Hospital data interaction platform based on HRP

Abstract

The present invention discloses a hospital data interaction platform based on HRP, which relates to the field of data processing technology, including a source system, a target system, a standardization processing module, a database processing module, an interaction mode adjustment module, and a splitting and integration module. The standardization processing module is used to standardize the data transmitted by various medical information and send it to the target system in a unified format for data interaction. The database processing module is used to write data of various medical information through an independent database as an intermediate medium, and then the target system reads the corresponding data for data interaction. The interaction mode adjustment module is used to estimate the total amount of data stored in the database, adjust the frequency of reading data, and adjust the ratio of the two data interaction modes according to the frequency of data entry in the source system. The present invention has the characteristics of taking into account both security and reading and writing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a hospital data interaction platform based on HRP. Background Art

[0002] Currently, there are two interaction methods for implementing HRP-based medical information interaction: one is to use the interface mode of an intermediate database, that is, the source system uses an independent database as an intermediate medium to write data, and then the target system reads the corresponding data to realize data transmission and sharing between different business systems. For example, the patient first registers on the APP and fills in the patient information and stores it in the source system. When seeing a doctor, he logs in to the target outpatient system to verify the patient information; the other is to standardize the data transmitted by various services, and use adapter technology to extract data, convert the format and route data messages, and then send it to the data recipient in a unified format. The target system will only send a request to the source system when it needs to obtain data, and the source system will send it immediately after receiving the request.

[0003] The first method requires defining an automatic background script to read data from the intermediate database at certain time intervals because the patient's registration time on the APP is random. If the target system's frequency of data retrieval is higher than the source system's frequency of data writing, there will be too many invalid data read requests, which will occupy too many server resources. Otherwise, data backlog will occur. As the medical information system becomes more and more data-oriented, the burden on the database will increase. Although the second method avoids the problems of invalid reading and data backlog, this standardized data may cause hidden dangers of privacy leakage and malicious tampering. Since these data are in a unified format, once intercepted by malicious programs, it will cause large-scale data security risks. Therefore, it is necessary to design an HRP-based hospital data interaction platform that takes into account both security and read and write efficiency. Summary of the Invention

[0004] The purpose of the present invention is to provide a hospital data interaction platform based on HRP to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a hospital data interaction platform based on HRP, including a source system, a target system, a standardization processing module, a database processing module, an interaction mode adjustment module, and a splitting and integration module. The standardization processing module is used to standardize the data transmitted by various medical information and send it to the target system in a unified format for data interaction. The database processing module is used to write data for various medical information through an independent database as an intermediate medium, and then the target system reads the corresponding data for data interaction. The interaction mode adjustment module is used to estimate the total amount of data stored in the database, adjust the frequency of reading data, and adjust the ratio of the two data interaction modes according to the frequency of data entry in the source system. The splitting and integration module is used to split each group of data entered by the source system, and when the target system needs to read, the two parts of information are integrated to obtain complete information. The source system generates various medical information data, and the target system reads various medical information data.

[0006] According to the above technical solution, the standardized processing module includes a data extraction module, a standardized format conversion module, and a data routing module. The data extraction module is electrically connected to the standardized format conversion module and the data routing module in sequence. The data extraction module is used to extract patient medical information related to the request from the source system database. The standardized format conversion module is used to perform standardized processing on the extracted data and convert it into a unified data format to adapt to different data transmission protocols. The data routing module routes the processed data message to the designated recipient based on the address information of the source system.

[0007] The database processing module includes a data storage module, an intermediate database, and a data reading module. The data storage module is electrically connected to the source system, and the intermediate database is electrically connected to the data storage module and the data reading module. The data storage module stores the received data in an independent intermediate database in a persistent manner. The intermediate database is used to store various medical information data. The data reading module is used to read the corresponding data from the intermediate database and package it for use by the target system.

