A data processing method, apparatus, electronic device, and storage medium

Abstract

This invention discloses a data processing method, apparatus, electronic device, and storage medium. The method includes: acquiring consumed data associated with a patient; determining reimbursement data from the consumed data based on the reimbursement type corresponding to the consumed data; determining the surgical procedure type and quantity corresponding to the patient based on the data consumption identifier of the reimbursement data, and / or determining ordinary reimbursement data corresponding to the patient; determining a first data processing method based on the quantity corresponding to the surgical procedure type and the patient's basic data; and / or determining a second data processing method based on the ordinary reimbursement data and the patient's basic data; and determining target reimbursement data corresponding to the patient based on the first and / or second data processing methods. This solves the problem of inaccurate reimbursement data for users and achieves the effect of accurately calculating the reimbursement data due to the user.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] When patients need to claim medical expenses, they need to be evaluated by the relevant review department to determine whether they are eligible for medical reimbursement and the reimbursement ratio.

[0003] Currently, reimbursement by disease type is one of the more advanced assessment methods. Specifically, it involves grouping patients according to their treatment information and medical expenses at medical institutions, and then reimbursing them according to the specified reimbursement standards for each group. This aims to guide medical institutions to reduce unnecessary treatments and services, thereby controlling medical reimbursement costs. However, this settlement method may suffer from inaccurate classification and requires a lengthy classification process.

[0004] To address these issues, improvements are needed in the methods for settling medical expenses. Summary of the Invention

[0005] This invention provides a data processing method, apparatus, electronic device, and storage medium to solve the problem of inaccurate reimbursement data caused by inaccurate reimbursement assessment methods when reimbursing user expenses.

[0006] In a first aspect, embodiments of the present invention provide a data processing method, including:

[0007] Obtain consumed data associated with patients;

[0008] Based on the reimbursement type corresponding to the consumed data, determine the consumption data to be reimbursed from the consumed data;

[0009] Based on the data consumption identifier of the expense data to be reimbursed, determine the surgical type and corresponding quantity corresponding to the patient, and / or determine the ordinary reimbursement data corresponding to the patient;

[0010] Based on the quantity corresponding to the surgical type and the basic data of the patients, a first data processing method is determined; and / or,

[0011] Based on the general reimbursement data and the basic data of the patients, a second data processing method is determined;

[0012] Based on the first data processing method and / or the second data processing method, the target reimbursement data corresponding to the patient is determined.

[0013] Secondly, embodiments of the present invention also provide a data processing apparatus, comprising:

[0014] The consumed data acquisition module is used to acquire consumed data associated with patients.

[0015] The pending expense data determination module is used to determine the pending expense data from the consumed data based on the reimbursement type corresponding to the consumed data.

[0016] The identifier matching module is used to determine the type of surgery and the corresponding quantity corresponding to the patient based on the data consumption identifier of the expense data to be reimbursed, and / or determine the ordinary reimbursement data corresponding to the patient;

[0017] The first data processing method determination module is used to determine a first data processing method based on the quantity corresponding to the surgical type and the basic data of the patients; and / or,

[0018] The second data processing method determination module is used to determine the second data processing method based on the ordinary reimbursement data and the basic data of the patient.

[0019] The target reimbursement data determination module is used to determine the target reimbursement data corresponding to the patient based on the first data processing method and / or the second data processing method.

[0020] Thirdly, embodiments of the present invention also provide an electronic device, comprising:

[0021] At least one processor; and

[0022] A memory communicatively connected to the at least one processor; wherein,

[0023] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the data processing method according to any embodiment of the present invention.

[0024] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that are used to cause a processor to execute the data processing method described in any embodiment of the present invention.

