Medical data governance method, system, and computer equipment based on metadata model

Abstract

This solution involves a medical data governance method based on a metadata model. The method includes: constructing a metadata model based on the collected and recovered metadata according to the medical data governance scenario; monitoring medical data in real time, and classifying and managing medical data through the TCG three-dimensional management model; determining the data governance type of the medical data when there are medical data governance scenario problems in the medical data; selecting the corresponding metadata model according to the data governance type of the medical data, thereby determining the data problems of the medical data, displaying the data problems and intervening. By constructing a metadata model, the medical data is input into different metadata models according to the type of medical data, and the data problems of each medical data are obtained, so that different intervention measures are taken for different data problems, without the need for manual data governance, thereby improving the effectiveness of data governance.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a medical data governance method, system, computer equipment and storage medium based on a metadata model. Background Art

[0002] With the continuous acceleration of the development of medical informatization, the digital transformation of medical care has become an important task that medical institutions and regional health institutions are actively promoting. However, to ensure the successful transformation of medical digitalization, the construction and implementation of medical data governance is a must. How to achieve medical data governance more efficiently, systematically and intelligently will determine the speed, effect and value of medical digital transformation. At present, in the practice of medical data governance, most of the data governance implementation methods and systems in the medical industry highlight the characteristics of manual governance and single module governance. It is difficult to form a data governance model or implementation method that is cohesive within the data itself, and it will lead to large human investment in the process of data governance projects, unsustainable governance effects, and it is difficult to achieve automated data governance. Medical data has the characteristics of sensitivity, zero error, high value, and diversity. Therefore, the implementation and effect of data governance in the medical industry are particularly important, which will have a direct impact on the overall medical quality, medical level and medical operation management. Medical data governance mainly includes data quality governance, data security governance and data asset governance. When conducting data governance, it is usually manually checked and located one by one, and then the problem is intervened and solved.

[0003] Therefore, traditional medical data governance methods rely heavily on people in the process of data governance. There is an island phenomenon in data governance in each scenario, and there is a disconnect between data governance and data management, which makes the data governance process difficult to sustain. Summary of the invention

[0004] Based on this, in order to solve the above technical problems, a medical data governance method, system, computer equipment and storage medium based on metadata model are provided, which can improve the disorder and inefficiency of current data governance implementation and break the pure manual experience reliance mode.

[0005] A medical data governance method based on a metadata model, the method comprising:

[0006] Based on the collected and recovered metadata, a metadata model is constructed according to the medical data governance scenario; the metadata model includes a TCG (target, classify, grade) three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot and cold relationship model;

[0007] Monitor medical data in real time, and classify and manage the medical data through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, determine the data governance type of the medical data; the data governance type includes data quality governance, data security governance, and data asset governance;

[0008] When the data governance type of the medical data is data quality governance, the cause of the data quality is investigated and located, and the dynamic blood relationship model is called; the medical data is input into the dynamic blood relationship model to obtain the data direct blood relationship; quality problem classification information is obtained according to the data direct blood relationship, the data direct blood relationship and the quality problem classification information are displayed, and quality problem intervention is performed;

[0009] When the data governance type of the medical data is data security governance, identify the data security risk situation and call the dynamic association relationship model; input the medical data into the dynamic association relationship model to obtain the data association relationship; obtain the security protection plan according to the data association relationship, display the data association relationship and the security protection plan, and perform data security protection intervention;

[0010] When the data governance type of the medical data is data asset governance, the data asset value is identified and the dynamic hot-cold relationship model is called; the medical data is input into the dynamic hot-cold relationship model to obtain hot-cold relationship data; the asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data and the asset value level are displayed, and the data asset value is marked.

[0011] In one embodiment, the classifying and managing the medical data by using the TCG three-dimensional management model includes:

[0012] The medical data is input into the TCG three-dimensional management model, and the TCG three-dimensional management model classifies and grades the medical data through the data object dimension; the TCG three-dimensional management model classifies the medical data into levels based on sensitivity and impact through the data classification dimension; the TCG three-dimensional management model classifies the medical data into types based on data type or data scenario application needs through the data classification dimension to obtain a classification management result.

[0013] In one embodiment, the medical data is input into the dynamic blood relationship model to obtain the data direct blood relationship; quality problem classification information is obtained according to the data direct blood relationship, the data direct blood relationship and the quality problem classification information are displayed, and quality problem intervention is performed, including:

[0014] Input the medical data into the dynamic blood relationship model, and dynamically extract data models and data jobs from the data warehouse through the dynamic blood relationship model to form a data model and job set;

[0015] The dynamic blood relationship model performs database analysis on the data model and the job set, identifies data dependencies between different sets, and forms a data dependency set;

[0016] The dynamic blood relationship model forms a data lineage relationship corresponding to the medical data according to the data dependency set and an association algorithm based on association rules by using the TCG three-dimensional management model, wherein the data lineage relationship is marked with the quality problem classification information;

[0017] Display the direct lineage relationship of the data and the classification information of the quality problems, and intervene in the quality problems.

[0018] In one of the embodiments, before performing the quality problem intervention, the method further includes:

[0019] Locating the medical data with quality problems according to the direct blood relationship and the quality problem classification information;

[0020] Acquire a quality evaluation strategy, determine the cause of the quality problem based on the quality evaluation strategy and the medical data with quality problems, and perform quality problem intervention based on the cause of the quality problem.

