Auditing method and device during function execution in reproductive medical service

Abstract

The invention discloses an auditing method and device during function execution in reproductive medical service. A server side method comprises the steps that an information operation request sent by a client side is received; the information operation request carries a globally unique identifier and auditing parameters of the patient; checking whether the information operation request has an operation authority or not; when the information operation request has the operation authority and the parameter state of the auditing parameter is to-be-stored, performing data desensitization on original medical information in the auditing parameter to obtain to-be-stored medical information; constructing a first operation log based on a data operation function expression and a service attribute in the audit parameter; and storing the to-be-stored medical information to the medical data table by adopting the global unique identifier, and storing the first operation log to the audit data table. By adopting the embodiment of the invention, the security of data transmission and storage can be improved. Meanwhile, the operation behavior of each link is accurately recorded and monitored through a refined management mode, and the transparency and traceability of data are improved.

Description

Technical Field

[0001] This application relates to the field of data integration technology, and in particular to an auditing method and apparatus for the performance of functions in reproductive medical services. Background Technology

[0002] In today's digital age, the healthcare industry, especially in the field of reproductive medicine, is heavily reliant on information systems for data management and business operations. Reproductive medicine systems encompass various types of data, including patient privacy information, complex medical business data, and critical laboratory data. The accurate, secure, and compliant use of this data is of paramount importance.

[0003] In the field of medical data management, some auditing techniques have been adopted to record and monitor data operation activities. However, these techniques still have many shortcomings when dealing with highly sensitive and privacy-sensitive data in the field of reproductive medicine. For example, insufficient encryption strength during the transmission and storage of audited data makes it easy for criminals to steal or tamper with the data. Secondly, the lack of refined management of data throughout the entire process during data auditing makes it impossible to accurately record and monitor the operation activities at each stage. Summary of the Invention

[0004] This application provides an auditing method and apparatus for the performance of functions in reproductive medical services. To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0005] In a first aspect, embodiments of this application provide an auditing method for the execution of functions in reproductive medical services, applied on the server side, the method comprising: Receive information operation requests sent by the client; the information operation request carries the patient's globally unique identifier and audit parameters, and the information operation request is obtained by the user triggering the target function in the online reproductive medical service; Check whether the information operation request has the necessary permissions; When the information operation request has the operation permission and the parameter status of the audit parameter is pending storage, the original medical information in the audit parameter is anonymized to obtain the medical information to be stored; at the same time, the first operation log is constructed based on the data operation function expression and business attributes in the audit parameter. A globally unique identifier is used to store the medical information to be stored in the medical data table, and the first operation log is stored in the audit data table.

[0006] Secondly, embodiments of this application provide an auditing device for the performance of functions in reproductive medical services, the device comprising: The information operation request receiving module is used to receive information operation requests sent by the client. The information operation request carries the patient's globally unique identifier and audit parameters. The information operation request is obtained by the user triggering the target function in the online reproductive medical service. The operation permission check module is used to check whether the information operation request has the required operation permission; The operation module is used to perform data anonymization on the original medical information in the audit parameters when the information operation request has operation permissions and the parameter status of the audit parameters is pending storage, so as to obtain the medical information to be stored; at the same time, it constructs the first operation log based on the data operation function expression and business attributes in the audit parameters. The data storage module is used to store medical information to be stored in the medical data table using a globally unique identifier, and to store the first operation log in the audit data table.

[0007] The technical solutions provided in this application embodiment may include the following beneficial effects: In this embodiment, on the one hand, if the request has the necessary permissions and the audit parameters are in a pending storage state, the system will perform data anonymization on the original medical information. This anonymization ensures that even if data is stolen during transmission or storage, attackers cannot directly obtain sensitive information, effectively reducing the risk of data theft or tampering and protecting patient privacy and data security. On the other hand, a first operation log is constructed based on the data operation function expression and business attributes in the audit parameters. Each operation request is recorded in detail in the operation log. This refined management approach allows for precise recording and monitoring of operational behaviors at each stage, improving data transparency and traceability.

[0008] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0009] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0010] Figure 1 This is a flowchart illustrating a method for auditing the execution of functions in reproductive medical services, as provided in an embodiment of this application. Figure 2 This is a UI interface diagram of a de-identified data preview provided in an embodiment of this application; Figure 3 This is a UI interface diagram for recording log information provided in an embodiment of this application; Figure 4This is a flowchart illustrating a method for querying reproductive medical data provided in an embodiment of this application; Figure 5 This is a UI interface diagram of a patient's personal information display provided in an embodiment of this application; Figure 6 This is a flowchart illustrating a method for fine-tuning a large language model provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of an auditing device for the execution of functions in reproductive medical services, provided in an embodiment of this application. Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0011] The following description and accompanying drawings fully illustrate specific embodiments of this application to enable those skilled in the art to practice them.

[0012] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0013] In the following description, when referring to the accompanying drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0014] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0015] Currently, the field of medical data management has adopted some auditing techniques to record and monitor data operation behavior.

