Regional standardized medical platform

Abstract

The invention relates to a regional standardized medical platform, which comprises a first-level platform end and a second-level platform end, and is characterized in that the first-level platform end comprises an existing standard medical term database, a standardized medical term platform and a first-level fully-structured electronic medical record platform; the standardized medical term platform imports existing standard terms in the existing standard medical term database, and issues the existing standard terms to the first-level fully-structured electronic medical record platform; the first-stage fully-structured electronic medical record platform is connected with the second-stage platform end, the second-stage platform end comprises a second-stage fully-structured electronic medical record platform, and data in the first-stage fully-structured electronic medical record platform is synchronized to the second-stage fully-structured electronic medical record platform for electronic medical record writing. According to the regional standardized medical platform, the standardization degree of medical terms in the region is improved, so that information exchange and data sharing among different medical institutions are promoted.

Description

Technical Field

[0001] The present invention relates to the field of medical services, and in particular to a regional standardized medical platform. Background Art

[0002] In modern medical services, the standardization of medical terminology is one of the key factors in improving medical quality and efficiency. Due to differences in the use of terminology in different regions and medical institutions, problems such as poor information exchange and difficulty in data sharing have arisen.

[0003] In a region, there are many medical institutions of all levels and types, and each medical institution has many departments. Each department has its own professional terminology and diagnostic standards, which makes cross-institutional medical collaboration complicated. In addition, with the popularization of electronic medical records and health information exchange systems, the need for standardized medical terminology has become more urgent. Existing solutions are often limited to the standardization of medical terminology of medical institutions of all levels and types, and fail to fully consider the problem of medical terminology unification in the entire region. There is a lack of a unified platform to integrate and coordinate the standardized medical terminology systems of different medical institutions in the region. Summary of the invention

[0004] The embodiment of the present invention provides a regional standardized medical terminology platform, the regional standardized medical terminology platform comprising: a first-level platform end and a second-level platform end, the first-level platform end comprising an existing standard medical terminology database, a standardized medical terminology platform and a first-level fully structured electronic medical record platform, the standardized medical terminology platform imports the existing standard terms in the existing standard medical terminology database, and sends the existing standard terms to the first-level fully structured electronic medical record platform;

[0005] The first-level fully structured electronic medical record platform is connected to the second-level platform end, and the second-level platform end includes a second-level fully structured electronic medical record platform. The data in the first-level fully structured electronic medical record platform is synchronized to the second-level fully structured electronic medical record platform for electronic medical record writing.

[0006] Furthermore, the regional standardized medical platform also includes a medical institution end and a quality control center end. The medical institution end calls the data in the second-level fully structured electronic medical record platform end to write electronic medical records. The quality control center end reviews the new medical terms generated during the medical record writing process of the medical institution end, and uploads the new medical terms that pass the review to the first-level standardized medical terminology platform.

[0007] Furthermore, the existing standard medical terms in the existing standard medical terminology database include the International Classification of Diseases (ICD), the SNOMED CT, the Advanced Therapeutic Drug Code (ATC), etc.

[0008] Furthermore, the medical institution end includes medical institutions of all levels and types, and each of the medical institutions of all levels and types is registered on the first-level platform end. After the first-level platform end receives the registration request of each of the medical institutions of all levels and types, it assigns each of the medical institutions of all levels and types a HOSPITAL_ID, and the HOSPITAL_ID serves as the primary key defined for each of the multiple medical institutions.

[0009] Furthermore, each of the medical institutions at all levels and types calls upon the standard medical terms in the second-level fully structured electronic medical record platform to write medical records, and each of the medical institutions at all levels and types uploads the medical records to the second-level platform end, and the second-level platform end uploads the medical records to the first-level platform end through the HTTP port using the ETL tool.

[0010] Furthermore, each medical record of each level and type of medical institution has a medical record ID, and the medical record ID is saved to the first-level platform end. When the medical record is modified, the medical record ID is sent to the review end. After review by the review end, the medical record ID is uploaded to the KAFKA message queue through the KAFKA port, and the modified medical record information corresponding to the medical record ID is uploaded to the first-level platform end.

[0011] Furthermore, the first-level platform receives the medical records uploaded by each of the medical institutions at all levels and types, and generates a primary index for the hospitalized registered patients in the medical records. Each primary index corresponds to multiple medical records, and each medical record corresponds to multiple medical records.