[0008] The interactive mode adjustment module includes an input statistics module, an input frequency calculation module, a processing ratio determination module, a data total amount estimation module, and a reading frequency adjustment module. The input statistics module is electrically connected to the input frequency calculation module, the input frequency calculation module is electrically connected to the data total amount estimation module, the data total amount estimation module is electrically connected to the reading frequency adjustment module, and the processing ratio determination module is electrically connected to the input frequency calculation module. The input statistics module counts the medical information data of the patient in the source system in real time. The input frequency calculation module is used to calculate the input frequency in combination with time. The processing ratio determination module is used to adjust the ratio of standardized processing and parallel processing of the intermediate database according to the input frequency. The data total amount estimation module is used to estimate the total amount of medical information data according to the input frequency. The reading frequency adjustment module is used to adjust the data reading frequency according to the estimated total amount of medical information data;

[0009] The splitting and integration module includes a data splitting module, a data integration module, a storage location marking module, and a data volume calculation module. The data splitting module is electrically connected to the storage location marking module and the data volume analysis module. The storage location marking module is electrically connected to the data integration module. The data splitting module is used to split each group of data that needs to be standardized before standardization processing. The data integration module is used to integrate the data in the source system and the database to form complete data when reading. The storage location marking module is used to mark the storage location of the split data. The data volume calculation module is used to count the amount of data stored in the database after each group of data is split, and to correct the processing ratio.

[0010] According to the above technical solution, the working method of the platform is:

[0011] S1. Patients enter medical information data into the source system, and the number of times each patient enters data into the source system and its frequency are counted in real time;

[0012] S2. Based on the statistical input frequency, when the input frequency is low, most of the data will be standardized in the source system, while a small portion of the data will be stored in the intermediate database. As the input frequency increases, a larger proportion of the data will be stored in the intermediate database.

[0013] S3. The standardized data is converted into a unified format through a standardized format conversion module to adapt to different data transmission protocols. When the target system needs to read it, this part of the processed data is routed to the designated recipient based on the address information of the target system. The data stored in the intermediate database is stored in a persistent manner in an independent intermediate database. When the target system needs to read the patient's medical information, the data reading module extracts the corresponding data from the intermediate database and packages it.

[0014] S4. Estimate the total amount of data stored in the database based on the registration frequency and the average data volume, and dynamically adjust the data reading frequency using the reading frequency adjustment module to reduce invalid reading and improve data security;

[0015] S5. Before standardization, each set of data to be standardized is split into two parts. One part is stored in the intermediate database, and the other part continues to exist in the source system after standardization in the source system. When the target system needs to read the information, the two parts of information are integrated to obtain the complete information.

[0016] According to the above technical solution, in S2, as the input frequency increases, a larger proportion of data will be stored in the intermediate database in the following specific manner:

[0017] S2-1, let the statistical period be Each time the source system enters patient medical information, the time point of entry is recorded to form a series ,in The total number of entries up to the current time. Each time a patient enters medical information data, the current time point Push the starting point forward one statistical period , statistical period Cumulative entry time points , the number of entries is , the current input frequency is , let the low contrast threshold of input frequency be ,when When the medical information data of the current patient is standardized, the high contrast threshold of the input frequency is ,when When the medical information data of the current patient is stored in the intermediate database, The medical information data of the current patient is processed alternately in two ways, and the input frequency is recorded each time. size.

[0018] According to the above technical solution, in S4, the specific method for estimating the total amount of data stored in the database is:

[0019] S4-1. Statistics of the statistical period in S2-1 The internal recording frequency is Number of times 、 Number of times and Number of times , based on experience, we assume that the average amount of data in each group of medical information data is , so the total amount of data stored in the database is estimated ;

[0020] S4-2. Every time the target system uses the automatic background script to read data from the intermediate database, the data in the intermediate database will be cleared and transferred to the target system. During each reading interval, data will be accumulated in the intermediate database, making the recommended data storage capacity of the intermediate database , if you want to make the amount of data in the intermediate database less than , then the interval between each reading is .

[0021] According to the above technical solution, in S4-1, due to This is an assumed value based on experience. The next read interval needs to be adjusted based on the actual amount of data. Make corrections, and before reading data each time, count the actual data storage capacity of the database and with the recommended capacity Subtract and adjust the next reading interval based on the result , specifically: ,in is the data redundancy coefficient, is the data growth coefficient, The actual data storage capacity when reading data last time. This means data redundancy and the next reading interval needs to be reduced. ,when This means that the amount of stored data is on an increasing trend, and the next reading interval needs to be reduced. Since the frequency of patient data entry changes periodically from morning to night, this adjustment method can quickly adjust to the appropriate reading interval during an upward or downward trend in data entry, reducing invalid data reading and backlogs.

[0022] According to the above technical solution, in S5, the specific method of splitting each set of standardized data into two parts is:

[0023] S5-1. Parse the medical information data and split it by field type. Separate the field types containing patient personal information and store them in an intermediate database. Standardize all remaining fields containing medical information within the source system and record the storage location of the fields within the source system.

