Medical record data processing method, device, electronic device and storage medium

Abstract

The present invention discloses a method, device, electronic device and storage medium for processing medical record data, and relates to the field of computer technology. A specific implementation of the method includes: determining the disease diagnosis group corresponding to the medical record data based on the target data in the medical record data; calling the quality control model corresponding to the disease diagnosis group to perform quality inspection on the target data, and determining that the quality inspection of the target data has passed based on the inspection result, and then generating a corresponding medical record structure according to the medical record data and the disease diagnosis group; receiving a query request sent by a disease diagnosis system, querying the corresponding medical record structure based on the medical record identifier in the query request and sending it; receiving the payment amount sent by the disease diagnosis system, and sending the payment amount and the corresponding medical record structure to the medical insurance system. This implementation can solve the problem that the quality of the medical record homepage is usually manually inspected by professionals, which is not only costly, but also takes a long time and is inefficient.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, electronic equipment and storage medium for processing medical record data. Background Art

[0002] Medical record data is the core data of medical insurance settlement and other businesses, and has a great impact on the results of business processing, especially the quality of the medical record homepage in the medical record data, which seriously affects the accuracy of the business processing results. Therefore, improving the quality of medical record data has become an important part of the medical insurance fund supervision process. At present, the quality of medical record data is usually controlled by manual inspection by professionals, but the manual inspection method is overly dependent on the professional level of the staff, which is not only costly, but also takes a long time and is inefficient. Summary of the invention

[0003] In view of this, the embodiments of the present invention provide a method, device, electronic device and storage medium for processing medical record data, which can solve the problem that manual inspection and control of medical record data quality is high in cost, takes a long time and has low efficiency.

[0004] Manual inspection by professionals is not only costly, but also time-consuming and inefficient.

[0005] To achieve the above objective, according to one aspect of an embodiment of the present invention, a method for processing medical record data is provided.

[0006] A method for processing medical record data in an embodiment of the present invention is used in a blockchain platform, including: receiving medical record data sent by a medical institution, and determining the disease diagnosis grouping corresponding to the medical record data based on target data in the medical record data; calling the quality control model corresponding to the disease diagnosis grouping to perform quality inspection on the target data, and determining whether the quality inspection of the target data has passed based on the inspection result, and then generating a corresponding medical record structure according to the medical record data and the disease diagnosis grouping; receiving a query request sent by a disease diagnosis system, and querying the corresponding medical record structure based on the medical record identifier in the query request and sending it, so that the disease diagnosis system calculates the payment amount corresponding to the medical record data based on the structure; receiving the payment amount sent by the disease diagnosis system, and sending the payment amount and the corresponding medical record structure to the medical insurance system, so that the medical insurance system performs settlement.

[0007] In one embodiment, before receiving the query request sent by the disease diagnosis system, it also includes: determining that the quality test of the target data fails based on the test results, and then sending a return message of the case data to the medical institution; judging whether the modification data corresponding to the case data is received within a preset effective time; if so, updating the case data based on the modification data, and generating a corresponding medical record structure based on the disease diagnosis grouping and the updated medical record data; if not, generating a corresponding medical record structure based on the test results, the disease diagnosis grouping and the updated medical record data.

[0008] In yet another embodiment, generating a corresponding medical record structure according to the medical record data and the disease diagnosis grouping includes:

[0009] Calculating the characteristic vector of the target data, calling a preset generation algorithm, and generating a data summary of the medical record data based on the characteristic vector;

[0010] Generate a group structure based on the digital summary, the disease diagnosis group and the pre-stored medical institution public key;

[0011] The medical record structure is generated based on the medical record identifier and the grouping structure.

[0012] In yet another embodiment, determining the disease diagnosis group corresponding to the medical record data based on the target data in the medical record data includes:

[0013] The preset grouping smart contract is called to query the grouping mapping relationship based on the target data, and then determine the disease diagnosis group corresponding to the medical record data.

[0014] In yet another embodiment, before determining the disease diagnosis group corresponding to the medical record data based on the target data in the medical record data, the method further includes:

[0015] Obtaining the disease code in the medical record data, and matching the disease code with a preset coding format to determine the coding format corresponding to the medical record data;

[0016] The verification smart contract corresponding to the encoding format is called to perform format verification on the medical record data.

