Medical data processing method and device, equipment, storage medium and program product

Abstract

The invention provides a medical data processing method and device, equipment, a storage medium and a program product, and relates to the technical field of data processing. The method comprises the following steps: acquiring updated medical data information in a target medical information system; performing fine-grained splitting on the medical data information based on a preset splitting rule to obtain initial medical data information; verifying whether the initial medical data information has a data mismatching condition or not; performing multi-dimensional data integration on the initial medical data information based on a preset data integration rule to obtain target medical data information; storing the target medical data information in a plurality of nodes of a distributed database; and in response to the change of the target medical data information in the distributed database, obtaining processing information of the target medical data information and storing the processing information on the block chain. According to the medical data processing method, the medical data information is not prone to single-point faults and tampering risks, and illegal behaviors of the medical data can be found in time.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a medical data processing method, device, equipment, storage medium and program product. Background Art

[0002] At present, most medical institutions use centralized storage and management for medical data, that is, after collecting medical data from the medical information system, the medical data is stored in a central database, and the centrally stored medical data is analyzed through data analysis tools to discover and prevent medical data violations. However, the above medical data processing methods have the problems of low data security and low data processing efficiency. Summary of the invention

[0003] The present application provides a medical data processing method, device, equipment, storage medium and program product to solve the problems of low data security and low data processing efficiency in existing medical data processing methods.

[0004] In a first aspect, the present application provides a medical data processing method, comprising:

[0005] In response to determining that there is medical data information update in the target medical information system, acquiring the updated medical data information in the target medical information system;

[0006] Fine-grained splitting of the medical data information is performed based on a preset splitting rule to obtain initial medical data information, wherein the preset splitting rule is a splitting rule based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information, and timestamp information;

[0007] Performing data verification based on the patient identification information, the diagnosis information, the treatment record, the examination and testing information, the medication information, and the cost information to determine whether there is a data mismatch in the initial medical data information;

[0008] In response to the initial medical data information not having a data mismatch, performing multi-dimensional data integration on the initial medical data information based on a preset data integration rule to obtain target medical data information;

[0009] Storing the target medical data information in multiple nodes of a distributed database;

[0010] In response to a change in the target medical data information in the distributed database, processing information of the target medical data information is obtained, and the processing information is stored on the blockchain.

[0011] In a possible design, the fine-grained splitting of the medical data information based on a preset splitting rule to obtain initial medical data information includes:

[0012] Splitting the medical data information according to the diagnosis information, the treatment record, the examination and testing information, the drug information, and the cost information to obtain first segmented medical data information;

[0013] Splitting the first subdivided medical data information according to the patient identity information to obtain second subdivided medical data information;

[0014] The second subdivided medical data information is split according to the timestamp information to obtain the initial medical data information.

[0015] In a possible design, the multi-dimensional data integration of the initial medical data information based on a preset data integration rule to obtain target medical data information includes:

[0016] Based on the patient identity information and the timestamp information, the patient's diagnosis information, treatment records, examination and testing information, drug information and cost information are integrated in chronological order to obtain target medical data information.

[0017] In one possible design, obtaining processing information of the target medical data information and storing the processing information on a blockchain includes:

[0018] Obtaining the processing time, processing personnel and processing content of the target medical data information;

[0019] The processing time, the processing personnel and the processing content are stored on the blockchain.

[0020] In a possible design, before storing the processing time, processing personnel and processing content on the blockchain, it also includes:

[0021] A data fingerprint is generated by a hash algorithm, and the data fingerprint is used to verify whether the processing time, the processing personnel and the processing content stored on the blockchain have been tampered with.

[0022] In one possible design, in response to determining that the initial medical data information has a data mismatch, data error information is sent to the target medical information system.

[0023] In a possible design, before performing multi-dimensional data integration on the initial medical data information based on a preset data integration rule to obtain target medical data information, the method further includes:

[0024] The initial medical data information is cleaned and standardized.

[0025] In a possible design, before storing the target medical data information in multiple nodes of a distributed database, the method further includes:

[0026] Performing a query in the distributed database based on the patient identity information to determine whether there is historical medical data information matching the patient identity information in the distributed database;

[0027] In response to determining that the historical medical data information exists in the distributed data, the target medical data information is integrated with the historical medical data information.

[0028] In a second aspect, the present application provides a medical data processing device, comprising:

[0029] an acquisition module, configured to acquire updated medical data information in the target medical information system in response to determining that there is updated medical data information in the target medical information system;

[0030] A splitting module, used for performing fine-grained splitting of the medical data information based on a preset splitting rule to obtain initial medical data information, wherein the preset splitting rule is a splitting rule based on patient identity information, diagnosis information, treatment record, examination and testing information, drug information, cost information and timestamp information;

[0031] A verification module, configured to perform data verification based on the patient identification information, the diagnosis information, the treatment record, the examination and testing information, the drug information, and the cost information to determine whether there is a data mismatch in the initial medical data information;

[0032] an integration module, configured to perform multi-dimensional data integration on the initial medical data information based on a preset data integration rule in response to the initial medical data information not having a data mismatch, so as to obtain target medical data information;

[0033] A storage module, used to store the target medical data information in multiple nodes of a distributed database;

[0034] The storage module is also used to obtain processing information of the target medical data information in response to changes in the target medical data information in the distributed database, and store the processing information on the blockchain.

[0035] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0036] The memory stores computer-executable instructions;

[0037] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0038] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any of the methods described in the first aspect. .