[0025] The technical solution of this embodiment obtains consumed data associated with patients. This consumed data can be obtained through a database associated with patients. Based on the reimbursement type corresponding to the consumed data, data to be reimbursed is determined from the consumed data. Keyword detection is used to determine whether the consumed data contains a keyword corresponding to a preset keyword. If so, the reimbursement type of the consumed data containing the keyword is determined to be reimbursable; otherwise, it is determined to be non-reimbursable. Based on the data consumption identifier of the data to be reimbursed, the surgical procedure type and quantity corresponding to the patient are determined. Based on the data consumption identifier, the surgical procedure type and quantity performed by the patient during treatment can be determined, thus determining the reimbursement category corresponding to the patient. Based on the quantity corresponding to each surgical procedure and the basic data of the patients, a primary data processing method is determined. Different quantities of surgical procedures and different basic data correspond to different reimbursement groups, and consequently, different data processing methods apply to different reimbursement groups. After determining the reimbursement group for each patient as the primary group, the reimbursement method corresponding to the primary group table is used as the primary data processing method. Based on this primary data processing method, target reimbursement data corresponding to each patient is determined, and reimbursement is then processed accordingly. This method solves the problem of inaccurate reimbursement data caused by inaccurate reimbursement assessment methods, achieving accurate calculation of reimbursement data corresponding to each user.

[0026] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart of a data processing method provided according to Embodiment 1 of the present invention;

[0029] Figure 2 This is a flowchart of a data processing method provided according to Embodiment 2 of the present invention;

[0030] Figure 3 This is a schematic diagram of the structure of a data processing device according to Embodiment 4 of the present invention;

[0031] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the data processing method of the present invention. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0034] Example 1

[0035] Figure 1 The flowchart of a data processing method is provided for Embodiment 1 of the present invention. This embodiment is applicable to determining the reimbursement expense status corresponding to a user. The method can be executed by a data processing device, which can be implemented in hardware and / or software. The data processing device can be configured in a computing device capable of executing the data processing method.

[0036] like Figure 1 As shown, the method includes:

[0037] S110. Obtain the consumed data associated with the patient.

[0038] Among them, "patients" can be understood as those who have received medical treatment at medical institutions. "Consumed data" refers to various expenses incurred by patients during their treatment, such as hospitalization fees, examination fees, medication fees, and surgical fees.

[0039] Specifically, during a patient's medical visit, a series of consumption data are typically generated. Among these expenses are some that can be reimbursed by relevant reimbursement agencies. To determine which consumption data a patient can claim reimbursement for, it is necessary to obtain the consumption data associated with the patient. For example, a medical institution's database records all relevant information about a patient from admission to the end of treatment. When a patient is discharged, the consumption data associated with that patient can be retrieved from the database.

[0040] S120. Based on the reimbursement type corresponding to the consumed data, determine the consumption data to be reimbursed from the consumed data.

[0041] During the treatment process, patients may undergo surgical procedures or only receive medication or general medical care. When reimbursing patients' expenses, the reimbursement methods differ depending on whether surgical procedures are included or not.

[0042] Among them, reimbursement type can be understood as the reimbursement type corresponding to the consumption data of patients that includes surgery-related consumption data, and the reimbursement type corresponding to the consumption data that does not include surgery-related consumption data.

[0043] Specifically, the reimbursement type of a patient's consumed data is determined based on whether the consumed data includes any consumption data related to surgical expenses. For example, if the patient's consumed data includes consumption data related to surgical expenses, then the patient's consumed data is determined to be reimbursement-pending data; conversely, if the patient's consumed data does not include consumption data related to surgical expenses, then the patient's consumed data is determined to be ordinary reimbursement data.

[0044] Optionally, based on the reimbursement type corresponding to the consumed data, the consumption data to be reimbursed is determined from the consumed data, including: determining the reimbursement type to be used corresponding to the keywords to be identified carried in the consumed data; and determining the consumption data to be reimbursed from the consumed data based on the association information of the reimbursement type to be used; wherein the association information includes at least one reimbursable data.