[0016] The applicant of this application recognizes that this technology still has many shortcomings when dealing with highly sensitive and private data in the field of reproductive medicine. For example, due to insufficient encryption strength during the auditing of data transmission and storage, data is easily stolen or tampered with by criminals. Secondly, the data auditing process lacks refined management of data throughout the entire process, making it impossible to accurately record and monitor the operational behavior at each stage.

[0017] To address the aforementioned issues, this application provides an auditing method and apparatus for the execution of functions in reproductive medical services, resolving the problems existing in the related technologies. In the embodiments of this application, on one hand, if the request has the necessary permissions and the audit parameters are in a pending storage state, the system performs data anonymization processing on the original medical information. This data anonymization ensures that even if data is stolen during transmission or storage, attackers cannot directly obtain sensitive information, effectively reducing the risk of data theft or tampering and protecting patient privacy and data security. On the other hand, a first operation log is constructed based on the data operation function expression and business attributes in the audit parameters. Each operation request is recorded in detail in the operation log. This refined management method allows for precise recording and monitoring of operational behaviors at each stage, improving data transparency and traceability. Exemplary embodiments are described in detail below.

[0018] The following will be combined with the appendix Figure 1 -Appendix Figure 6 This application provides a detailed description of the auditing method for the execution of functions in reproductive medical services, as provided in the embodiments of this application. This method can be implemented using a computer program and can run on an auditing device for the execution of functions in reproductive medical services based on the von Neumann architecture. This computer program can be integrated into an application or run as a standalone utility application.

[0019] Please see Figure 1 This document provides a flowchart illustrating an auditing method for the execution of functions in reproductive medical services, applicable to the server side. Figure 1 As shown, the method in this application embodiment includes the following steps: S101, the server receives an information operation request sent by the client; the information operation request carries the patient's globally unique identifier and audit parameters, and the information operation request is obtained by the user triggering the target function in the online reproductive medical service; In this system, the server is the application running on the server, responsible for handling requests from clients and returning responses. The client is the user's device or software that initiates the request, such as a browser, mobile application, or desktop application. An information operation request is a request sent by the client to the server, containing information about the operation the user wishes to perform. A patient's globally unique identifier is an identifier used to uniquely identify the patient; it can be a string or a number. Recording parameters are additional information related to the operation, used to record and monitor its execution. The user is the entity that triggers the operation. Online reproductive medical services refer to reproductive medical services that have been deployed and are available to users. The target function is the specific function the user wishes to perform, such as querying patient information or updating patient medical records.

[0020] In some embodiments of this application, the client's browser or mobile application constructs an HTTP request containing the patient's globally unique identifier and audit parameters. The server listens on a specified port and receives the HTTP request sent by the client. The server parses the request body and extracts the patient's globally unique identifier and audit parameters.

[0021] For example, the extracted globally unique identifier is 123e4567-e89b-12d3-a456-426614174000; the audit parameters are as follows: { "operationType": "update", "operationTime": "2025-08-12T14:30:00Z", "operator": "doctor123" }

[0022] In some embodiments of this application, it is necessary to establish a medical data table and an audit data table. The specific process for establishing the medical data table includes: receiving a patient registration request sent by the client, the patient registration request carrying the patient identity information of the target patient; constructing a globally unique identifier for the target patient based on the patient identity information; and establishing a medical data table and an audit data table for the target patient based on the globally unique identifier. The medical data table is used to store the medical information of the target patient during the process of receiving reproductive medical services, and the audit data table is used to store the operation logs of operations performed on the medical information.

[0023] Patient identification information refers to the basic information used to identify patients, such as name, ID number, and contact information. Target patients are those who need to have their medical records established. Medical information refers to all information generated during the process of providing reproductive medical services, such as medical records, examination results, and treatment plans. Operation logs record detailed information about operations performed on medical information, such as operation type, operation time, and operator.

[0024] In one possible implementation, the client's browser or mobile application constructs an HTTP request containing the target patient's identity information. The server listens on a specified port and receives HTTP requests from the client. The server parses the request body and extracts the patient's identity information. The server generates a globally unique identifier based on the UUID algorithm and the patient's identity information. Based on this globally unique identifier, the server creates medical data tables and audit data tables for the patient.

[0025] For example, a user (such as a doctor) needs to create a profile for a new patient, Zhang San. The doctor selects the function to create a profile for the new patient Zhang San within the mobile application. The mobile application constructs an HTTP POST request containing the patient's identity information. The HTTP POST request body is as follows: { "name": "Zhang San", "idNumber": "123456789012345678", "contact": "13812345678" The server generates a globally unique identifier (123e4567-e89b-12d3-a456-426614174000) based on the UUID algorithm and the patient's identity information. Using this globally unique identifier, the server creates a medical data table and an audit data table for patient Zhang San. The patient_id in both the medical data table and the audit data table is 123e4567-e89b-12d3-a456-426614174000.

[0026] S102, The server checks whether the information operation request has the necessary operation permissions; In some embodiments of this application, the specific process of checking whether an information operation request has operation permissions includes: extracting the user identity identifier, user role identifier, and operation type from the information operation request; querying a preset user session table to check whether the user identity identifier exists and is valid, and obtaining an authentication result; obtaining a list of target permissions that allow the user role identifier to perform from a pre-established user role and permission mapping table; checking whether the operation type is in the target permission list, and obtaining a permission verification result; if both the authentication result and the permission verification result are yes, determining that the information operation request has operation permissions; or if either the authentication result or the permission verification result is no, determining that the information operation request does not have operation permissions.