[0021] In one embodiment, the step of inputting the medical data into the dynamic association model to obtain a data association relationship; obtaining a security protection scheme according to the data association relationship, displaying the data association relationship and the security protection scheme, and performing data security protection intervention includes:

[0022] Inputting the medical data into the dynamic association relationship model to form a data dependency set through the dynamic association relationship model;

[0023] The dynamic association relationship model filters out the horizontal association data in the medical data according to the data dependency set, and intelligently classifies the horizontal association data through the statistical clustering algorithm and the TCG three-dimensional management model to form an initial data association relationship;

[0024] The dynamic association relationship model integrates and deduplicates the initial data association relationship to obtain the data association relationship, and obtains the security protection plan corresponding to the data association relationship, displays the data association relationship and the security protection plan, and performs data security protection intervention.

[0025] In one embodiment, the step of inputting the medical data into the dynamic hot-cold relationship model to obtain hot-cold relationship data; obtaining an asset value grade according to the hot-cold relationship data, displaying the hot-cold relationship data and the asset value grade, and marking the data asset value includes:

[0026] Inputting the medical data into the dynamic hot-cold relationship model, extracting and parsing data processing logs through the dynamic hot-cold relationship model, and obtaining the usage frequency of the medical data;

[0027] The dynamic hot-cold relationship model calculates the hot-cold label of the medical data according to the usage frequency in combination with a clustering algorithm;

[0028] The dynamic hot-cold relationship model clusters and classifies the medical data according to the hot-cold label and in combination with the TCG three-dimensional management model to obtain the hot-cold relationship data; obtains the asset value level according to the hot-cold relationship data, displays the hot-cold relationship data and the asset value level, and marks the data asset value.

[0029] A medical data governance system based on a metadata model, the system comprising:

[0030] A model building module is used to build a metadata model based on the collected and recovered metadata according to the medical data governance scenario; the metadata model includes a TCG (target, classify, grade) three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot and cold relationship model;

[0031] A data governance type determination module is used to monitor medical data in real time and classify and manage the medical data through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, determine the data governance type of the medical data; the data governance type includes data quality governance, data security governance, and data asset governance;

[0032] A data quality governance module, for, when the data governance type of the medical data is data quality governance, to troubleshoot and locate the cause of data quality, and to call the dynamic blood relationship model; to input the medical data into the dynamic blood relationship model to obtain the direct blood relationship of the data; to obtain quality problem classification information according to the direct blood relationship of the data, to display the direct blood relationship of the data, the quality problem classification information, and to intervene in quality problems;

[0033] A data security governance module, for identifying data security risk situations and calling the dynamic association relationship model when the data governance type of the medical data is data security governance; inputting the medical data into the dynamic association relationship model to obtain a data association relationship; obtaining a security protection plan according to the data association relationship, displaying the data association relationship and the security protection plan, and performing data security protection intervention;

[0034] A data asset governance module is used to identify the data asset value and call the dynamic hot-cold relationship model when the data governance type of the medical data is data asset governance; input the medical data into the dynamic hot-cold relationship model to obtain hot-cold relationship data; obtain the asset value level according to the hot-cold relationship data, display the hot-cold relationship data, the asset value level and mark the data asset value.

[0035] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0036] Based on the collected and recovered metadata, a metadata model is constructed according to the medical data governance scenario; the metadata model includes a TCG (target, classify, grade) three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot and cold relationship model;

[0037] Monitor medical data in real time, and classify and manage the medical data through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, determine the data governance type of the medical data; the data governance type includes data quality governance, data security governance, and data asset governance;

[0038] When the data governance type of the medical data is data quality governance, the cause of the data quality is investigated and located, and the dynamic blood relationship model is called; the medical data is input into the dynamic blood relationship model to obtain the data direct blood relationship; quality problem classification information is obtained according to the data direct blood relationship, the data direct blood relationship and the quality problem classification information are displayed, and quality problem intervention is performed;

[0039] When the data governance type of the medical data is data security governance, identify the data security risk situation and call the dynamic association relationship model; input the medical data into the dynamic association relationship model to obtain the data association relationship; obtain the security protection plan according to the data association relationship, display the data association relationship and the security protection plan, and perform data security protection intervention;

[0040] When the data governance type of the medical data is data asset governance, the data asset value is identified and the dynamic hot-cold relationship model is called; the medical data is input into the dynamic hot-cold relationship model to obtain hot-cold relationship data; the asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data and the asset value level are displayed, and the data asset value is marked.

[0041] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0042] Based on the collected and recovered metadata, a metadata model is constructed according to the medical data governance scenario; the metadata model includes a TCG (target, classify, grade) three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot and cold relationship model;

[0043] Monitor medical data in real time, and classify and manage the medical data through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, determine the data governance type of the medical data; the data governance type includes data quality governance, data security governance, and data asset governance;

[0044] When the data governance type of the medical data is data quality governance, the cause of the data quality is investigated and located, and the dynamic blood relationship model is called; the medical data is input into the dynamic blood relationship model to obtain the data direct blood relationship; quality problem classification information is obtained according to the data direct blood relationship, the data direct blood relationship and the quality problem classification information are displayed, and quality problem intervention is performed;

[0045] When the data governance type of the medical data is data security governance, identify the data security risk situation and call the dynamic association relationship model; input the medical data into the dynamic association relationship model to obtain the data association relationship; obtain the security protection plan according to the data association relationship, display the data association relationship and the security protection plan, and perform data security protection intervention;

[0046] When the data governance type of the medical data is data asset governance, the data asset value is identified and the dynamic hot-cold relationship model is called; the medical data is input into the dynamic hot-cold relationship model to obtain hot-cold relationship data; the asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data and the asset value level are displayed, and the data asset value is marked.