[0045] The keywords to be identified can be understood as keyword information corresponding to different consumption items in the consumed data. For example, the keyword to be identified can be set as "A. Tumor". When the consumed data of a patient includes consumption data corresponding to "A. Tumor", and the consumption data corresponding to "A. Tumor" is surgical consumption data, it can be determined that the patient's reimbursement type is the reimbursement type corresponding to the consumption data containing surgery. The reimbursement type to be used can be understood as the corresponding consumption type determined based on whether surgical consumption data is included.

[0046] Specifically, reimbursable expenses are pre-set, and corresponding keywords are set according to the reimbursable expenses. When the keyword to be identified is detected in the consumed data based on the keyword detection conditions, if the keyword to be identified is consistent with the preset keyword, it is determined whether the consumption data corresponding to the keyword to be identified is related to the surgical consumption data, and the reimbursement type corresponding to the consumption data is determined, so as to identify the consumption data to be reimbursed from the consumed data.

[0047] S130. Based on the data consumption identifier of the consumption data to be reimbursed, determine the type of surgery and the corresponding quantity for the patient.

[0048] Here, "data consumption identifier" can be understood as an identifier used to represent the specific consumption item for which reimbursement data is pending. "Surgery type" can be understood as the type of surgery involved in the patient's instructions.

[0049] It is understandable that the reimbursable percentages in the pending reimbursement data may differ. For example, the reimbursement percentages for medications may differ from those for surgeries. Therefore, it is necessary to determine the specific consumption items corresponding to the patients based on the data consumption identifiers in the pending reimbursement data. For example, the types of surgeries involved in the patient's treatment and the total number of surgeries, etc., are needed to classify the patients into the corresponding reimbursement groups based on the types of surgeries and the corresponding number.

[0050] Optionally, based on the target mapping table, the data consumption identifier corresponding to the reimbursement consumption data is matched to obtain the surgical type and corresponding quantity corresponding to the patient.

[0051] The target mapping table includes at least one surgical technique type and the corresponding data identifier for each surgical technique type.

[0052] Specifically, after obtaining the consumption data of patients, the system queries and matches the data consumption identifier of the consumption data to be reimbursed in the consumption data in the consumption data, and obtains the surgical type and corresponding quantity corresponding to the patients based on the matching results.

[0053] S140. Determine the first data processing method based on the quantity corresponding to the type of surgery and the basic data of the patients.

[0054] The basic data of patients can include their age, type of complications, discharge method, and length of hospital stay. The first data processing method can be understood as the reimbursement processing method corresponding to the patient when their consumed data includes consumption data corresponding to a preset surgical procedure type.

[0055] When a user's consumed data includes a preset surgical type, it indicates that the user has undergone the corresponding surgical treatment, and the user's reimbursable data needs to be processed using the first data processing method. Specifically, the reimbursement method will differ depending on the number of surgical types performed by the user and the corresponding basic data. The first data processing method corresponding to each user needs to be determined based on the number of surgical types performed and the corresponding basic data.

[0056] Optionally, based on the number corresponding to the surgical type and the basic data of the patients, a first data processing method is determined, including: obtaining basic data corresponding to the patients from the user information database; generating first matching information based on the basic data and the number corresponding to the surgical type, and determining a first group corresponding to the patients based on the first identifier carried by the first matching information; and retrieving the data processing method corresponding to the first group as the first data processing method.

[0057] The user information database can be understood as a database used to store relevant information about patients, containing basic data for each patient. The first matching information can be understood as information containing the surgical type corresponding to the patient, the number of surgical types, and basic data. For example, the first matching information may include surgical type 1, surgical type 2, and surgical type 3, as well as the basic data associated with the patient. The first identifier can be understood as the number of surgical types in the first matching information. For example, if the first matching information includes 3 surgical types, then there can be 3 first identifiers. The first group can be understood as different reimbursement groups set according to the number of surgical types.

