to our drug-curing disease has always existed, in addition to many of our people are heavy treatment of light prevention, We may not pay attention to health care when we are not sick, but I am willing to spend as much as I can in treatment. In addition, we also lack of a number of tiered medical system, our doctor's service radius is also subject to some restrictions.

This is our 18 session of the plenary proposed a number of health reform proposals, looks a lot, the 2014 government work report also specifically for these health reform programs also identified a number of targets, we record a few key words can be, the first is that it has a call five measures simultaneously, 31 linkage, five measures is medical security, medical services, Public health, drug supply, regulatory system, 31 linkage is medical, health care and medicine, there is also the model of grading diagnosis and treatment, now all over the exploration. In addition, we as it people should especially remember, make full use of information means to promote the vertical flow of high-quality medical resources, strengthen regional public health services. Finally there is a doctor to allow more practice, we remember these few keywords on it.

Then he is also promoting mobile Internet medical services from various ministries and departments, such as the State Council and the FDA have introduced a number of measures. The background is so much.

Let's look at what's going on in the industry recently. Let's take a look at our health care ecosystem, which contains the most relevant to our doctors and patients, this is the core, there are some needs, they have different needs, the outermost layer around a lot of institutions, including government, companies, research institutes and hospitals, which are our industrial biosphere, contains a lot of In fact, there are many extensions. Let's take a look at the companies that go into the medical market. We have some operators and some smart wearable devices, and some of the new mobile apps on the Internet, the main position in the traditional medical information vendors, such as Wanda, home purchase and some other manufacturers, He all from the traditional do local information this product to gradually to the wisdom of treatment changes. Including equipment, like Huawei has done some industry solutions, in pushing some of their own ideas. There are also a number of large integrators, who are moving into the medical field.

Internet medicine This piece is heated, we look at the recent investment projects can be seen, currently able to count 8 of this project, a total of 4 categories, the first category is wearable equipment, a total of 16 projects, medical services have 10, as well as mobile medical application category has 13, There are 6 projects for the Health Application project. This is also a better understanding, like Bat is also in the layout of the application of medical care, like Ali recently made a healthy Ali of the app, is the doctor after reading, through the mobile phone shot down, in the online bidding, each pharmacy can carry out snap, the three giants are entering the mobile medical market, in some layout. This is something in the industry.

What are we going to do as asiainfo? Take a look. We are concerned about the health, the concept of big health that covers medical, drug safety, environmental protection, including old-age and so on, we are concerned about health-related areas, at present we may be from the medical this piece into the first, look at our sub-letter team any talk about large data, we have their own perspective, We compare big data to a store, and we do a few things? One is power generation, we are pooling data, we form a power plant of information resources, then we carry on transmission, transmission means that we use these emerging cloud computing such as the Internet facilities, we realize a low-cost transmission of information resources, and we also have to change power, We use large data cloud computing tools to refine these raw data into knowledge and then to process it at a multi-level level, so that this information can be applied to some of our decisions, the final distribution is that we process these things to form this information, to be distributed to the right people to fit the place, the right scene, The last electricity, we put these electrical storage, the various departments, agencies or enterprises can be based on their own needs to facilitate the delivery.

Look at what is medical large data, in fact, the concept of large medical data I have not found a suitable word to describe, here is one, the bottom of this diagram is a diagram, which we wrote a word ourselves, we feel that the medical large data contains at least from the birth of the population to death, the whole life cycle of data, The lifecycle should contain a healthy state and behavioral information for each life phase, for example, from the newborn to the baby to the preschool, he had an act and a healthy state before each stage, and we all had to record it for him, and the data that came out of it was the big health data we wanted.

What are the sources of large medical data, I'm here. There are some from the two levels of the first one it has some basic sources, including four aspects, the first one is the data of the scientific research institution, the second is the data of the reimbursement and behavior of the patient's own activities, and the third is clinical data, This amount of data is still relatively large, the fourth is the data produced by the patient's behavior. On the basis of technical sources, we believe that there are some sources of expansion based on the current technology, including something. The first one we know the internet of things is now developing very quickly, the internet of things in the future everyone may buy some hand ring wear equipment, unintentional will have data generation, will converge to the database inside. In addition, our mobile internet will produce some data, and our traditional Internet, some of our search on the Internet or searching for some health queries, we may be able to bring it together in different ways, so that our entire data source includes tradition and our emerging, which is more , the real possibility is that there will be big data.

Let's see if this data is big enough, how many, here is a general hospital data volume, I only listed three, his data is 30-50gb,li is 50-100gb,ris is 10-30TB, each person together is 750 trillion data volume, A normal CT is 150 trillion, the standard pathological examination of this volume is larger than 5 G, this amount of data is large enough. We look at the life cycle of medical data, the medical data of different data in fact, the country has some different requirements, that is, its time is different, such as outpatient records, save time not less than 15 years, this is a rule. In addition, as in the hospital to save a longer, conditional hospitals, he may be a lifetime to save him. In addition, from online time, image data online data requirements are three years, three years ago can be offline archive, this is its life cycle.

