Multi-center medical data structure standardization system based on general data model

Abstract

The invention discloses a multi-center medical data structure standardization system based on a general data model. The system comprises a source database, a cache database, a target database, a dataconnection management module, a data structure scanning module, a mapping construction unit, a mapping execution unit, an incremental updating unit and a quality control unit. The source database is adatabase for executing a medical business process by each medical data center. The cache database and the target database are deployed in an exclusive front server of each medical data center. The target database of each medical data center is connected with the cloud server to realize collaborative analysis among the multi-center medical data. The medical data structure mapping relation design process is improved, cooperation between information technicians and medical staff is facilitated, and the working efficiency is improved. An incremental updating mechanism is provided, and the systemoperation efficiency is improved.

Description

technical field [0001] The invention belongs to the field of data structure standardization, in particular to a multi-center medical data structure standardization system based on a general data model. Background technique [0002] With the improvement of domestic informatization level, more and more hospitals have established their own hospital information system (HIS), including electronic medical record system (EMR), image acquisition and transmission system (PACS), laboratory examination information system (LIS) ) including various clinical business information systems. Many hospitals with a high degree of informatization have also established a clinical data center (CDR), which has realized the centralization of hospital-wide business data and provided convenience for hospital management, patient services, and clinical research. However, due to the huge differences in the medical information systems adopted by different hospitals, the heterogeneity of the data structur...

AI Technical Summary

Problems solved by technology

[0004] 1. The data structure mapping process requires a large number of frequent queries to the database. The existing technical solutions directly operate on the source database, which increases the operating pressure of the source server and affects normal business activities.

[0005] 2. Medical data has its own inherent specialization and complexity

It is difficult for information technology personnel to complete the mapping relationship design work independently, and the cooperation of non-technical personnel with medical background is required

However, the existing mapping relationship design method is not intuitive enough, it is not friendly to non-technical personnel, and it is not conducive to good communication and cooperation between technical personnel and non-technical personnel

[0006] 3. There is a large amount of medical data, and the performance requirements for data structure mapping are high, so it is necessary to optimize the data structure mapping script in a targeted manner

Existing methods require technicians to manually query the source database to understand the distribution of data, and the operation is cumbersome

[0007] 4. The existing technical solutions do not provide an incremental update solution, or provide an incremental update function but need to re-do data structure mapping for all data during update, which is inefficient

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