[0017] In yet another embodiment, generating a corresponding medical record structure according to the medical record data and the disease diagnosis grouping includes:

[0018] A corresponding medical record structure is generated according to the coding format, the medical record data and the disease diagnosis grouping.

[0019] In yet another embodiment, further comprising:

[0020] receiving an accurate grouping result sent by the disease diagnosis system, wherein the accurate grouping result is determined by the disease diagnosis system based on the medical record structure;

[0021] A preset scoring smart contract is called to calculate the scoring level of the medical record data based on the medical record data, the disease diagnosis grouping of the medical record data, the payment amount and the precise grouping result.

[0022] To achieve the above objective, according to another aspect of an embodiment of the present invention, a device for processing medical record data is provided.

[0023] A medical record data processing device according to an embodiment of the present invention is arranged on a blockchain platform, and includes: a determination unit, used to receive medical record data sent by a medical institution, and determine the disease diagnosis group corresponding to the medical record data based on target data in the medical record data; a generation unit, used to call the quality control model corresponding to the disease diagnosis group to perform quality inspection on the target data, and determine whether the quality inspection of the target data has passed based on the inspection result, and then generate a corresponding medical record structure according to the medical record data and the disease diagnosis group; a query unit, used to receive a query request sent by a disease diagnosis system, and query the corresponding medical record structure based on the medical record identifier in the query request and send it, so that the disease diagnosis system calculates the payment amount corresponding to the medical record data based on the structure; a sending unit, used to receive the payment amount sent by the disease diagnosis system, and send the payment amount and the corresponding medical record structure to the medical insurance system, so that the medical insurance system performs settlement.

[0024] In one embodiment, the generating unit is further used for:

[0025] Based on the test results, it is determined that the quality test of the target data fails, and then a return message of the case data is sent to the medical institution; it is determined whether the modification data corresponding to the case data is received within a preset effective time; if so, the case data is updated based on the modification data, and a corresponding medical record structure is generated based on the disease diagnosis group and the updated medical record data; if not, a corresponding medical record structure is generated based on the test results, the disease diagnosis group and the updated medical record data.

[0026] In yet another embodiment, the generating unit is specifically configured to:

[0027] Calculating the characteristic vector of the target data, calling a preset generation algorithm, and generating a data summary of the medical record data based on the characteristic vector;

[0028] Generate a group structure based on the digital summary, the disease diagnosis group and the pre-stored medical institution public key;

[0029] The medical record structure is generated based on the medical record identifier and the grouping structure.

[0030] In yet another embodiment, the determining unit is further configured to:

[0031] The preset grouping smart contract is called to query the grouping mapping relationship based on the target data, and then determine the disease diagnosis group corresponding to the medical record data.

[0032] In yet another embodiment, the determining unit is further used to obtain the disease code in the medical record data, and match the disease code with a preset coding format to determine the coding format corresponding to the medical record data;

[0033] The device also includes:

[0034] A verification unit is used to call the verification smart contract corresponding to the encoding format to perform format verification on the medical record data.

[0035] In yet another embodiment, the generating unit is further configured to:

[0036] A corresponding medical record structure is generated according to the coding format, the medical record data and the disease diagnosis grouping.

[0037] In yet another embodiment, the apparatus further comprises:

[0038] A receiving unit, configured to receive an accurate grouping result sent by the disease diagnosis system, wherein the accurate grouping result is determined by the disease diagnosis system based on the medical record structure;

[0039] The scoring unit is used to call a preset scoring smart contract to calculate the scoring level of the medical record data based on the medical record data, the disease diagnosis grouping of the medical record data, the payment amount and the precise grouping result.

[0040] To achieve the above objective, according to another aspect of an embodiment of the present invention, an electronic device is provided.

[0041] An electronic device according to an embodiment of the present invention comprises: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for processing medical record data provided by the embodiment of the present invention.

[0042] To achieve the above objective, according to another aspect of an embodiment of the present invention, a computer readable medium is provided.

[0043] A computer-readable medium according to an embodiment of the present invention stores a computer program, which, when executed by a processor, implements the method for processing medical record data provided by the embodiment of the present invention.