[0039] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which implements the method described in any one of the first aspects when executed by a processor.

[0040] The medical data processing method, apparatus, device, storage medium and program product provided by the present application obtain updated medical data information in a target medical information system in response to determining that there is an update of medical data information in a target medical information system; perform fine-grained splitting of the medical data information based on preset splitting rules to obtain initial medical data information, wherein the preset splitting rules are rules for splitting based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information and timestamp information; perform data verification based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information and cost information to determine whether there is a data mismatch in the initial medical data information; in response to the absence of a data mismatch in the initial medical data information, perform multi-dimensional data integration on the initial medical data information based on preset data integration rules to obtain target medical data information; store the target medical data information in multiple nodes of a distributed database; in response to changes in the target medical data information in the distributed database, obtain processing information of the target medical data information, and store the processing information on a blockchain. The medical data processing method performs fine-grained splitting of medical data information so that the medical data information is split into smaller data units that are not easily tampered with or forged; then performs data verification on the initial medical data information to determine whether there is a data mismatch in the initial medical data information, and can instantly discover whether there is a medical data violation in the medical data information; performs multi-dimensional data integration on the initial medical data information based on preset data integration rules, and stores the integrated target medical data information on multiple nodes of a distributed database, which can avoid single-point data failures; stores the processing information of the target medical data information on a blockchain, ensuring high transparency of data processing and facilitating data traceability, and can effectively curb the risk of data tampering. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] Figure 1 An application scenario diagram of a medical data processing method provided in an embodiment of the present application;

[0043] Figure 2 A flowchart of a medical data processing method provided in one embodiment of the present application;

[0044] Figure 3 A flowchart of a medical data processing method provided in yet another embodiment of the present application;

[0045] Figure 4 A schematic diagram of the structure of a medical data processing device provided in one embodiment of the present application;

[0046] Figure 5 A structural diagram of an electronic device provided in one embodiment of the present application.

[0047] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0048] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0049] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of information such as financial data or user data involved shall comply with the provisions of relevant laws and regulations and shall not violate public order and good morals.

[0050] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0051] In order to clearly understand the technical solution of the present application, the solution of the prior art is first introduced in detail.

[0052] With the continuous development of medical information technology, the degree of informatization of domestic medical institutions is also getting higher and higher. At present, most medical institutions still use centralized storage and management for medical data. Specifically, after collecting medical data from the medical information system, the medical institutions store the medical data in a central database, and use data analysis tools to analyze and mine the centrally stored medical data in order to discover and prevent potential medical data violations. However, the existing method of centrally storing medical data in a central database is prone to single point failures and data tampering risks. The poor data transparency makes it difficult to effectively curb data tampering. In addition, relying on data analysis tools for post-data analysis lacks timeliness and cannot detect medical data violations in a timely manner. Therefore, the existing medical data processing methods still have problems with low data security and low data processing efficiency.

[0053] Therefore, in the face of the technical problems of the above-mentioned prior art, in order to improve the data security and data processing efficiency of the medical data processing method. First, obtain the updated medical data information in the medical information system, perform fine-grained splitting of the medical data information based on the preset splitting rules to obtain the initial medical data information, and then perform data verification on the initial medical data information to determine whether there is a data mismatch in the initial medical data information, so that it can be immediately discovered whether there is a medical data violation in the medical data information. If there is no data mismatch in the initial medical data information, perform multi-dimensional data integration on the initial medical data information based on the preset data integration rules, and store the integrated target medical data information on multiple nodes of the distributed database to avoid single point failure of data; when the target medical data information in the distributed database changes, obtain the processing information and store it on the blockchain, so that the data processing is highly transparent and easy to trace, which can effectively curb the risk of data tampering.

[0054] Figure 1 An application scenario diagram corresponding to the medical data processing method provided in one embodiment of the present application, such as Figure 1As shown, the application scenario provided by this embodiment specifically includes: a medical information system terminal 11, a medical data processing terminal 12 and a distributed database 13. Specifically, when the medical data information in the medical information system terminal 11 is updated, the medical information system terminal 11 sends the updated medical data information to the medical data processing terminal 12; the medical data processing terminal 12 performs fine-grained splitting of the medical data information based on the preset splitting rules to obtain the initial medical data information, wherein the preset splitting rules are splitting rules based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information and timestamp information; after the medical data information is split, data verification is performed based on the patient identity information, diagnosis information, treatment records, examination and testing information, drug information and cost information to determine whether there is a data mismatch in the initial medical data information; when it is determined that there is no data mismatch in the initial medical data information, the initial medical data information is multi-dimensionally integrated based on the preset data integration rules to obtain the target medical data information. The medical information system terminal 11 sends the target medical data information to the distributed database 13 for storage during distribution. When the target medical data information in the distributed database 13 changes, the processing information of the target medical data information is sent to the medical information processing terminal 12, and the medical data processing terminal 12 stores the processing information on the blockchain.

[0055] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0056] Figure 2 A flowchart of a medical data processing method provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the execution subject of this embodiment is a medical data processing device, which can be implemented by a computer program or a medium storing relevant computer programs, such as a USB flash drive and / or a CD, etc.; or, it can also be implemented by a physical device integrated or installed with relevant computer programs, such as a chip, an electronic device, etc. The electronic device can be a computer or a server, etc. The medical data processing method provided in this embodiment includes the following steps:

[0057] Step S201: in response to determining that there is updated medical data information in the target medical information system, obtaining updated medical data information in the target medical information system.

