Medical information display method and device, electronic equipment and readable storage medium

Abstract

The invention provides a medical information display method and device, electronic equipment and a readable storage medium. The method comprises the steps that a java mapping rule input request uploaded by a user terminal is acquired; establishing a java mapping rule according to the java mapping rule input request; obtaining an analysis result generation request uploaded by a user terminal; according to information carried in the analysis result generation request and a pre-established java mapping rule, calling attribute information of a target field in the system; generating an analysis result according to the analysis rule and the called attribute information; inquiring identity information of a target user sending the analysis result generation request, and determining an encryption permission level of the target user according to the identity information; and encrypting the analysis result according to an encryption mode corresponding to the encryption permission level, and sending the encrypted analysis result to the target user so as to display the analysis result in a target terminal used by the target user. Through the method, the flexibility and the accuracy of information searching are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computers, and in particular to a medical information display method and device, electronic equipment and readable storage medium. BACKGROUND

[0002] The traditional clinical trial statistical data processing method relies on a full-process operation dominated by manual operation, which is tedious and inefficient. First, researchers need to extract raw data from scattered data sources of different clinical trial projects. These data sources are diverse, including unstructured or semi-structured documents such as paper medical records and Excel spreadsheets, and also include electronic data stored in isolation in hospital information systems (HIS) and laboratory information systems (LIS), and the form fields of different projects have great differences in naming and format (for example, the "subject enrollment date" field in project A is "enrollment_date", and the "recruit_time" field in project B, and even handwritten in the paper form in project C). When extracting data, researchers need to connect different data sources one by one, manually enter or copy and paste data into a unified table.

[0003] After the data collection is completed, a large amount of preprocessing work needs to be done, such as manually sorting field meanings, unifying data formats, removing duplicate or invalid data, and filling in missing values. Then, for the preset statistical items (such as "weekly enrollment number", "adverse event rate in different test centers", and "subject age distribution"), researchers need to manually write complex formulas in Excel for calculation, and if it involves multi-dimensional statistics (such as grouping by age + test center dimension statistics enrollment), the table needs to be split and the formula needs to be adjusted multiple times.

[0004] After the calculation is completed, bar charts, line charts and other charts need to be manually drawn using Excel or other simple tools, and the chart style, coordinate axis setting and data series annotation all need to be manually adjusted; if new statistical items (such as adding "differences in efficacy of subjects of different genders") or switching statistical dimensions (such as changing from "weekly statistics" to "monthly statistics") are needed during the clinical trial process, the data needs to be reselected, the calculation formula needs to be modified, and the chart needs to be reconstructed. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a medical information display method, device, electronic equipment and readable storage medium to ensure the flexibility and accuracy of information searching and improve the security of information sending.

[0006] In a first aspect, the embodiments of the present application provide a medical information display method, which includes a database establishment stage and an information display stage. The database establishment stage includes: The server acquires a java mapping rule input request uploaded by the user terminal; the java mapping rule input request carries multiple items including project identification, form identification, field information and statistical item information; The server establishes a java mapping rule according to the java mapping rule input request, and the java mapping rule represents the mapping relationship between the field information and the statistical item information, the project identification and the form identification; The information display stage includes: The server acquires an analysis result generation request uploaded by the user terminal, and the analysis result generation request carries the analysis rule, the project identification, the form identification and the statistical item information; The server calls the attribute information of the target field in the system according to the information carried in the analysis result generation request and the pre-established java mapping rule; The server generates an analysis result according to the analysis rule and the called attribute information; The server queries the identity information of the target user who sends the analysis result generation request, and determines the encryption permission level of the target user according to the identity information; The server encrypts the analysis result according to the encryption method corresponding to the encryption permission level, and sends the encrypted analysis result to the target user to display the analysis result on the target terminal used by the target user.

[0007] With reference to the first aspect, the first possible implementation manner of the first aspect is provided, and the server encrypts the analysis result according to the encryption method corresponding to the encryption permission level, including: If the encryption permission level is a low level, the public key is used for encryption; If the encryption permission level is a middle level, the personal key is used for encryption; If the encryption permission level is a high level, the personal key and the temporary key are used for encryption.

[0008] With reference to the first aspect, the second possible implementation manner of the first aspect is provided, and the encrypted analysis result is sent to the target user, including: If the encryption permission level is a low level, the encrypted analysis result is transmitted to the target user through a public network link; If the encryption permission level is a middle level, the encrypted analysis result is sent to the target user through a project group intranet special link; If the encryption permission level is a high level, the encrypted analysis result is sent to the target user through a VPN dedicated line connection.

[0009] With reference to the first aspect, in a third possible implementation of the first aspect, the method further comprises: The target terminal, after receiving the encrypted analysis result, performs verification in any of the following manners, and displays the analysis result after the verification is passed: Data integrity verification, signature verification, identity token verification, VPN account verification, and temporary approval token verification.