[0044] One embodiment of the above invention has the following advantages or beneficial effects: In the embodiment of the present invention, after the blockchain platform receives the medical record data sent by the medical institution, it can determine the corresponding disease diagnosis grouping based on the target data in the medical record data, and perform quality inspection on the target data based on the quality control model corresponding to the disease diagnosis grouping. Since the target data is the main data in the medical record data, the quality of the medical record data can be determined by quality inspection of the target data; after determining that the quality inspection of the target data passes, a corresponding medical record structure is generated according to the medical record data and the disease diagnosis grouping, so that when the disease diagnosis system queries, the structure can be sent to the disease diagnosis system to calculate the payment amount, and then the payment amount is sent to the medical insurance system for results. In the embodiment of the present invention, the disease diagnosis grouping corresponding to the medical record data can be determined based on the target data, and then the quality of the target data can be inspected by the quality control model corresponding to the disease diagnosis grouping. In this way, not only can the automatic grouping of the medical record data be realized, but also the quality of the medical record data can be improved, so as to avoid manual operation to control the quality of the medical record data and improve the processing efficiency of the medical record data.

[0045] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0047] Figure 1 is a schematic diagram of a main process of a method for processing medical record data according to an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of another main process of the method for processing medical record data according to an embodiment of the present invention;

[0049] Figure 3 is a schematic diagram of main units of a device for processing medical record data according to an embodiment of the present invention;

[0050] Figure 4 is another exemplary system architecture diagram to which the embodiments of the present invention can be applied;

[0051] Figure 5 It is a schematic diagram of the structure of a computer system suitable for implementing the embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0053] It should be pointed out that the embodiments of the present invention and the features in the embodiments may be combined with each other if there is no conflict.

[0054] An embodiment of the present invention provides a medical record data processing system, which can be used in scenarios where medical record data is grouped and medical insurance is settled. The medical record data processing system may include a medical institution, a disease diagnosis system (DRG system), a medical insurance system, and a blockchain platform. Medical institutions, disease diagnosis systems, and medical insurance systems can establish connections based on the blockchain platform to enable the circulation of medical record data among medical institutions, disease diagnosis systems, and medical insurance systems. The blockchain platform may specifically be an alliance chain platform. In an embodiment of the present invention, an alliance chain network is established between multiple participants such as medical institutions, disease diagnosis systems, and medical insurance systems, and the alliance chain identity can be established and accessed for each participant on the alliance chain platform. Each participant can calculate a unique identifier based on a preset number as an identity identifier. Specifically, the unique identifier (ID) can be calculated based on the formula ID = SHA256 (SHA256 (s) + T)), where SHA256 is a hash algorithm, s can be the participant number, T is a high-intensity salt value, and T can use a unified constant value as an important means of identity obfuscation and encryption. The calculation result is a 32-bit hexadecimal string, which is used as the unique ID value of the participant and an important credential and identity authentication for data processing on the alliance chain platform. The ID of the medical institution can also be the Key key of the state variable Key-Value uploaded to the alliance chain platform. The Value value of the state variable Key-Value can be structured data J such as the basic information, personnel composition, and department specialty of the medical institution, thereby forming a (ID, J) key-value pair, which can be saved in the basic information column of the alliance chain platform. At the same time, the alliance chain platform can also generate corresponding public and private keys for each participant to ensure that the identity information is not maliciously attacked and tracked when the data is uploaded and unloaded.

[0055] The embodiment of the present invention provides a method for processing medical record data, which can be executed by a blockchain platform, such as Figure 1 As shown, the method includes:

[0056] S101: Receive medical record data sent by a medical institution, and determine the disease diagnosis group corresponding to the medical record data based on target data in the medical record data.

[0057] Among them, the target data can specifically be the data on the first page of the medical record.

[0058] Medical institutions can generate medical record data based on medical records and other data, and can generate medical record homepage data in the medical record data based on a preset parameter format when generating medical record data, and then upload the medical record data to the blockchain platform. When medical institutions upload medical record data to the blockchain, they can generate a digital signature corresponding to the medical record data based on a preset private key, and then upload it to the blockchain platform. The blockchain platform can verify the uploaded data based on the pre-stored public key of the medical institution, thereby preventing data tampering and ensuring data security.

[0059] After receiving the medical record data, the blockchain platform can obtain the target data in the medical record data, such as the data on the medical record homepage, and then determine the disease diagnosis group corresponding to the medical record data based on the target data. Specifically, the blockchain platform can preset the group mapping relationship between each target parameter and the disease diagnosis group, that is, different target data corresponds to different disease diagnosis groups, and then in this step, by calling the preset grouping smart contract, the group mapping relationship can be queried based on the target data, and then the disease diagnosis group corresponding to the medical record data can be determined.