[0058] Specifically, when there is medical data information update in the target medical information system, the updated medical data information in the target medical information system is instantly acquired for subsequent data processing.

[0059] The target medical information system is a system for storing, managing and transmitting medical data information. Optionally, the target medical information system can store, including but not limited to, patient identity information, diagnosis information, treatment records, examination and testing information, drug information and cost information.

[0060] Optionally, stream processing technology is used to collect, transmit, process and analyze the medical data information in the target medical information system in real time, such as Apache Kafka and Apache Flink, so as to achieve real-time monitoring and analysis of medical data information.

[0061] Step S202: Fine-grained splitting of the medical data information is performed based on preset splitting rules to obtain initial medical data information, wherein the preset splitting rules are rules for splitting based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information, and timestamp information.

[0062] Specifically, after obtaining updated medical data information, the medical data information is finely split based on the preset splitting rules, so as to obtain initial medical data information for subsequent processing and verification. The preset splitting rules are pre-set rules for fine-grained splitting of medical data information, and specifically, the preset splitting rules are rules for splitting based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information, and timestamp information.

[0063] The initial medical data information is the medical data information after fine-grained splitting.

[0064] Among them, fine-grained splitting refers to the process of splitting medical data information into smaller and more specific components according to preset splitting rules, so as to facilitate more in-depth analysis, processing and storage. At the same time, because medical data information is broken down into smaller parts, each part contains less information, and fine-grained splitting also helps to better protect patient privacy, thereby reducing the risk of data leakage.

[0065] Among them, patient identity information includes but is not limited to the patient's name, gender, age, contact information and ID number; diagnostic information includes the patient's medical history, chief complaint, current medical history, past history, family history, etc.; treatment records record the treatment measures received by the patient, such as surgery, drug therapy, physical therapy, etc., specifically including the start and end time of treatment, evaluation of the effectiveness of treatment, etc.; examination and testing information is the results of various examinations and tests (such as blood routine, urine routine, etc.) received by the patient; drug information is the name, dosage, usage and time of medication used by the patient; cost information is the cost incurred by the patient for receiving medical services, including examination fees, treatment fees, drug fees, etc.; timestamp information is the time point or time period when the above information occurs.

[0066] Optionally, after the medical data information is split into fine-grained units, each split data unit can be encrypted and digitally signed to ensure the security of the data during transmission and storage, so as to better prevent the data from being tampered with.

[0067] Optionally, there are many ways to achieve fine-grained splitting of medical data information, such as through relational database technology, regular expressions, XML / JSON parsing, etc., where the table structure and foreign key constraints of the relational database can split complex medical data into multiple fine-grained tables to ensure data standardization and consistency, and foreign key constraints ensure data association between different tables and improve data integrity. It should be noted that the fine-grained splitting method is not specifically limited in this embodiment, as long as the fine-grained splitting of medical data information can be achieved.

[0068] Optionally, through service-oriented architecture design, the fine-grained split data can be accessed and managed through different service interfaces, thereby ensuring that the fine-grained split data can be shared and interoperable between different systems.

[0069] Optionally, the fine-grained split data is temporarily stored in a NoSQL database, such as Cassandra, MongoDB, etc. These NoSQL databases are known for their high scalability and flexibility, and are very suitable for storing and managing fine-grained data units, which can ensure data consistency and high availability.

[0070] Specifically, in this embodiment, medical data information is fine-grainedly split, so that the medical data information is split into smaller data units, which are not easily tampered with or forged, and the split data units can be tracked and audited separately to ensure the traceability of the entire process from data generation to storage; the split data units are also convenient for data standardization and unification, reducing data redundancy and ensuring the consistency of data formats of different information modules.

[0071] Step S203: perform data verification based on the patient's identity information, diagnosis information, treatment records, examination and testing information, medication information, and cost information to determine whether there is any data mismatch in the initial medical data information.

[0072] Specifically, after obtaining the initial medical data information, data verification is performed based on the patient's identity information, diagnosis information, treatment records, examination and testing information, drug information and cost information. Specifically, cross-verification is performed through the diagnosis information, treatment records, examination and testing information, drug information and cost information of the same patient, for example, whether the treatment records are consistent with the drug information, whether the cost information matches the diagnosis information, treatment records, examination and testing information and drug information, etc.; thereby determining whether there is any mismatch in the initial medical data information.

[0073] Optionally, different processing is performed based on the matching of the initial medical data information. For example, when the initial medical data information does not match, it indicates that the initial medical data information may have been tampered with. At this time, a data error log is recorded and an alarm may be triggered or relevant personnel may be notified, such as sending a data error reminder to the patient, medical staff or manager by way of a message. When the initial medical data information does not match, it indicates that there is no error in the data, and the subsequent medical data processing process continues to be executed.

[0074] Optionally, there are multiple ways of data verification, such as format verification (such as date format, telephone number format, etc.), range verification (such as drug dosage range, etc.) and logic verification (such as whether the diagnostic information is consistent with the drug). The specific method of data verification is not specifically limited here.

[0075] Optionally, there are multiple options for data verification tools, such as rule engines, data comparison tools, or custom scripts and programs. In this embodiment, the data verification tools are not specifically limited.