[0012] Furthermore, when the quality control center reviews a single medical term, after the review is passed, the approved single medical term is converted into JSON text format and sent to the KAFKA message center. The medical institution receives the approved medical term from the KAFKA message center and saves it to the standard medical term database.

[0013] Furthermore, when the amount of medical record data is relatively large, the medical institution will decompose the medical record data into medical record metadata, write the medical record metadata information into the local KFAKA middleware, and start the ETL tool to upload it to the first-level platform.

[0014] Furthermore, the medical institution uses every-other-day synchronization to synchronize the medical record data to the first-level platform.

[0015] The beneficial technical effects of this application are:

[0016] It has improved the standardization of medical terminology in the region, thereby promoting information exchange and data sharing between different medical institutions, improving the overall quality and efficiency of medical services, and realizing cross-institutional medical collaboration by integrating professional terminology and diagnostic standards of medical institutions at all levels and types, simplifying medical processes, and reducing the possibility of medical errors and repeated examinations. It provides unified and standardized medical terminology support for electronic medical records and health information exchange systems, making the writing and management of electronic medical records more standardized and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Schematic diagram of the regional standardized medical platform of this application;

[0018] Figure 2 Schematic diagram of a specific embodiment of the regional standardized medical platform of the present application;

[0019] Figure 3 Schematic diagram of data transmission of the regional standardized medical platform of this application;

[0020] Figure 4 Schematic diagram of medical record upload on the regional standardized medical platform of this application;

[0021] Figure 5 Schematic diagram of uploading large medical record data on the regional standardized medical platform of this application;

[0022] Figure 6 Synchronous schematic diagram of the regional standardized medical platform of this application; DETAILED DESCRIPTION

[0023] Terminology explanation:

[0024] Standard medical terminology refers to the uniform language used to describe diseases, symptoms, diagnoses, treatments, and medical procedures. These terms are developed and maintained by professional organizations to ensure accurate communication between medical professionals around the world. For example, the International Classification of Diseases (ICD) and the Clinical Procedure Classification (CPT) are widely used standard terminology systems. In clinical practice, doctors and nurses use standard terminology to record medical records, prescribe medicines, and develop treatment plans. For example, when a doctor diagnoses "hypertension," they use the ICD code "I10" to record this diagnosis. Similarly, when a surgeon performs an "appendectomy," they use the CPT code "44950" to describe the procedure. These codes are not only used in medical records, but also in medical insurance claims and statistical reports.

[0025] JSON text format refers to a lightweight data exchange format. It is text-based and easy for people to read and write, and also easy for machines to parse and generate. JSON is the abbreviation of JavaScript Object Notation. Although it is derived from JavaScript, JSON is language-independent. Almost all programming languages ​​support data processing in JSON format.

[0026] KAFKA message middleware refers to a high-throughput distributed messaging system that is mainly used to build real-time data pipelines and streaming applications. It has the characteristics of high performance, scalability and reliability, and can process large amounts of data and ensure the order of data in the system.

[0027] SSL encryption refers to the Secure Sockets Layer protocol, which is a security technology widely used in Internet communications. The main purpose of the SSL protocol is to establish an encrypted channel between the client and the server to ensure that data cannot be stolen or tampered with during transmission. In this way, SSL encryption can protect the privacy of users and the integrity of data.

[0028] ETL tool refers to the abbreviation of "Extract, Transform, Load", which is a software tool used for data warehouse and data integration. It can extract data from various data sources, clean, transform and integrate the data, and finally load the processed data into the target data warehouse or data storage system.

[0029] The provincial health cloud refers to a health information platform covering the entire province led by the provincial health commission. The platform aims to achieve centralized storage, processing and sharing of health data in the province through modern information technologies such as cloud computing, big data and artificial intelligence, thereby improving medical service efficiency, optimizing resource allocation and promoting the overall improvement of health management level.

[0030] The technical solution of the present application is described in detail below through some embodiments.