[0060] It should be noted that the disease diagnosis grouping determined in this step can be a preliminary grouping of medical record data. The grouping contract can be pre-set in the blockchain platform to determine the disease diagnosis grouping corresponding to the medical record data by calling the grouping contract. The grouping contract can be a smart contract established on the blockchain platform. Specifically, the grouping logic can be implemented through the Turing-complete solidity language and deployed to the blockchain network. The execution and calling can use permission authentication and other methods to ensure data security.

[0061] In an embodiment of the present invention, the data format of the medical record data can be verified before grouping the medical record data to ensure that the data format of the medical record data is correct, so as to improve the accuracy of the grouping. Since different medical institutions may use different coding formats to generate medical record data, and different coding formats have different verification methods, the embodiment of the present invention can preset verification smart contracts corresponding to each coding format to perform data format verification based on the verification smart contract corresponding to the medical record data. Specifically, the verification process can be performed as follows: obtaining the disease code in the medical record data, matching the disease code with the preset coding format to determine the coding format corresponding to the medical record data; calling the verification smart contract corresponding to the coding format to perform format verification on the medical record data.

[0062] Medical institutions can send RPC requests according to the preset interface call method to upload medical record data to the blockchain platform, and then the blockchain platform can call the preset code matching smart contract to obtain the disease code in the medical record data, and then match the disease code with the preset coding format to obtain the coding format corresponding to the medical record data. The coding format can specifically include: International Classification of Diseases ICD9, ICD10, or custom standard codes, etc., where the custom standard code can be a labeled disease code and knowledge base constructed in combination with the International Classification of Diseases ICD code, national policies, local medical insurance catalogs, etc.

[0063] S102: Call the quality control model corresponding to the disease diagnosis group to perform quality inspection on the target data, determine whether the quality inspection of the target data has passed based on the inspection result, and then generate a corresponding medical record structure according to the medical record data and the disease diagnosis group.

[0064] Among them, the quality control model is pre-set. In order to ensure the accuracy of quality detection, in the embodiment of the present invention, the corresponding quality control model can be set based on each disease diagnosis group. In this step, by calling the quality control model corresponding to the disease diagnosis group, the target data can be quality tested to obtain the test results. Specifically, the quality test can detect whether the target data stores grouping errors, the difference between the group payment amount and the actual amount is too large, and the high-code and low-set grouping. If these problems occur, it means that there are problems with the quality of the target data, and the quality test of the target data fails, and then it can be determined that there are quality problems with the medical record data. At this time, the medical record data can be returned to the medical institution so that the medical institution can update the medical record data; if these problems do not occur, it means that the quality of the target data has not been detected. The quality test of the target data passes, and then it can be determined that the medical record data passes the test. At this time, the blockchain platform can store the medical record data with relevant parameters of the medical record data, such as the disease diagnosis group corresponding to the medical record data.

[0065] When the blockchain platform determines that the target data fails the quality inspection based on the test results and returns the medical record data to the medical institution, it can send a return message of the case data to the medical institution and set the effective time for the medical institution to update the medical record data at the same time, so that the medical institution can update the medical record data within the effective period. After sending the return message, the blockchain platform can record the timestamp to determine whether the modification data corresponding to the case data is received within the preset effective time after the effective time has passed; if so, the case data is updated based on the modification data, and the corresponding medical record structure is generated based on the disease diagnosis group and the updated medical record data; if not, it means that the medical institution has failed to update the medical record data, and the corresponding medical record structure can be generated based on the test results, disease diagnosis group and the medical record data received in step S101.

[0066] It should be noted that the blockchain platform can use structures to store medical record data and related parameters of the medical record data to facilitate subsequent processing of the medical record data.

[0067] The specific structure of the medical record structure can be preset, for example, it can include {"coding version": string, "disease diagnosis group": struct, "precise group": struct, "medical record rating": string, "medical record DID": string, "payment amount": float, "others": string[]}. Specifically, the medical record DID can be calculated based on the formula: SHA256 (SHA256 (medical insurance treatment serial number in medical record data + salt value)), and the coding version, precise group, medical record rating, payment amount, and others all represent the relevant parameters corresponding to the medical record data, which can be stored in the medical record structure after the corresponding results are obtained in the subsequent processing of the shelter data.