[0024] S5-2. When the target system needs to read the patient's complete medical data, it first generates a data request containing the patient's personal information, searches for the fields containing the patient's personal information in the target system and the intermediate database, routes the processed data message to the designated recipient based on the address information of the source system, finds all remaining fields containing medical information, and concatenates the two fields to obtain the current patient's medical information data.

[0025] According to the above technical solution, the ratio of data stored in the intermediate database and the data processed in the standardized manner is also modified according to the data splitting situation: since after the data splitting, some fields in the data that originally needed to be standardized are directly stored in the intermediate database without being standardized, it is concluded based on experience that the average proportion of data containing patient personal information fields in the medical information data is , that is, to estimate the total amount of data stored in the database When , the corrected Read interval Calculation.

[0026] Compared with the prior art, the present invention has the following beneficial effects: the present invention adopts a method of parallel processing of standardization processing and intermediate database processing, firstly establishes an entry statistics module in the source system, counts the number of registrations of each patient in the source system, and when the registration frequency within the statistical period is low, most of the data is processed by the standardization method, and a small part of the data is stored in the intermediate database. As the registration frequency increases, a larger proportion of the data will be stored in the intermediate database, effectively reducing the proportion of standardization processing according to the amount of data, and reducing the loss caused by data leakage while achieving real-time data reading;

[0027] The total amount of data stored in the database is estimated based on the registration frequency and ratio, and the frequency of reading data is adjusted to ensure that the frequency of reading data is consistent with the total amount of stored data as much as possible, thereby reducing invalid data reading and backlog.

[0028] Each set of data that needs to be standardized is split, and a part of it is selected and stored in the intermediate database. The remaining part is standardized and continues to exist in the source system. When the target system needs to read it, the two parts of information are integrated to obtain complete information. Even if the source system is attacked, the patient's complete data cannot be obtained, which improves data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0030] Figure 1 It is a schematic diagram of the overall module structure of the present invention. DETAILED DESCRIPTION

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0032] See also Figure 1 The present invention provides a technical solution: a hospital data interaction platform based on HRP, including a source system, a target system, a standardization processing module, a database processing module, an interaction mode adjustment module, and a splitting and integration module. The standardization processing module is used to standardize the data transmitted by various medical information and send it to the target system in a unified format for data interaction. The database processing module is used to write data of various medical information through an independent database as an intermediate medium, and then the target system reads the corresponding data for data interaction. The interaction mode adjustment module is used to estimate the total amount of data stored in the database, adjust the frequency of reading data, and adjust the ratio of the two data interaction modes according to the frequency of data entry in the source system. The splitting and integration module is used to split each group of data entered by the source system, and when the target system needs to read, the two parts of information are integrated to obtain complete information. The source system generates various medical information data, and the target system reads various medical information data.

[0033] The standardized processing module includes a data extraction module, a standardized format conversion module, and a data routing module. The data extraction module is electrically connected to the standardized format conversion module and the data routing module in sequence. The data extraction module is used to extract patient medical information related to the request from the source system database. The standardized format conversion module is used to perform standardized processing on the extracted data and convert it into a unified data format to adapt to different data transmission protocols. The data routing module routes the processed data message to the designated recipient based on the address information of the source system.

[0034] The database processing module includes a data storage module, an intermediate database, and a data reading module. The data storage module is electrically connected to the source system, and the intermediate database is electrically connected to the data storage module and the data reading module. The data storage module stores the received data in a persistent manner in an independent intermediate database. The intermediate database is used to store various medical information data. The data reading module is used to read the corresponding data from the intermediate database and package it for use by the target system.

[0035] The interactive mode adjustment module includes an input statistics module, an input frequency calculation module, a processing ratio determination module, a data total amount estimation module, and a reading frequency adjustment module. The input statistics module is electrically connected to the input frequency calculation module, the input frequency calculation module is electrically connected to the data total amount estimation module, the data total amount estimation module is electrically connected to the reading frequency adjustment module, and the processing ratio determination module is electrically connected to the input frequency calculation module. The input statistics module counts the medical information data of the patient in the source system in real time. The input frequency calculation module is used to calculate the input frequency in combination with time. The processing ratio determination module is used to adjust the ratio of standardized processing and parallel processing of the intermediate database according to the input frequency. The data total amount estimation module is used to estimate the total amount of medical information data according to the input frequency. The reading frequency adjustment module is used to adjust the data reading frequency according to the estimated total amount of medical information data;