[0010] With reference to the first aspect, in a fourth possible implementation of the first aspect, the server generates the analysis result according to the analysis rule and the called attribute information, and the generating comprises: The server queries a matching degree of the attribute information and the target user access permission level according to the access permission level of the attribute information, and calls target information that meets the matching from the attribute information according to the matching degree; The server generates the analysis result according to the target information.

[0011] With reference to the fourth possible implementation of the first aspect, in a fifth possible implementation of the first aspect, the matching degree comprises: only viewing, viewing and analyzing, and being unable to view and analyze.

[0012] In a second aspect, the embodiments of the present application further provide a medical information display device, which is applied to a server, and comprises: A first obtaining module is configured to obtain a java mapping rule input request uploaded by a user terminal, wherein the java mapping rule input request carries multiple items selected from the following: project identification, form identification, field information, and statistical item information. A establishing module is configured to establish a java mapping rule according to the java mapping rule input request, wherein the java mapping rule represents a mapping relationship between the field information, the statistical item information, the project identification, and the form identification. A second obtaining module is configured to obtain an analysis result generation request uploaded by the user terminal, wherein the analysis result generation request carries an analysis rule, a project identification, a form identification, and statistical item information. A calling module is configured to call attribute information of a target field in the system according to information carried in the analysis result generation request and the pre-established java mapping rule. A generating module is configured to generate an analysis result according to the analysis rule and the called attribute information. A querying module is configured to query identity information of a target user who sends the analysis result generation request, and determine an encryption permission level of the target user according to the identity information. The encryption module is configured to encrypt the analysis result according to an encryption manner corresponding to the encryption permission level, and send the encrypted analysis result to the target user, so as to display the analysis result on a target terminal used by the target user.

[0013] With reference to the second aspect, the first possible implementation manner of the second aspect is provided in the embodiments of the present application, and the encryption module is configured to: If the encryption permission level is a low level, the public key is used for encryption; If the encryption permission level is a middle level, the personal key is used for encryption; If the encryption permission level is a high level, the personal key and the temporary key are used for encryption.

[0014] In the third aspect, the embodiments of the present application further provide an electronic device, which comprises a processor, a memory and a bus, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, and the machine readable instructions are executed by the processor to perform the steps in any one of the possible implementation manners of the first aspect.

[0015] In the fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores a computer program, and the computer program is executed by the processor to perform the steps in any one of the possible implementation manners of the first aspect.

[0016] The medical information display method and device, the electronic device and the readable storage medium provided by the embodiments of the present application can ensure the flexibility and accuracy of information searching by using the java mapping method to search information before displaying the information, and the encryption permission control mechanism is added before displaying the information, so that the security of information transmission is improved.

[0017] In order to make the above objectives, characteristics and advantages of the present application more apparent and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiments, and it should be understood that the following drawings only show some embodiments of the present application, and should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can be obtained without creative labor on the basis of these drawings.

[0019] Figure 1 A flow chart of a medical information display method provided by an embodiment of the application is shown; Figure 2 A schematic diagram of a communication connection relationship between a user terminal and a server provided by an embodiment of the application is shown; Figure 3 A structural schematic diagram of a medical information display device provided by an embodiment of the application is shown; Figure 4 A structural schematic diagram of an electronic device provided by an embodiment of the application is shown. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and superiorities of the embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0021] In the scenarios of clinical trial project management, multi-project data statistics, and the like, a user often needs to analyze different dimension data based on a column chart and the like, and needs to dynamically switch a statistical item (such as “subject enrollment quantity”, “trial center start progress”, and “adverse event occurrence rate”). However, the existing chart generation technology has significant defects: Poor adaptability of a statistical item to a field: the form structures of different clinical trial projects are quite different (for example, the field name of “enrollment quantity” is “enrollment_count” in project A, and is “subject_recruit_num” in project B), and the statistical item and the form field lack a flexible mapping mechanism, and the statistical item cannot be dynamically switched across projects and forms.

[0022] Lack of data standardization: the form field format and naming rules are not unified, directly leading to chaotic statistical data, and the field meaning and statistical logic need to be repeatedly arranged manually, which is inefficient and prone to errors.

[0023] Technical implementation rigidity: the statistical process relies on fixed coding to associate a field with a statistical item (such as hard coding “enrollment_count→enrollment quantity”), and when a statistical item is added or modified, it needs to be redeveloped and deployed, which has poor expansibility and cannot quickly respond to dynamic statistical requirements of clinical trial projects.

[0024] User operation threshold is high: non-technical users cannot independently configure the association between statistical items and fields, and need to rely on the support of developers, resulting in a long chart generation cycle and difficulty in meeting the real-time decision-making needs of clinical trial project management.