[0068] In an embodiment of the present invention, the disease diagnosis group and medical record data can first be grouped into a group structure, and then the group structure and other parameters of the above medical record data can be combined to generate a medical record structure. The group structure can specifically include: {"digital summary": string, "digital signature": string, "public key of medical institution": string, "disease diagnosis group": string, "problem prediction": string[]}, wherein the problem prediction represents the problem found in the target data quality detection, the digital signature is the digital signature generated when the medical institution uploads the medical record data to the chain, and the digital summary can be generated based on the target data. For example, the method of generating a digital summary can be executed as follows: calculating the feature vector of the target data, calling a preset generation algorithm, and generating a data summary of the medical record data based on the feature vector. In an embodiment of the present invention, the feature vector of the target data can be calculated based on the formula SHA256(SHA512(cis_mod(medical record content))), where SHA256 and SHA512 represent hash algorithms, that is, preset generation algorithms, cis_mod is an algorithm for generating feature vectors, and the input parameter can be medical record content, such as target data. The output value is a string in JSON format: {"zhuyaozhenduan":string[],"ciyaozhenduan":string[],"jibing_code":string,"shoushu_code":string[],"zhifujine":float[],"moxingcanshu":int[]}, and finally the digital summary can be obtained as a 32-bit string.

[0069] In the embodiment of the present invention, a storage block may be preset for the medical record structure, and then stored in the form of a key-Value pair, wherein the key may be the medical record DID and the Value may be the medical record structure.

[0070] S103: receiving a query request sent by the disease diagnosis system, querying the corresponding medical record structure based on the medical record identifier in the query request and sending it, so that the disease diagnosis system calculates the payment amount corresponding to the medical record data based on the medical record structure.

[0071] Among them, the disease diagnosis (DRG) system can calculate the amount that needs to be paid by the medical insurance system based on the medical record data, so the disease diagnosis system sends a query request to the blockchain platform to query the medical record data that needs to be settled by the medical insurance system, that is, the medical record structure. Therefore, after the blockchain platform receives the query request sent by the disease diagnosis system, it can query the corresponding medical record structure based on the medical record identifier in the query request, and then send it to the disease diagnosis system, so that the disease diagnosis system can calculate the payment amount corresponding to the medical record data based on the medical record structure.

[0072] Since the disease diagnosis system needs to accurately group the medical record data before calculating the payment amount, the disease diagnosis system can determine the accurate grouping of the disease diagnosis to which the medical record data belongs, and then upload the accurate grouping and the payment amount to the blockchain platform. After receiving the accurate grouping and the payment amount, the blockchain platform can store them in the corresponding medical record structure. The accurate grouping can be a more specific grouping in the disease diagnosis grouping.

[0073] Specifically, the disease diagnosis system can process the medical record data based on a preset cycle, for example, it can be processed on a monthly basis. When sending a query request, the medical record DID of the medical record data that needs to be processed can be used to generate a medical record DID list to obtain the corresponding medical record data from the blockchain platform, and then perform relevant precise grouping and payment amount calculation.

[0074] S104: receiving the payment amount sent by the disease diagnosis system, and sending the payment amount and the corresponding medical record structure to the medical insurance system so that the medical insurance system can settle the account.

[0075] Among them, the disease diagnosis system can send the payment amount of the medical record data to the blockchain platform after calculating it. When the medical insurance system settles, the blockchain platform can send the medical record structure storing the payment amount to the medical insurance system so that the medical insurance system can settle the medical record data.

[0076] It should be noted that for controversial medical record data, such as medical record data that fails quality inspection, it can be handled using the special case single-discussion process preset based on the blockchain platform.

[0077] In an embodiment of the present invention, after obtaining the medical record structure of the medical record data, it can be scored based on the medical record structure to determine the level of its medical record quality control. Specifically, it can be implemented based on a smart contract, and can be executed as follows: calling a preset scoring smart contract to calculate the score level of the medical record data based on the medical record data, the disease diagnosis grouping of the medical record data, the payment amount, and the precise grouping result. After determining the score level of each medical record data, the medical institution's medical record quality control level can be judged and stored based on parameters such as the proportion of problem medical records in the medical record data corresponding to the medical institution, so as to achieve control over the quality of the medical records of the medical institution.

