A large-scale infection control data storage and processing method

Abstract

A large-scale infection control data storage processing method includes the following steps that 1 a client A submits original data 1 to a storage server, a data storage unit conducts processing of filtering, error detection and formatting on the original data 1 to obtain a data structure 2, and the data structure 2 is stored in a cluster device by the data server according to a set storage optimization strategy; 2 a client B submits a data withdrawing request 3 to the storage server, a data withdrawing unit analyzes and decomposes a minimum-particle-size inquire statement 4 of the data withdrawing request 3 and distributes the minimum-particle-size inquire statement 4 to a corresponding cluster; 3 a cluster storage node responds to the minimum-particle-size inquire statement 4, a cluster main node combines inquiry data as a data set 5, and after the data set 5 is processed by the data withdrawing unit to be a data flow 6, the data flow 6 is sent to the client B; 4 a capacity monitoring unit monitors system capacity changes and evaluates a cluster storage condition; and 5 a backup recovery unit finishes data backup and data disaster tolerance work automatically.

Description

technical field [0001] The invention relates to a large-scale infection control data storage and processing device. Background technique [0002] With the development and popularization of computer technology, office automation has penetrated into all walks of life. Hospitals are a service-oriented industry, and medical information management is particularly important. When a hospital conducts transaction processing, it will generate a large amount of data, including structured, semi-structured and unstructured data. The development of medical technology has greatly changed the daily business of hospitals. Various medical equipment are applied to medical services, generating a large amount of image data. Realizing information traceability and accident location from massive amounts of information has become a new requirement. In addition, the massive amount of information generated by the hospital's daily affairs is required to be kept for at least 5 years. [0003] At th...

AI Technical Summary

Problems solved by technology

With the existing technical solutions, it is very difficult to add a storage node, which has a great impact on the stability of the system

[0016] 2. Information traceability is difficult: the existing system does not consider the issue of information traceability, so little work has been done in this area, which makes information traceability very difficult

[0017] 3. Lack of management of log files: the traditional HIS lacks management of equipment, and does not create log files for equipment. When equipment fails, it is difficult to track the cause of the failure, which causes a lot of inconvenience to management.

[0018] 4. Poor system scalability: the existing HIS, PACS, and EMR systems basically cover all the businesses of the hospital, and these businesses have been modeled and realized

However, the development of modern technology makes it difficult for these pre-defined business rules to deal with such new applications. If you want to add new applications to the system, you may need to change the existing business rules, so the scalability of the system is poor

[0019] 5. Poor system adaptability: At this stage, RFID technology, two-dimensional code technology, and video surveillance technology have been applied in many fields, especially in the fields of logistics and information traceability. These technologies have huge demand

In the near future, these technologies will be applied in hospitals, but the existing system does not consider providing an interactive interface for these technologies, so it is necessary to re-establish the system application or even replace the system architecture

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