[0047] The above-mentioned medical data governance method, system, computer device and storage medium based on metadata model build metadata model according to medical data governance scenario based on collected and recovered metadata; the metadata model includes TCG (target, classify, grade) three-dimensional management model, dynamic blood relationship model, dynamic association relationship model, dynamic hot and cold relationship model; real-time monitoring of medical data, and classification and management of the medical data through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, determining the data governance type of the medical data; the data governance type includes data quality governance, data security governance, and data asset governance; when the data governance type of the medical data is data quality governance, troubleshooting and locating the cause of data quality, and calling the dynamic blood relationship model; inputting the medical data into the dynamic blood relationship model to obtain the data direct blood relationship model. The data governance type of the medical data is data security governance, the data security risk situation is identified, and the dynamic association relationship model is called; the medical data is input into the dynamic association relationship model to obtain the data association relationship; the security protection scheme is obtained according to the data association relationship, the data association relationship, the security protection scheme are displayed, and data security protection intervention is performed; when the data governance type of the medical data is data asset governance, the data asset value is identified, and the dynamic hot-cold relationship model is called; the medical data is input into the dynamic hot-cold relationship model to obtain the hot-cold relationship data; the asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data, the asset value level are displayed, and the data asset value is marked. By constructing a metadata model, the medical data is input into different metadata models according to the type of medical data, and the data problems of each medical data are obtained, so that different intervention measures are taken for different data problems, without manual data governance, and the effectiveness of data governance is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 The diagram is an application environment diagram of a medical data governance method based on a metadata model in one embodiment;

[0049] Figure 2 A flowchart of a medical data governance method based on a metadata model in one embodiment;

[0050] Figure 3 It is a flowchart of a medical data governance method based on a metadata model in another embodiment;

[0051] Figure 4is a schematic diagram of a TCG three-dimensional management model in one embodiment;

[0052] Figure 5 is a schematic diagram of a dynamic blood relationship model in one embodiment;

[0053] Figure 6 is a schematic diagram of a dynamic association relationship model in an embodiment;

[0054] Figure 7 A schematic diagram of a dynamic hot-cold relationship model in one embodiment;

[0055] Figure 8 is a flowchart of a medical data governance method based on a metadata model in another embodiment;

[0056] Fig. 9 is a structural block diagram of a medical data governance system based on a metadata model in one embodiment;

[0057] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0059] The medical data governance method based on metadata model provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Figure 1As shown, the application environment includes a computer device 110. The computer device 110 can build a metadata model based on the collected and recovered metadata according to the medical data governance scenario; the metadata model includes a TCG (target, classify, grade) three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot and cold relationship model; the computer device 110 can monitor medical data in real time and classify and manage the medical data through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, the computer device 110 can determine the data governance type of the medical data; the data governance types include data quality governance, data security governance, and data asset governance; when the data governance type of the medical data is data quality governance, the computer device 110 can troubleshoot and locate the cause of data quality and call the dynamic blood relationship model; the computer device 110 can input the medical data into the dynamic blood relationship model to obtain the direct blood relationship of the data; the computer device 110 can The data direct lineage relationship obtains the quality problem classification information, displays the data direct lineage relationship, the quality problem classification information and performs quality problem intervention; when the data governance type of medical data is data security governance, the computer device 110 can identify the data security risk situation and call the dynamic association relationship model; the computer device 110 can input the medical data into the dynamic association relationship model to obtain the data association relationship; the computer device 110 can obtain the security protection plan according to the data association relationship, display the data association relationship, the security protection plan and perform data security protection intervention; when the data governance type of medical data is data asset governance, identify the data asset value and call the dynamic hot and cold relationship model; the computer device 110 can input the medical data into the dynamic hot and cold relationship model to obtain the hot and cold relationship data; the computer device 110 can obtain the asset value level according to the hot and cold relationship data, display the hot and cold relationship data, the asset value level and perform data asset value marking. Among them, the computer device 110 can be, but not limited to, various personal computers, laptops, smart phones, robots, tablet computers and other devices.

[0060] In one embodiment, Figure 2 As shown, a medical data governance method based on a metadata model is provided, comprising the following steps:

[0061] Step 202, based on the collected and recovered metadata, build a metadata model according to the medical data governance scenario; the metadata model includes a TCG (target, classify, grade) three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot and cold relationship model.

[0062] Computer equipment can build models from two directions, metadata classification management and metadata analysis, based on the metadata of the data warehouse. Specifically, computer equipment can build four core models of metadata from two dimensions, metadata management and metadata analysis, based on the collected and recovered source data, according to actual scenario needs and technical characteristics. That is, computer equipment can build metadata models based on medical data governance scenarios.

[0063] Among them, the metadata models constructed can include TCG (target, classify, grade) three-dimensional management model, dynamic blood relationship model, dynamic association relationship model, and dynamic hot and cold relationship model. The TCG three-dimensional management model is a detailed classification process of specific metadata from the perspective of data management; the dynamic blood relationship model is designed from the perspective of blood relationship of data dependence, clarifying the subordinate and dependent relationship between data and data, and facilitating data traceability and tracing; the dynamic association relationship model is to build and design relationships from the perspective of the association between data and data. Different from the vertical direct blood relationship of data blood relationship, the association relationship model focuses on the horizontal connection between data, such as left-right collateral relationships such as "brothers and sisters" and "partners"; the dynamic hot and cold relationship model is a model designed from the perspective of data value. Combined with the thinking of "using data for practical use", the more active the data value, the better.

