Big Data How to save our lives

"Zhong Yun network &http://www.aliyun.com/zixun/aggregation/37954.html" >nbsp; "Abstract:" Robert Volc (Robert Walker) is the head of the U.S. Military Medical Service, director of Medical innovation. In recent years, he has been more like a frustrated data-entry registrar than a failed physician sharing with thousands of colleagues.

The electronic health file (EHR) used by Dr. Volcker became the third person in the diagnostic room, allowing him to stop facing patients and not focus on patients. The problem, however, is not the electronic health files that Volcker uses, but the overall technical flaws.

"E-medical files have become a barrier to simplifying my daily work," Walter explained in a recent interview, "which has made me stop focusing on patients, all by computer." People click the option box and return it to the patient, all of which are jamming data. ”

Electronic health files enable each medical facility to electronically capture a patient's family history, illness, treatment, and current lifestyle. It promises to save 81 billion of dollars a year for the U.S. health care system by simplifying workflows, creating a large number of clinical databases, digging up data, improving preventive care and disease treatment.

But that didn't happen, and doctors were less obsessed with electronic health records. Last month, the American College of Physicians and the U.S. Electronic Health Records partners published a survey of 4,279 doctors. The survey found that 39% of doctors did not recommend electronic health records to their colleagues, compared with 24% in 2010. And 34% of respondents said they were extremely disappointed with the ability of electronic health files to reduce their workload.

Under the auspices of the Health Information technology promotion Economic and Clinical Health Act (HiTech Act), the U.S. government is requiring health-care providers-hospitals, clinics and similar personal behaviors-to implement electronic health files. Providers must also demonstrate the significance of using these systems through a three-stage management process, but within the next four years.

Regardless of how unevenly deployed the US electronic health files are so far, Volcker and others are actually creating a treasure trove of patient information and tapping patient information to improve the patient's treatment. In other words, if everyone knows how to classify information, organize information and access information smoothly, the patient information repository will bring about a medical revolution in the next few 10 years.

Commitment

Large data analysis machines such as Hadoop can tap into the clinical database of electronic health files, and the database is filled with valuable unstructured data that helps doctors make decisions about patient healing.

Doctors and pharmaceutical companies are still heavily reliant on textbooks and very small clinical research, often used to treat patients with only one disease. These pool of objects are difficult to imitate in most real patients, many of whom suffer from more than one health problem.

About 25% of hospitals use some form of data analysis to tap into traditional databases to better understand past treatments and how to improve in the future. However, the patient information collected in the rows and columns of the database is a trivial part and the most important information is in unstructured data-doctor's notes, radiological images, and lifestyle information collected in mobile devices used by the patient.

"This is the real revival in health care," Volcker said. "With big data, the doctor's office will become completely different from what we see now." In the United States, the top five or top ten American life killers are the result of a bad lifestyle, which is ridiculous. Maybe, without vital signs, I just need to look at what people have bought in the grocery store (to know the fatal disease). ”

Today, most hospital data analysis is used to manage costs and improve the quality of treatment. However, the more promising use of large data is to discover the correlation between treatment and outcomes by using the data from doctors ' and nurses ' notes and genetic maps.

But with large data and genetic maps, scientists can now determine how patients respond to a particular medicinal herb, and perhaps one day scientists can even predict who is sick and-if they are really sick-which custom medicine will do the best to treat the disease.

"When I look at the historical growth rate, the big data is definitely a hot-hold application on the market," said James Gaston, senior head of clinical and business intelligence at the medical Information and Management Systems Association (HIMSS).

(Responsible editor: The good of the Legacy)