[0076] Specifically, in this embodiment, after obtaining the initial medical data information, it is convenient to perform data verification on the patient's identity information, diagnosis information, treatment records, examination and testing information, drug information, and cost information to determine whether there is any data mismatch in the initial medical data information; thereby, it is possible to instantly discover whether there is data tampering or data errors in the medical data information, thereby reducing the risk of medical data violations.

[0077] Step S204: In response to the fact that there is no data mismatch in the initial medical data information, multi-dimensional data integration is performed on the initial medical data information based on a preset data integration rule to obtain target medical data information.

[0078] Specifically, after it is determined that there is no data mismatch in the initial medical data information, multi-dimensional data integration is performed on the initial medical data information based on a preset data integration rule to obtain target medical data information.

[0079] Among them, the target medical data information is the medical data information obtained through multi-dimensional data integration.

[0080] The preset data integration rules are preset rules for integrating the initial medical data information. Optionally, the preset data integration rules can be the following rules: deduplication rules, ensuring that the same data of the same patient in the same time period is recorded only once; aggregation rules, aggregating data under the same dimension, such as calculating the number of treatments for a certain type of disease, the amount of a certain drug used; association rules, associating and integrating data of different dimensions but related to each other, such as associating the results of a certain examination with the treatment record.

[0081] Among them, multi-dimensional data integration is a method of integrating data from different sources and dimensions, such as patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information and timestamp information, to form a more complete and consistent data set.

[0082] Optionally, data preprocessing is first performed before the multi-dimensional integration of the initial medical data information, so that the data integration can be performed efficiently and accurately. The data preprocessing may include removing invalid data, unifying data formats, etc.

[0083] Optionally, there are many ways to perform multi-dimensional data integration on the initial medical data information, such as ETL (Extract, Transform, Load) technology, data integration platform, data lake technology, data middle platform structure, etc.

[0084] Specifically, in this embodiment, the initial medical data information is integrated into multiple dimensions to form a more complete and consistent data set, providing strong data support for medical decision-making, disease diagnosis, personalized treatment, etc. In addition, multi-dimensional data integration can also provide a comprehensive view of patient medical behavior.

[0085] Step S205: store the target medical data information in multiple nodes of the distributed database.

[0086] Specifically, storing the integrated target medical data information on multiple nodes of a distributed database can avoid single point failure of the target medical data information and ensure the continuous availability of the data.

[0087] Optionally, the distributed database may be a NoSQL database, such as MongoDB, Cassandra; or a distributed relational database, such as Greenplum, Teradata, etc.

[0088] It should be noted that the sharding and synchronization mechanism of the distributed database ensures data consistency and high availability. Each node stores part of the data and maintains data consistency through an efficient synchronization strategy. Even if a node fails, other nodes can quickly take over its work to ensure service continuity.

[0089] Step S206: In response to changes in the target medical data information in the distributed database, obtain processing information of the target medical data information, and store the processing information on the blockchain.

[0090] Specifically, when it is determined that the target medical data information in the distributed database has changed, such as adding new medical data information or modifying the content of medical data information, the processing information of the target medical data information is obtained and stored on the blockchain, thereby utilizing blockchain technology to ensure the immutability and traceability of the processing information, and to ensure the transparency and reliability of the data operation of the target medical data information.

[0091] The processing information includes but is not limited to the processing personnel, processing time and processing content.

[0092] Optionally, smart contracts are used to automate the process of recording and verifying information, thereby improving the efficiency of data processing.

[0093] The medical data processing method provided in the present embodiment obtains updated medical data information in the target medical information system in response to determining that there is an update of medical data information in the target medical information system; performs fine-grained splitting of the medical data information based on preset splitting rules to obtain initial medical data information, wherein the preset splitting rules are rules for splitting based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information and timestamp information; performs data verification based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information and cost information to determine whether there is a data mismatch in the initial medical data information; in response to the absence of a data mismatch in the initial medical data information, performs multi-dimensional data integration on the initial medical data information based on preset data integration rules to obtain target medical data information; stores the target medical data information in multiple nodes of a distributed database; in response to changes in the target medical data information in the distributed database, obtains processing information of the target medical data information, and stores the processing information on a blockchain. The medical data processing method performs fine-grained splitting of medical data information so that the medical data information is split into smaller data units that are not easily tampered with or forged; then performs data verification on the initial medical data information to determine whether there is a data mismatch in the initial medical data information, and can instantly discover whether there is a medical data violation in the medical data information; performs multi-dimensional data integration on the initial medical data information based on preset data integration rules, and stores the integrated target medical data information on multiple nodes of a distributed database, which can avoid single-point data failures; stores the processing information of the target medical data information on a blockchain, ensuring high transparency of data processing and facilitating data traceability, and can effectively curb the risk of data tampering.

[0094] As an optional implementation, based on any of the above embodiments, fine-grained splitting of the medical data information is performed based on a preset splitting rule to obtain initial medical data information, including:

[0095] Splitting the medical data information according to diagnosis information, treatment records, examination and testing information, drug information, and cost information to obtain first segmented medical data information;

[0096] Splitting the first segmented medical data information according to the patient identity information to obtain second segmented medical data information;

[0097] The second segmented medical data information is split according to the timestamp information to obtain initial medical data information.

[0098] Specifically, when fine-grained splitting of medical data information is performed based on preset splitting rules, first, the medical data information is split according to diagnosis information, treatment records, examination and testing information, drug information, and cost information, so as to obtain first segmented medical data information of different types; then, the first segmented medical data information is split based on the patient identity information to obtain second segmented medical data information, so as to distinguish the medical data information of different patients; finally, the second segmented medical data information is split according to timestamp information to obtain initial medical data information, so that the initial medical data information is medical data information of the same patient, the same type, and different time periods.