[0036] The splitting and integration module includes a data splitting module, a data integration module, a storage location marking module, and a data volume calculation module. The data splitting module is electrically connected to the storage location marking module and the data volume analysis module. The storage location marking module is electrically connected to the data integration module. The data splitting module is used to split each group of data that needs to be standardized before the standardization processing. The data integration module is used to integrate the data in the source system and the database to form complete data when reading. The storage location marking module is used to mark the storage location of the split data. The data volume calculation module is used to count the amount of data stored in the database after each group of data is split, and to correct the processing ratio;

[0037] The platform works as follows:

[0038] S1. Patients enter medical information data into the source system, and the number of times each patient enters data into the source system and its frequency are counted in real time;

[0039] S2. Based on the statistical input frequency, when the input frequency is low, most of the data will be standardized in the source system, while a small portion of the data will be stored in the intermediate database. As the input frequency increases, a larger proportion of the data will be stored in the intermediate database.

[0040] S3. The standardized data is converted into a unified format through a standardized format conversion module to adapt to different data transmission protocols. When the target system needs to read it, this part of the processed data is routed to the designated recipient based on the address information of the target system. The data stored in the intermediate database is stored in a persistent manner in an independent intermediate database. When the target system needs to read the patient's medical information, the data reading module extracts the corresponding data from the intermediate database and packages it.

[0041] S4. Estimate the total amount of data stored in the database based on the registration frequency and the average data volume, and dynamically adjust the data reading frequency using the reading frequency adjustment module to reduce invalid reading and improve data security;

[0042] S5. Before normalization, split each set of data to be normalized into two parts. One part is stored in an intermediate database, while the other part remains in the source system after normalization. When the target system needs to read the data, the two parts are integrated to obtain the complete information.

[0043] In S2, as the input frequency increases, a larger proportion of data will be stored in the intermediate database in the following specific ways:

[0044] S2-1, let the statistical period be Each time the source system enters patient medical information, the time point of entry is recorded to form a series ,in The total number of entries up to the current time. Each time a patient enters medical information data, the current time point Push the starting point forward one statistical period , statistical period Cumulative entry time points , the number of entries is , the current input frequency is , let the low contrast threshold of input frequency be ,when When the medical information data of the current patient is standardized, the high contrast threshold of the input frequency is ,when When the medical information data of the current patient is stored in the intermediate database, The medical information data of the current patient is processed alternately in two ways, and the input frequency is recorded each time. size;

[0045] In S4, the specific method for estimating the total amount of data stored in the database is:

[0046] S4-1. Statistics of the statistical period in S2-1 The internal recording frequency is Number of times 、 Number of times and Number of times , based on experience, we assume that the average amount of data in each group of medical information data is , so the total amount of data stored in the database is estimated ;

[0047] S4-2. Every time the target system uses the automatic background script to read data from the intermediate database, the data in the intermediate database will be cleared and transferred to the target system. During each reading interval, data will be accumulated in the intermediate database, making the recommended data storage capacity of the intermediate database , if you want to make the amount of data in the intermediate database less than , then the interval between each reading is ;

[0048] In S4-1, due to This is an assumed value based on experience. The next read interval needs to be adjusted based on the actual amount of data. Make corrections, and before reading data each time, count the actual data storage capacity of the database and with the recommended capacity Subtract and adjust the next reading interval based on the result , specifically: ,in is the data redundancy coefficient, is the data growth coefficient, The actual data storage capacity when reading data last time. This means data redundancy and the next reading interval needs to be reduced. ,when This means that the amount of stored data is on an increasing trend, and the next reading interval needs to be reduced. Since the frequency of patient data entry varies cyclically from morning to night, this adjustment method can quickly adjust to the appropriate reading interval during an upward or downward trend in data entry, reducing invalid data reading and backlogs.

[0049] In S5, the specific method of splitting each set of standardized data into two parts is as follows:

[0050] S5-1. Parse the medical information data and split it by field type. Separate the field types containing patient personal information and store them in an intermediate database. Standardize all remaining fields containing medical information within the source system and record the storage location of the fields within the source system.