[0027] The system includes the following components: User Identity ID (for uniquely identifying a user), User Role ID (for identifying a user's role, such as doctor, nurse, or admin), Operation Type (for the specific operation performed by the user, such as query, update, or delete), Preset User Session Table (for verifying the validity of the user identity ID), User Role and Permission Mapping Table (for verifying user roles and corresponding permissions), Target Permission List (for listing the operations allowed for a user role), Authentication Result (a boolean value indicating validity, where true indicates validity and false indicates invalidity), and Permission Validation Result (for verifying permission to perform a specific operation).

[0028] In one possible implementation, the user identity, user role identity, and operation type are extracted from the information operation request. For example, user identity: user123, user role identity: doctor, operation type: update. The session token of user123 is checked for validity, and the authentication result is returned. The permission list for the doctor role ["query", "update"] is obtained. It is checked whether update is in ["query", "update"], and the permission verification result is returned. If both the authentication result and the permission verification result are true, the information operation request is determined to have the necessary permissions. If either the authentication result or the permission verification result is false, the information operation request is determined to lack the necessary permissions.

[0029] S103, when the server has the operation permission for the information operation request and the parameter status of the audit parameter is pending storage, the original medical information in the audit parameter is anonymized to obtain the medical information to be stored; at the same time, the first operation log is constructed based on the data operation function expression and business attributes in the audit parameter. Here, parameter status refers to the current state of the audit parameter, such as whether it needs to be stored. Raw medical information refers to unprocessed medical data, a JSON object containing specific medical information, such as patient medical records and examination results. Data operation function expressions describe the specific logic for operating on the data. Business attributes refer to the business context information related to the operation, a JSON object containing information such as operation time, operator, and operation target. The first operation log is a JSON object containing information such as operation type, operation time, and operator.

[0030] In one possible implementation, the system confirms that the information operation request has the necessary permissions. It then checks if the audit parameter status is "pending storage." The raw medical information is then extracted from the audit parameters. The raw medical information is shown below: { "patientId": "123e4567-e89b-12d3-a456-426614174000", "medicalInfo": { "name": "Zhang San", "idNumber": "123456789012345678", "diagnosis": Acute appendicitis } }

[0031] In some embodiments of this application, the specific process of data anonymizing the original medical information in the audit parameters to obtain the medical information to be stored includes: parsing the original medical information to obtain each target field and the field attribute value of each target field; obtaining the target anonymized description text corresponding to each target field from the pre-established mapping relationship between fields and anonymized description text; the anonymized description text is used to characterize the specific rules for data anonymizing the fields; constructing anonymized prompt words for the original medical information based on the field attribute value of each target field and the target anonymized description text corresponding to each target field; inputting the field attribute value of each target field and the anonymized prompt words into a pre-fine-tuned large language model to output the anonymized attribute value and the anonymized sensitive characters corresponding to each target field; encrypting the anonymized sensitive characters corresponding to each target field to obtain the character encryption result corresponding to each target field; associating the character encryption result corresponding to each target field with the anonymized attribute value corresponding to each target field to obtain the medical data corresponding to each target field; and packaging the medical data corresponding to each target field to obtain the medical information to be stored. For example... Figure 2 As shown, during the operation, the doctor enters "Name is Zhang San", and can then see the relevant results of the desensitization preview. After the doctor clicks to confirm the update, it can be stored in the medical data table.

[0032] The target field refers to the specific field that needs to be de-identified, such as name, ID number, disease diagnosis, etc., for example, "Zhang San" or "123456789012345678". The mapping relationship between fields and de-identified description text is the de-identification rule corresponding to each field, as shown in Table 1.

[0033] Table 1

[0034] In this context, "de-sensitization prompts" refers to the information used to guide the de-sensitization process. "Pre-tuned large language model" refers to a language model trained for a specific task, such as GPT or BERT. "De-sensitized attribute values" refer to the field values ​​after de-sensitization processing. "De-sensitized sensitive characters" refer to the de-sensitized portions of the original field values.

[0035] In one possible implementation, each target field and its field attribute values ​​are extracted. For example, {"name":"Zhang San","idNumber": "123456789012345678","diagnosis": "acute appendicitis"}. From the mapping relationship between fields and the desensitized description text, the desensitization rule corresponding to each target field is obtained. For example, {"name": "Replace name with random characters","idNumber": "Retain the first 6 and last 4 digits of the ID number, replace the middle part with random numbers","diagnosis": "Fuzzyize the specific disease name to the system's corresponding disease"}. Based on the field attribute values ​​of each target field and the target desensitized description text, desensitization prompts are constructed. The prompts could be: For the field "Name", whose original value is "Zhang San", please perform desensitization according to the following rules: replace the name with random characters; For the field "ID Number", whose original value is "123456789012345678", please perform desensitization according to the following rules: retain the first 6 and last 4 digits of the ID number, and replace the middle part with random numbers; For the field "Disease Diagnosis", whose original value is "Acute Appendicitis", please perform desensitization according to the following rules: obfuscate the specific disease name to the system's disease category.