[0064] Step 204, monitor the medical data in real time, and classify and manage the medical data through the TCG three-dimensional management model; when there are medical data governance scenario problems with the medical data, determine the data governance type of the medical data; data governance types include data quality governance, data security governance, and data asset governance.

[0065] Computer equipment can monitor medical data in real time and classify and manage it through the TCG three-dimensional management model. When medical data has medical data governance scenario problems or is triggered to generate governance scenario problems, computer equipment can determine the data governance type of the medical data. Among them, data governance types can be divided into data quality governance, data security governance, and data asset governance.

[0066] Step 206, when the data governance type of medical data is data quality governance, investigate and locate the cause of data quality, and call the dynamic blood relationship model; input the medical data into the dynamic blood relationship model to obtain the direct blood relationship of the data; obtain quality problem classification information based on the direct blood relationship of the data, display the direct blood relationship of the data and the quality problem classification information, and intervene in quality problems.

[0067] The computer device can analyze and confirm the data governance type of medical data. The computer device can first determine whether the data governance type is data quality governance. If not, the computer device can further determine whether the data governance type is data security governance. If not, the computer device can further determine whether the data governance type is data asset governance.

[0068] When the data governance type of medical data is data quality governance, the computer device can troubleshoot and locate the data quality reasons of the medical data and call the dynamic lineage model. The computer device can input the medical data into the dynamic lineage model to obtain the data lineage relationship corresponding to the medical data, and further obtain the corresponding quality problem classification information. The computer device can display the data lineage relationship and quality problem classification information in the display interface, and the user can intervene in the quality problem according to the data lineage relationship and quality problem classification information.

[0069] Step 208, when the data governance type of medical data is data security governance, identify data security risk situations and call the dynamic association model; input the medical data into the dynamic association model to obtain the data association relationship; obtain the security protection plan based on the data association relationship, display the data association relationship and security protection plan, and perform data security protection intervention.

[0070] In this embodiment, when the data governance type of medical data is data security governance, the computer device can identify the security risk of the medical data and call the dynamic association model, thereby inputting the medical data into the dynamic association model to obtain the data association relationship. The computer device can obtain the security protection plan corresponding to the data association relationship and display the data association relationship and the security protection plan in the display interface. The user can perform data security protection intervention based on the data association relationship and the security protection plan.

[0071] Step 210, when the data governance type of medical data is data asset governance, identify the data asset value and call the dynamic hot-cold relationship model; input the medical data into the dynamic hot-cold relationship model to obtain the hot-cold relationship data; obtain the asset value level according to the hot-cold relationship data, display the hot-cold relationship data and asset value level, and mark the data asset value.

[0072] The hot-cold relationship data and asset value registration can be displayed in the display interface of the computer device, and the user can mark the data asset value based on the hot-cold relationship data and asset value registration.

[0073] In this embodiment, if Figure 3As shown, based on the established TCG three-dimensional management model of medical metadata, computer equipment implements dynamic blood relationship model, G dynamic association relationship model and dynamic hot and cold relationship model, and materializes the model at the data warehouse level; for data quality troubleshooting scenarios such as inaccurate data, abnormal data operation, and data modification impact, it is necessary to call the dynamic blood relationship model to first locate the relevant data involved, and then combine the specific strategies such as integrity, consistency, standardization, timeliness, and accuracy in the quality evaluation strategy to determine the specific quality causes; for data security protection scenarios such as sensitive data protection, data leakage, and medical data compliance, the dynamic association relationship model is called to divide the data class collection, and then combined with data security protection strategies, such as desensitization, encryption, watermarking, etc., to form security assessment and policy protection for data with different association relationships; based on asset assessment scenarios such as data cost control and data asset management, the dynamic hot and cold relationship model is called to form data assets with different activities, and then combined with asset assessment strategies to form the final asset grade division and labeling.

[0074] In this embodiment, the computer device builds a metadata model according to the medical data governance scenario based on the collected and recovered metadata; the metadata model includes the TCG (target, classify, grade) three-dimensional management model, the dynamic blood relationship model, the dynamic association relationship model, and the dynamic hot and cold relationship model; the medical data is monitored in real time, and the medical data is classified and managed through the TCG three-dimensional management model; when the medical data has medical data governance scenario problems, the data governance type of the medical data is determined; the data governance types include data quality governance, data security governance, and data asset governance; when the data governance type of the medical data is data quality governance, the data quality reasons are checked and located, and the dynamic blood relationship model is called; the medical data is input into the dynamic blood relationship model to obtain the direct blood relationship of the data; According to the direct lineage relationship of data, the classification information of quality problems is obtained, the direct lineage relationship of data and the classification information of quality problems are displayed, and quality problems are intervened; when the data governance type of medical data is data security governance, the data security risk situation is identified, and the dynamic association relationship model is called; the medical data is input into the dynamic association relationship model to obtain the data association relationship; the security protection plan is obtained according to the data association relationship, the data association relationship, the security protection plan is displayed, and data security protection intervention is performed; when the data governance type of medical data is data asset governance, the data asset value is identified, and the dynamic hot-cold relationship model is called; the medical data is input into the dynamic hot-cold relationship model to obtain the hot-cold relationship data; the asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data, the asset value level is displayed, and the data asset value is marked. By constructing a metadata model, the medical data is input into different metadata models according to the type of medical data, and the data problems of each medical data are obtained, so that different intervention measures are taken for different data problems, without manual data governance, which improves the effectiveness of data governance.