This is based on the amount of data in the life cycle that includes the previous items. Is the population of an average intermediate city, the amount of medical data he can reach, which is estimated in a city of 3 million people, estimated to be 20 years old, with a PB-level amount of data, and in other words, by 2020, The medical data will grow to 35GB, as one report says, IDC recently reported that the digital universe drives data growth in the healthcare industry, which reports data growth of 48% annually.

Medical large Data special I want to be different from other big data, including diversity, privacy. Let's take a look at the value of large data, as President Guo mentioned in 2012, big data is the value of new wealth, more expensive than oil, McKinsey also has a high definition of large data, large data is the means of production. We looked at some reports and also showed that medical data analysis will produce 300 billion of the value of the United States, this is quite large, the data to achieve its value, we think there may be a few steps, the first step of data to become information, is after the initial screening or indicators, it will form a message, Reached a level of initial availability, in addition, from the information to processing knowledge, through some means of excavation through what, we summed up into some knowledge to rule, and finally through the application of knowledge, we can realize our wisdom, that is, from data to wisdom, his value is in the representation of the geometric level of growth.

The characteristics of intelligent medicine, this is a summary of the IBM official website, I think he summed up or more comprehensive, the first is interconnected, he believes that the wisdom of medical care in the future must be interconnected, including hospitals, patients and all the relevant participants are interconnected, to achieve a seamless degree. The second is collaboration, through which intelligent medical care can eliminate islands of information and can achieve a degree of collaboration. Then the prevention, that is, through this prevention, we can carry out their own personal health management, to predict some of the disease, the body of some cases, we can break through the boundaries between urban and rural and large hospitals, we can provide better services to our grassroots people. Innovation, which I think is the most core, all the interconnection, or collaboration or popularization, I think will be through some innovative means to achieve. Finally, the question of security.

To sum up, I think that smart medicine is really a very complex system, system, it involves a lot of things, including the role of many, such as the government, the health Department of various epidemic prevention departments, hospitals and so on, involved in a lot of areas, such as medical care has a lot of professional knowledge, preventive health education emergency also many, involved in the level of Very much, there is a legal dimension to the policy level, there are also our professional and insurance levels, and there's a lot of technology, and we talked about smart medicine, not just a smart medical treatment with big data, he also involves technologies like cloud computing, Internet of Things, and many other concepts, like electronic medical records, Regional medical care is a new emerging concept. In addition, there are a lot of mainline goals like the various considerations, so I think the wisdom of medicine is a very, very complex system.

What do we understand about intelligent medicine? Let's look at the diagram below is that before we do this medical information is good, said that intelligent medical care, mainly from the government, health, hospital from the point of view, from its needs to do this information, and now we have to make a change, we want from medical workers, individuals and practitioners to change, We think that the core of intelligent medicine is not a technical problem, but a thinking, that is, we can use large data thinking to solve all kinds of medical problems, to meet the needs of patients, with a variety of human core demand, promote the industry to achieve industrial value. This is my understanding of the industry.

First look at two cases, the first of this machine, you may have seen, it is called Watson, IBM's Super Robot, it was in 11 in the intellectual competition to challenge themselves, defeated a person's experts, what is his use? Now IBM has invested 1 billion dollars for this super robot, and set up a company, what does the company do? He opened up this ability, for the needs of the enterprise in this calculation, it is a lot of the above, concentrated a lot of calculations and algorithms of some capabilities, so that the United States has an insurance company, he used this to do one thing, this thing he is to help the doctor diagnose the patient's condition, A service for 70 million people in his insurance company, and they've done a lot of trying, like in cancer treatment, we know a cancer from a diagnosis to a cure, a period of about one months to three months, and he uses this to shorten the cycle considerably and shorten it to one day. In addition, he has some applications in other areas of insurance, as well as attempts to prevent fraud.

The second case, we proposed when the big data and artificial intelligence collision after this result will be, the morning listen to Guo Director, is a deputy director of CMC said, Gezelay China visit, also especially to Baidu participated in the situation of intelligent robot, when large data and artificial intelligence then in the medical field what collision? This is a blood collection robot, it can automatically carry out blood collection, this is a remote diagnosis of the robot, he can be placed at home, you have any disease, you can through it with the remote doctor to carry out a dialogue, give you a test report and prescription. The robot called a portable robot called the Big Crow, it was launched by the U.S. Department of Defense, its main purpose is to combat the battlefield of the wounded, as well as remote areas, as well as the space station, astronauts if they are sick can use this thing to diagnose. We have these things, we believe that in the future, we may not have to go directly to the hospital, each home with such a robot doctor, you just put your illness told him he will give you a prescription, I believe that the hospital is difficult to see a doctor expensive, many problems will be solved.

