A DRG grouping method and device, electronic device and storage medium

Abstract

The present disclosure discloses a DRG grouping method and device, an electronic device and a storage medium, and relates to the field of data processing technology. The main technical scheme includes: first, obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance; secondly, performing field matching on the DRG data to be grouped according to the preset field file; secondly, when the field matching is successful, the DRG data to be grouped is measured according to a preset measurement algorithm, and an analysis report is generated. Compared with the related art, the embodiment of the present application improves data processing efficiency and accuracy by realizing the process of automating the processing of the DRG data to be grouped, and performs field matching through a pre-configured field file, which reduces the possibility of manual intervention and reduces the error rate.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a DRG grouping method and device, an electronic device and a storage medium. Background Art

[0002] In the existing technology, diagnosis-related group (DRG) is a method of classifying patients according to diagnosis, treatment and rehabilitation process. It is an important tool for outpatient cost management and control, and is widely used in medical insurance, hospital management and medical quality assessment. The application of DRG can help hospitals and insurance companies better manage and control outpatient expenses and promote the rational allocation and utilization of resources. At the same time, DRG can also be used for medical quality assessment and medical research to help understand the characteristics and treatment effects of different cases.

[0003] The current DRG grouping uses relatively simple grouping rules, which makes it difficult to correctly group special cases. In addition, the grouping process mainly relies on manual operations, which results in low grouping efficiency and makes it difficult to fully guarantee the accuracy of the grouping. Summary of the invention

[0004] The present disclosure provides a DRG grouping method, device, electronic device and storage medium.

[0005] According to a first aspect of the present disclosure, a DRG grouping method is provided, comprising:

[0006] Obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance;

[0007] Performing field matching on the DRG data to be grouped according to the preset field file;

[0008] When the field matching is successful, the DRG data to be grouped is calculated according to a preset calculation algorithm, and an analysis report is generated.

[0009] Optionally, after performing field matching on the DRG data to be grouped according to the preset field file, the method further includes:

[0010] The field matching results are displayed in a preset display area; wherein the display content includes the matching results and the field matching content.

[0011] Optionally, after performing field matching on the DRG data to be grouped according to the preset field file, the method further includes:

[0012] In the event of a field match failure, the reason for the failure will be displayed in the preset display area to prompt the completion of the DRG data.

[0013] Optionally, when the field matching is successful, the DRG data to be grouped is calculated according to a preset calculation algorithm, and before generating an analysis report, the method further includes:

[0014] Determine the region and version information corresponding to the DRG data to be grouped;

[0015] The preset calculation algorithm is determined according to the region and version information of the DRG data to be grouped.

[0016] Optionally, after determining a preset calculation algorithm according to the region and version information of the DRG data to be grouped, the method further includes:

[0017] Obtaining a preset key and determining whether the preset key is correct;

[0018] When the preset secret key is correct, the DRG data to be grouped is calculated according to the preset calculation algorithm.

[0019] According to a second aspect of the present disclosure, a DRG grouping device is provided, including:

[0020] A first acquisition unit is used to acquire the DRG data to be grouped and a preset field file; wherein the preset field file is configured in advance;

[0021] A field matching unit, used for performing field matching on the DRG data to be grouped according to the preset field file;

[0022] The calculation unit is used to calculate the DRG data to be grouped according to a preset calculation algorithm and generate an analysis report when the field matching is successful.

[0023] Optionally, the device further comprises:

[0024] A display unit is used to display the field matching results in a preset display area after the field matching unit performs field matching on the DRG data to be grouped according to the preset field file; wherein the display content includes the matching results and the field matching content.

[0025] Optionally, the device further comprises:

[0026] The display unit is also used to display the reason for failure in the preset display area after the field matching unit performs field matching on the DRG data to be grouped according to the preset field file, in case of field matching failure, to prompt the completion of the DRG data.

[0027] Optionally, the device further comprises:

[0028] A determination unit, used to calculate the DRG data to be grouped according to a preset calculation algorithm when the calculation unit field matches successfully, and determine the region and version information corresponding to the DRG data to be grouped before generating an analysis report;

[0029] The determination unit is also used to determine a preset calculation algorithm according to the region and version information of the DRG data to be grouped.