[0036] Secondly, the encryption result corresponding to each target field is associated with the de-identified attribute value to obtain the medical data corresponding to each target field. For example: {"name": {"desensitizedValue":"ABCDEF","encryptedCharacters":"encrypted_string"}, "idNumber": {"desensitizedValue":"123456...1234","encryptedCharacters":"encrypted_string"}, "diagnosis": The data is packaged into a single file: {"desensitizedValue":"Digestive system diseases","encryptedCharacters":"encrypted_string"}}. Finally, the medical data corresponding to each target field is packaged to obtain the medical information to be stored.

[0037] In this embodiment, by parsing the original medical information and combining it with preset desensitization rules to desensitize key fields, and encrypting sensitive information, not only is patient privacy effectively protected and sensitive data leakage prevented, but the security of data during storage and transmission is also enhanced, ensuring the compliance and integrity of medical data, providing reliable data support for medical services, and increasing patients' trust in medical data management.

[0038] In some embodiments, the specific process of constructing desensitization prompts for original medical information based on the field attribute values ​​of each target field and the target desensitization description text corresponding to each target field includes: creating key-value pairs; using the field attribute values ​​of each target field as the keys in the key-value pairs and the target desensitization description text corresponding to each target field as the values ​​in the key-value pairs, to obtain multiple target key-value pairs for filling parameters; and using the multiple target key-value pairs as desensitization prompts for the original medical information. The key-value pair method is clear in structure, easy to extend, and convenient to debug, making it suitable for use in the development and maintenance phases, especially in scenarios with a large number of fields or frequent changes in desensitization rules.

[0039] In other embodiments, the specific process of constructing desensitized prompts for original medical information based on the field attribute values ​​of each target field and the corresponding desensitized description text includes: associating the field attribute values ​​of each target field with the corresponding desensitized description text to obtain desensitized prompts for each target field; and sequentially merging the desensitized prompts for each target field according to their field order in the original medical information to obtain the desensitized prompts for the original medical information. The advantage of the field order association method is that it preserves the field order and contextual relationships of the original data, making it suitable for scenarios where logical relationships between fields need to be considered or data traceability needs to be performed.

[0040] It should be noted that the two methods for constructing anonymized prompts can respond to user settings or make intelligent decisions based on business parameters of the business scenario.

[0041] Among them, the data operation function expression is used to describe the operation logic on the data, and the business attribute is the business context information related to the operation.

[0042] In some embodiments of this application, the specific process of constructing a first operation log based on data operation function expressions and business attributes in audit parameters includes: parsing the data operation function expressions using regular expressions or a syntax parser to extract the operation type and operation target; generating a specific operation description based on the operation type and operation target; constructing a basic framework for the operation log based on a preset audit log template; and filling the specific operation description and operation-related business context information into the basic framework of the operation log to obtain the first operation log. For example... Figure 3 As shown, administrators can view the operation log information by clicking on the log details.

[0043] Regular expressions are used to match patterns of character combinations in a string. A syntax parser is a tool used to parse and understand the structure of code or text. A preset audit log template refers to a predefined log format used to record detailed operation information; it is a string template containing placeholders, for example: Log ID: {logId}. Patient ID: {patientId} Operation Type: {operationType}、 Operation Time: {operationTime}、 Operator: {operator}、 Operation Details: {operationDetails}.

[0044] S104, the server uses a globally unique identifier to store the medical information to be stored in the medical data table and the first operation log in the audit data table.

[0045] The medical information to be stored is, for example: { "patientId": "123e4567-e89b-12d3-a456-426614174000", "medicalInfo": { "name": { "desensitizedValue": "ABCDEF", "encryptedCharacters": "encrypted_string" }, "idNumber": { "desensitizedValue": "123456......1234", "encryptedCharacters": "encrypted_string" }, "diagnosis": { "desensitizedValue": "Digestive system diseases", "encryptedCharacters": "encrypted_string" } } }

[0046] The first operation log is, for example, as follows: { "logId": "log123", "patientId": "123e4567-e89b-12d3-a456-426614174000", "operationType": "update", "operationTime": "2025-08-12T14:30:00Z", "operator": "doctor123", "operationDetails": "Updated patient diagnosis to 'digestive system disease'" }

[0047] Finally, a globally unique identifier (patientId) is used to store the medical information to be stored in a medical data table, as shown in Table 2.

[0048] Table 2

[0049] The first operation log is stored in the audit data table using a globally unique identifier (patientId), as shown in Table 3.

[0050] Table 3

[0051] In some embodiments of this application, when the information operation request has operation permissions and the parameter status of the audit parameters is pending update, the data to be updated is obtained from the medical data table based on the business attributes and globally unique identifiers; the data operation function expression is executed to update the data to be updated, and the medical data update result is obtained; at the same time, a second operation log is constructed based on the data operation function expression and business attributes in the audit parameters; the medical data update result is stored in the medical data table using a globally unique identifier, and the second operation log is stored in the audit data table; or, if the information operation request does not have operation permissions, the user who initiated the information operation request is controlled to exit the system.