[0051] S5-2: When the target system needs to read the patient's complete medical data, it first generates a data request containing the patient's personal information. It then searches for the fields containing the patient's personal information in the target system and the intermediate database. Based on the source system's address information, it routes the processed data message to the designated recipient. It then finds all remaining fields containing the medical information and concatenates the two fields to obtain the current patient's medical information.

[0052] S5 also includes the correction of the ratio of data stored in the intermediate database and the data processed in the standardized process according to the data splitting situation: since after the data splitting, some fields in the data that originally needed to be standardized are directly stored in the intermediate database without being standardized, the average proportion of the data containing the patient's personal information field in the medical information data is obtained based on experience. , that is, to estimate the total amount of data stored in the database When , the corrected Read interval Calculation.

[0053] Using a method of parallel processing of standardization and intermediate database, we first establish an entry statistics module in the source system to count the number of registrations of each patient in the source system. When the registration frequency is low during the statistical period, most of the data is processed using the standardization method, and a small portion of the data is stored in the intermediate database. As the registration frequency increases, a larger proportion of the data will be stored in the intermediate database, effectively reducing the proportion of standardization processing according to the data volume, and reducing the losses caused by data leakage while achieving real-time data reading;

[0054] The total amount of data stored in the database is estimated based on the registration frequency and ratio, and the frequency of reading data is adjusted to ensure that the frequency of reading data is consistent with the total amount of stored data as much as possible, thereby reducing invalid data reading and backlog.

[0055] Each set of data that needs to be standardized is split, and a part of it is selected and stored in the intermediate database. The remaining part is standardized and continues to exist in the source system. When the target system needs to read it, the two parts of information are integrated to obtain complete information. Even if the source system is attacked, the patient's complete data cannot be obtained, which improves data security.

[0056] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0057] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. The HRP-based hospital data interaction platform is characterized by: It includes a source system, a target system, a standardization processing module, a database processing module, an interaction mode adjustment module, and a splitting and integration module. The standardization processing module is used to standardize the data transmitted by various medical information and send it to the target system in a unified format for data interaction. The database processing module is used to write data of various medical information through an independent database as an intermediate medium, and then the target system reads the corresponding data for data interaction. The interaction mode adjustment module is used to estimate the total amount of data stored in the database, adjust the frequency of reading data, and adjust the ratio of the two data interaction modes according to the frequency of data entry in the source system. The splitting and integration module is used to split each group of data entered by the source system, and when the target system needs to read, the two parts of information are integrated to obtain complete information. The source system generates various medical information data, and the target system reads various medical information data; The platform works as follows: S1. Patients enter medical information data into the source system, and the number of times each patient enters data into the source system and its frequency are counted in real time; S2. Based on the statistical input frequency, when the input frequency is low, most of the data will be standardized in the source system, while a small portion of the data will be stored in the intermediate database. As the input frequency increases, a larger proportion of the data will be stored in the intermediate database. S3. The standardized data is converted into a unified format through a standardized format conversion module to adapt to different data transmission protocols. When the target system needs to read the data, the processed data is routed to the address of the specified target system based on the address information of the target system. The data stored in the intermediate database is stored in an independent intermediate database in a persistent manner. When the target system needs to read the patient's medical information, the data reading module extracts the corresponding data from the intermediate database and packages it. S4. Estimate the total amount of data stored in the database based on the registration frequency and the average data volume, and dynamically adjust the data reading frequency using the reading frequency adjustment module to reduce invalid reading and improve data security; S5. Before normalization, split each set of data to be normalized into two parts. One part is stored in an intermediate database, while the other part remains in the source system after normalization. When the target system needs to read the data, the two parts are integrated to obtain the complete information. In S5, the specific method of splitting each set of data into two parts after standardization is as follows: S5-1. Parse the medical information data and split it by field type. Separate the field types containing patient personal information and store them in an intermediate database. Standardize all remaining fields containing medical information within the source system and record the storage location of the fields within the source system. S5-2. When the target system needs to read the patient's complete medical data, it first generates a data request containing the patient's personal information, searches for the fields containing the patient's personal information in the target system and the intermediate database, routes the processed data message to the designated recipient based on the address information of the source system, finds all remaining fields containing medical information, and concatenates the two fields to obtain the current patient's medical information data.

