Big data, what changes to the health industry_Data Analyst Exam
You send every microblogging, play every phone call, may be able to warn you whether there is a risk of infected epidemics ...... This is not science fiction, which is the whole world has begun to carry out the big data precision medicine.
A few days ago, the first hospital of Zhejiang University officially set up a "precision medicine center", academician of the Chinese Academy of Engineering, director of the State Key Laboratory of Diagnosis and Treatment of Infectious Diseases of the first hospital of Zhejiang University, director of the Collaborative Innovation Center for the Diagnosis and Treatment of Infectious Diseases, Prof. Li Lanjuan, made a special report on the topic of "health care and big data and precision medicine". "The special report.
"The popularization of precision medicine big data is bringing about changes in China and even the global health industry." In an exclusive interview with Qian Daily, Li Lanjuan said that in the near future, precision medicine supported by big data will customize treatment plans for every patient, and it will also change the pattern of the country's medical investment.
Precision medicine
Provides personalized treatment
Big data technology, which is capable of analyzing a large number of complicated data sets and discovering effective links between diseases and treatments, will change the traditional treatment plan.
The U.S. has come up with a plan for precision medicine, which uses the analysis of big data to identify personalized flaws and to truly treat the symptoms of a disease, depending on the individual. This approach helped Steve Jobs extend his life by several years.
Our country's precision medicine research, too, is actively following suit. in July 2014, Li Lanjuan and her team published a treatise on scientific research results in Nature, revealing the secrets of intestinal flora and cirrhosis of the liver, which gave new ideas to global medical science and technology research.
Many patients with cirrhosis have been treated with antibiotics, but Li and her team found that this did not bring good results because the antibiotics not only killed the harmful bacteria in the intestines, but the beneficial bacteria were also killed.
The intestinal microorganisms are indispensable "organs" that provide nutrition to the human body and regulate the development of the intestinal epithelium and innate immunity, so she focused her attention on the "intestinal flora," and after nearly three years of research, they collected 181 samples of Chinese human intestinal flora. After nearly three years of research, they collected 181 samples of Chinese intestinal flora, including 98 fecal samples from patients with cirrhosis and 83 from healthy volunteers.
The team used next-generation sequencing technology and big data analysis to produce nearly 860GB of sequence data, and found 28 types of "bad bacteria" that are closely related to cirrhosis patients; data comparison also showed that 38 types of "good bacteria," which are closely related to healthy people, were not found in patients with cirrhosis, while 38 types of "good bacteria," which are closely related to healthy people, were found in patients with cirrhosis. The data also showed that 38 "good bacteria", which are closely associated with healthy people, were present in very small amounts in the gut flora of cirrhotic patients.
This means that future treatments for cirrhotic patients can be more precise, "We will replenish cirrhotic patients with more 'good bacteria' and kill the excessive 'bad bacteria.' " Based on pharmacogenomics, Li Lanjuan said, this work can also be done with great precision, "applying the right drug, the right dose, for different patients."
"Fine-tuning"
Surgery
Big data technology has already begun to be used in surgery to help patients get more efficient surgical outcomes.
Professor Zheng Shusen, an academician of the Chinese Academy of Engineering and president of the First Hospital of Zhejiang University, is a renowned organ transplant expert in China. So far, he has led a team that has successfully performed more than 200 living liver transplants.
The liver is the blood-forming organ of a human being, "commanding" thousands of blood vessels, and it is difficult to operate on the liver.
With advanced digital technology support, Zheng Shusen's team was able to utilize virtual reality software to view various structures in the patient's liver before and during the living liver transplant. The big data analysis was also able to accurately calculate the portion of the liver that needed to be transplanted to ensure, on the one hand, that the recipient was provided with an adequate blood supply and was able to survive; and at the same time, assessing whether the recipient's remaining liver would be able to grow a new liver within six months to ensure that it would resume normal liver function.
Around the world, surgical instruments with big data processing capabilities have become powerful assistants to surgeons. For example, in surgery to remove tumor tissue, the biggest challenge surgeons encounter is whether they can cut the cancerous tissue cleanly in one operation. Nearly one-third of surgeries like those for breast cancer tumors can't manage to erase all traces of the tumor.
Not long ago, Zoltan Takats, of Imperial College, University of London, explored a "precision surgery" that uses an advanced weapon called the iknife, which installs sensors and mass spectrometry analyzers in front of a traditional scalpel, and the iknife can tell you the boundaries of the lesion and the nature of the lesion in the first place.
Big data
Guiding healthcare policy
Big data can more scientifically demonstrate the effectiveness of drug use and guide the direction of healthcare policy.
In 2012, Li Lanjuan led a team to do a project related to the transmission rate of hepatitis B, and collected data from 1,000 medical checkups in Zhejiang province. Through analysis, it was found that the hepatitis B infection rate of samples above 20 years old (born in 1992) was 8-10 percent, while the hepatitis B infection rate of samples below 20 years old was less than 1.5 percent.
Why is there such a big difference in hepatitis B infection rates when there is only a one-year difference?
The key word is 1992, the year in which the Ministry of Health incorporated the hepatitis B vaccine into its immunization program. Through the analysis of big data technology, Li Lanjuan's team verified the effectiveness of the drug, and such analysis will give the country to formulate public **** health policy, bring scientific guidance.
"If China continues to maintain full vaccination of newborns against hepatitis B, while adults also receive hepatitis B vaccine as soon as possible, then in ten years, China will get rid of the hat of hepatitis country." Li Lanjuan said.
Developing big data
Predicting disease
With big data analytics, the "seeing the doctor" paradigm is shifting to "being seen by the doctor".
"The long-term goal of precision medicine is to manage everyone's health." Moving forward, Li Lanjuan's team will create a cohort of volunteers in Zhejiang, numbering more than a million people, who are willing to ****enjoy their genetic data, biological samples, life information, and all their electronic health information.
This is a new research model that incorporates participants, responsible data*** sharing, and privacy protection. Based on this big health data, the team at ZJU1 will be able to do a series of new studies, such as pharmacogenomic studies, where doctors can more accurately prescribe the right medication and the right dosage for each patient; for example, setting new treatment and prevention goals for patients.
The world's most developed medical industry, the United States, in the field of medical entrepreneurship has sprung up a number of high-tech products based on big data, to do the prevention of disease --
American Anmol Madan and the team founded a company that focuses on the study of cell phone through the analysis of the data, predicting the owner's disease.
After collecting and analyzing more than 320,000 hours of data from the cell phones of experimental participants, they were eventually able to model people's phones to predict colds, mental illnesses and more. For example, when people are depressed, they can usually be seen to change in their interactions with others, and daily data analysis was able to capture those changes. In testing, the app was able to correctly determine 60 to 90 percent of people's daily physical symptoms and general breathing conditions, while sending notifications of these changes to the owner and, in the future, to friends or family.
Deeply exploiting big data to predict disease also has the potential to dramatically reduce the cost of health care. The McKinsey Global Institute reports that if the U.S. healthcare industry were to utilize big data effectively, it could reduce costs by about 8 percent, creating $300 billion in value annually.
"In China, big data will also influence specific policies for healthcare reform, such as healthcare insurance investment.
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