Cloud computing and large data-assisted medical collaboration

When the concept of cloud computing and big data came out, some people once thought is Yunshan, unintelligible, but now, cloud computing and large data is to push through layers of clouds, showing its unstoppable momentum of development, landing to various industry applications, to help enterprise development, improve people's lives, medical industry is its typical application.

Cloud mode realizes medical information interconnection and interworking

"Difficult to see a doctor" has always been one of the most difficult problems of Chinese people, and "difficult to see a doctor" is due to the relative shortage of medical resources, to solve this problem needs to increase the supply of medical resources, and in addition to medical facilities such as the increase in hospital efficiency is also an important measure Cloud computing and large data can just solve the problem.

Fangzheng County, Harbin City, Heilongjiang province, as a 260,000 population counties and cities, with 8 Township hospitals, 128 village health room. The information construction resources of each medical and health Organization are unevenly distributed, uneven level: Part for the information construction has a certain foundation, some functions still need to improve the health care institutions, but subject to the objective conditions, such as LIS, PACS, such as inspection and imaging systems, rational drug use, electronic medical records and other systems have not been built; Some of the medical and health institutions, such as the poor foundation of information construction and the overall need to upgrade, such as the Urban Community Health Service Center is still under construction, the urban residents ' electronic health files have not been established, Township hospitals and village Health room information level is weak.

Because the information system is isolated, it is impossible to realize the sharing of health information resources and the interconnection of information in county region. le-Chen technology to this situation put forward its intelligent medical Program products "Lok Chen Regional Health information management platform", the platform based on cloud computing as the basis for the design and construction of regional health information management system, the core content include: Primary health care Management Information System, regional health information management platform, Digital hospital solutions, New agricultural and municipal management platform, remote diagnosis and treatment management system, as well as cloud computing data center.

Through this platform, the patient can realize the network appointment, the off-site treatment, the medical insurance information instantaneous settlement, the medical organization can realize the peer examination result mutual recognition, saves the medical resources, reduces the patient duplicate examination and the examination burden. This not only realizes the interconnection of various medical information, improves the medical efficiency, but also reduces the cost of hardware equipment and the corresponding maintenance investment of medical institutions.

The value and challenge of large medical data

The large amount of data in the medical profession is not only large and complex, but also contains rich and diverse information value. It is understood that the main sources of medical data include four categories: first, pharmaceutical enterprises and life sciences; The second is clinical decision support and other clinical applications, including diagnosis of related image information, three is cost reimbursement, utilization and fraud supervision; four is patient behavior, social network. Correspondingly, these large data contain considerable value.

Although it is effectively stored, processed, queried and analyzed, it can assist clinicians to make more scientific and accurate decision on diagnosis and medication, or help the hospital to develop new personalized service and automatic service according to the latent needs of patients, and even help relevant research institutions to break through the medical methods and the innovation of medicine, or support regional and even national medical industry authorities to optimize the allocation of medical resources and services.

But there are also statistics that, in the current medical profession, an ordinary CT scan image contains about 150MB of data; the size of a genome sequence file is about 750MB; The standard pathology chart is much larger, and is close to 5GB. If you multiply this amount of data by the number of people and the average life expectancy, only one community hospital accumulates data volumes that can be terabytes or even petabytes, and it is rich in unstructured data such as images and video, not to mention the data sets compiled by larger medical institutions and even regional medical authorities.

Wu Yunyu, Intel Global Healthcare Solutions architect, said: "By 2020, medical data will be increased to 35ZB, equivalent to 44 times times the amount of data in 2009." Among them, the image data growth is the fastest, followed by EMR Electronic medical record data. ”

Large data improves business analysis efficiency

How to minimize the storage, processing and protection cost of the massive and complex data, but also to the real-time or quasi real-time processing, second-level query demand response and intelligent, in-depth analysis, but face a lot of challenges. The first hurdle of "Getting Started" is the problem of storing, processing and querying large datasets.

In this regard, Intel assisted Ufida to conduct a reasonable framework analysis and guidance, for the solution based on large data analysis in-depth exploration and research, and the development of a large Intel data solution based on the regional Health Data center construction goals: first, in the vast number of data, The data center must have the performance of fast document retrieval; second, as future medical systems upgrade and medical standards are upgraded, data centers must be able to solve the problem of how storage patterns meet the updating of data patterns; Third, data centers must have the ability to scale horizontally and to be transparent to applications, Requirements can be done to the bottom of the expansion of the upper-level business isolation, through more servers proportional to the expansion of capacity and performance.

Intel Corporation and Ufida solutions are used in a regional health data center after repeated single business load tests, large quantities of tests, and a combination of multiple technologies. Compared with the traditional database and minicomputer scheme, this large data solution has better openness and better economy; The integrated graphical interface provides convenient node management and lateral extension capabilities, dramatically reduces management costs, leverages existing hardware resources, and lowers upgrade costs.

If Intel is more at the hardware level for large medical data storage, processing and query efficiently, then IBM, Oracle and other enterprises rely on software in large data analysis and mining more to play the value of large data.

IBM Analytics and data mining technology helps hospitals analyze data, drive insights, simplify management, and support decision-making based on its practice in domestic and international healthcare industry and large data advantages. Based on this technology, the IBM Hospital intelligent Operation System helps the hospital to carry on the daily operation information conformity, embarks from the hospital management goal to the hospital operation Data Warehouse to plan and the modelling, takes the hospital his, the EMR, the medical record management, the health insurance and so on system as the data source, carries on the data For the intelligent analysis and utilization of data to lay a good foundation.

(Responsible editor: The good of the Legacy)