[0031] In some embodiments, Figure 1 As shown, an embodiment of the present invention provides a regional standardized medical terminology platform, the regional standardized medical terminology platform includes: a first-level platform end and a second-level platform end, the first-level platform end includes an existing standard medical terminology database, a standardized medical terminology platform and a first-level fully structured electronic medical record platform, the standardized medical terminology platform imports the existing standard terms in the existing standard medical terminology database, and sends the existing standard terms to the first-level fully structured electronic medical record platform;

[0032] The first-level fully structured electronic medical record platform is connected to the second-level platform end, and the second-level platform end includes a second-level fully structured electronic medical record platform. The data in the first-level fully structured electronic medical record platform is synchronized to the second-level fully structured electronic medical record platform for electronic medical record writing.

[0033] like Figure 2 As shown, in some specific embodiments, taking a certain province as an example, the first-level platform end is a health cloud of a provincial health commission, and the health cloud of a provincial health commission includes a standardized medical terminology platform of a certain province and a fully structured electronic medical record platform of a certain province. In this embodiment, the standardized medical terminology platform refers to the standardized medical terminology platform of a certain province importing the existing standard terms in the existing standard medical terminology database, and sending these terms to a fully structured electronic medical record platform of a certain province. A fully structured electronic medical record platform of a certain province is connected to the second-level platform end. In this embodiment, the second-level platform end is the health cloud of the health commissions of various prefecture-level cities under the jurisdiction of a certain province. These health clouds of prefecture-level health commissions are connected to the health cloud of a provincial health commission to achieve data synchronization and sharing. The health cloud of the prefecture-level health commission includes a fully structured electronic medical record platform of a prefecture-level city, and the data in the fully structured electronic medical record platform of a certain province is synchronized to the fully structured electronic medical record platform of the prefecture-level city for electronic medical record writing.

[0034] like Figure 1 or Figure 3 As shown, in some embodiments, the regional standardized medical platform also includes a medical institution end and a quality control center end. The medical institution end calls the data in the second-level fully structured electronic medical record platform end to write electronic medical records, and the quality control center end reviews the new medical terms generated during the medical record writing process of the medical institution end, and uploads the new medical terms that pass the review to the first-level standardized medical terminology platform.

[0035] like Figure 2 As shown, in this embodiment, the medical institution end is a medical institution of all levels and types under the jurisdiction of the municipal health commission, and the quality control center end is a medical quality control center under a provincial health commission. When a medical institution encounters special circumstances that cannot be covered by existing standard medical terms during the writing of electronic medical records, it can apply for new terms. After these new terms are reviewed and verified by the quality control center, if they meet the standards, they will be included in a provincial standardized medical terminology platform, thereby continuously enriching and improving the medical terminology system.

[0036] In addition, in order to ensure the accuracy and consistency of medical terminology, a provincial standardized medical terminology platform is also connected to the National Standardized Medical Terminology Platform of the National Health Commission. Through this hierarchical structure, terminology can be unified from the local to the national level, ensuring smoother medical information exchange and collaboration across the country.

[0037] In some embodiments, in order to further improve the standardization of medical terminology, a provincial standardized medical terminology platform has also introduced artificial intelligence technology. Through machine learning and natural language processing technology, the platform can automatically identify and recommend the most appropriate medical terminology, reduce human errors, and improve work efficiency. At the same time, artificial intelligence technology can also assist the quality control center in the preliminary screening and classification of new terms, reducing the pressure of manual review.

[0038] In some embodiments, the existing standard medical terminology in the existing standard medical terminology database includes the International Classification of Diseases (ICD), the National Clinical Terminology System (SNOMED CT), the Advanced Technical Code (ATC), and the like.

[0039] In these embodiments, by matching patient data with an existing standard medical terminology database, standardized processing of patient health information can be achieved. For example, when entering the patient's diagnostic information, the system automatically converts the doctor's descriptive diagnostic terms into corresponding ICD codes. This not only improves the accuracy of the data, but also facilitates subsequent data analysis and statistical work. Using the clinical terminology system SNOMED CT, the patient's clinical manifestations, examination results and treatment process can be recorded in detail. SNOMED CT covers a wide range of medical concepts, including diseases, symptoms, signs, anatomical structures, drugs and procedures, making the record of clinical information more comprehensive and accurate. In terms of drug management, by applying the ATC coding system, the drugs used by patients can be classified and coded. The ATC system not only includes the chemical composition of the drug, but also covers information such as the therapeutic use and pharmacological effects of the drug. This helps medical institutions monitor the use of drugs and ensure the safety and rationality of drug use. In order to further improve the standardization of medical terminology, some embodiments also introduce natural language processing (NLP) technology. Through NLP technology, the system can automatically parse the doctor's natural language description and convert it into standard medical terminology. This not only reduces the workload of medical staff, but also improves the speed and quality of data entry.