[0025] The authority control is extensive: the "view-statistics" authority is not subdivided according to "information type + user type", the authority control of the same type of information is not differentiated for different user roles, there are conflicts of unauthorized statistics or insufficient authority, and the data transmission does not adapt to the security scheme according to the information type, with a high risk of sensitive information leakage.

[0026] Currently, although some data visualization tools (such as ECharts and Tableau) support basic chart generation, they do not solve the core problem of "dynamic mapping of fields-statistical items + data standardization + 'information type-user type' authority subdivision + differentiated encryption transmission" under multiple projects and multiple forms, and cannot meet the needs of high sensitivity, strong compliance, and multi-role division in the medical field. Therefore, there is an urgent need in the art for a chart generation technical solution that precisely matches authority and information type, supports dynamic switching of statistical items, and takes into account security.

[0027] Based on this, the embodiments of the present application provide a medical information display method and device, electronic equipment and readable storage medium, which are described below through embodiments.

[0028] To facilitate understanding of the present embodiment, first, a medical information display method disclosed by the present application is described in detail. As shown in Figure 1 The database establishment stage includes the following steps S101-S102: S101: The server obtains a java mapping rule input request uploaded by the user terminal; the java mapping rule input request carries multiple items selected from the group consisting of: project identifier, form identifier, field information, and statistical item information; S102: The server establishes a java mapping rule according to the java mapping rule input request, and the java mapping rule represents the mapping relationship between the field information, the statistical item information, the project identifier, and the form identifier; The information display stage includes the following steps S103-S107: S103: The server obtains an analysis result generation request uploaded by the user terminal, and the analysis result generation request carries an analysis rule, a project identifier, a form identifier, and statistical item information; S104: The server calls the attribute information of the target field in the system according to the information carried in the analysis result generation request and the pre-established java mapping rule; S105: The server generates an analysis result according to the analysis rule and the called attribute information; S106: The server queries the identity information of the target user who sends the analysis result generation request, and determines the encryption permission level of the target user according to the identity information; S107: The server encrypts the analysis result according to the encryption mode corresponding to the encryption permission level, and sends the encrypted analysis result to the target user to display the analysis result in the target terminal used by the target user.

[0029] In step S101, the server refers to the core computing and storage device (which can be a physical server or a cloud server cluster) deployed in the background of the clinical trial project, which is the core processing unit of the entire scheme. Its core responsibilities include: receiving various requests uploaded by user terminals (mapping rule input request, analysis result generation request); parsing request parameters, establishing and storing mapping rules; calling target field attribute information, executing analysis and calculation to generate results; querying user identity and matching encryption permission level; encrypting the analysis result and feeding back to the user terminal, overall planning data processing, permission control and secure transmission.

[0030] The user terminal refers to the terminal device used by the user (such as a clinical trial researcher, administrative personnel, supervisory personnel, or other temporary users such as patients for diagnosis) for operation, including computers, tablets, etc., and is the carrier for user interaction with the server. The user uploads the mapping rule input request (configures the association of fields and statistical items) through the visual interface (such as the web-based configuration tool or the dedicated client) on the terminal, submits the analysis result generation request (initiates data statistical analysis), and receives the analysis result returned by the server after encryption, and finally displays the analysis result such as column chart, statistical report, etc. through the terminal interface, so that the user can view the messages he is interested in.

[0031] As shown in Figure 2 The java mapping rule input request is an instruction data packet uploaded by the user terminal to the server for configuring the mapping relationship, which is a request to establish the association of "fields and statistical items". The request carries project identification, form identification, field information, statistical item information and other key parameters. In essence, it is an instruction for the user to inform the server that "in a certain form of a certain clinical trial project, which field corresponds to which statistical item". The server establishes standardized java mapping rules accordingly after receiving the request.

[0032] The project identification is a unique identification (such as a string, a combination of numbers "LC003 - lung cancer III phase test") for distinguishing different clinical trial projects, which is equivalent to the "identity card" of the clinical trial project. Its function is to help the server accurately locate the data ownership and avoid data confusion of different projects (such as "lung cancer III phase test" and "gastric cancer II phase test"), and ensure that the mapping rule and the analysis request can be accurately associated to the target project.

[0033] Form ID is a unique identifier (e.g. string "EN001-Subject Recruit Form") for different data forms under the same clinical trial project, which is equivalent to the "number" of each data form within the project. A clinical trial project may involve multiple forms (e.g. recruit form, adverse event record form, test result form), and through the form ID, the server can clearly map the specific form corresponding to the analysis request, ensuring that the association between fields and statistical items does not mislocate across forms.

[0034] Field information refers to the complete information related to the smallest unit of original data stored in the clinical trial form (i.e. data field), including field name (e.g. "subject_recruit_num" "medical_record_no"), field type (e.g. integer, string), field meaning (e.g. "monthly recruit number" "subject medical record number") etc. It is the "data source" of statistical analysis, and the server needs to extract original data through field information to perform subsequent statistical calculations.

