Healthcare Big Data (HBD)
It has four characteristics of the data is called large data. Large data is first considered to have a large volume of data (Volume). This is the first feature of large data. Large data tend to grow at times of speed (Velocity), which is the second feature. The data contained in the data structure is significantly different, not only contains structured data, there are a lot of unstructured data. This is the third feature (Variety). Large data usually has a hidden amount of valuable information, which is the fourth feature (Valuable). Technically speaking, the first three features are easily recognized, and the last feature is rather special, difficult to identify, suggesting that important information in the data is often not exposed, with information ambiguity. This is the key to large data technology. People need to adopt an innovative thinking to establish a model of data analysis.
The world-renowned consulting firm, the McKinsey Global Institute (MGI), published a study in May 2011, stating that the concept of "big data" has attracted the attention of governments, academia, industry and industry. The report pointed out that a large number of data penetrate into various industries and business areas, has gradually become an important factor in production. Make full use of large amounts of data, people can predict the growth of consumer productivity and profitability. McKinsey further pointed out that in the US health care industry, through large data mining, can be carried out in the health care business services analysis and decision-making, with the value of more than 300 billion US dollars potential, can make US health care spending fell more than 8% per year. Today, the development of high-tech information technology, making the industry's data into the production and physical assets, human capital and the third important factor.
Large numbers of medical and public medical data are growing rapidly. These health care data are divided into different levels, with different data structures, and their document formats are presented in a mix. This includes not only clinical case documentation, laboratory reports, image data, medical device test signal data, and so on. These data are also closely related to social, environmental, family, political views, religious beliefs, national and regional policies, legal and legal, business and management information. How medical health data acquisition, management, processing, analysis and mining can help prevent disease, reduce medical costs and improve the quality of human life.
Unfortunately, current regional and country-wide health care information technology (HIT) focuses primarily on low- and medium-sized data management. Lack of analysis and mining, new knowledge discovery and decision making on systematic health and health data on a large scale integrated data basis. According to the MGI analysis, one of the major bottlenecks in the analysis of dynamic large data to achieve new value is the lack of correlation between large data information technology and industry expertise. The use of large data will promote health care reform around the world and improve the quality of human routine medical services.