[0040] In some embodiments, the medical institution end includes medical institutions of all levels and types, and each of the medical institutions of all levels and types is registered on the first-level platform end. After the first-level platform end receives the registration request of each of the medical institutions of all levels and types, it assigns each of the medical institutions of all levels and types a HOSPITAL_ID, and the HOSPITAL_ID serves as the primary key defined for each of the multiple medical institutions.

[0041] After completing the registration process, medical institutions of all levels and types will be able to access various services provided by the first-level platform through their unique HOSPITAL_ID. These services include but are not limited to electronic medical record management, appointment registration, drug procurement, medical resource allocation and data analysis. Through these services, medical institutions can achieve information sharing, improve work efficiency and optimize resource allocation.

[0042] To ensure data security and privacy, the first-level platform will use advanced encryption technology and access control mechanisms. Each medical institution's HOSPITAL_ID will be bound to its security key to ensure that only authorized users can access its relevant data. In addition, the platform will conduct regular security audits to prevent data leakage and illegal access.

[0043] like Figure 3 As shown, in some embodiments, each of the medical institutions at all levels and types calls the standard medical terms in the second-level fully structured electronic medical record platform to write medical records, and each of the medical institutions at all levels and types uploads the medical records to the second-level platform end, and the second-level platform end uploads the medical records to the first-level platform end through the HTTP port through the ETL tool.

[0044] In these embodiments, after receiving the medical record data uploaded by each medical institution, the first-level platform will automatically clean and format the data. Through advanced data processing algorithms, the accuracy and consistency of medical record information are ensured. Subsequently, these standardized medical record data are stored in the database for further data analysis and mining.

[0045] In some embodiments, the first-level platform receives the medical records uploaded by each of the medical institutions at all levels and types, and generates a primary index for the inpatient registered patients in the medical records.

[0046] In some specific embodiments, the generation of the primary index is based on the patient's unique identifier, such as an ID number or a medical card number. In this way, it can be ensured that each patient has only one unique primary index in the system, thereby avoiding duplicate records and data redundancy. The generation of the primary index not only helps to improve the efficiency of data management, but also facilitates the subsequent tracking and analysis of patient information.

[0047] like Figure 3 As shown, in some embodiments, when the quality control center reviews a single medical term, after the review is passed, the approved single medical term is converted into JSON text format and sent to the KAFKA message center. The medical institution receives the approved medical term from the KAFKA message center and saves it to the standard medical term database.

[0048] Specifically, Figure 3 As shown, for example, the medical institution end includes medical institution end 01, medical institution end 02 and medical institution end 03. When writing medical records, medical institution end 01 generates a new medical term X, medical institution end 02 generates a new medical term Y, and medical institution end 03 generates a new medical term Z. In the review process, whenever the medical institution ends (such as medical institution ends 01, 02, and 03) independently create new medical terms (such as X, Y, and Z), these terms will be automatically marked as pending review and uploaded to the quality control center end. The quality control center end can use manual review or machine review. The review process is not limited to the legality check of the vocabulary, but also includes the accuracy, consistency, and compatibility of the terms with existing medical standards. For example, if the new term X is accurate and concise in describing the symptoms of a disease, and does not repeat or ambiguous any item in the existing medical terminology library, then X is likely to pass the review smoothly.

[0049] Once a medical term has passed review, e.g. Figure 3 After the Chinese medical term X and medical term Y pass the review, they will be converted into JSON (JavaScript Object Notation), a lightweight data exchange format, which not only ensures the integrity and readability of the data when it is transmitted between different systems, but also facilitates subsequent data processing and analysis. Subsequently, the medical term encapsulated in JSON text format will be pushed to the KAFKA message center, a high-performance, high-throughput distributed messaging system, and then the approved medical terms X and Y will be stored in the standard medical term database.