[0035] Statistical item information refers to the information related to the statistical analysis target that the user needs, i.e. "what do you want to analyze", including statistical item name (e.g. "monthly recruit number" "positive rate of genetic test results"), statistical rule (e.g. sum by month, count by mutation type) etc. It is the "target-oriented" of statistical analysis, and the core of mapping rules is to establish the association between "field information" and "statistical item information", so that the server knows "which field data to use, what rules to follow, and what results to calculate".

[0036] Mapping relationship refers to the standardized association established by the server according to the rule input request, and the core is the one-to-one (or many-to-one) binding of "project ID-form ID-field information-statistical item information". For example, "project LC003-form EN001-field subject_recruit_num (monthly recruit number, integer type)-statistical item'monthly recruit number statistics' (sum by month)", this relationship is the basis for the server to quickly match fields and statistical items and perform analysis calculations, avoiding repeated manual association.

[0037] Attribute information refers to the detailed technical characteristics and configuration information of the target field, in addition to the field type and meaning included in the field information, it also includes field storage path (e.g. corresponding column name in the database table), data format specification (e.g. date format "YYYY-MM-DD"), associated permission configuration (e.g. whether it is a sensitive field) etc. The server calls attribute information to clearly know how to extract field data and how to adapt statistical rules (e.g. integer type field can perform sum, string type field can perform count), ensuring the accuracy of statistical calculations.

[0038] The analysis result refers to the structured statistical data generated by the server based on the analysis rules submitted by the user (such as summing up by month, grouping by department, and proportion). The server performs calculations on the original data corresponding to the field attribute information called by the user, and generates structured statistical data (such as "2024-01: 120 people, 2024-02: 150 people" and "Internal Medicine: 35%, Surgery: 28%"). The result is the final statistical output that the user needs, which can be directly used for terminal visualization (such as bar charts and line charts), and is the core output of the entire analysis process.

[0039] The analysis result generation request is an instruction data packet initiated by the user terminal to the server to trigger statistical analysis, and is the basis for starting the "generate analysis result" process. In addition to carrying analysis rules, project identifiers, form identifiers, and statistical item information, it is essentially an execution instruction for the server to "statistically analyze the target statistical item according to the specified rules for a certain project and a certain form". After receiving the instruction, the server will retrieve data and calculate based on the pre-set mapping rules.

[0040] The analysis rule is a specific statistical calculation logic defined by the user (such as "sum by month grouping", "calculate proportion by department splitting", and "filter subjects aged over 60 and count"). It is the core basis for the server to generate analysis results. It clearly shows "how to process field data" and needs to be adapted to field attribute information (such as integer type field adaptation "sum" rule and string type field adaptation "count" rule).

[0041] The target user refers to the specific operator who initiates the "analysis result generation request" (such as clinical trial researchers, supervisors, and administrative personnel). Their identity information (role, department affiliation, approval status, etc.) is the core basis for the server to determine the encryption permission level, directly affecting the encryption method of the analysis result.

[0042] Identity information is the target user's exclusive identity data stored in the server, including user roles (such as attending physicians and auditors), project / department affiliation, permission level records, and approval records. The server queries this information to confirm whether the user has the right to access the analysis result and the corresponding encryption permission level.

[0043] The encryption permission level is a permission level (such as L1-L4 mentioned in the scheme) divided according to the user's identity information and bound to the encryption method, which is the basis for the server to select the encryption scheme. Different levels correspond to different encryption strengths and transmission security policies, ensuring the security of analysis result transmission and the matching of permissions.

[0044] The encryption method is a specific secure transmission scheme corresponding to the encryption permission level, including encryption algorithm (such as AES-128-GCM, SM4-256), transmission link (such as public network HTTPS, intranet private line, SD-WAN, etc.), auxiliary security mechanism (such as request signature, digital signature, dynamic token), etc. The server selects the corresponding encryption method to encrypt the analysis result according to the level to prevent data leakage or tampering during transmission.

[0045] The target terminal is the terminal device actually used by the target user to receive and display the encrypted analysis result (essentially the same as the "user terminal", focusing on the scenario of "receiving results and displaying"). It needs to support decryption functions corresponding to the encryption method, as well as visual display of the analysis results (such as rendering column charts, statistical reports).

[0046] In the above scheme, the user establishes a java mapping rule in the server during the database establishment stage, and the users in the database establishment stage and the information display stage are generally different users. The user in the database establishment stage is generally a server administrator (such as a software technology developer) who uploads the rules to the server after collecting actual use requirements, that is, sets the rules. The information display stage is used by practitioners in the medical field, that is, this stage is used by non-soft-shell technology developers.