[0058] Specifically, if the number of surgical procedures matching the preset surgical procedures in the reimbursement data of a patient is different or the basic data is different, the reimbursement ratio may be different. Therefore, it is necessary to generate first matching information based on the patient's basic data and the number corresponding to the surgical procedures, and determine the first group corresponding to the patient based on the first matching information, so as to process the patient's reimbursement data based on the first data processing method corresponding to the first group.

[0059] S150. Based on the first data processing method, determine the target reimbursement data corresponding to the patient.

[0060] Among them, the target reimbursement data can be understood as the consumption data that can be reimbursed from the consumption data of medical users.

[0061] In practical applications, based on the first data processing method, the target reimbursement data corresponding to the patient is determined, including: determining the reimbursement data for at least one surgical procedure type, and determining the target surgical procedure reimbursement data corresponding to the patient based on each reimbursement data; determining the reimbursement basic data corresponding to the basic data based on the patient's basic data; and determining the target reimbursement data corresponding to the patient based on the sum of the target surgical procedure reimbursement data and the reimbursement basic data.

[0062] The data on procedures to be reimbursed can be understood as consumption data corresponding to preset procedure types. It should be noted that a patient may undergo multiple surgeries during treatment, some of which match the preset procedure types, while others do not. In this technical solution, the reimbursement data corresponding to the procedures that match the preset procedure types is used as the target procedure reimbursement data. The basic data to be reimbursed can be understood as the reimbursable data within the patient's basic data.

[0063] Specifically, based on the reimbursement data corresponding to the surgical procedures for which patients are eligible for reimbursement, the target surgical procedure reimbursement data corresponding to each patient is determined. Simultaneously, the reimbursement data corresponding to the basic reimbursement data within the patient's basic data is used as the basic data to be reimbursed. By overlaying the target surgical procedure reimbursement data and the basic data to be reimbursed, the target reimbursement data corresponding to each patient can be obtained.

[0064] The technical solution of this embodiment obtains consumed data associated with patients. This consumed data can be obtained through a database associated with patients. Based on the reimbursement type corresponding to the consumed data, data to be reimbursed is determined from the consumed data. Keyword detection is used to determine whether the consumed data contains a keyword corresponding to a preset keyword. If so, the reimbursement type of the consumed data containing the keyword is determined to be reimbursable; otherwise, it is determined to be non-reimbursable. Based on the data consumption identifier of the data to be reimbursed, the surgical procedure type and quantity corresponding to the patient are determined. Based on the data consumption identifier, the surgical procedure type and quantity performed by the patient during treatment can be determined, thus determining the reimbursement category corresponding to the patient. Based on the quantity corresponding to each surgical procedure and the basic data of the patients, a primary data processing method is determined. Different quantities of surgical procedures and different basic data correspond to different reimbursement groups, and consequently, different data processing methods apply to different reimbursement groups. After determining the reimbursement group for each patient as the primary group, the reimbursement method corresponding to the primary group table is used as the primary data processing method. Based on this primary data processing method, target reimbursement data corresponding to each patient is determined, and reimbursement is then processed accordingly. This method solves the problem of inaccurate reimbursement data caused by inaccurate reimbursement assessment methods, achieving accurate calculation of reimbursement data corresponding to each user.

[0065] Example 2

[0066] Figure 2 The flowchart of a data processing method provided in Embodiment 2 of the present invention is shown. Optionally, when the data to be reimbursed is ordinary reimbursement data, the target consumption data associated with the patient is determined based on the second data processing method.

[0067] like Figure 2 As shown, the method includes:

[0068] S210. Obtain the consumed data associated with the patient.

[0069] S220. Based on the reimbursement type corresponding to the consumed data, determine the consumption data to be reimbursed from the consumed data.

[0070] S230. Based on the data consumption identifier of the consumption data to be reimbursed, determine the ordinary reimbursement data corresponding to the patient.

[0071] Specifically, when the reimbursement data of a patient does not include reimbursement data related to surgery, the reimbursement data corresponding to the patient can be identified as ordinary reimbursement data, such as inpatient reimbursement data and medication reimbursement data.