2. The HRP-based hospital data interaction platform according to claim 1, characterized in that: The standardized processing module includes a data extraction module, a standardized format conversion module, and a data routing module. The data extraction module is electrically connected to the standardized format conversion module and the data routing module in sequence. The data extraction module is used to extract patient medical information related to the request from the source system database. The standardized format conversion module is used to perform standardized processing on the extracted data and convert it into a unified data format to adapt to different data transmission protocols. The data routing module routes the processed data message to a designated recipient based on the address information of the source system. The database processing module includes a data storage module, an intermediate database, and a data reading module. The data storage module is electrically connected to the source system, and the intermediate database is electrically connected to the data storage module and the data reading module. The data storage module stores the received data in an independent intermediate database in a persistent manner. The intermediate database is used to store various medical information data. The data reading module is used to read the corresponding data from the intermediate database and package it for use by the target system. The interactive mode adjustment module includes an input statistics module, an input frequency calculation module, a processing ratio determination module, a data total amount estimation module, and a reading frequency adjustment module. The input statistics module is electrically connected to the input frequency calculation module, the input frequency calculation module is electrically connected to the data total amount estimation module, the data total amount estimation module is electrically connected to the reading frequency adjustment module, and the processing ratio determination module is electrically connected to the input frequency calculation module. The input statistics module counts the medical information data of the patient in the source system in real time. The input frequency calculation module is used to calculate the input frequency in combination with time. The processing ratio determination module is used to adjust the ratio of standardized processing and parallel processing of the intermediate database according to the input frequency. The data total amount estimation module is used to estimate the total amount of medical information data according to the input frequency. The reading frequency adjustment module is used to adjust the data reading frequency according to the estimated total amount of medical information data; The splitting and integration module includes a data splitting module, a data integration module, a storage location marking module, and a data volume calculation module. The data splitting module is electrically connected to the storage location marking module and the data volume analysis module. The storage location marking module is electrically connected to the data integration module. The data splitting module is used to split each group of data that needs to be standardized before standardization processing. The data integration module is used to integrate the data in the source system and the database to form complete data when reading. The storage location marking module is used to mark the storage location of the split data. The data volume calculation module is used to count the amount of data stored in the database after each group of data is split, and to correct the processing ratio.

3. The HRP-based hospital data interaction platform according to claim 1, characterized in that: In S2, as the input frequency increases, a larger proportion of data will be stored in the intermediate database in the following specific manner: S2-1, let the statistical period be Each time the source system enters patient medical information, the time point of entry is recorded to form a series ,in The total number of entries up to the current time. Each time a patient enters medical information data, the current time point Push the starting point forward one statistical period , statistical period Cumulative entry time points , the number of entries is , the current input frequency is , let the low contrast threshold of input frequency be ,when When the medical information data of the current patient is standardized, the high contrast threshold of the input frequency is ,when When the medical information data of the current patient is stored in the intermediate database, The medical information data of the current patient is processed alternately in two ways, and the input frequency is recorded each time. size.

4. The HRP-based hospital data interaction platform according to claim 3, characterized in that: In S4, the specific method for estimating the total amount of data stored in the database is: S4-1. Statistics of the statistical period in S2-1 The internal recording frequency is Number of times 、 Number of times and Number of times , based on experience, we assume that the average amount of data in each group of medical information data is , so the total amount of data stored in the database is estimated ; S4-2. Every time the target system uses the automatic background script to read data from the intermediate database, the data in the intermediate database will be cleared and transferred to the target system. During each reading interval, data will be accumulated in the intermediate database, making the recommended data storage capacity of the intermediate database , if you want to make the amount of data in the intermediate database less than , then the interval between each reading is .

5. The HRP-based hospital data interaction platform according to claim 4, characterized in that: In S4-1, since This is an assumed value based on experience. The next read interval needs to be adjusted based on the actual amount of data. Make corrections, and before reading data each time, count the actual data storage capacity of the database and with the recommended capacity Subtract and adjust the next reading interval based on the result , specifically: ,in is the data redundancy coefficient, is the data growth coefficient, The actual data storage capacity when reading data last time. This means data redundancy and the next reading interval needs to be reduced. ,when This means that the amount of stored data is on an increasing trend, and the next reading interval needs to be reduced. .

6. The HRP-based hospital data interaction platform according to claim 5, characterized in that: The S5 also includes modifying the ratio of data stored in the intermediate database and the standardized data according to the data splitting situation: based on experience, the average proportion of data containing patient personal information fields in the medical information data is obtained. , that is, to estimate the total amount of data stored in the database When , the corrected Read interval Calculation.

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