[0047] In step S106, the determined encryption permission level mainly determines which encryption means need to be used in the transmission process. Specifically, there are at least three ways to encrypt: If the encryption permission level is low, encrypt using a public key; If the encryption permission level is medium, encrypt using a personal key; If the encryption permission level is high, encrypt using a personal key and a temporary key.

[0048] The sending process has at least the following three ways: If the encryption permission level is low, the encrypted analysis result is transmitted to the target user through a public network link; If the encryption permission level is medium, the encrypted analysis result is sent to the target user through a project group intranet private link; If the encryption permission level is high, the encrypted analysis result is sent to the target user through a VPN private line connection.

[0049] More specifically, in actual use, the level can be divided into four levels: L1 level (low level): transmitted through a regular HTTPS (TLS1.2) public network link, statistical results are sent in plaintext, and only rely on HTTPS basic protection; L2 level (medium level): automatically switch to the project group intranet dedicated link, enable HTTPS (TLS1.3), use project group shared key to encrypt statistical results with AES-128-GCM, add SHA-256 checksum for transmission, and ensure that data is not tampered with; L3 level (high level): force connection through VPN dedicated line, verify that the VPN account and identity token are consistent, enable HTTPS (TLS1.3), first generate SHA-256 signature for statistical results + timestamp + user key, then perform AES-256-GCM encryption with role-specific key, and transmit signature and encrypted data together; L4 level (highest level): activate medical exclusive SD-WAN channel, confirm physical isolation of the channel, enable HTTPS (TLS1.3), obtain user personal key through hardware dongle, combine temporary approval token to perform SM4-256 national encryption algorithm on statistical results, add RSA-2048 digital signature, monitor link status in real time during transmission, and immediately interrupt transmission and alarm if an exception occurs.

[0050] Correspondingly, the target terminal can perform a check before display to ensure that the information received by the target terminal is trustworthy. The specific check includes: The front end receives the encrypted statistical results and performs a legality check before display: Check data integrity check: L2-L4 level data verification checksum or signature to ensure that the transmission process has not been tampered with; Check the authority timeliness check: L3 / L4 level data check the validity period of user identity token, VPN account, SD-WAN key and temporary approval token, and refuse to decrypt if any is expired; Check access legality check: check if the access terminal IP meets the communication IP specification of the corresponding level; If the check is passed, go to the decryption step, if not, prompt "data illegal, authority has expired or access method is abnormal", do not display data.

[0051] In addition to encryption during transmission, data access permission level restrictions can also be added in step S105. Specifically, step S105 can be executed as follows: S1051, the server queries the matching degree of the attribute information and the target user access permission level according to the access permission level of the attribute information, and retrieves the target information that meets the match from the attribute information according to the matching degree; S1052, the server generates analysis results according to the target information.

[0052] Among them, the matching degree includes three cases: only view (the target user can only view the intuitive data, but cannot be analyzed by the server), view and analyze (this is the maximum permission, both raw data and analysis results can be viewed), and cannot view and analyze (this is the lowest permission, neither raw data nor analysis results can be viewed).

[0053] As shown in Tables 1-4 below, the correspondence between different types of information and corresponding access permission levels and encryption permission levels is shown. In this scheme, the permissions corresponding to the information type are different for different users, that is, the permissions are determined according to the information type and the user type, rather than the information type. The permission A in the table below represents that the raw data can be viewed, and the statistical results can be viewed. The raw / desensitized details of the information can be viewed, the statistical items can be selected autonomously, the statistical rules (such as grouping, aggregation, and filtering) can be customized, and the statistical results (after desensitization) can be exported.

[0054] Permission B represents that only raw data can be viewed, and statistical results cannot be viewed. Only fixed format displays of information (such as preset charts and desensitized aggregation results) can be viewed, and custom statistical rules, switching statistical items, and result export / copy functions are prohibited.

[0055] Permission C represents that raw data cannot be viewed, and statistical results cannot be viewed. There is no access permission, and the interface hides the corresponding information entry.

[0056] Information type 1: public statistical information (encryption permission is low level, such as project overall enrollment amount, trial center number, and public progress report).

[0057] Information type 2: internal operation information (encryption permission is medium level, such as non-private field statistics, trial center progress, and enrollment details (without patient identification)).

[0058] Information type 3: sensitive clinical information (encryption permission is high level, such as subject medical record association statistics, age / gender grouping data, and non-core privacy field statistics).

[0059] Information type 4: highly sensitive privacy information (encryption permission is the highest level, such as patient medical record number, genetic test data, raw test results, and efficacy association privacy data).