[0072] Optionally, if no surgical type matching the data consumption identifier is found in the target mapping table, the reimbursement consumption data of the patient is determined to be ordinary reimbursement data.

[0073] Specifically, if the data identifier in the pending reimbursement consumption data cannot be found in the target mapping table, it means that the pending reimbursement data of the patient does not contain pending reimbursement data that matches the preset surgical type, and the pending reimbursement data corresponding to the patient will be determined as ordinary reimbursement data.

[0074] S240. Determine the second data processing method based on the general reimbursement data and the basic data of the patients.

[0075] The second data processing method can be understood as the reimbursement method when the reimbursement data of a patient only contains ordinary reimbursement data.

[0076] Specifically, if the reimbursement data of a patient only contains ordinary reimbursement data, then the basic data associated with the patient is obtained, and based on the ordinary reimbursement data and the basic data, a second data processing method corresponding to the patient is determined.

[0077] Optionally, based on ordinary reimbursement data and the basic data of patients, a second data processing method is determined, including: generating corresponding second matching information based on ordinary reimbursement data and the basic data of patients; determining a second group corresponding to the patients based on the second identifier carried by the second matching information; and retrieving the data processing method corresponding to the second group as the second data processing method.

[0078] Specifically, the second matching information can be understood as information generated based on ordinary reimbursement data and the basic data of the patient. Based on the second identifier of the second matching information, the reimbursement group corresponding to the patient can be determined, and the reimbursement method corresponding to that group is used as the second data processing method corresponding to the patient. Here, the second identifier can be understood as the identifying information corresponding to the second matching information.

[0079] S250. Based on the second data processing method, determine the target reimbursement data corresponding to the patient.

[0080] In practical applications, at least one piece of general reimbursement data corresponding to the general reimbursement data is retrieved; based on the sum of all the general reimbursement data, the target reimbursement data corresponding to the patient is determined.

[0081] In this embodiment, the patient may not undergo a specific surgical procedure during treatment. Therefore, the patient cannot be categorized into a reimbursement group that includes surgical procedures. Instead, a second group is determined based on the patient's general reimbursement data and associated basic data. The reimbursement method corresponding to this second group is then used as a second data processing method to determine the target reimbursement data for the patient. This solves the problem of inaccurate reimbursement data due to inaccurate reimbursement assessment methods, achieving accurate calculation of reimbursement data corresponding to the user.

[0082] Example 3

[0083] In a specific example, the system retrieves the consumed data associated with the patient and determines the patient's reimbursement type as either a reimbursement type including or excluding surgical procedures based on whether the consumed data includes consumption data corresponding to a preset surgical procedure type. If the patient's reimbursement type includes surgical procedures, the patient is assigned to the corresponding first group based on the number of surgical procedures matching the preset surgical procedure type involved in the patient's treatment, as well as the basic data associated with the patient. For example, if the patient's relevant information includes relevant diagnostic information and relevant surgical procedure information, and if the patient's pending reimbursement data includes one pending reimbursement data corresponding to the preset surgical procedure type, the patient is assigned to the single-surgery group; if the patient's pending reimbursement data includes three pending reimbursement data corresponding to the preset surgical procedure type, the patient is assigned to the three-surgery group. It should be noted that when grouping patients, the division should be based on the number of surgical procedures that match the preset surgical types. For example, if a patient involves 5 surgical procedures during treatment, but only 2 of them match the preset surgical types, the patient will be divided into two surgical groups. All groups involving surgery belong to the first group in this technical solution. The reimbursement method corresponding to the first group is determined as the first data processing method, and the patient's reimbursement data is calculated based on this method to obtain the target reimbursement data corresponding to the patient.

[0084] Furthermore, the reimbursement data of patients may not include reimbursement data related to the type of surgery. In order to accurately process the reimbursement data of patients, patients are divided into a second group based on their basic data, and the reimbursement method corresponding to the second group is determined as the second data processing method. That is, the reimbursement data of patients is determined as ordinary reimbursement data. The target reimbursement data corresponding to the patients is determined based on the sum of the ordinary reimbursement data and the basic reimbursement data corresponding to the basic data.