[0075] In one embodiment, a medical data governance method based on a metadata model is provided, which may also include a process of classifying and managing medical data using a TCG three-dimensional management model. The specific process includes: inputting medical data into the TCG three-dimensional management model, and the TCG three-dimensional management model classifies and grades the medical data through the data object dimension; the TCG three-dimensional management model classifies medical data into levels based on sensitivity and impact through the data classification dimension; the TCG three-dimensional management model classifies medical data into types based on data type or data scenario application needs through the data classification dimension to obtain a classification management result.

[0076] like Figure 4 As shown, the three dimensions in the TCG three-dimensional management model specifically include: data object dimension (T, target), data grading dimension (C, classify), and data classification dimension (G, grade).

[0077] The data object dimension mainly refers to the specific content types that need to be classified and graded, including technical metadata, business metadata, and management metadata. It can be further subdivided as needed, for example: technical metadata: database, data table, field, etc., business metadata: analysis model, indicator, etc., management metadata: personnel, organization, etc.

[0078] The data classification dimension mainly refers to the classification of medical data based on sensitivity and impact, such as Figure 3 As shown, there are five levels: extremely sensitive L5, generally sensitive L4, controlled access L3, partially public L2, and fully public L1.

[0079] The data classification dimension mainly refers to the classification of data from the perspective of data type or data scenario application needs, including at least six types: personal attributes, health status, medical applications, medical payment, health resources, and public health.

[0080] For example, the three fields of metadata related to patients in technical metadata: ID number, patient complaint, and diagnosis name, are classified and managed through the TCG three-dimensional model, and the results are as follows:

[0081]

[0082]

[0083] In one embodiment, a medical data governance method based on a metadata model is provided, which may also include a process of performing data processing using a dynamic blood relationship model, and the specific process includes: inputting medical data into the dynamic blood relationship model, and dynamically extracting data models and data job jobs from the data warehouse through the dynamic blood relationship model to form a data model and job set; the dynamic blood relationship model performs database parsing on the data model and job set to identify data dependencies between different sets to form a data dependency set; the dynamic blood relationship model uses an association algorithm based on association rules according to the data dependency set to form a data direct blood relationship corresponding to the medical data using the TCG three-dimensional management model, and the data direct blood relationship is marked with quality problem classification information; the data direct blood relationship and quality problem classification information are displayed, and quality problem intervention is performed.

[0084] When the data governance type of medical data is data quality governance, the computer device can call the dynamic lineage relationship model and input the medical data into the dynamic lineage relationship model. Figure 5As shown, the dynamic blood relationship model dynamically extracts data models and data jobs from the data warehouse every day to form data models and data sets; the dynamic blood relationship model identifies data dependencies between different data sets by parsing a series of SQL relationships such as job logs and modeling SQL to form data dependency sets; the dynamic blood relationship model uses the TCG three-dimensional management model and the association algorithm based on association rules to further merge by category and connect relationships based on the parsed results to form a "family tree" type of direct blood relationship of data, in which the direct blood relationship of data contains quality problem classification information.

[0085] Computer equipment can use visualization technology to form a clear data lineage relationship diagram for clear data lineage relationship and display it in the display interface, which is convenient for users to display and call scenes. Users can intervene in quality issues based on the displayed data lineage relationship.

[0086] In one embodiment, a medical data governance method based on a metadata model is provided that may also include a process for determining the cause of quality problems, the specific process including: locating medical data with quality problems based on direct blood relationships and quality problem classification information; obtaining a quality evaluation strategy, determining the cause of the quality problem based on the quality evaluation strategy and the medical data with quality problems, and performing quality problem intervention based on the cause of the quality problem.

[0087] Among them, medical data with different quality problems can correspond to different quality evaluation strategies. After the computer equipment locates the medical data with quality problems, it can obtain the corresponding quality evaluation strategy and further determine the cause of the quality problem. Users can manually intervene in the quality of the medical data according to the cause of the quality problem.

[0088] In one embodiment, a medical data governance method based on a metadata model is provided, which may also include a process of data processing using a dynamic association relationship model, the specific process including: inputting medical data into the dynamic association relationship model, and forming a data dependency set through the dynamic association relationship model; the dynamic association relationship model filters out the horizontal association data in the medical data according to the data dependency set, and intelligently classifies the horizontal association data through a statistical clustering algorithm and a TCG three-dimensional management model to form an initial data association relationship; the dynamic association relationship model integrates and deduplicates the initial data association relationship to obtain a data association relationship, and obtains a security protection plan corresponding to the data association relationship, displays the data association relationship and the security protection plan, and performs data security protection intervention.

[0089] When the data governance type of medical data is data security governance, the computer device can call the dynamic association relationship model and input the medical data into the dynamic association relationship model. Figure 6 As shown, the computer equipment can extract data models from the data warehouse through daily dynamics to form a collection of data models, and then perform SQL parsing through parsing tools; the dynamic association relationship model filters out horizontally associated content based on the specific situation of the parsed data relationship, and then uses statistical clustering algorithms and TCG three-dimensional management models to perform different types of intelligent classification such as derivative relationships and homology relationships. The classified data forms a data association relationship, and the dynamic association relationship model can further integrate and remove similar association relationships; for the processed data association relationship, the computer equipment can use visualization technology to form a clear association relationship diagram and display the scene in the display interface. Among them, different data association relationships can correspond to different security protection plans. The computer equipment can obtain the security protection plan corresponding to the data association relationship and display the security protection plan in the display interface. The user can call the data association relationship and perform manual intervention in data security protection.