[0099] Optionally, the above splitting order can be adaptively adjusted according to actual splitting requirements, for example, first split according to patient identity information, then split according to type, and finally split according to timestamp information.

[0100] Optionally, after the second segmented medical data information is split according to the timestamp information, it can be split again based on actual conditions to obtain smaller data units.

[0101] The medical data processing method provided in this embodiment, when performing fine-grained splitting of medical data information based on preset splitting rules to obtain initial medical data information, specifically includes splitting the medical data information according to diagnosis information, treatment records, examination and testing information, drug information, and cost information to obtain first subdivided medical data information; splitting the first subdivided medical data information according to patient identity information to obtain second subdivided medical data information; splitting the second subdivided medical data information according to timestamp information to obtain initial medical data information. This method subdivides medical data information into smaller data units through a three-step splitting process, which can reduce the risk of data tampering and help to achieve subsequent accurate management and analysis of data.

[0102] As an optional implementation, based on any of the above embodiments, the initial medical data information is integrated in multiple dimensions based on a preset data integration rule to obtain target medical data information, including:

[0103] Based on the patient's identity information and timestamp information, the patient's diagnosis information, treatment records, examination and testing information, drug information, and cost information are integrated in chronological order to obtain the target medical data information.

[0104] Specifically, when the initial medical data information is integrated in multiple dimensions based on preset data integration rules, the patient's diagnosis information, treatment records, examination and testing information, drug information, and cost information are integrated in chronological order based on the patient's identity information and timestamp information to obtain the target medical data information.

[0105] Among them, patient identity information is used to distinguish the medical data information of different patients, and timestamp information is used to determine the time sequence of the medical data of the same patient. According to the timestamp information, the diagnosis information, treatment records, examination and testing information, drug information and cost information belonging to the same patient are sorted in chronological order, ensuring the time sequence of the data, so that the integrated data can reflect the order in which the medical process occurs.

[0106] Optionally, on the basis of sorting the medical data information by time, data belonging to the same time period or closely related data can be integrated. For example, the diagnosis information and treatment records of the same day can be integrated together to form a complete record of a visit. Similarly, the inspection and testing information within the same inspection cycle can be integrated together to facilitate the analysis of the changing trend of the disease.

[0107] It should be noted that the integrated target medical data information includes the complete medical records of the same patient, and the medical records are time-series and related, providing data support for subsequent data analysis and research. For example, doctors can use the integrated target medical data information to more comprehensively understand the patient's condition and treatment history, so as to make more accurate diagnosis and treatment decisions; medical institutions can evaluate the quality and effect of the medical process by analyzing the integrated data, thereby improving the medical process and service quality; researchers can use the integrated data to conduct more in-depth medical research.

[0108] The medical data processing method provided in this embodiment integrates the initial medical data information in multiple dimensions based on the preset data integration rules to obtain the target medical data information, including integrating the patient's diagnosis information, treatment records, examination and testing information, drug information, and cost information in chronological order based on the patient's identity information and timestamp information to obtain the target medical data information. The target medical data information integrated by this method makes the timeline of the patient's medical process clearly visible, and also ensures the relevance between various information, which is convenient for subsequent data analysis.

[0109] As an optional implementation, based on any of the above embodiments, obtaining processing information of target medical data information and storing the processing information on a blockchain includes:

[0110] Obtain the processing time, processing personnel and processing content of target medical data information;

[0111] The processing time, processing personnel and processing content are stored on the blockchain.

[0112] Specifically, when obtaining the processing information of the target medical data information and storing the processing information on the blockchain, the following steps are specifically included: first, the processing time, processing personnel and processing content of the target medical data information are obtained, and then the processing time, processing personnel and processing content are stored on the blockchain.

[0113] The processing time is the specific time point or time period when the target medical data information is processed, the processing personnel are the specific personnel who process the target medical data information, and the processing content is the specific operation or modification content of the target medical data information. In this way, it is convenient to carry out subsequent responsibility tracing and auditing.

[0114] Optionally, the smart contract function of the blockchain can be used to further define data access rights, verification rules, and processing procedures to ensure that only authorized personnel or systems can access and modify the data.

[0115] Specifically, the application of blockchain to store and process information has the following advantages: transparency. The public ledger feature of blockchain allows anyone to verify the authenticity and integrity of data, which improves the transparency of data; immutability. Once data is recorded on the blockchain, it cannot be tampered with or deleted, ensuring the authenticity and credibility of the data; traceability. Through the chain structure of blockchain, the processing history and source of data can be easily tracked, which facilitates responsibility tracing and auditing; security. The distributed storage and encryption algorithm of blockchain ensure the security of data. Even if some nodes are attacked, the data will not be lost or tampered with.

[0116] The medical data processing method provided in this embodiment, when obtaining the processing information of the target medical data information and storing the processing information on the blockchain, includes: obtaining the processing time, processing personnel and processing content of the target medical data information; storing the processing time, processing personnel and processing content on the blockchain. This method stores the processing time, processing personnel and processing content on the blockchain, which is highly secure and cannot be tampered with, and can facilitate subsequent responsibility tracing and auditing.