[0085] The technical solution of this embodiment obtains consumed data associated with patients. This consumed data can be obtained through a database associated with patients. Based on the reimbursement type corresponding to the consumed data, data to be reimbursed is determined from the consumed data. Keyword detection is used to determine whether the consumed data contains a keyword corresponding to a preset keyword. If so, the reimbursement type of the consumed data containing the keyword is determined to be reimbursable; otherwise, it is determined to be non-reimbursable. Based on the data consumption identifier of the data to be reimbursed, the surgical procedure type and quantity corresponding to the patient are determined. Based on the data consumption identifier, the surgical procedure type and quantity performed by the patient during treatment can be determined, thus determining the reimbursement category corresponding to the patient. Based on the quantity corresponding to each surgical procedure and the basic data of the patients, a primary data processing method is determined. Different quantities of surgical procedures and different basic data correspond to different reimbursement groups, and consequently, different data processing methods apply to different reimbursement groups. After determining the reimbursement group for each patient as the primary group, the reimbursement method corresponding to the primary group table is used as the primary data processing method. Based on this primary data processing method, target reimbursement data corresponding to each patient is determined, and reimbursement is then processed accordingly. This method solves the problem of inaccurate reimbursement data caused by inaccurate reimbursement assessment methods, achieving accurate calculation of reimbursement data corresponding to each user.

[0086] Example 4

[0087] Figure 3 This is a schematic diagram of the structure of a data processing device provided in Embodiment 4 of the present invention. Figure 3 As shown, the device includes: a consumed data acquisition module 310, a consumption data determination module 320, an identifier matching module 330, a first data processing method determination module 340, a second data processing method determination module 350, and a target reimbursement data determination module 360.

[0088] Among them, the consumed data acquisition module 310 is used to acquire consumed data associated with the patient.

[0089] The pending expense data determination module 320 is used to determine the pending expense data from the consumed data based on the reimbursement type corresponding to the consumed data.

[0090] The identifier matching module 330 is used to determine the type of surgery and the corresponding quantity corresponding to the patient based on the data consumption identifier of the consumption data to be reimbursed, and / or determine the ordinary reimbursement data corresponding to the patient.

[0091] The first data processing method determination module 340 is used to determine the first data processing method based on the quantity corresponding to the surgical type and the basic data of the patients; and / or,

[0092] The second data processing method determination module 350 is used to determine the second data processing method based on ordinary reimbursement data and the basic data of patients.

[0093] The target reimbursement data determination module 360 ​​is used to determine the target reimbursement data corresponding to the patient based on the first data processing method and / or the second data processing method.

[0094] The technical solution of this embodiment obtains consumed data associated with patients. This consumed data can be obtained through a database associated with patients. Based on the reimbursement type corresponding to the consumed data, data to be reimbursed is determined from the consumed data. Keyword detection is used to determine whether the consumed data contains a keyword corresponding to a preset keyword. If so, the reimbursement type of the consumed data containing the keyword is determined to be reimbursable; otherwise, it is determined to be non-reimbursable. Based on the data consumption identifier of the data to be reimbursed, the surgical procedure type and quantity corresponding to the patient are determined. Based on the data consumption identifier, the surgical procedure type and quantity performed by the patient during treatment can be determined, thus determining the reimbursement category corresponding to the patient. Based on the quantity corresponding to each surgical procedure and the basic data of the patients, a primary data processing method is determined. Different quantities of surgical procedures and different basic data correspond to different reimbursement groups, and consequently, different data processing methods apply to different reimbursement groups. After determining the reimbursement group for each patient as the primary group, the reimbursement method corresponding to the primary group table is used as the primary data processing method. Based on this primary data processing method, target reimbursement data corresponding to each patient is determined, and reimbursement is then processed accordingly. This method solves the problem of inaccurate reimbursement data caused by inaccurate reimbursement assessment methods, achieving accurate calculation of reimbursement data corresponding to each user.

