What changes will big data bring to the health industry_Data Analyst Exam

Big data can more scientifically prove the effectiveness of drug use and guide the direction of medical policy.

In 2012, Li Lanjuan once led a team to do a topic related to the transmission rate of hepatitis B, and collected 1,000 physical examination data samples from Zhejiang. 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 included the hepatitis B vaccine in its immunization program. Through the analysis of big data technology, Li Lanjuan's team verified the effectiveness of the drug, such analysis will give the country to develop 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 to Predict Disease

With big data analysis, the "see the doctor" model is shifting to "be watched by the doctor" -- your wearable device can do that 24 hours a day. Your wearable device can do a 24-hour "checkup" for you, and this all-data model is so low-cost and efficient that it's available to almost everyone.

"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 1 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 drug 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 aspect of the disease --

American Anmol Madan and the team founded a company that focuses on research through the analysis of data on cell phones, 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 annual value.

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