[0052] In this embodiment, on the one hand, if the request has the necessary permissions and the audit parameters are in a pending storage state, the system will perform data anonymization on the original medical information. This anonymization ensures that even if data is stolen during transmission or storage, attackers cannot directly obtain sensitive information, effectively reducing the risk of data theft or tampering and protecting patient privacy and data security. On the other hand, a first operation log is constructed based on the data operation function expression and business attributes in the audit parameters. Each operation request is recorded in detail in the operation log. This refined management approach allows for precise recording and monitoring of operational behaviors at each stage, improving data transparency and traceability.

[0053] Please see Figure 4 This is a flowchart illustrating a method for querying reproductive medical data, as provided in this application embodiment, applied to the server side. For example... Figure 4 As shown, the method in this application embodiment includes the following steps: S201, Receive information query request sent by the client. The information query request carries the globally unique identifier of the target patient and the query conditions. S202 combines globally unique identifiers and query conditions into a data query script; S203, Execute the data query script to obtain the target patient's medical data package from the medical data table. The medical data package includes the character encryption result corresponding to each field and the desensitized attribute value corresponding to each field. S204 uses a local encryption algorithm to decrypt the encrypted character result corresponding to each field, obtaining the desensitized sensitive characters corresponding to each field; S205, insert the desensitized sensitive characters corresponding to each field into the corresponding positions of the desensitized attribute values ​​of each field to obtain the original field attribute values ​​of each field; S206 generates query results based on the original field attribute values ​​of each field; S207 displays the query results.

[0054] For example Figure 5 As shown, the query results displayed when a doctor clicks on a user are as follows: Figure 5 As shown.

[0055] In this embodiment, data is transmitted in encrypted form during the query process. Even if intercepted during transmission, the encryption algorithm exists only locally on the doctor's client, preventing attackers from decrypting and restoring the data, thus enhancing data security during transmission. Furthermore, by inserting the decrypted sensitive characters into the corresponding positions of the anonymized attribute values, the original field attribute values ​​can be completely restored. This ensures the integrity and accuracy of the data during querying and use, guaranteeing that doctors can obtain complete patient information.

[0056] Please see Figure 6 This is a flowchart illustrating a method for fine-tuning a large language model, as provided in this application embodiment. Figure 6 As shown, the method in this application embodiment may include the following steps: S301, Collect sample data containing raw medical information, covering all field types that need to be de-identified; S302, perform sensitive data annotation on the attribute values ​​of each field to be desensitized in the sample data to obtain the desensitization result corresponding to each field to be desensitized; S303, Based on the field attribute values ​​of each field to be de-identified in the sample data and the pre-established mapping relationship between the fields and the de-identification description text, construct the de-identification prompt words for each field to be de-identified; S304. Associate and bind the desensitization result corresponding to each field to be desensitized with the desensitization prompt word of each field to be desensitized to obtain the labeled training data. S305, Load the large language model; the large language model can be ChatGPT.

[0057] S306. The labeled training data is input into the large language model for model fine-tuning to obtain the pre-fine-tuned large language model.

[0058] In this embodiment, the finely tuned large language model can automatically de-identify sensitive data based on de-identification prompts, reducing the need for manual intervention and lowering the risk of data leakage due to human error. Furthermore, the de-identified data is more secure during storage and transmission; even if illegally obtained, it cannot be directly restored to its original sensitive information.

[0059] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0060] Please see Figure 7This illustration shows a schematic diagram of an auditing device for the execution of functions in a reproductive medical service, provided by an exemplary embodiment of this application. This auditing device for the execution of functions in a reproductive medical service can be implemented as all or part of an electronic device through software, hardware, or a combination of both. The device 1 includes an information operation request receiving module 10, an operation permission checking module 20, an operation module 30, and a data storage module 40.

[0061] The information operation request receiving module 10 is used to receive information operation requests sent by the client; wherein, the information operation request carries the patient's globally unique identifier and audit parameters, and the information operation request is obtained by the user triggering the target function in the online reproductive medical service; The operation permission check module 20 is used to check whether the information operation request has the operation permission; Operation module 30 is used to perform data anonymization on the original medical information in the audit parameters when the information operation request has operation permissions and the parameter status of the audit parameters is pending storage, so as to obtain the medical information to be stored; at the same time, it constructs the first operation log based on the data operation function expression and business attributes in the audit parameters. The data storage module 40 is used to store the medical information to be stored in the medical data table using a globally unique identifier, and to store the first operation log in the audit data table.

[0062] It should be noted that the auditing device for the execution of functions in reproductive medical services provided in the above embodiments is only illustrated by the division of the above functional modules when executing the auditing method for the execution of functions in reproductive medical services. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the auditing device for the execution of functions in reproductive medical services and the auditing method for the execution of functions in reproductive medical services provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0063] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0064] In this embodiment, on the one hand, if the request has the necessary permissions and the audit parameters are in a pending storage state, the system will perform data anonymization on the original medical information. This anonymization ensures that even if data is stolen during transmission or storage, attackers cannot directly obtain sensitive information, effectively reducing the risk of data theft or tampering and protecting patient privacy and data security. On the other hand, a first operation log is constructed based on the data operation function expression and business attributes in the audit parameters. Each operation request is recorded in detail in the operation log. This refined management approach allows for precise recording and monitoring of operational behaviors at each stage, improving data transparency and traceability.