[0050] In other embodiments, the quality control center adopts a multi-level review mechanism when reviewing medical terms. First, a primary reviewer conducts a preliminary check to ensure the accuracy and standardization of the terminology. After the primary review is passed, the term will be submitted to a senior reviewer for further review. The senior reviewer will focus on checking the clinical applicability and semantic consistency of the terminology to ensure its effective application in actual medical scenarios.

[0051] After the approved medical terms are converted into JSON text format, in addition to being sent to the KAFKA message center, they may also be backed up and stored through other secure channels. For example, the approved terms are stored in a distributed file system, such as Hadoop HDFS, to ensure data persistence and high availability. After receiving the approved medical terms in the KAFKA message center, the medical institution will update the local database. In order to ensure data consistency and integrity, the medical institution may adopt a transaction processing mechanism to ensure that no data is lost or damaged during the update process. In addition, in order to improve data retrieval efficiency, the medical institution may also optimize the index of the local database to make the query and retrieval of medical terms faster.

[0052] The first-level platform receives the medical records uploaded by each of the various medical institutions at all levels, and generates a primary index for the inpatients registered in the medical records. Each primary index corresponds to multiple medical records, and each medical record corresponds to multiple medical records.

[0053] Each medical record of each level and type of medical institution has a medical record ID, and the medical record ID is saved to the first-level platform end. When the medical record is modified, the medical record ID is sent to the review end. After review by the review end, the medical record ID is uploaded to the KAFKA message queue through the KAFKA port, and the modified medical record information corresponding to the medical record ID is uploaded to the first-level platform end.

[0054] like Figure 4 As shown, when the medical records written by the medical institution are uploaded to the first-level platform, the medical records generated by the medical institution can also be uploaded to the first-level platform through the KAFAKA middleware and ETL tools.

[0055] like Figure 5 As shown, in some other embodiments, when the amount of medical record data is relatively large, the medical institution end decomposes the medical record data into medical record metadata, writes the medical record metadata information into the local KFAKA middleware, and starts the ETL tool to upload it to the first-level platform end.

[0056] When the amount of medical record data is large and it is inconvenient to upload, the medical record data can be decomposed into medical record metadata first. For example, "fever for 3 days" recorded in the medical record can be decomposed into a combination of 3 data elements: symptoms, duration, and time unit.

[0057] After breaking down the medical record data into medical record metadata, the medical institution can use the efficient message processing capabilities of the local Kafka middleware to write these metadata information into the middleware in a streaming manner. The Kafka middleware can ensure high data throughput and low latency, thereby ensuring that the medical record metadata can be quickly and reliably transmitted to the first-level platform.

[0058] like Figure 6 As shown, in some embodiments, the medical institution end synchronizes the medical record data to the first-level platform end by synchronizing every other day. The provincial platform opens the HTTP port. At 0:00 every day, each medical institution uploads the inpatient registration patients of the previous day to the provincial platform through the ETL tool. The new patients generate the main index. The discharged patient information of the previous day is also uploaded to the provincial platform to update the discharge information.

[0059] In summary, this application provides a standardized medical platform for a certain province, which realizes the efficient sharing and management of medical information by integrating the data resources of various medical institutions at all levels. This platform not only improves the efficiency and quality of medical services, but also provides valuable data support for medical research and policy making.

[0060] The embodiments and functional operations of the subject matter described in this specification may be implemented in: digital electronic circuitry, tangibly implemented computer software or firmware, computer hardware, including the structures disclosed in this specification and their structural equivalents, or a combination of more than one of the above. The embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on one or more tangible non-transitory program carriers, for execution by a data processing device or to control the operation of a data processing device.

[0061] Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode information for transmission to an appropriate receiver device for execution by a data processing device. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of the above devices.

[0062] Although this specification contains many specific implementation details, these should not be construed as limitations on the scope of any invention or on the scope of what may be claimed, but rather as descriptions of features that may concretize particular embodiments of particular inventions. Certain features described in this specification in the context of separate embodiments may also be implemented in combination with a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented independently.

[0063] The invention can be implemented in multiple embodiments, or in any suitable subcombination. In addition, although the features may be described above as acting in combination and even initially claimed, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may be turned into a subcombination or a variation of the subcombination.