[0095] Optionally, the reimbursement consumption data determination module includes: a reimbursement type determination unit, used to determine the reimbursement type to be used corresponding to the keywords to be identified based on the keywords to be identified carried in the consumed data;

[0096] The unit for determining consumption data to be reimbursed is used to determine consumption data to be reimbursed from consumption data based on the association information of the type of reimbursement to be used; wherein the association information includes at least one reimbursable data.

[0097] Optionally, the identifier matching module includes: a quantity determination unit, used to match the data consumption identifiers corresponding to the reimbursement consumption data based on the target mapping table, to obtain the surgical type and corresponding quantity corresponding to the patient; wherein, the target mapping table includes at least one surgical type and the data identifiers corresponding to each surgical type; and / or

[0098] The ordinary reimbursement data determination unit is used to determine that the reimbursement consumption data of the patient is ordinary reimbursement data if no surgical type matching the data consumption identifier is found in the target mapping table.

[0099] Optionally, the first data processing method determination module includes: a basic data acquisition unit, used to acquire basic data corresponding to the patient from the user information database;

[0100] The first group determination unit is used to generate first matching information based on basic data and the quantity corresponding to the surgical type, and to determine the first group corresponding to the patient based on the first identifier carried by the first matching information.

[0101] The first data processing method determination unit is used to retrieve the data processing method corresponding to the first group as the first data processing method.

[0102] Optionally, the second data processing method determination module includes: a matching information generation unit, used to generate corresponding second matching information based on ordinary reimbursement data and basic data of patients;

[0103] The second group determination unit is used to determine the second group corresponding to the patient based on the second identifier carried in the information to be matched;

[0104] The second data processing method determination unit is used to retrieve the data processing method corresponding to the second group as the second data processing method.

[0105] Optionally, the target reimbursement data determination module includes: a surgical procedure reimbursement data determination unit, used to determine the surgical procedure data to be reimbursed corresponding to at least one surgical procedure type, and to determine the target surgical procedure reimbursement data corresponding to the patient based on each surgical procedure data to be reimbursed;

[0106] The unit for determining basic data to be reimbursed is used to determine the basic data to be reimbursed corresponding to the basic data of the patient.

[0107] The first target reimbursement data determination unit is used to determine the target reimbursement data corresponding to the patient based on the sum of the target surgical procedure reimbursement data and the basic data to be reimbursed.

[0108] Optionally, the target reimbursement data determination module includes: a general data determination unit for reimbursement, used to retrieve at least one general data for reimbursement corresponding to the general reimbursement data;

[0109] The second target reimbursement data determination unit is used to determine the target reimbursement data corresponding to the patient based on the sum of all general data to be reimbursed.

[0110] The data processing apparatus provided in the embodiments of the present invention can execute the data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0111] Example 5

[0112] Figure 4 A schematic diagram of the structure of an electronic device 10 according to an embodiment of the present invention 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 may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0113] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0114] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0115] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as data processing methods.

[0116] In some embodiments, the data processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the data processing method by any other suitable means (e.g., by means of firmware).

[0117] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] Computer programs for implementing the data processing methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0119] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0120] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device 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 pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, 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 sound input, voice input, or tactile input).