[0065] This application also provides a computer-readable medium having program instructions stored thereon, which, when executed by a processor, implement the auditing method for the execution of functions in the reproductive medical services provided in the above-described method embodiments.

[0066] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to perform an auditing method for the execution of functions in the reproductive medical services described in the various method embodiments above.

[0067] Please see Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 8 As shown, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, and at least one communication bus 1002.

[0068] The communication bus 1002 is used to realize the connection and communication between these components.

[0069] The user interface 1003 may include a display screen and a camera. Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0070] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0071] The processor 1001 may include one or more processing cores. The processor 1001 connects to various parts within the electronic device 1000 using various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and by calling data stored in the memory 1005. Optionally, the processor 1001 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 1001 may integrate one or more of the following: a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), and a modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip, without being integrated into the processor 1001.

[0072] The memory 1005 may include random access memory (RAM) or read-only memory. Optionally, the memory 1005 may include a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 1005 may also be at least one storage system located remotely from the aforementioned processor 1001. Figure 8 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an auditing application for the execution of functions in reproductive medical services.

[0073] exist Figure 8In the illustrated electronic device 1000, the user interface 1003 is mainly used to provide an input interface for the user and to obtain the user's input data; while the processor 1001 can be used to call the audit application stored in the memory 1005 for the execution of functions in reproductive medical services, and specifically perform the following operations: Receive information operation requests sent by the client; the information operation request carries the patient's globally unique identifier and audit parameters, and the information operation request is obtained by the user triggering the target function in the online reproductive medical service; Check whether the information operation request has the necessary permissions; When the information operation request has the operation permission and the parameter status of the audit parameter is pending storage, the original medical information in the audit parameter is anonymized to obtain the medical information to be stored; at the same time, the first operation log is constructed based on the data operation function expression and business attributes in the audit parameter. A globally unique identifier is used to store the medical information to be stored in the medical data table, and the first operation log is stored in the audit data table.

[0074] In one embodiment, when processor 1001 performs data anonymization on the original medical information in the audit parameters to obtain the medical information to be stored, it specifically performs the following operations: Parse the raw medical information to obtain each target field and the field attribute value of each target field; Obtain the target desensitization description text corresponding to each target field from the pre-established mapping relationship between fields and desensitization description text; the desensitization description text is used to characterize the specific rules for data desensitization of the field; Based on the field attribute values ​​of each target field and the target de-identification description text corresponding to each target field, construct de-identification prompts for the original medical information; Input the field attribute value and desensitization prompt of each target field into the pre-fine-tuned large language model, and output the desensitization attribute value and desensitized sensitive characters corresponding to each target field; Encrypt the sensitive characters that have been de-identified for each target field to obtain the character encryption result for each target field; The encrypted character result corresponding to each target field is associated with the de-identified attribute value corresponding to each target field to obtain the medical data corresponding to each target field; The medical data corresponding to each target field is packaged to obtain the medical information to be stored.

[0075] In one embodiment, when the processor 1001 constructs de-identification prompts for the original medical information based on the field attribute values ​​of each target field and the target de-identification description text corresponding to each target field, it specifically performs the following operations: Create key-value pairs; The field attribute value of each target field is used as the key in the key-value pair, and the target de-identification description text corresponding to each target field is used as the value in the key-value pair, thus obtaining multiple target key-value pairs for filling parameters; Use multiple target key-value pairs as desensitization prompts for the original medical information; or... Associate the field attribute value of each target field with the target desensitization description text corresponding to each target field to obtain the desensitization prompt words for each target field; Based on the field order of each target field in the original medical information, the desensitization prompts for each target field are merged sequentially to obtain the desensitization prompts for the original medical information.

[0076] In one embodiment, when the processor 1001 generates a pre-fine-tuned large language model, it specifically performs the following operations: Collect sample data containing raw medical information, covering all field types that need to be anonymized; Sensitive data annotation is performed on the attribute values ​​of each field to be de-identified in the sample data to obtain the de-identification result corresponding to each field to be de-identified; Based on the field attribute values ​​of each field to be de-identified in the sample data and the pre-established mapping relationship between the fields and the de-identification description text, construct de-identification prompts for each field to be de-identified; The anonymization results for each field to be anonymized are associated with the anonymization prompts for each field to be anonymized, thus obtaining labeled training data. Loading a large language model; The labeled training data is input into the large language model for fine-tuning, resulting in a pre-tuned large language model.

[0077] In one embodiment, the processor 1001 also performs the following operations: Receive information query requests sent by clients, which carry the globally unique identifier of the target patient and query conditions; Combine globally unique identifiers and query conditions into a data query script; Execute the data query script to retrieve the target patient's medical data package from the medical data table. The medical data package includes the character encryption result for each field and the desensitized attribute value for each field. Using a local encryption algorithm, the encrypted character result corresponding to each field is decrypted to obtain the de-identified sensitive characters corresponding to each field; Insert the desensitized sensitive characters corresponding to each field into the corresponding positions of the desensitized attribute values ​​of each field to obtain the original field attribute values ​​of each field; Generate query results based on the original field attribute values ​​of each field; Display the query results.