[0060] Table 1 below shows the correspondence between the access permission level and the encryption permission level corresponding to information type 1:

[0061] Table 2 below shows the correspondence between the access permission level and the encryption permission level corresponding to information type 2:

[0062] The following Table 3 shows the correspondence between the access permission level and the encryption permission level corresponding to information type 3:

[0063] The following Table 4 shows the correspondence between the access permission level and the encryption permission level corresponding to information type 4:

[0064] The following is a simple example to describe the process of the scheme provided in the present application (without access permission and encryption permission): S1: Mapping configuration and standardized storage (database establishment stage) The user terminal (front end) provides a visual mapping configuration interface, the user selects a target clinical trial project (such as "Lung Cancer III Trial") and a corresponding project form (such as "Subject Enrollment Form"), and configures the mapping relationship between the target field and the statistical item under the form - the field name (such as "subject_recruit_num") needs to be specified, the field type (such as "integer type"), the statistical item name (such as "monthly enrollment number"), and the statistical rule (such as "sum by month grouping"); the system performs standardized checking on the mapping relationship (checking whether the field exists in the project form, whether the statistical rule conforms to the field type), and after the checking is passed, the "project identifier-form identifier-field information-statistical item information" is associated and stored in the mapping configuration database, forming a unified standardized mapping library.

[0065] S2: Statistical item selection and request submission (information display stage) The user selects a clinical trial project to be analyzed, a corresponding form, and a target statistical item (such as "monthly enrollment number") from a drop-down list through the front-end chart operation interface, and clicks "generate column chart" to submit a request; the request data packet carries key parameters such as project identifier, form identifier, and selected statistical item ID.

[0066] S3: Dynamic analysis of mapping relationship (information display stage) After receiving the request, the back end queries the corresponding "field-statistical item" mapping relationship from the mapping configuration database according to the project identifier and the form identifier; a Java reflection utility class is called to dynamically load the entity class corresponding to the project form (such as "com.clinical.trial.entity.Lung Cancer Enrollment Form") through the full path of the entity class, obtain the attribute information of the target field in the mapping relationship (including field type and getter method), and confirm the association method of the statistical item and the field (such as whether the statistical rule "sum" matches the field type "integer type").

[0067] S4: Data statistics and bar chart generation (information display stage) The backend extracts the original data of the target field (such as the monthly data of "subject_recruit_num" in "Lung Cancer III Trial" "Subject Recruitment Form") from the clinical trial project database according to the parsed mapping relationship; performs statistical calculation according to the statistical rule defined by the mapping relationship (such as "sum by month grouping"); generates structured statistical results (such as "2024-01: 120 people, 2024-02: 150 people"); calls a chart rendering engine (such as ECharts) to automatically convert the statistical results into bar chart configuration parameters (including X-axis "month", Y-axis "number", data series "monthly enrollment number"), and returns the configuration parameters to the front end.

[0068] S5: Statistical item dynamic switching response (information display stage) When the user switches the statistical item in the front end (such as from "monthly enrollment number" to "center enrollment proportion"), the front end repeats step S2 and submits a new statistical item request; the backend repeats steps S3-S4, re-queries the mapping relationship, reflects the parsed field, performs statistical calculation and generates a new bar chart, the whole process does not need to modify the code, realizes the real-time dynamic switching of the statistical item.

[0069] In the S1 mapping configuration stage The user can perform the following operations: the user selects the clinical trial project "Lung Cancer III Trial (project identifier: LC003)", the form "Subject Recruitment Form (form identifier: EN001)", and configures two groups of mapping relationships: Mapping 1: field name "subject_recruit_num" (integer type) → statistical item "monthly enrollment number" → statistical rule "sum by month grouping"; Mapping 2: field name "center_id" (string type) → statistical item "center enrollment proportion" → statistical rule "count by center grouping, calculate the proportion of each group"; After the system verification, the two groups of mapping relationships associated with "LC003-EN001" are stored in the mapping configuration database.

[0070] At S4, when the chart is generated for the first time, the user can perform the following operations: the user selects the project "LC003", the form "EN001", and the statistical item "monthly enrollment number" to submit a request; the backend queries the mapping relationship, loads the entity class "com.clinical.trial.entity.Lung Cancer Enrollment Form" through reflection, and parses the getter method of "subject_recruit_num"; the data of the field from January to March 2024 (January: 120, February: 150, March: 130) is extracted from the project database, and the column chart configuration parameters are generated after being statistically summed up by month; and the front end renders the column chart with "X axis: month, Y axis: number".

[0071] At S5, when the statistical item is switched, the user can perform the following operations: the user switches the statistical item to "center enrollment ratio"; the backend re-queries the mapping relationship, reflects and parses the "center_id" field, extracts the data (center A: 80 people, center B: 100 people, center C: 220 people), and performs statistical calculation (center A: 20%, center B: 25%, center C: 55%) according to the "center count + ratio calculation", generates new column chart configuration parameters, and the front end updates the chart in real time to realize code-free switching.