[0030] Optionally, the device further comprises:

[0031] A second obtaining unit is used to obtain a preset key after the determining unit determines the preset calculation algorithm according to the region and version information of the DRG data to be grouped, and determine whether the preset key is correct;

[0032] The calculation unit is also used to calculate the DRG data to be grouped according to the preset calculation algorithm when the preset key is correct.

[0033] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0034] at least one processor; and

[0035] a memory communicatively connected to the at least one processor; wherein,

[0036] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0037] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0038] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0039] The present disclosure provides a DRG grouping method, device, electronic device and storage medium, and the main technical scheme includes: first, obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance; second, performing field matching on the DRG data to be grouped according to the preset field file; second, when the field matching is successful, the DRG data to be grouped is measured according to the preset measurement algorithm, and an analysis report is generated. Compared with the related art, the embodiment of the present application improves data processing efficiency and accuracy by realizing the process of automating the processing of the DRG data to be grouped, and performs field matching through pre-configured field files, which reduces the possibility of manual intervention and reduces the error rate.

[0040] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0042] Figure 1 A flowchart of a DRG grouping method provided by an embodiment of the present disclosure;

[0043] Figure 2 A schematic diagram of another process of DRG grouping provided by an embodiment of the present disclosure;

[0044] Figure 3 A flowchart of a DRG grouping method provided by an embodiment of the present disclosure;

[0045] Figure 4 A structural diagram of a DRG grouping device provided in an embodiment of the present disclosure;

[0046] Figure 5 A structural diagram of a DRG grouping device provided in an embodiment of the present disclosure;

[0047] Figure 6 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0048] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure 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 disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0049] A DRG grouping method, device, electronic device, and storage medium according to an embodiment of the present disclosure will be described below with reference to the accompanying drawings.

[0050] Figure 1 A flowchart of a DRG grouping method provided in an embodiment of the present disclosure.

[0051] like Figure 1 As shown, the method comprises the following steps:

[0052] Step 101, obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance.

[0053] Use SQL query or data extraction tools to obtain data. For example, use the responsive function reactive in shiny to respond to the operation of the data upload interface. After uploading the local file, call the read.csv function to read the uploaded file. In actual use, the method of obtaining data can be determined according to the actual situation, and the embodiment of the present application does not limit this.

[0054] The DRG data to be grouped is matched with a preset field file, which contains different data items. In some embodiments, the data items in the preset field file are determined in advance and are used to eliminate useless data in the grouped DRG data to improve the efficiency of data grouping.

[0055] Step 102: Perform field matching on the DRG data to be grouped according to the preset field file.

[0056] Match the fields in the DRG data to be grouped with the fields in the preset field file, determine the fields in the DRG data to be grouped that match the data items in the preset field file and process them accordingly. Based on the matched fields, the DRG data to be grouped can be further processed, such as data grouping, analysis, and other operations.

[0057] Step 103, when the field matching is successful, the DRG data to be grouped is calculated according to a preset calculation algorithm, and an analysis report is generated.

[0058] The matched fields are calculated according to the preset calculation algorithm, such as numerical calculation, logical judgment, etc. of the fields. For the detailed implementation process of the specific calculation, please refer to any implementation method in the prior art, and the embodiments of this application will not be described one by one here.

[0059] In some embodiments, the analysis report includes parameters such as a disease group directory, disease group weights, and a calculation report. The analysis report classifies patients with similar conditions or treatment plans into the same "disease group", and assigns a weight parameter to each disease group to determine the payment standard for the disease group.

[0060] In some embodiments, a corresponding analysis report or output result can be generated based on the measurement results and combined with business needs, and more data analysis, visualization and other operations can be performed.

[0061] The present disclosure provides a DRG grouping method, the main technical scheme of which includes: first, obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance; second, performing field matching on the DRG data to be grouped according to the preset field file; second, when the field matching is successful, the DRG data to be grouped is measured according to the preset measurement algorithm, and an analysis report is generated. Compared with the related art, the embodiment of the present application improves data processing efficiency and accuracy by realizing the process of automating the processing of the DRG data to be grouped, and performs field matching through a pre-configured field file, which reduces the possibility of manual intervention and reduces the error rate.

[0062] In some embodiments, after performing field matching on the DRG data to be grouped according to the preset field file in step 102, the matching result may be displayed to the user. The specific steps include:

[0063] The field matching results are displayed in a preset display area; wherein the display content includes the matching results and the field matching content.