[0078] In one embodiment, before executing the message operation request sent by the client, the processor 1001 also performs the following operations: Receive patient registration requests sent by the client. The patient registration requests carry the patient's identity information. Based on patient identity information, construct a globally unique identifier for the target patient; Based on a globally unique identifier, establish a medical data table and an audit data table for the target patient; the medical data table is used to store the medical information of the target patient during the process of receiving reproductive medical services, and the audit data table is used to store the operation log of operations performed on the medical information.

[0079] In one embodiment, when the processor 1001 performs the operation of checking whether the information operation request has the necessary permissions, it performs the following operations: Extract the user identity identifier, user role identifier, and operation type from the information operation request; Query the preset user session table to check if the user identity exists and is valid, and obtain the authentication result; Retrieve the list of target permissions that can be performed by user role identifiers from the pre-established user role and permission mapping table; Check if the operation type is in the target permission list and obtain the permission verification result; If both the authentication and permission verification results are positive, the information operation request is determined to have the necessary permissions; otherwise, if either the authentication or permission verification result is negative, the information operation request is determined to lack the necessary permissions.

[0080] In one embodiment, when processor 1001 constructs the first operation log based on the data operation function expression and business attributes in the audit parameters, it specifically performs the following operations: Use regular expressions or a syntax parser to parse data manipulation function expressions to extract the operation type and operation target; Generate a detailed operation description based on the operation type and operation objective; Construct the basic framework of the operation log based on the preset audit log template; The first operation log is obtained by filling the basic framework of the operation log with the specific operation description and the business context information related to the operation.

[0081] In one embodiment, the processor 1001 also performs the following operations: When the information operation request has the operation permission and the parameter status of the audit parameter is pending update, the data to be updated is obtained from the medical data table based on the business attributes and the globally unique identifier; Execute the data manipulation function expression to update the data to be updated and obtain the medical data update result; at the same time, construct a second operation log based on the data manipulation function expression and business attributes in the audit parameters; Using globally unique identifiers, the medical data update results are stored in the medical data table, and the second operation log is stored in the audit data table; or, If the user who initiated the information operation request does not have the necessary permissions, the system will log the user out of the system.

[0082] In this embodiment, on the one hand, if the request has the necessary permissions and the audit parameters are in a pending storage state, the system will perform data anonymization on the original medical information. This anonymization ensures that even if data is stolen during transmission or storage, attackers cannot directly obtain sensitive information, effectively reducing the risk of data theft or tampering and protecting patient privacy and data security. On the other hand, a first operation log is constructed based on the data operation function expression and business attributes in the audit parameters. Each operation request is recorded in detail in the operation log. This refined management approach allows for precise recording and monitoring of operational behaviors at each stage, improving data transparency and traceability.

[0083] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The auditing program for the execution of functions in reproductive medical services can be stored in a computer-readable storage medium. When executed, this program can include the processes of the embodiments of the above methods. The storage medium for the auditing program for the execution of functions in reproductive medical services can be a magnetic disk, optical disk, read-only memory, or random access memory, etc.

[0084] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for auditing the performance of functions in reproductive medical services, characterized in that, Applied to the server side, the method includes: Receive information operation requests sent by the client; wherein, the information operation request carries the patient's globally unique identifier and audit parameters, and the information operation request is obtained by the user triggering a target function in the online reproductive medical service; Check whether the information operation request has the necessary permissions; When the information operation request has operation permission and the parameter status of the audit parameter is pending storage, the original medical information in the audit parameter is anonymized to obtain the medical information to be stored; at the same time, a first operation log is constructed based on the data operation function expression and business attributes in the audit parameter. Using the globally unique identifier, the medical information to be stored is stored in the medical data table, and the first operation log is stored in the audit data table.

2. The method according to claim 1, characterized in that, The process of desensitizing the original medical information in the audit parameters to obtain the medical information to be stored includes: The original medical information is parsed to obtain each target field and the field attribute value of each target field; From the pre-established mapping relationship between fields and desensitized description text, obtain the target desensitized description text corresponding to each target field; the desensitized description text is used to characterize the specific rules for data desensitization of the field; Based on the field attribute value of each target field and the target de-identification description text corresponding to each target field, de-identification prompt words for the original medical information are constructed; The field attribute value of each target field and the desensitized prompt word are input into a pre-fine-tuned large language model, and the desensitized attribute value and desensitized sensitive character corresponding to each target field are output. The sensitive characters corresponding to each target field that have been de-identified are encrypted to obtain the character encryption result corresponding to each target field; The character encryption result corresponding to each target field is associated with the de-identification attribute value corresponding to each target field to obtain the medical data corresponding to each target field; The medical data corresponding to each target field is packaged to obtain the medical information to be stored.