[0072] The core technical point of the scheme provided in the present application is: 1. The technical point of the multi-dimensional standardized mapping configuration method is that the mapping relationship between "clinical trial project-project form-form field" and the statistical item is constructed through the front-end visual interface, and after the field legality and statistical rule matching are verified, it is stored in the database with "project identifier-form identifier" as the index to form a standardized mapping library. Innovation: Break the traditional hard-coded mapping mode, realize the configuration management of the mapping relationship in the multi-project multi-form scenario, and provide a standardized data basis for dynamic switching of statistical items.

[0073] 2. The technical point of the mapping dynamic analysis method based on Java reflection is that the backend receives the chart request, queries the mapping relationship according to the project + form identifier, dynamically loads the form entity class through the Java reflection mechanism, analyzes the attribute information (type, access method) of the target field, automatically matches the field corresponding to the statistical item, and does not need to hard-code the field access logic. Innovation: Solve the analysis problem caused by the difference between multi-project form fields, realize the dynamic adaptation of field-statistical item mapping, and improve the system versatility.

[0074] 3. Technical Details of the Closed-Loop Chart Generation Method for Dynamic Switching of Statistical Items: When a user switches statistical items, the system does not require code modification. Through a closed-loop process of "resubmitting the request → querying the mapping relationship → reflection parsing → statistical calculation → chart generation," it generates a bar chart corresponding to the new statistical item in real time, with a response time of ≤1 second. Innovation: This achieves code-free dynamic switching of statistical items, significantly improving the flexibility and efficiency of chart generation, and meeting the real-time decision-making needs of clinical trial project management.

[0075] Based on the same technical concept, this application also provides a medical information display device, which is applied to a server, such as... Figure 3 As shown, the device includes: The first acquisition module 301 is used to acquire the Java mapping rule input request uploaded by the user terminal; the Java mapping rule input request carries multiple of the following: project identifier, form identifier, field information and statistical item information; Module 302 is used to establish Java mapping rules based on input requests, wherein the Java mapping rules represent the mapping relationship between field information and statistical item information, item identifier, and form identifier; The second acquisition module 303 is used to acquire the analysis result generation request uploaded by the user terminal, wherein the analysis result generation request carries analysis rules, project identifiers, form identifiers and statistical item information; Module 304 is invoked to generate the information carried in the request based on the analysis results and the pre-established Java mapping rules, and to invoke the attribute information of the target field in the system. The generation module 305 is used to generate analysis results based on the analysis rules and the attribute information retrieved. The query module 306 is used to query the identity information of the target user who issued the request to generate analysis results, and to determine the encryption permission level of the target user based on the identity information. The encryption module 307 is used to encrypt the analysis results according to the encryption method corresponding to the encryption permission level, and send the encrypted analysis results to the target user so that the analysis results can be displayed on the target terminal used by the target user.

[0076] Optionally, when the encryption module 307 encrypts the analysis results according to the encryption method corresponding to the encryption permission level, it is specifically used for: If the encryption permission level is low, encryption is performed using the public key; If the encryption permission level is medium, then encryption is performed using a personal key; If the encryption permission level is high, encryption is performed using a personal key and a temporary key.

[0077] Optionally, the encryption module 307 is configured to, when sending the encrypted analysis result to the target user, specifically configured to: if the encryption permission level is a low level, transmitting the encrypted analysis result to the target user through a public network link; if the encryption permission level is a medium level, sending the encrypted analysis result to the target user through a project group intranet special link; if the encryption permission level is a high level, sending the encrypted analysis result to the target user through a VPN dedicated line connection.

[0078] Optionally, the target terminal is configured to, after receiving the encrypted analysis result, verify through any at least one of the following ways, and display the analysis result after verification: data integrity verification, signature verification, identity token verification, VPN account verification, and temporary approval token verification.

[0079] Optionally, the generation module 305 is configured to, when generating the analysis result according to the analysis rule and the called attribute information, specifically configured to: the server queries the matching degree of the attribute information and the target user access permission level according to the access permission level of the attribute information, and calls the target information that meets the matching from the attribute information according to the matching degree; the server generates the analysis result according to the target information.

[0080] Optionally, the matching degree includes: only viewing, viewing and analyzing, and unable to view and analyze.

[0081] Figure 4 A structure schematic diagram of an electronic device provided by the embodiment of the application, comprising: a processor 401, a memory 402 and a bus 403, the memory 402 stores machine readable instructions executable by the processor 401, when the electronic device runs the above-mentioned information processing method, the processor 401 and the memory 402 communicate through the bus 403, and the processor 401 executes the machine readable instructions to execute the method steps described in embodiment one.

[0082] The embodiment of the application further provides a computer readable storage medium, the computer readable storage medium stores a computer program, and the computer program is run by a processor to execute the method steps described in embodiment one.