[0064] To display the field matching results in the preset display area, including the matching results and field matching content, you can display them through a graphical interface or a web page, for example, design a display area to display the field matching results and field matching content. You can use a GUI library (such as Tkinter) or web development technology (such as HTML, CSS, JavaScript) to create a display interface.

[0065] Display the matching results and field matching content in the display area. According to the successful field matching results, the successfully matched fields and corresponding content are displayed in the display area. Users can view the matching results and field content in the display area to understand the field matching situation more intuitively.

[0066] In some embodiments, after performing field matching on the DRG data to be grouped according to the preset field file, the method further includes:

[0067] In the event of a field match failure, the reason for the failure will be displayed in the preset display area to prompt the completion of the DRG data.

[0068] See also Figure 2 , Figure 2 A schematic diagram of another DRG grouping process provided by an embodiment of the present disclosure, such as Figure 2 As shown, in the case of a field match failure, the failure reason can be displayed in a preset display area, and the user can be prompted to complete the DRG data. This can help users find and solve problems with incomplete or erroneous data more quickly, and improve the efficiency and accuracy of data processing.

[0069] Ways to show the reason for failure include:

[0070] Displays which fields failed to match and the specific reasons for the failure, such as field name mismatch, data format error, etc.

[0071] Show which fields are missing to help users understand how to complete or correct the data so as to successfully perform field matching and subsequent measurement work.

[0072] In some embodiments, the DRG grouping information of different regions is different, and the DRG grouping information may also vary with different versions. Therefore, when grouping the DRG data to be grouped, the grouping standard or grouping algorithm needs to be determined according to the region and version information of the DRG data to be grouped. Figure 2 , Figure 2 A flowchart of a DRG grouping method provided in an embodiment of the present disclosure includes:

[0073] Step 201, determining the region and version information corresponding to the DRG data to be grouped.

[0074] In some embodiments, the DRG data to be grouped may contain region and version information, or the attributes or metadata of the data file may be checked to determine whether the field contains region and version information.

[0075] Step 202: determine a preset calculation algorithm based on the region and version information of the DRG data to be grouped.

[0076] According to the region to which the DRG data to be grouped belongs, select the preset calculation algorithm applicable to the region. Different regions may have different medical standards, cost regulations, etc., so it is necessary to select an algorithm that conforms to the actual situation of the region; and consider the version information of the DRG data to be grouped, and select the preset calculation algorithm that matches the version. Different versions of data may have differences in field structure, data format, etc., and it is necessary to select an algorithm applicable to this version for calculation.

[0077] By determining the preset calculation algorithm according to the region and version information of the DRG data to be grouped, the accuracy and applicability of data processing can be improved, ensuring that the calculation results are in line with the actual situation and can provide users with useful information and decision-making support.

[0078] In some embodiments, for data security, after step 102, the following steps are further included:

[0079] Obtaining a preset key and determining whether the preset key is correct;

[0080] When the preset secret key is correct, the DRG data to be grouped is calculated according to the preset calculation algorithm.

[0081] Obtain the key information entered by the user, and verify whether the preset key is correct, and perform parameter calculation if it is correct.

[0082] Corresponding to the above-mentioned DRG grouping method, the present invention also provides a DRG grouping device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0083] Figure 4 A structural diagram of a DRG grouping device provided in an embodiment of the present disclosure is shown in FIG. Figure 4 As shown, including:

[0084] The first acquisition unit 31 is used to acquire the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance;

[0085] A field matching unit 32, configured to perform field matching on the DRG data to be grouped according to the preset field file;

[0086] The calculation unit 33 is used to calculate the DRG data to be grouped according to a preset calculation algorithm and generate an analysis report when the field matching is successful.

[0087] The present disclosure provides a DRG grouping device, and the main technical scheme includes: first, obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance; second, performing field matching on the DRG data to be grouped according to the preset field file; third, when the field matching is successful, the DRG data to be grouped is measured according to the preset measurement algorithm, and an analysis report is generated. Compared with the related art, the embodiment of the present application improves the data processing efficiency and accuracy by realizing the process of automating the processing of the DRG data to be grouped, and performs field matching through the pre-configured field file, which reduces the possibility of manual intervention and reduces the error rate.