[0090] In one embodiment, a medical data governance method based on a metadata model is provided, which may also include a process of data processing using a dynamic hot-cold relationship model, and the specific process includes: inputting medical data into the dynamic hot-cold relationship model, extracting and parsing data processing logs through the dynamic hot-cold relationship model to obtain the frequency of use of the medical data; the dynamic hot-cold relationship model calculates the hot-cold label of the medical data based on the frequency of use in combination with a clustering algorithm; the dynamic hot-cold relationship model clusters and classifies the medical data based on the hot-cold label in combination with a TCG three-dimensional management model to obtain hot-cold relationship data; the asset value level is obtained based on the hot-cold relationship data, the hot-cold relationship data and asset value level are displayed, and the data asset value is marked.

[0091] When the data governance type of medical data is data asset governance, the computer device can call the dynamic hot-cold relationship model and input the medical data into the dynamic hot-cold relationship model. Figure 7As shown, the computer equipment can use the dynamic hot-cold relationship model to extract and parse the call interface log, data modeling log and other contents of the data processing log system; the dynamic hot-cold relationship model can be divided into four different levels of ice data, cold data, warm data and hot data according to the frequency and frequency of the data being called or modeled, combined with the k-means clustering algorithm, and marked with hot and cold labels; the dynamic hot-cold relationship model can be combined with the TCG three-dimensional management model to further classify and aggregate medical business for data of different levels, and after multiple clustering and classification, hot-cold relationship data of different business types are formed; among them, different hot-cold relationship data can correspond to different asset value levels, and the computer equipment can obtain the asset value level corresponding to the hot-cold relationship data, and display the hot-cold relationship data and asset value level in the display interface, and the user can further mark the data asset value.

[0092] like Figure 8 As shown, in one embodiment, a medical data governance method based on a metadata model is provided. In combination with actual business, a computer device discovers data governance scenario requirements and existing governance problems in specific business, classifies and analyzes data governance requirements and problems, and finds a suitable metadata model and governance solution. Specifically:

[0093] 1. For data quality issues, identification of problems requires locating problems based on data lineage relationship models and quality evaluation strategies, and forming precise and intelligent intervention plans;

[0094] 2. For data security issues, identify the current situation, call the data association model and security protection plan, clarify the security plan for each type of data, and then conduct security implementation intervention;

[0095] 3. Regarding data asset issues, identify the current status of asset value, call on data hot and cold relationship models and asset valuation strategies, form assets of different levels, and then complete the classification and labeling of asset value.

[0096] It should be understood that, although the steps in the above-mentioned flowcharts are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above-mentioned flowcharts may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0097] In one embodiment, Fig. 9 As shown, a medical data governance system based on a metadata model is provided, including: a model building module 910, a data governance type determination module 920, a data quality governance module 930, a data security governance module 940 and a data asset governance module 950, wherein:

[0098] Model building module 910, used to build metadata models according to medical data governance scenarios based on the collected metadata; the metadata models include TCG (target, classify, grade) three-dimensional management model, dynamic blood relationship model, dynamic association relationship model, and dynamic hot and cold relationship model;

[0099] The data governance type determination module 920 is used to monitor medical data in real time and classify and manage medical data through the TCG three-dimensional management model; when there are medical data governance scenario problems with the medical data, the data governance type of the medical data is determined; the data governance types include data quality governance, data security governance, and data asset governance;

[0100] The data quality governance module 930 is used to, when the data governance type of medical data is data quality governance, troubleshoot and locate the cause of data quality, and call the dynamic blood relationship model; input the medical data into the dynamic blood relationship model to obtain the direct blood relationship of the data; obtain the quality problem classification information according to the direct blood relationship of the data, display the direct blood relationship of the data, the quality problem classification information, and perform quality problem intervention;

[0101] The data security governance module 940 is used to identify data security risk situations and call the dynamic association relationship model when the data governance type of medical data is data security governance; input the medical data into the dynamic association relationship model to obtain the data association relationship; obtain the security protection plan according to the data association relationship, display the data association relationship and the security protection plan, and perform data security protection intervention;

[0102] The data asset governance module 950 is used to identify the data asset value and call the dynamic hot-cold relationship model when the data governance type of medical data is data asset governance; input the medical data into the dynamic hot-cold relationship model to obtain the hot-cold relationship data; obtain the asset value level according to the hot-cold relationship data, display the hot-cold relationship data and the asset value level, and mark the data asset value.

[0103] In one embodiment, the data governance type determination module 920 is also used to input medical data into the TCG three-dimensional management model. The TCG three-dimensional management model classifies and grades medical data through the data object dimension; the TCG three-dimensional management model classifies medical data based on sensitivity and impact through the data classification dimension; the TCG three-dimensional management model classifies medical data based on data type or data scenario application needs through the data classification dimension to obtain classification management results.

[0104] In one embodiment, the data quality governance module 930 is also used to input medical data into a dynamic blood relationship model, and dynamically extract data models and data jobs from the data warehouse through the dynamic blood relationship model to form data models and job sets; the dynamic blood relationship model performs database parsing on the data models and job sets, identifies data dependencies between different sets, and forms a data dependency set; the dynamic blood relationship model uses the TCG three-dimensional management model to form a data direct blood relationship corresponding to the medical data based on the data dependency set and an association algorithm based on association rules, and the data direct blood relationship is marked with quality problem classification information; the data direct blood relationship and quality problem classification information are displayed, and quality problem intervention is performed.

[0105] In one embodiment, the data quality governance module 930 is also used to locate medical data with quality problems based on direct blood relationship and quality problem classification information; obtain quality evaluation strategies, determine the causes of quality problems based on the quality evaluation strategies and the medical data with quality problems, and intervene in quality problems based on the causes of quality problems.