[0083] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned device, electronic device and computer readable storage medium can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0084] In several embodiments provided in the present application, it should be understood that the disclosed methods, devices, electronic devices and computer readable storage media can be implemented in other manners. The above described device embodiments are only schematic. For example, the division of the modules is only a logical function division. There can be another division manner for the actual implementation. For example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interface, device or module, and can be in electrical, mechanical or other forms.

[0085] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0086] In addition, each functional unit in the various embodiments of the present application can be integrated into one processing unit, or each unit can be a physically independent unit, or two or more units can be integrated into one unit.

[0087] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application or the part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0088] Finally, it should be noted that the above-described embodiments are merely specific embodiments of the present application, which are used to illustrate the technical solutions of the present application, but not to limit the same. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that any skilled person in the art can still modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features, within the technical range disclosed by the present application. The modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for displaying medical information, characterized in that, include: Database creation phase and information display phase; The database establishment phase includes: The server obtains the Java mapping rule input request uploaded by the user terminal; the Java mapping rule input request carries multiple of the following: project identifier, form identifier, field information, and statistical item information; The server establishes Java mapping rules based on the input request. These Java mapping rules represent the mapping relationship between field information and statistical item information, item identifier, and form identifier. The information display phase includes: The server obtains the analysis result generation request uploaded by the user terminal. The analysis result generation request carries analysis rules, project identifiers, form identifiers, and statistical item information. The server generates the information carried in the request and the pre-established Java mapping rules based on the analysis results, and calls the attribute information of the target field in the system; The server generates analysis results based on the analysis rules and the attribute information retrieved. The server queries the identity information of the target user who issued the analysis result generation request, and determines the encryption permission level of the target user based on the identity information; The server encrypts the analysis results according to the encryption method corresponding to the encryption permission level, and sends the encrypted analysis results to the target user so that the analysis results can be displayed on the target terminal used by the target user.

2. The method according to claim 1, characterized in that, The server encrypts the analysis results according to the encryption method corresponding to the encryption permission level, including: If the encryption permission level is low, encryption is performed using the public key; If the encryption permission level is medium, then encryption is performed using a personal key; If the encryption permission level is high, encryption is performed using a personal key and a temporary key.

3. The method according to claim 1, characterized in that, Sending the encrypted analysis results to the target user includes: If the encryption permission level is low, the encrypted analysis results will be transmitted to the target user via a public network link. If the encryption permission level is medium, the encrypted analysis results will be sent to the target user through a dedicated link within the project team's intranet. If the encryption permission level is high, the encrypted analysis results will be sent to the target user via a VPN dedicated line connection.

4. The method according to claim 1, characterized in that, The method further includes: After receiving the encrypted analysis results, the target terminal verifies them using at least one of the following methods, and displays the analysis results upon successful verification: Data integrity verification, signature verification, identity token verification, VPN account verification, and temporary approval token verification.

5. The method according to claim 1, characterized in that, The server generates analysis results based on the analysis rules and the retrieved attribute information, including: The server queries the matching degree between the access permission level of the attribute information and the access permission level of the target user, and retrieves the matching target information from the attribute information based on the matching degree. The server generates analysis results based on the target information.

6. The method according to claim 5, characterized in that, Matching degree includes: View only, view and analyze, cannot view and cannot analyze.

7. A medical information display device, characterized in that, The device is used in a server, and the device includes: The first acquisition module is used to acquire the Java mapping rule input request uploaded by the user terminal; the Java mapping rule input request carries multiple of the following: project identifier, form identifier, field information and statistical item information; A module is established to create Java mapping rules based on input requests. These Java mapping rules represent the mapping relationship between field information and statistical item information, item identifier, and form identifier. The second acquisition module is used to acquire the analysis result generation request uploaded by the user terminal. The analysis result generation request carries analysis rules, project identifiers, form identifiers and statistical item information. The calling module is used to generate the information carried in the request based on the analysis results and the pre-established Java mapping rules, and to call the attribute information of the target field in the system; The generation module is used to generate analysis results based on the analysis rules and the attribute information retrieved. The query module is used to query the identity information of the target user who issued the request to generate analysis results, and to determine the encryption permission level of the target user based on the identity information; The encryption module is used to encrypt the analysis results according to the encryption method corresponding to the encryption permission level, and send the encrypted analysis results to the target user so that the analysis results can be displayed on the target terminal used by the target user.

8. The apparatus according to claim 7, characterized in that, When the encryption module encrypts the analysis results according to the encryption method corresponding to the encryption permission level, it is specifically used for: If the encryption permission level is low, encryption is performed using the public key; If the encryption permission level is medium, then encryption is performed using a personal key; If the encryption permission level is high, encryption is performed using a personal key and a temporary key.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is in operation, the processor communicates with the memory via the bus, and the machine-readable instructions, when executed by the processor, perform the steps of the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method as described in any one of claims 1 to 6.

Images