Big data can show the effect of medication more scientifically and guide the direction of medical policy.
In 20 12, Li Lanjuan led a team to do a project related to the infection rate of hepatitis B, and collected 1000 physical examination data samples from Zhejiang. Through the analysis, it is found that the infection rate of hepatitis B is 8%-1992 in samples over 20 years old; In the samples under 20 years old, the infection rate of hepatitis B is less than 1.5%.
Why is there such a big gap in hepatitis B infection rate when there is only one year difference?
1992 this year is a key word. 65438-0992, the Ministry of Health brought hepatitis B vaccine into the planned immunization management. Through the analysis of big data technology, Li Lanjuan's team verified the effectiveness of the drug, and the analysis results will bring scientific guidance for the country to formulate public health policies.
"If China continues to fully vaccinate newborns and adults get hepatitis B vaccine as soon as possible, then ten years later, China will get rid of the hat of a big hepatitis country." Li Lanjuan said.
Developing Big Data to Predict Diseases
With the analysis of big data, the mode of "seeing a doctor" is changing to "being watched by a doctor"-your wearable device can give you a "physical examination" 24 hours a day. This all-data mode is low in cost and high in efficiency, and can be used by almost everyone.
"The long-term goal of precision medicine is the health management of everyone." Next, Team Li Lanjuan will create a volunteer queue with a population of over 6.5438+0 million in Zhejiang. They are willing to enjoy their genetic data, biological samples, vital information and all electronic health information.
This is a new research model that integrates participants, responsible data sharing and privacy protection. Based on this health big data, the team of the First Hospital of Zhejiang University will be able to do a series of new studies, such as pharmacogenomics research, so that doctors can prescribe appropriate drugs and appropriate doses for each patient more accurately; For example, setting new treatment and prevention goals for patients.
In the United States, where the medical industry is the most developed in the world, many high-tech products based on big data and disease prevention have emerged in the field of medical entrepreneurship.
American Anmo Madan and his team set up a company, focusing on the study of predicting the owner's disease through the data analysis of mobile phones.
After collecting and analyzing more than 320,000 hours' data of mobile phones of experimental participants, they can finally model people's mobile phones to predict colds, mental illness and so on. For example, when people are depressed, they can usually see changes in communication with others, and daily data analysis can capture these changes. In the test, this application can correctly judge the daily physiological symptoms and ordinary breathing of 60%~90% people, and inform the owner of these changes, or send them to friends or family in the future.
Further development of big data to predict diseases may also significantly reduce medical costs. The McKinsey Global Institute reports that if the US healthcare industry effectively uses big data, it can reduce the cost by about 8%, thus creating $300 billion in value every year.
The above is what Bian Xiao shared for you about the changes that big data has brought to the health industry. For more information, you can pay attention to Global Ivy and share more dry goods.