3. The method according to claim 2, characterized in that, The process of constructing desensitization prompts for the original medical information based on the field attribute values ​​of each target field and the corresponding desensitization description text for each target field includes: Create key-value pairs; The field attribute value of each target field is used as the key in the key-value pair, and the target de-identification description text corresponding to each target field is used as the value in the key-value pair, to obtain multiple target key-value pairs for filling parameters; Use the multiple target key-value pairs as desensitization prompts for the original medical information; or... The field attribute value of each target field is associated with the target de-identification description text corresponding to each target field to obtain the de-identification prompt words for each target field; According to the field order of each target field in the original medical information, the desensitization prompts of each target field are merged sequentially to obtain the desensitization prompts of the original medical information.

4. The method according to claim 2, characterized in that, Generate a pre-tuned large language model by following these steps: Collect sample data containing raw medical information, covering all field types that need to be anonymized; Sensitive data annotation is performed on the attribute values ​​of each field to be de-identified in the sample data to obtain the de-identification result corresponding to each field to be de-identified; Based on the field attribute values ​​of each field to be de-identified in the sample data and the pre-established mapping relationship between the fields and the de-identification description text, construct the de-identification prompt words for each field to be de-identified; The desensitization result corresponding to each field to be desensitized is associated and bound with the desensitization prompt word of each field to be desensitized to obtain labeled training data; Loading a large language model; The labeled training data is input into the large language model for model fine-tuning to obtain a pre-fine-tuned large language model.

5. The method according to claim 1, characterized in that, The method further includes: Receive an information query request sent by a client, the information query request carrying a globally unique identifier of the target patient and query conditions; Combine the globally unique identifier and query conditions into a data query script; The data query script is executed to obtain the medical data package of the target patient from the medical data table. The medical data package includes the character encryption result corresponding to each field and the desensitized attribute value corresponding to each field. A local encryption algorithm is used to decrypt the character encryption result corresponding to each field to obtain the de-identified sensitive characters corresponding to each field; The de-sensitized sensitive characters corresponding to each field are inserted into the corresponding positions of the de-sensitized attribute values ​​of each field to obtain the original field attribute values ​​of each field; Based on the original field attribute values ​​of each field, generate query results; Display the query results.

6. The method according to any one of claims 1-5, characterized in that, Before receiving the information operation request sent by the client, the method further includes: Receive a patient registration request sent by the client, wherein the patient registration request carries the patient identity information of the target patient; Based on the patient's identity information, a globally unique identifier for the target patient is constructed; Based on the globally unique identifier, a medical data table and an audit data table are established for the target patient; the medical data table is used to store the medical information of the target patient during the process of receiving reproductive medical services, and the audit data table is used to store the operation log of operations performed on the medical information.

7. The method according to any one of claims 1-5, characterized in that, The step of checking whether the information operation request has the necessary permissions includes: Extract the user identity identifier, user role identifier, and operation type from the information operation request; The system queries a preset user session table to check if the user identity identifier exists and is valid, and obtains the authentication result. Obtain a list of target permissions that are allowed to be executed by the user role identifier from the pre-established user role and permission mapping table; Check whether the operation type is in the target permission list to obtain the permission verification result; If both the authentication result and the permission verification result are yes, the information operation request is determined to have operation permission; or if either the authentication result or the permission verification result is no, the information operation request is determined to not have operation permission.

8. The method according to any one of claims 1-5, characterized in that, The data operation function expression is used to describe the operation logic on the data, and the business attribute is the business context information related to the operation; The construction of the first operation log based on the data operation function expression and business attributes in the audit parameters includes: The data manipulation function expression is parsed using regular expressions or a syntax parser to extract the operation type and operation target; Based on the operation type and operation objective, generate a specific operation description; Construct the basic framework of the operation log based on the preset audit log template; The specific operation description and the business context information related to the operation are filled into the basic framework of the operation log to obtain the first operation log.

9. The method according to any one of claims 1-5, characterized in that, The method further includes: When the information operation request has operation permission and the parameter status of the audit parameter is pending update, the data to be updated is obtained from the medical data table according to the business attribute and the globally unique identifier; The data manipulation function expression is executed to update the data to be updated, resulting in a medical data update; simultaneously, a second operation log is constructed based on the data manipulation function expression and business attributes in the audit parameters. Using the globally unique identifier, the medical data update result is stored in the medical data table, and the second operation log is stored in the audit data table; or, If the user who initiated the information operation request does not have the necessary permissions, the system will control the user to exit the system.

10. An auditing device for the performance of functions in reproductive medical services, characterized in that, The device includes: The information operation request receiving module is used to receive information operation requests sent by the client; wherein, the information operation request carries the patient's globally unique identifier and audit parameters, and the information operation request is obtained by the user triggering the target function in the online reproductive medical service; The operation permission check module is used to check whether the information operation request has the required operation permission; The operation module is used to perform data anonymization on the original medical information in the audit parameters to obtain the medical information to be stored when the information operation request has operation permission and the parameter status of the audit parameters is pending storage; at the same time, it constructs a first operation log based on the data operation function expression and business attributes in the audit parameters. The data storage module is used to store the medical information to be stored in the medical data table using the globally unique identifier, and to store the first operation log in the audit data table.

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