[0078] In an embodiment of the present invention, the disease diagnosis grouping corresponding to the medical record data can be determined based on the target data, and then the quality of the target data can be checked using the quality control model corresponding to the disease diagnosis grouping. This not only realizes the automatic grouping of the medical record data, but also can improve the quality of the medical record data, avoids manual operation to control the quality of the medical record data, and improves the processing efficiency of the medical record data.

[0079] Combine the following Figure 1 The embodiment shown in the figure specifically describes the method for processing medical record data in the embodiment of the present invention. Figure 2 As shown, the method includes:

[0080] S201: Medical institutions upload medical record data to the chain.

[0081] S202: The blockchain platform calls a preset grouping smart contract to query the grouping mapping relationship based on the target data, and then determines the disease diagnosis group corresponding to the medical record data.

[0082] S203: The blockchain platform calls the quality control model corresponding to the disease diagnosis group to perform quality inspection on the target data and obtain the inspection results.

[0083] S204: The blockchain platform determines whether the target data has passed the quality inspection based on the inspection results, and then calculates the characteristic vector of the target data, calls the preset generation algorithm, and generates a data summary of the medical record data based on the characteristic vector; generates a grouping structure based on the digital summary, disease diagnosis grouping and pre-stored medical institution public key; and generates a medical record structure based on the medical record identifier and the grouping structure.

[0084] In the embodiment of the present invention, the quality detection of target data is taken as an example for description.

[0085] S205: The disease diagnosis system sends a query request.

[0086] S206: The blockchain platform queries the corresponding medical record structure based on the medical record identifier in the query request and sends it.

[0087] S207: The disease diagnosis system calculates the payment amount and accurate grouping corresponding to the medical record data based on the medical record structure and sends it.

[0088] S208: The blockchain platform stores the payment amount and precise grouping into the corresponding medical record structure.

[0089] S209: Query request sent by the medical insurance system.

[0090] S210: The blockchain platform queries the corresponding medical record structure based on the medical record identifier in the query request and sends it.

[0091] S211: The medical insurance system settles accounts based on the medical record structure.

[0092] It should be noted that the data processing principle of each step in the embodiment of the present invention is the same as Figure 1 The corresponding data processing principles in the illustrated embodiments are the same and will not be described in detail here.

[0093] In an embodiment of the present invention, the disease diagnosis grouping corresponding to the medical record data can be determined based on the target data, and then the quality of the target data can be checked using the quality control model corresponding to the disease diagnosis grouping. This not only realizes the automatic grouping of the medical record data, but also can improve the quality of the medical record data, avoids manual operation to control the quality of the medical record data, and improves the processing efficiency of the medical record data.

[0094] In order to solve the problems existing in the prior art, the embodiment of the present invention provides a device 300 for processing medical record data, such as Figure 3 As shown, the device 300 includes:

[0095] The determination unit 301 is used to receive medical record data sent by a medical institution, and determine the disease diagnosis group corresponding to the medical record data based on the target data in the medical record data;

[0096] A generating unit 302 is used to call the quality control model corresponding to the disease diagnosis group to perform quality detection on the target data, determine whether the quality detection of the target data passes based on the detection result, and then generate a corresponding medical record structure according to the medical record data and the disease diagnosis group;

[0097] The query unit 303 is used to receive a query request sent by the disease diagnosis system, query the corresponding medical record structure based on the medical record identifier in the query request, and send it, so that the disease diagnosis system calculates the payment amount corresponding to the medical record data based on the structure;

[0098] The sending unit 304 is used to receive the payment amount sent by the disease diagnosis system, and send the payment amount and the corresponding medical record structure to the medical insurance system so that the medical insurance system can settle the bill.

[0099] It should be understood that the manner of implementing the embodiments of the present invention is different from the Figure 1 The method of the illustrated embodiment is the same and will not be repeated here.

[0100] In an implementation of the embodiment of the present invention, the generating unit 302 is further configured to:

[0101] Based on the test results, it is determined that the quality test of the target data fails, and then a return message of the case data is sent to the medical institution; it is determined whether the modification data corresponding to the case data is received within a preset effective time; if so, the case data is updated based on the modification data, and a corresponding medical record structure is generated based on the disease diagnosis group and the updated medical record data; if not, a corresponding medical record structure is generated based on the test results, the disease diagnosis group and the updated medical record data.