[0117] As an optional implementation, based on any of the above embodiments, before storing the processing time, processing personnel and processing content on the blockchain, it also includes:

[0118] The data fingerprint is generated through the hash algorithm, and the data fingerprint is used to verify whether the processing time, processing personnel and processing content stored on the blockchain have been tampered with.

[0119] Specifically, when the processing time, processing personnel and processing content need to be stored on the blockchain, the processing time, processing personnel and processing content are first hashed through a hash algorithm to generate a data fingerprint. This data fingerprint, as the unique identifier of the data, will be stored on the blockchain together with the original data or separately. When it is necessary to verify whether the processing time, processing personnel and processing content have been tampered with, the hash value of this information can be recalculated and compared with the hash value stored on the blockchain: if the two are consistent, it means that the information has not been tampered with after storage; if they are inconsistent, it means that the information may have been tampered with.

[0120] The hash algorithm converts the original data into a hash value of fixed length, i.e., the data fingerprint. Specifically, the hash value has the characteristics of uniqueness and tamper-proof, which can ensure the security of the data.

[0121] The medical data processing method provided in this embodiment, before storing the processing time, processing personnel and processing content on the blockchain, further includes: generating a data fingerprint through a hash algorithm, and the data fingerprint is used to verify whether the processing time, processing personnel and processing content stored on the blockchain have been tampered with. This method can ensure the security of data and prevent data from being tampered with at will.

[0122] As an optional implementation manner, based on any of the above embodiments, it also includes:

[0123] In response to determining that the initial medical data information has a data mismatch, data error information is sent to the target medical information system.

[0124] Specifically, when data verification is performed based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, and cost information to determine whether the initial medical data information has a data mismatch, it also includes: when it is determined that the initial medical data information has a data mismatch, sending data error information to the target medical information system. Thus, the staff can perform error checking and correction according to the data error information in the target medical information system.

[0125] Among them, the initial medical data information mismatch includes but is not limited to data format errors, values ​​outside a reasonable range, logically inconsistent entries, or records inconsistent with other data sources.

[0126] The data error information includes but is not limited to the error type, unmatched data items, error cause and correction suggestions.

[0127] Optionally, the data error information is sent to the target medical information system via network request, message queue, email, etc.

[0128] The medical data processing method provided in this embodiment further includes: in response to determining that the initial medical data information has a data mismatch, sending data error information to the target medical information system. The method provided in this embodiment sends data error information immediately when the initial medical data information has a data mismatch, so that the staff can immediately perform error checking and correction according to the data error information to avoid the risk of medical data violation.

[0129] As an optional implementation, based on any of the above embodiments, before performing multi-dimensional data integration on the initial medical data information based on a preset data integration rule to obtain the target medical data information, the method further includes:

[0130] Perform data cleaning and standardization on initial medical data information.

[0131] Specifically, before the initial medical data information is integrated into multiple dimensions, the initial medical data information is first cleaned and standardized, thereby improving the accuracy and consistency of the data and ensuring the efficiency of subsequent data processing.

[0132] Among them, data cleaning includes but is not limited to: identifying and correcting obvious errors, such as spelling errors, format errors, missing values, etc.; removing invalid data, deleting data that is irrelevant to medical data or invalid data, and reducing data redundancy.

[0133] Optionally, a data cleaning tool or data cleaning technology is used to clean the initial medical data information. In this embodiment, there is no specific limitation on the data cleaning tool as long as the purpose of data cleaning can be achieved.

[0134] Among them, standardization processing includes but is not limited to: data format unification, unifying the format of initial medical data information into a format that is convenient for subsequent processing; data unit unification, converting units for data from different sources but representing the same physical quantity, such as blood pressure and blood sugar.

[0135] Optionally, a standardization processing tool or a standardization processing technology is used to perform data standardization processing on the initial medical data information. In this embodiment, there is no specific limitation on the standardization processing tool, as long as the purpose of data standardization processing can be achieved.

[0136] The medical data processing method provided in this embodiment, before performing multi-dimensional data integration on the initial medical data information based on the preset data integration rules to obtain the target medical data information, further includes: performing data cleaning and standardization processing on the initial medical data information. The method of this embodiment can improve the accuracy and consistency of the data through data cleaning and standardization processing, and ensure the efficiency of subsequent data processing.

[0137] As an optional implementation, based on any of the above embodiments, before storing the target medical data information in multiple nodes of the distributed database, it also includes:

[0138] Based on the patient identity information, a query is performed in the distributed database to determine whether there is historical medical data information matching the patient identity information in the distributed database;

[0139] In response to determining that historical medical data information exists in the distributed data, the target medical data information is integrated with the historical medical data information.

[0140] Specifically, before storing the target medical data information in multiple nodes of the distributed database, first, a query is performed in the distributed database based on the patient's identity information to determine whether there is historical medical data information matching the patient; when it is determined that there is historical medical data information in the distributed database, the current target medical data information is integrated with the historical medical data information. Thus, the integrity and continuity of the patient's medical data can be guaranteed.

[0141] The patient identity information may be name, gender, date of birth, ID number, medical record number, etc. Optionally, a query is performed in a distributed database based on one or more combinations of the above patient identity information.

[0142] Optionally, when integrating the target medical data information with the historical medical data information, the integration process may include steps such as data merging, deduplication, conversion, and standardization.

[0143] Optionally, when there is no historical medical data information in the distributed database, it indicates that the patient's medical data is stored in the distributed database for the first time, and the target medical data information can be directly stored in multiple nodes of the distributed database.