[0106] In one embodiment, the data security governance module 940 is also used to input medical data into a dynamic association relationship model to form a data dependency set through the dynamic association relationship model; the dynamic association relationship model filters out the horizontal association data in the medical data according to the data dependency set, and intelligently classifies the horizontal association data through a statistical clustering algorithm and a TCG three-dimensional management model to form an initial data association relationship; the dynamic association relationship model integrates and deduplicates the initial data association relationship to obtain the data association relationship, and obtains the security protection plan corresponding to the data association relationship, displays the data association relationship and the security protection plan, and performs data security protection intervention.

[0107] In one embodiment, the data asset governance module 950 is also used to input medical data into a dynamic hot-cold relationship model, extract and parse data processing logs through the dynamic hot-cold relationship model, and obtain the frequency of use of medical data; the dynamic hot-cold relationship model calculates the hot-cold label of medical data based on the frequency of use in combination with a clustering algorithm; the dynamic hot-cold relationship model clusters and classifies medical data based on the hot-cold label in combination with the TCG three-dimensional management model to obtain hot-cold relationship data; the asset value level is obtained based on the hot-cold relationship data, the hot-cold relationship data and asset value level are displayed, and the data asset value is marked.

[0108] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a medical data governance method based on a metadata model is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0109] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0110] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0111] Based on the collected and recovered metadata, a metadata model is constructed according to the medical data governance scenario; the metadata model includes the TCG (target, classify, grade) three-dimensional management model, the dynamic blood relationship model, the dynamic association relationship model, and the dynamic hot and cold relationship model;

[0112] Monitor medical data in real time and manage medical data by category through the TCG three-dimensional management model; determine the data governance type of medical data when there are medical data governance scenario problems; data governance types include data quality governance, data security governance, and data asset governance;

[0113] When the data governance type of medical data is data quality governance, the causes of data quality are investigated and located, and the dynamic lineage relationship model is called; the medical data is input into the dynamic lineage relationship model to obtain the direct lineage relationship of the data; quality problem classification information is obtained based on the direct lineage relationship of the data, the direct lineage relationship of the data and the quality problem classification information are displayed, and quality problem intervention is carried out;

[0114] When the data governance type of medical data is data security governance, identify data security risks and call the dynamic association model; input the medical data into the dynamic association model to obtain the data association; obtain the security protection plan based on the data association, display the data association and security protection plan, and perform data security protection intervention;

[0115] When the data governance type of medical data is data asset governance, identify the data asset value and call the dynamic hot-cold relationship model; input the medical data into the dynamic hot-cold relationship model to obtain the hot-cold relationship data; obtain the asset value level based on the hot-cold relationship data, display the hot-cold relationship data and asset value level, and mark the data asset value.

[0116] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0117] Based on the collected and recovered metadata, a metadata model is constructed according to the medical data governance scenario; the metadata model includes the TCG (target, classify, grade) three-dimensional management model, the dynamic blood relationship model, the dynamic association relationship model, and the dynamic hot and cold relationship model;

[0118] Monitor medical data in real time and manage medical data by category through the TCG three-dimensional management model; determine the data governance type of medical data when there are medical data governance scenario problems; data governance types include data quality governance, data security governance, and data asset governance;

[0119] When the data governance type of medical data is data quality governance, the causes of data quality are investigated and located, and the dynamic lineage relationship model is called; the medical data is input into the dynamic lineage relationship model to obtain the direct lineage relationship of the data; quality problem classification information is obtained based on the direct lineage relationship of the data, the direct lineage relationship of the data and the quality problem classification information are displayed, and quality problem intervention is carried out;

[0120] When the data governance type of medical data is data security governance, identify data security risks and call the dynamic association model; input the medical data into the dynamic association model to obtain the data association; obtain the security protection plan based on the data association, display the data association and security protection plan, and perform data security protection intervention;

[0121] When the data governance type of medical data is data asset governance, identify the data asset value and call the dynamic hot-cold relationship model; input the medical data into the dynamic hot-cold relationship model to obtain the hot-cold relationship data; obtain the asset value level based on the hot-cold relationship data, display the hot-cold relationship data and asset value level, and mark the data asset value.

[0122] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0123] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A medical data governance method based on metadata model, characterized in that: The method comprises: Based on the collected and recovered metadata, a metadata model is constructed according to the medical data governance scenario; the metadata model includes a TCG three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot-cold relationship model; the three dimensions in the TCG three-dimensional management model specifically include: data object dimension target, data classification dimension classify, and data classification dimension grade; Monitor medical data in real time, and classify and manage the medical data through the TCG three-dimensional management model, including: input the medical data into the TCG three-dimensional management model, and the TCG three-dimensional management model classifies and grades the medical data through the data object dimension; the TCG three-dimensional management model classifies the medical data from the perspective of sensitivity and impact through the data classification dimension; the TCG three-dimensional management model classifies the medical data from the perspective of data type or data scenario application needs through the data classification dimension to obtain classification management results; when the medical data has medical data governance scenario problems, determine the data governance type of the medical data; the data governance types include data quality governance, data security governance, and data asset governance; When the data governance type of the medical data is data quality governance, the cause of the data quality is investigated and located, and the dynamic blood relationship model is called; the medical data is input into the dynamic blood relationship model to obtain the data direct blood relationship; quality problem classification information is obtained according to the data direct blood relationship, the data direct blood relationship and the quality problem classification information are displayed, and quality problem intervention is performed; When the data governance type of the medical data is data security governance, identify the data security risk situation and call the dynamic association relationship model; input the medical data into the dynamic association relationship model to obtain the data association relationship; obtain the security protection plan according to the data association relationship, display the data association relationship and the security protection plan, and perform data security protection intervention; When the data governance type of the medical data is data asset governance, the data asset value is identified and the dynamic hot-cold relationship model is called; the medical data is input into the dynamic hot-cold relationship model to obtain hot-cold relationship data; the asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data and the asset value level are displayed, and the data asset value is marked.