[0102] In another implementation of the embodiment of the present invention, the generating unit 302 is specifically configured to:

[0103] Calculating the characteristic vector of the target data, calling a preset generation algorithm, and generating a data summary of the medical record data based on the characteristic vector;

[0104] Generate a group structure based on the digital summary, the disease diagnosis group and the pre-stored medical institution public key;

[0105] The medical record structure is generated based on the medical record identifier and the grouping structure.

[0106] In another implementation of the embodiment of the present invention, the determining unit 301 is further configured to:

[0107] The preset grouping smart contract is called to query the grouping mapping relationship based on the target data, and then determine the disease diagnosis group corresponding to the medical record data.

[0108] In another implementation of the embodiment of the present invention, the determining unit 301 is further used to obtain the disease code in the medical record data, and match the disease code with a preset coding format to determine the coding format corresponding to the medical record data;

[0109] The device 300 further includes:

[0110] A verification unit is used to call the verification smart contract corresponding to the encoding format to perform format verification on the medical record data.

[0111] In another implementation of the embodiment of the present invention, the generating unit 302 is further configured to:

[0112] A corresponding medical record structure is generated according to the coding format, the medical record data and the disease diagnosis grouping.

[0113] In another implementation of the embodiment of the present invention, the device 300 further includes:

[0114] A receiving unit, configured to receive an accurate grouping result sent by the disease diagnosis system, wherein the accurate grouping result is determined by the disease diagnosis system based on the medical record structure;

[0115] The scoring unit is used to call a preset scoring smart contract to calculate the scoring level of the medical record data based on the medical record data, the disease diagnosis grouping of the medical record data, the payment amount and the precise grouping result.

[0116] It should be understood that the manner of implementing the embodiments of the present invention is different from the Figure 1 or Figure 2 The method of the illustrated embodiment is the same and will not be repeated here.

[0117] In an embodiment of the present invention, the disease diagnosis grouping corresponding to the medical record data can be determined based on the target data, and then the quality of the target data can be checked using the quality control model corresponding to the disease diagnosis grouping. This not only realizes the automatic grouping of the medical record data, but also can improve the quality of the medical record data, avoids manual operation to control the quality of the medical record data, and improves the processing efficiency of the medical record data.

[0118] According to an embodiment of the present invention, the embodiment of the present invention further provides an electronic device and a readable storage medium.

[0119] The electronic device of an embodiment of the present invention includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the data comparison method provided by the embodiment of the present invention.

[0120] Figure 4 An exemplary system architecture 400 is shown to which the method for processing medical record data or the apparatus for processing medical record data according to the embodiment of the present invention can be applied.

[0121] like Figure 4 As shown, system architecture 400 may include terminal devices 401, 402, 403, network 404 and server 405. Network 404 is used to provide a medium for communication links between terminal devices 401, 402, 403 and server 405. Network 404 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0122] The user can use the terminal devices 401, 402, 403 to interact with the server 405 through the network 404 to receive or send messages, etc. Various client applications can be installed on the terminal devices 401, 402, 403.

[0123] The terminal devices 401 , 402 , 403 may be, but are not limited to, smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0124] The server 405 may be a server that provides various services. The server may analyze and process the received medical record data and the like, and feed back the processing results (such as the medical record structure - just an example) to the terminal device.

[0125] It should be noted that the data comparison method provided in the embodiment of the present invention is generally executed by the server 405 , and accordingly, the data comparison device is generally set in the server 405 .

[0126] It should be understood that Figure 4 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0127] Reference below Figure 5 , which shows a schematic diagram of the structure of a computer system 500 suitable for implementing an embodiment of the present invention. Figure 5 The computer system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0128] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the system 500 are also stored. The CPU 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0129] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage section 508 as needed.

[0130] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-mentioned functions defined in the system of the present invention are executed.

[0131] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0132] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a unit, a program segment, or a part of a code, and the above-mentioned unit, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0133] The units involved in the embodiments of the present invention may be implemented by software or hardware. The units described may also be arranged in a processor, for example, it may be described as: a processor includes a receiving unit, a determining unit, an acquiring unit, and a comparing unit. The names of these units do not constitute a limitation on the units themselves in some cases, for example, the receiving unit may also be described as a "unit of the function of the receiving unit".