[0088] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the device also includes:

[0089] The display unit 34 is used to display the field matching result in a preset display area after the field matching unit 32 performs field matching on the DRG data to be grouped according to the preset field file; wherein the display content includes the matching result and the field matching content.

[0090] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the device also includes:

[0091] The display unit 34 is also used to display the reason for failure in the preset display area after the field matching unit 32 performs field matching on the DRG data to be grouped according to the preset field file, in case of field matching failure, to prompt the completion of the DRG data.

[0092] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the device also includes:

[0093] The determination unit 35 is used to calculate the DRG data to be grouped according to a preset calculation algorithm when the field matching of the calculation unit 33 is successful, and determine the region and version information corresponding to the DRG data to be grouped before generating an analysis report;

[0094] The determination unit 35 is further used to determine a preset calculation algorithm according to the region and version information of the DRG data to be grouped.

[0095] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the device also includes:

[0096] A second obtaining unit 36 ​​is used to obtain a preset key and determine whether the preset key is correct after the determining unit 35 determines the preset calculation algorithm according to the region and version information of the DRG data to be grouped;

[0097] The calculation unit is also used to calculate the DRG data to be grouped according to the preset calculation algorithm when the preset key is correct.

[0098] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principle is the same, which is no longer limited in the embodiment of the present disclosure.

[0099] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0100] Figure 6 A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0101] like Figure 6 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 to a RAM (Random Access Memory) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0102] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0103] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as a DRG grouping method. For example, in some embodiments, a DRG grouping method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned DRG grouping method in any other appropriate manner (for example, by means of firmware).

[0104] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a special purpose or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0105] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0106] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0107] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0108] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0109] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0110] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0111] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0112] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A DRG grouping method, characterized in that: include: Obtaining the DRG data to be grouped and the preset field file; wherein the preset field file is configured in advance; Performing field matching on the DRG data to be grouped according to the preset field file; When the field matching is successful, the DRG data to be grouped is calculated according to a preset calculation algorithm, and an analysis report is generated. Wherein, when the field matching is successful, the DRG data to be grouped is calculated according to a preset calculation algorithm, and before generating an analysis report, the method further includes: Determine the region and version information corresponding to the DRG data to be grouped; The preset calculation algorithm is determined according to the region and version information of the DRG data to be grouped. Wherein, after determining the preset calculation algorithm according to the region and version information of the DRG data to be grouped, the method further includes: Obtaining a preset key and determining whether the preset key is correct; When the preset secret key is correct, the DRG data to be grouped is calculated according to the preset calculation algorithm.

2. The method according to claim 1, characterized in that After performing field matching on the DRG data to be grouped according to the preset field file, the method further includes: The field matching results are displayed in a preset display area; wherein the display content includes the matching results and the field matching content.

3. The method according to claim 2, characterized in that After performing field matching on the DRG data to be grouped according to the preset field file, the method further includes: In the event of a field match failure, the reason for the failure will be displayed in the preset display area to prompt the completion of the DRG data.

4. A DRG grouping device, characterized in that: include: A first acquisition unit is used to acquire the DRG data to be grouped and a preset field file; wherein the preset field file is configured in advance; A field matching unit, used for performing field matching on the DRG data to be grouped according to the preset field file; A calculation unit, used to calculate the DRG data to be grouped according to a preset calculation algorithm and generate an analysis report when the field matching is successful; Wherein, the device further comprises: A determination unit, used to calculate the DRG data to be grouped according to a preset calculation algorithm when the calculation unit field matches successfully, and determine the region and version information corresponding to the DRG data to be grouped before generating an analysis report; The determination unit is also used to determine a preset calculation algorithm according to the region and version information of the DRG data to be grouped. Wherein, the device further comprises: A second obtaining unit is used to obtain a preset key after the determining unit determines the preset calculation algorithm according to the region and version information of the DRG data to be grouped, and determine whether the preset key is correct; The calculation unit is further configured to calculate the DRG data to be grouped according to the preset calculation algorithm when the preset secret key is correct.

5. The device according to claim 4, characterized in that The device also includes: A display unit is used to display the field matching results in a preset display area after the field matching unit performs field matching on the DRG data to be grouped according to the preset field file; wherein the display content includes the matching results and the field matching content.

6. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 3.

7. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-3.

8. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 3.

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