2. The medical data governance method based on metadata model according to claim 1 is characterized in that: The medical data is input into the dynamic blood relationship model to obtain the direct blood relationship of the data; Acquiring quality problem classification information according to the data direct lineage relationship, displaying the data direct lineage relationship and the quality problem classification information, and performing quality problem intervention, including: Input the medical data into the dynamic blood relationship model, and dynamically extract data models and data jobs from the data warehouse through the dynamic blood relationship model to form a data model and job set; The dynamic blood relationship model performs database analysis on the data model and the job set, identifies data dependencies between different sets, and forms a data dependency set; The dynamic blood relationship model forms a data lineage relationship corresponding to the medical data according to the data dependency set and an association algorithm based on association rules by using the TCG three-dimensional management model, wherein the data lineage relationship is marked with the quality problem classification information; Display the direct lineage relationship of the data and the classification information of the quality problems, and intervene in the quality problems.

3. The medical data governance method based on metadata model according to claim 2 is characterized in that: Prior to intervening in a quality issue, the method further includes: Locating the medical data with quality problems according to the direct blood relationship and the quality problem classification information; Acquire a quality evaluation strategy, determine the cause of the quality problem based on the quality evaluation strategy and the medical data with quality problems, and perform quality problem intervention based on the cause of the quality problem.

4. The medical data governance method based on metadata model according to claim 1 is characterized in that: The step of inputting the medical data into the dynamic association relationship model to obtain a data association relationship; obtaining a security protection scheme according to the data association relationship, displaying the data association relationship and the security protection scheme, and performing data security protection intervention includes: Inputting the medical data into the dynamic association relationship model to form a data dependency set through the dynamic association relationship model; The dynamic association relationship model filters out the horizontal association data in the medical data according to the data dependency set, and intelligently classifies the horizontal association data through a statistical clustering algorithm and the TCG three-dimensional management model to form an initial data association relationship; The dynamic association relationship model integrates and deduplicates the initial data association relationship to obtain the data association relationship, and obtains the security protection plan corresponding to the data association relationship, displays the data association relationship and the security protection plan, and performs data security protection intervention.

5. The medical data governance method based on metadata model according to claim 1 is characterized in that: The medical data is input into the dynamic hot-cold relationship model to obtain hot-cold relationship data; Acquiring the asset value level according to the hot-cold relationship data, displaying the hot-cold relationship data and the asset value level, and marking the data asset value, including: Inputting the medical data into the dynamic hot-cold relationship model, extracting and parsing data processing logs through the dynamic hot-cold relationship model, and obtaining the usage frequency of the medical data; The dynamic hot-cold relationship model calculates the hot-cold label of the medical data according to the usage frequency in combination with a clustering algorithm; The dynamic hot-cold relationship model performs clustering and classification processing on the medical data according to the hot-cold label in combination with the TCG three-dimensional management model to obtain the hot-cold relationship data; The asset value level is obtained according to the hot-cold relationship data, the hot-cold relationship data and the asset value level are displayed, and the data asset value is marked.

6. A medical data governance system based on metadata model, characterized in that: The system comprises: A model building module is used to build a metadata model based on the collected and recovered metadata according to the medical data governance scenario; the metadata model includes a TCG three-dimensional management model, a dynamic blood relationship model, a dynamic association relationship model, and a dynamic hot-cold relationship model; the three dimensions in the TCG three-dimensional management model specifically include: data object dimension target, data classification dimension classify, and data classification dimension grade; A data governance type determination module is used to monitor medical data in real time and classify and manage the medical data through the TCG three-dimensional management model, including: inputting the medical data into the TCG three-dimensional management model, and the TCG three-dimensional management model classifies and grades the medical data through the data object dimension; the TCG three-dimensional management model classifies the medical data from the perspective of sensitivity and impact through the data classification dimension; the TCG three-dimensional management model classifies the medical data from the perspective of data type or data scenario application needs through the data classification dimension to obtain a classification management result; when the medical data has a medical data governance scenario problem, determining the data governance type of the medical data; the data governance types include data quality governance, data security governance, and data asset governance; A data quality governance module, for, when the data governance type of the medical data is data quality governance, to troubleshoot and locate the cause of data quality, and to call the dynamic blood relationship model; to input the medical data into the dynamic blood relationship model to obtain the direct blood relationship of the data; to obtain quality problem classification information according to the direct blood relationship of the data, to display the direct blood relationship of the data, the quality problem classification information, and to intervene in quality problems; A data security governance module, for identifying data security risk situations and calling the dynamic association relationship model when the data governance type of the medical data is data security governance; inputting the medical data into the dynamic association relationship model to obtain a data association relationship; obtaining a security protection plan according to the data association relationship, displaying the data association relationship and the security protection plan, and performing data security protection intervention; A data asset governance module is used to identify the data asset value and call the dynamic hot-cold relationship model when the data governance type of the medical data is data asset governance; input the medical data into the dynamic hot-cold relationship model to obtain hot-cold relationship data; obtain the asset value level according to the hot-cold relationship data, display the hot-cold relationship data, the asset value level and mark the data asset value.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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