[0144] The medical data processing method provided in this embodiment, before storing the target medical data information in multiple nodes of the distributed database, further includes: querying in the distributed database based on the patient identity information to determine whether there is historical medical data information matching the patient identity information in the distributed database; in response to determining that there is historical medical data information in the distributed data, integrating the target medical data information with the historical medical data information. The method of this embodiment, when there is historical medical data information of the patient in the distributed data, integrates the target medical data information with the historical medical data information, thereby forming complete and continuous data information of the same patient, providing more comprehensive and accurate data support for subsequent medical analysis, decision-making and research.

[0145] Figure 3A flowchart of a complete medical data processing method provided by another embodiment of the present application is as follows: Figure 3 As shown, the execution subject of this embodiment is a medical data processing device. The medical data processing method provided by this embodiment includes the following steps:

[0146] Step 301: Acquire updated medical data information in the target medical information system.

[0147] Step 302: split the medical data information according to diagnosis information, treatment records, examination and testing information, drug information, and cost information to obtain first segmented medical data information.

[0148] Step 303: split the first segmented medical data information according to the patient identity information to obtain second segmented medical data information.

[0149] Step 304: split the second segmented medical data information according to the timestamp information to obtain initial medical data information.

[0150] Step 305: Verify whether there is any data mismatch in the initial medical data information.

[0151] Specifically, data verification is performed based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, and cost information.

[0152] Step 306: In response to determining that the initial medical data information has a data mismatch, data error information is sent to the target medical information system.

[0153] Step 307: In response to the fact that there is no data mismatch in the initial medical data information, the initial medical data information is cleansed and standardized.

[0154] Step 308: Integrate the patient's diagnosis information, treatment records, examination and testing information, drug information, and cost information in chronological order based on the patient's identity information and timestamp information to obtain target medical data information.

[0155] Step 309: Query the distributed database to determine whether there is historical medical data information that matches the patient's identity information.

[0156] Specifically, a query is performed in a distributed database based on the patient identity information.

[0157] Step 310: In response to determining that historical medical data information exists in the distributed data, the target medical data information is integrated with the historical medical data information.

[0158] Step 311: In response to determining that no historical medical data information exists in the distributed data, the target medical data information is stored in multiple nodes of the distributed database.

[0159] Step 312: In response to a change in the target medical data information in the distributed database, the processing time, processing personnel, and processing content of the target medical data information are obtained.

[0160] Step 313: Generate a data fingerprint through a hash algorithm.

[0161] Step 314: Store the processing time, processing personnel, and processing content on the blockchain.

[0162] Figure 4 A schematic diagram of the structure of a medical data processing device provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the medical data processing device provided in this embodiment is located in an electronic device. The medical data processing device 40 provided in this embodiment includes: an acquisition module 41 , a separation module 42 , a verification module 43 , an integration module 44 and a storage module 45 .

[0163] Among them, the acquisition module 41 is used to obtain the updated medical data information in the target medical information system in response to determining that there is an update of medical data information in the target medical information system; the splitting module 42 is used to perform fine-grained splitting of the medical data information based on the preset splitting rules to obtain the initial medical data information, wherein the preset splitting rules are rules for splitting based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information and timestamp information; the verification module 43 is used to perform data verification based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information and cost information to determine whether there is a data mismatch in the initial medical data information; the integration module 44 is used to perform multi-dimensional data integration on the initial medical data information based on the preset data integration rules in response to the absence of data mismatch in the initial medical data information to obtain the target medical data information; the storage module 45 is used to store the target medical data information in multiple nodes of the distributed database; the storage module 45 is also used to obtain the processing information of the target medical data information in response to changes in the target medical data information in the distributed database, and store the processing information on the blockchain.

[0164] Optionally, the splitting module 42, when performing fine-grained splitting of medical data information based on preset splitting rules to obtain initial medical data information, is specifically used to: split the medical data information according to diagnosis information, treatment records, examination and testing information, drug information, and cost information to obtain first segmented medical data information; split the first segmented medical data information according to patient identity information to obtain second segmented medical data information; split the second segmented medical data information according to timestamp information to obtain initial medical data information.

[0165] Optionally, the integration module 44, when performing multi-dimensional data integration on the initial medical data information based on preset data integration rules to obtain target medical data information, is specifically used to: integrate the patient's diagnosis information, treatment records, examination and testing information, drug information and cost information in chronological order based on the patient's identity information and timestamp information to obtain the target medical data information.

[0166] Optionally, the storage module 45, when obtaining the processing information of the target medical data information and storing the processing information on the blockchain, is specifically used to: obtain the processing time, processing personnel and processing content of the target medical data information; and store the processing time, processing personnel and processing content on the blockchain.

[0167] Optionally, before storing the processing time, processing personnel and processing content on the blockchain, the storage module 45 is also used to: generate a data fingerprint through a hash algorithm, and the data fingerprint is used to verify whether the processing time, processing personnel and processing content stored on the blockchain have been tampered with.

[0168] Optionally, the verification module 43 is further configured to send data error information to the target medical information system in response to determining that there is a data mismatch in the initial medical data information.

[0169] Specifically, the medical data processing device 40 provided in this embodiment further includes: a data preprocessing module and a query module.

[0170] Optionally, the data preprocessing module is used to perform data cleaning and standardization on the initial medical data information before performing multi-dimensional data integration on the initial medical data information based on preset data integration rules to obtain target medical data information.