[0064] Similarly, although operations are described in the accompanying drawings in a particular order, it should not be understood that: in order to achieve the desired results, such operations are required to be performed in the particular order shown or in a sequential order, or that all illustrated operations are performed. In certain cases, multitasking and parallel processing can be advantageous. In addition, the separation of various system modules and components in the above-mentioned embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that program components and systems can generally be integrated into a single software product or packaged into multiple software products.

[0065] Specific implementations of the subject matter have been described. Other implementations are within the scope of the following claims. For example, the activities recited in the claims can be performed in a different order and still achieve the desired results. As an example, the processes described in the accompanying drawings do not necessarily require the specific order or sequential order shown in order to achieve the desired results. In certain implementations, multitasking and parallel processing may be advantageous.

Claims

1. A regional standardized medical terminology platform, characterized by: The regional standardized medical platform includes: A first-level platform end and a second-level platform end, wherein the first-level platform end includes an existing standard medical terminology database, a standardized medical terminology platform, and a first-level fully structured electronic medical record platform, wherein the standardized medical terminology platform imports the existing standard terminology in the existing standard medical terminology database, and sends the existing standard terminology to the first-level fully structured electronic medical record platform; The first-level fully structured electronic medical record platform is connected to the second-level platform end, and the second-level platform end includes a second-level fully structured electronic medical record platform. The data in the first-level fully structured electronic medical record platform is synchronized to the second-level fully structured electronic medical record platform for electronic medical record writing.

2. The regional standardized medical platform according to claim 1, characterized in that: The regional standardized medical platform also includes a medical institution side and a quality control center side. The medical institution side calls the data in the second-level fully structured electronic medical record platform side to write electronic medical records. The quality control center side reviews the new medical terms generated during the medical record writing process of the medical institution side, and uploads the new medical terms that pass the review to the first-level standardized medical terminology platform.

3. The regional standardized medical terminology platform according to claim 1, characterized in that: The existing standard medical terms in the existing standard medical terminology database include the International Classification of Diseases (ICD), the SNOMED CT, the Advanced Therapeutic Drug Code (ATC), etc.

4. The regional standardized medical platform according to claim 1, characterized in that: The medical institution end includes medical institutions of all levels and types. Each of the medical institutions of all levels and types is registered on the first-level platform end. After the first-level platform end receives the registration request of each of the medical institutions of all levels and types, it assigns each of the medical institutions of all levels and types a HOSPITAL_ID, and the HOSPITAL_ID serves as the primary key defined for each of the multiple medical institutions.

5. The regional standardized medical platform according to claim 4, characterized in that: Each of the medical institutions at all levels and types calls upon the standard medical terminology in the second-level fully structured electronic medical record platform to write medical records, and each of the medical institutions at all levels and types uploads the medical records to the second-level platform end, and the second-level platform end uploads the medical records to the first-level platform end through the HTTP port using the ETL tool.

6. The regional standardized medical platform according to claim 5, characterized in that: Each medical record of each level and type of medical institution has a medical record ID, and the medical record ID is saved to the first-level platform end. When the medical record is modified, the medical record ID is sent to the review end. After review by the review end, the medical record ID is uploaded to the KAFKA message queue through the KAFKA port, and the modified medical record information corresponding to the medical record ID is uploaded to the first-level platform end.

7. The regional standardized medical terminology platform according to claim 5, characterized in that: The first-level platform receives the medical records uploaded by each of the various medical institutions at all levels, and generates a primary index for the inpatients registered in the medical records. Each primary index corresponds to multiple medical records, and each medical record corresponds to multiple medical records.

8. The regional standardized medical platform according to claim 2, characterized in that: When the quality control center reviews a single medical term, after the review is passed, the approved single medical term is converted into JSON text format and sent to the KAFKA message center. The medical institution receives the approved medical term from the KAFKA message center and saves it to the standard medical term database.

9. The regional standardized medical platform according to claim 5, characterized in that: When the amount of medical record data is relatively large, the medical institution will decompose the medical record data into medical record metadata, write the medical record metadata information into the KFAKA middleware, and start the ETL tool to upload it to the first-level platform.

10. The regional standardized medical terminology platform according to claim 1, characterized in that: The medical institution uses every other day synchronization to synchronize the medical record data to the first-level platform.

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