[0134] As another aspect, the present invention further provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device executes the method for processing medical record data provided by the present invention.

[0135] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for processing medical record data, characterized in that: For blockchain platforms, including: Receiving medical record data sent by a medical institution, and determining a disease diagnosis group corresponding to the medical record data based on target data in the medical record data; Calling the quality control model corresponding to the disease diagnosis group to perform quality inspection on the target data, determining that the quality inspection of the target data has passed based on the inspection result, and then generating a corresponding medical record structure according to the medical record data and the disease diagnosis group; Receiving a query request sent by a disease diagnosis system, querying a corresponding medical record structure based on a medical record identifier in the query request and sending the query request, so that the disease diagnosis system calculates a payment amount corresponding to the medical record data based on the medical record structure; receiving the payment amount sent by the disease diagnosis system, and sending the payment amount and the corresponding medical record structure to the medical insurance system so that the medical insurance system can settle the account; Generate a corresponding medical record structure according to the medical record data and disease diagnosis grouping, including: Calculating the characteristic vector of the target data, calling a preset generation algorithm, and generating a digital summary of the medical record data based on the characteristic vector; Generate a group structure based on the digital summary, the disease diagnosis group and the pre-stored medical institution public key; The medical record structure is generated based on the medical record identifier and the grouping structure.

2. The method according to claim 1, characterized in that Before receiving the query request sent by the disease diagnosis system, the method further includes: Determining based on the detection result that the target data fails the quality detection, and then sending a return message of the medical record data to the medical institution; Determine whether the modified data corresponding to the medical record data is received within a preset effective time; If so, the medical record data is updated based on the modified data, and a corresponding medical record structure is generated based on the disease diagnosis group and the updated medical record data; if not, a corresponding medical record structure is generated based on the test results, disease diagnosis group and the medical record data.

3. The method according to claim 1, characterized in that Determining the disease diagnosis group corresponding to the medical record data based on the target data in the medical record data includes: The preset grouping smart contract is called to query the grouping mapping relationship based on the target data, and then determine the disease diagnosis group corresponding to the medical record data.

4. The method according to claim 1, characterized in that Before determining the disease diagnosis group corresponding to the medical record data based on the target data in the medical record data, the method further includes: Obtaining the disease code in the medical record data, and matching the disease code with a preset coding format to determine the coding format corresponding to the medical record data; The verification smart contract corresponding to the encoding format is called to perform format verification on the medical record data.

5. The method according to claim 4, characterized in that Generate a corresponding medical record structure according to the medical record data and disease diagnosis grouping, including: A corresponding medical record structure is generated according to the coding format, the medical record data and the disease diagnosis grouping.

6. The method according to claim 1, characterized in that Also includes: receiving an accurate grouping result sent by the disease diagnosis system, wherein the accurate grouping result is determined by the disease diagnosis system based on the medical record structure; A preset scoring smart contract is called to calculate the scoring level of the medical record data based on the medical record data, the disease diagnosis grouping of the medical record data, the payment amount and the precise grouping result.

7. A device for processing medical record data, characterized in that: Set up on the blockchain platform, including: A determination unit, configured to receive medical record data sent by a medical institution, and determine a disease diagnosis group corresponding to the medical record data based on target data in the medical record data; A generating unit, configured to call a quality control model corresponding to the disease diagnosis grouping to perform a quality test on the target data, determine whether the quality test of the target data has passed based on the test result, and then generate a corresponding medical record structure according to the medical record data and the disease diagnosis grouping; A query unit, used to receive a query request sent by a disease diagnosis system, query a corresponding medical record structure based on the medical record identifier in the query request and send it, so that the disease diagnosis system calculates the payment amount corresponding to the medical record data based on the structure; A sending unit, used to receive the payment amount sent by the disease diagnosis system, and send the payment amount and the corresponding medical record structure to the medical insurance system so that the medical insurance system can settle the account; The generating unit is specifically used for: Calculating the characteristic vector of the target data, calling a preset generation algorithm, and generating a digital summary of the medical record data based on the characteristic vector; Generate a group structure based on the digital summary, the disease diagnosis group and the pre-stored medical institution public key; The medical record structure is generated based on the medical record identifier and the grouping structure.

8. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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