Back to reality, because we talked about a lot of other situations, we return to the state of medical information, I concluded that the previous is our National Health Plan Twelve-Five Planning proposed 35212 this project, the following is my summary of medical information problems, the first problem is that its system is fragmented, The island is very serious, the second is the process is not unified, not standardized, our previous information construction is dominated by the management, the lack of a holistic planning and top-level design, information development is uneven, this imbalance in our east-West information development is very different, even in the same region at various levels of the hospital, Its information level is also very different. We met in Xianyang, his first-level hospital information construction is very good, but you to his township level and even village health room, 90% of the basic information is not, so the difference is also very large in the same area.

And then, based on our research, we propose several directions for the socialization of medical data, the first of which is the pharmaceutical enterprise, which can assist the enterprise in the development of medicine, including some preclinical analysis. The second is from the doctor's point of view, it can help doctors to carry out treatment and a number of ancillary decision-making, the third is from the government point of view, can carry out the control of communicable diseases and the new Agricultural Fund fraud prevention. Four is from the patient's perspective, can do some planning treatment, including some early health management, this is our medical wisdom of several application direction summary.

Here are a few examples, for several scenarios we have done several cases, including disease monitoring, I will not elaborate. How to assist decision-making, and then the monitoring of medication, can be based on individual health conditions combined with information can be different people different doses of monitoring. This is just about the pharmaceutical companies and research institutions of his new drug development, we think this piece can be an application direction? It is because we know that doctors or medical practitioners know that a pharmaceutical product from research and development to our pharmacy this cycle is very long, this cycle is 15 years, is a medical drug research and development is very long, we large data in this area is a lot of play space. And then there's health management, Medicare, we're doing a landing plan, and its core idea is to make sure that the patient and the hospital bed and the doctor and the establishment of the relationship through the health care staff of the two-time comparison to determine whether his hospitals are doing some hanging bed this fraud.

Finally, mention this data to realize, because we also push this idea in the letter, that is, after the data, how we play its maximum value, through the transformation is a very good means. There are actually a lot of ways to do this, you can form some of this report, can also open some of the ability, which is a way to realize, through the realization of the words we can grasp the data can achieve greater significance, that is, we said before our data may play in their own home, now we have to open the data, we play together, The mode of solo Lele we want to become the mode of the public Lele, in this way we play a greater value, the future O2O model is also a means of transformation, we combine the community's information system, with the community around the service agencies, and then through our system to PHI, it contains a knowledge of personal health, Through this understanding we can provide him with a number of personalized services, by the offline service agencies to carry out. This change is given an example, that is, through the collection of equipment to collect some data, what can be changed the way, the first way is targeted to each of us to provide healthy weight loss training programs and fitness programs, In addition, we can use some data with the insurance company of his new insurance for an actuarial and insurance policy to carry out a subsidiary.

Finally, I would like to mention the safety of large data, because Mr Tung has mentioned the safety of the data in particular, and I feel that in the course of the development of large data, we should pay special attention to it.

Finally, we have the following points for the wisdom of large data in the medical profession, we have just talked about the first time that the wisdom of medical treatment based on large data we think that we have just started, at this beginning stage we need people from all walks of life to work together and may go through some long-term exploration. The second is that different regions, depending on the degree of medical information, our wisdom of the entry point may be different, some of us may think that the realization of wisdom must have a prerequisite, that is to say your level of information to achieve a certain degree, in fact, I think it is not so, is different information level of the place, We think that there are also some entry points to the wisdom of it, just to see if we can catch these points.

The third is the wisdom of medical care to emphasize the human needs as the core, change before our thinking, to solve the problem of patients, doctors and managers of the contradictions and problems as the starting point, in line with the national reform of the big goal, with innovative application as the hand, with our intelligent realization of the institutional mechanism of breakthrough, because the institutional mechanism to deepen reform, The road is still very long, we have a large number of information has a very good technology, you can intelligently reflect some of the institutional mechanisms of breakthroughs, and then resolve the problems of health reform, improve service quality.

The last thing I want to emphasize is that we're talking about this big data, many people understand that the big data itself, in fact, I think there may be three aspects, is the data thinking technology, large data cover these three aspects, it provides us with a new view of the world, we have to use this method to solve the problem of the treatment industry. So we should first from the thinking to understand and then guide our medical industry smarter process. Finally, we'll do a sale. Our first sentence is that big data is the foundation of Intelligent Medical treatment, the second is that intelligent medical care is to realize the health and happiness of citizens, the third is that the health and happiness of citizens is the cornerstone of the realization of Chinese dream, so we can draw large data is a cornerstone of the realization of the Chinese dream. If so, I feel honored to have such a mission as an IT person. Thank you.

(Responsible editor: Mengyishan)