[0121] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0122] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0123] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0124] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data processing method, characterized in that, include: Obtain consumed data associated with patients; Based on the reimbursement type corresponding to the consumed data, determine the consumption data to be reimbursed from the consumed data; Based on the data consumption identifier of the expense data to be reimbursed, determine the surgical type and corresponding quantity corresponding to the patient, and / or determine the ordinary reimbursement data corresponding to the patient; Based on the quantity corresponding to the surgical type and the basic data of the patients, a first data processing method is determined; And / or, Based on the general reimbursement data and the basic data of the patients, a second data processing method is determined; Based on the first data processing method and / or the second data processing method, determine the target reimbursement data corresponding to the patient; The step of determining the surgical type and quantity corresponding to the patient based on the data consumption identifier of the reimbursement data, and / or determining the ordinary reimbursement data corresponding to the patient, includes: matching the data consumption identifier corresponding to the reimbursement data based on a target mapping table to obtain the surgical type and quantity corresponding to the patient; wherein the target mapping table includes at least one surgical type and a data identifier corresponding to each surgical type; and / or if no surgical type matching the data consumption identifier is found in the target mapping table, then the patient's reimbursement data is determined to be the ordinary reimbursement data.

2. The method according to claim 1, characterized in that, The step of determining the expense data to be reimbursed from the consumed data according to the reimbursement type corresponding to the consumed data includes: Based on the keywords to be identified carried in the consumed data, determine the reimbursement type to be used corresponding to the keywords to be identified; Based on the association information of the reimbursement type to be used, the consumption data to be reimbursed is determined from the consumed data; wherein, the association information includes at least one reimbursable data.

3. The method according to claim 1, characterized in that, The step of determining the first data processing method based on the quantity corresponding to the surgical type and the basic data of the patients includes: Retrieve basic data corresponding to the patient from the user information database; Based on the basic data and the quantity corresponding to the surgical type, first matching information is generated, and a first group corresponding to the patient is determined based on the first identifier carried by the first matching information. The data processing method corresponding to the first group is the first data processing method.

4. The method according to claim 1, characterized in that, The step of determining the second data processing method based on the general reimbursement data and the basic data of the patients includes: Based on the general reimbursement data and the basic data of the patients, corresponding second matching information is generated; Based on the second identifier carried by the second information to be matched, determine the second group corresponding to the patient. The data processing method corresponding to the second group is the second data processing method.

5. The method according to claim 1, characterized in that, The step of determining the target reimbursement data corresponding to the patient based on the first data processing method includes: Determine the reimbursement data for at least one surgical procedure type, and determine the target surgical procedure reimbursement data corresponding to the patient based on each reimbursement data. Based on the basic data of the patients, determine the basic data to be reimbursed corresponding to the basic data; Based on the sum of the reimbursement data for the target surgical procedure and the basic data to be reimbursed, the target reimbursement data corresponding to the patient is determined.

6. The method according to claim 1, characterized in that, The step of determining the target reimbursement data corresponding to the patient based on the second data processing method includes: Retrieve at least one piece of general reimbursement data corresponding to the general reimbursement data; Based on the sum of all general reimbursement data, the target reimbursement data corresponding to the patient is determined.

7. A data processing apparatus, characterized in that, include: The consumed data acquisition module is used to acquire consumed data associated with patients. The pending expense data determination module is used to determine the pending expense data from the consumed data based on the reimbursement type corresponding to the consumed data. The identifier matching module is used to determine the type of surgery and the corresponding quantity corresponding to the patient based on the data consumption identifier of the expense data to be reimbursed, and / or determine the ordinary reimbursement data corresponding to the patient; The first data processing method determination module is used to determine the first data processing method based on the quantity corresponding to the surgical type and the basic data of the patients. And / or, The second data processing method determination module is used to determine the second data processing method based on the ordinary reimbursement data and the basic data of the patient. The target reimbursement data determination module is used to determine the target reimbursement data corresponding to the patient based on the first data processing method and / or the second data processing method. The identifier matching module includes: a quantity determination unit, used to match the data consumption identifier corresponding to the reimbursement consumption data based on the target mapping table, to obtain the surgical type and corresponding quantity corresponding to the patient; wherein the target mapping table includes at least one surgical type and the data identifier corresponding to each surgical type; and / or a general reimbursement data determination unit, used to determine that the patient's reimbursement consumption data is general reimbursement data if no surgical type matching the data consumption identifier is found in the target mapping table.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the data processing method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the data processing method according to any one of claims 1-6.

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