[0171] Optionally, before storing the target medical data information in multiple nodes of the distributed database, the query module is specifically used to: query the distributed database based on the patient identity information to determine whether there is historical medical data information matching the patient identity information in the distributed database; in response to determining that there is historical medical data information in the distributed data, integrate the target medical data information with the historical medical data information.

[0172] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the electronic device 50 provided in this embodiment includes: a processor 51 and a memory 52 communicatively connected to the processor.

[0173] The memory 52 stores computer-executable instructions; the processor 51 executes the computer-executable instructions stored in the memory 52 to implement the medical data processing method provided by any one of the above-mentioned embodiments.

[0174] The program may include program codes, and the program codes include computer-executable instructions. The memory 52 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0175] In this embodiment, the memory 52 is connected to the processor 51 via a bus. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 The fact that only one straight line is used in the diagram does not mean that there is only one bus or only one type of bus.

[0176] An embodiment of the present application also provides a computer-readable storage medium, including computer-readable storage medium storing computer execution instructions, which are used to implement the medical data processing method provided in any one of the above embodiments when executed by a processor.

[0177] An embodiment of the present application also provides a computer program product, including a computer program, which implements the medical data processing method provided in any one of the above embodiments when the computer program is executed by a processor.

[0178] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0179] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0180] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above-mentioned module-composed unit can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0181] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the methods of various embodiments of the present application.

[0182] It should be understood that the above processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0183] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0184] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0185] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0186] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0187] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0188] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A medical data processing method, characterized in that: include: In response to determining that there is medical data information update in the target medical information system, acquiring the updated medical data information in the target medical information system; Fine-grained splitting of the medical data information is performed based on a preset splitting rule to obtain initial medical data information, wherein the preset splitting rule is a splitting rule based on patient identity information, diagnosis information, treatment records, examination and testing information, drug information, cost information, and timestamp information; Performing data verification based on the patient identification information, the diagnosis information, the treatment record, the examination and testing information, the medication information, and the cost information to determine whether there is a data mismatch in the initial medical data information; In response to the initial medical data information not having a data mismatch, performing multi-dimensional data integration on the initial medical data information based on a preset data integration rule to obtain target medical data information; Storing the target medical data information in multiple nodes of a distributed database; In response to a change in the target medical data information in the distributed database, processing information of the target medical data information is obtained, and the processing information is stored on the blockchain.

2. The method according to claim 1, characterized in that The fine-grained splitting of the medical data information based on a preset splitting rule to obtain initial medical data information includes: Splitting the medical data information according to the diagnosis information, the treatment record, the examination and testing information, the drug information, and the cost information to obtain first segmented medical data information; Splitting the first subdivided medical data information according to the patient identity information to obtain second subdivided medical data information; The second subdivided medical data information is split according to the timestamp information to obtain the initial medical data information.

3. The method according to claim 2, characterized in that The performing multi-dimensional data integration on the initial medical data information based on the preset data integration rules to obtain target medical data information includes: Based on the patient identity information and the timestamp information, the patient's diagnosis information, treatment records, examination and testing information, drug information and cost information are integrated in chronological order to obtain target medical data information.

4. The method according to claim 1, characterized in that The obtaining processing information of the target medical data information and storing the processing information on the blockchain includes: Obtaining the processing time, processing personnel and processing content of the target medical data information; The processing time, the processing personnel and the processing content are stored on the blockchain.

5. The method according to claim 4, characterized in that Before storing the processing time, processing personnel and processing content on the blockchain, it also includes: A data fingerprint is generated by a hash algorithm, and the data fingerprint is used to verify whether the processing time, the processing personnel and the processing content stored on the blockchain have been tampered with.

6. The method according to any one of claims 1 to 5, characterized in that Also includes: In response to determining that the initial medical data information has a data mismatch, data error information is sent to the target medical information system.

7. The method according to any one of claims 1 to 5, characterized in that Before performing multi-dimensional data integration on the initial medical data information based on the preset data integration rules to obtain the target medical data information, the method further includes: The initial medical data information is cleaned and standardized.

8. The method according to any one of claims 1 to 5, characterized in that Before storing the target medical data information in multiple nodes of the distributed database, the method further includes: Performing a query in the distributed database based on the patient identity information to determine whether there is historical medical data information matching the patient identity information in the distributed database; In response to determining that the historical medical data information exists in the distributed data, the target medical data information is integrated with the historical medical data information.

9. A medical data processing device, characterized in that: include: an acquisition module, configured to acquire updated medical data information in the target medical information system in response to determining that there is updated medical data information in the target medical information system; A splitting module, used for performing fine-grained splitting of the medical data information based on a preset splitting rule to obtain initial medical data information, wherein the preset splitting rule is a splitting rule based on patient identity information, diagnosis information, treatment record, examination and testing information, drug information, cost information and timestamp information; A verification module, configured to perform data verification based on the patient identification information, the diagnosis information, the treatment record, the examination and testing information, the drug information, and the cost information to determine whether there is a data mismatch in the initial medical data information; an integration module, configured to perform multi-dimensional data integration on the initial medical data information based on a preset data integration rule in response to the initial medical data information not having a data mismatch, so as to obtain target medical data information; A storage module, used to store the target medical data information in multiple nodes of a distributed database; The storage module is also used to obtain processing information of the target medical data information in response to changes in the target medical data information in the distributed database, and store the processing information on the blockchain.

10. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

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