Medical record processing method and apparatus, device and storage device

Abstract

The present application discloses a medical record processing method and apparatus, an electronic device and a computer readable storage medium. The medical record processing method comprises: when it is detected in a patient information base that a plurality of pieces of patient information are bound to a target patient, determining target patient information, the target patient information being one piece of patient information among the plurality of pieces of patient information (S201); on the basis of data associated with the target patient information, searching the patient information base for patient information matching the target patient information, the associated data comprising data in the target patient information that can be used for fuzzy search (S202); and merging the matched patient information to the target patient information, and on the basis of the merged patient information, processing a medical record of the target patient and a medical record of a patient corresponding to the matched patient information (S203). The medical record creation efficiency can be improved, a large search range is ensured while the patient information search efficiency is improved, and the search result is more accurate.

Description

Medical record processing method, device, equipment and storage device

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on August 29, 2023, with application number 202311103437.3 and application name “Method, device, electronic device and storage medium for processing medical records”, all contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of data processing, and in particular to a medical record processing method, device, electronic device and computer-readable storage medium. Background Art

[0003] When a patient visits a dental clinic, the clinic's medical staff creates a dental order for the patient. The dental order needs to include the patient's information, so the medical staff needs to enter the patient's information into the dental software system.

[0004] For the same patient, when creating a dental order for the patient, if the patient's information does not exist in the dental software system, the medical staff needs to first enter the patient's information into the dental software system. If the patient's information has already been entered into the dental software system, the patient's information can be directly searched for and selected for use. However, due to operational errors and other reasons, the medical staff may not use the entered patient information and repeatedly enter the same patient's information into the dental software system. In the subsequent process of creating a dental order, when searching for the entered patient information, there may be multiple duplicate patient information for the same patient, which brings inconvenience to data selection and editing and reduces the efficiency of creating orders.

[0005] Summary of the Invention

[0006] To address the above technical issues, the present application provides a medical record processing method, device, electronic device, and computer-readable storage medium. The technical solutions are as follows:

[0007] According to the first aspect of the present application, a method for processing medical records is provided, the method comprising: when it is detected in a patient information database that a target patient is bound to multiple patient information, determining the target patient information, the target patient information being one of the multiple patient information; based on data associated with the target patient information, searching the patient information database for patient information that matches the target patient information, the associated data including data in the target patient information that can be used for fuzzy search; merging the matched patient information into the target patient information, so as to process the medical records of the target patient and the medical records of the patient corresponding to the matched patient information according to the merged patient information.

[0008] According to the second aspect of the present application, a medical record processing device is provided, which includes: a determination unit, configured to determine the target patient information when it is detected in the patient information database that a target patient is bound to multiple patient information, the target patient information being one of the multiple patient information; a search unit, configured to search the patient information database for patient information that matches the target patient information based on data associated with the target patient information, the associated data including data in the target patient information that can be used for fuzzy search; a merging unit, configured to merge the matched patient information into the target patient information, so as to process the medical records of the target patient and the medical records of the patient corresponding to the matched patient information according to the merged patient information.

[0009] According to a third aspect of the present application, an electronic device is provided, comprising: a processor; and a memory configured to store processor-executable instructions; wherein the processor is configured to implement the method described in the first aspect.

[0010] According to a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the method described in the first aspect are implemented.

[0011] The technical solution provided by the present application determines a target patient information when there are multiple duplicate patient information for a target patient in a patient information database, and merges all patient information matching the target patient information into the target patient information. This allows the creation or editing of the target patient's medical records and the medical records of the patients corresponding to the matched patient information to be performed only on the basis of the merged patient information, thereby improving the efficiency of medical record creation. At the same time, when searching for patient information matching the target patient information in the patient information database, fuzzy matching can be performed in the patient information database based on data in the target patient information that can be used for fuzzy search, thereby improving the search efficiency while ensuring a larger search range and making the search results more accurate.

[0012] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0014] FIG1 is a schematic diagram of a patient's medical record processing scenario in the related art;

[0015] FIG2 is a flow chart of a medical record processing method of the present application;

[0016] FIG3 is a schematic diagram of a patient's medical record processing scenario according to an embodiment of the present application;

[0017] FIG4 is a schematic structural diagram of a medical record processing device according to an embodiment of the present application;

[0018] FIG5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be described in detail below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art should fall within the scope of protection of this application.

[0020] Please refer to Figure 1. First, a patient medical record processing scenario in the related technology is introduced. Take the dental scenario as an example, and take the patient's medical record as the patient's order as an example. When the patient visits a dental clinic or hospital, the clinic medical staff creates a dental order for the patient. The dental order needs to include the patient's information. The medical staff needs to enter the patient information in the dental software system. The entered patient information belongs to the dental clinic or hospital. Different medical staff in the same clinic or hospital may share the patient information entered in the dental software system when creating an order for the patient.

[0021] When creating a dental order for the same patient, if the patient's information does not exist in the dental software system, the medical staff must first enter the patient's information into the dental software system. If the patient's information has already been entered into the dental software system, the patient's information can be directly searched and selected for use. However, due to operational errors or other reasons, the medical staff may not use the entered patient information and repeatedly enter the same patient's information into the dental software system. When the same patient's information is entered into the dental software system, only the patient's name, contact information, and other information are entered. For identifiers such as name and contact information, the same patient can be changed. However, for privacy reasons, private data that can uniquely identify the same patient, such as ID number, is often not entered. Therefore, the entered patient information is not unique, resulting in the dental software system being unable to determine whether the patient information of the same patient entered multiple times actually belongs to the same patient, and can only be recorded as different patient information. In the subsequent process of creating dental orders, when searching for the entered patient information, there may be multiple duplicate patient information for the same patient, which brings inconvenience to data selection and editing and reduces the efficiency of creating medical records.

[0022] Taking Figure 1 as an example, the above scenario is described as follows:

[0023] Assume that there is a patient B. If the information of patient B does not exist in the dental software system, the medical staff who sees patient B must first enter the patient information of patient B into the dental software system. For example, for medical staff 1, if patient B is seeing the clinic where medical staff 1 is for the first time, the information of patient B may not exist in the dental software. In this case, medical staff 1 needs to enter the information of patient B (patient B information 1) when seeing patient B. Assume that there is a patient A. If in The dental software system has already entered the patient information of patient A. For example, the three patient information in Figure 1 are patient A information 1, patient A information 2, and patient A information 3. If medical staff 2 needs to create a dental order for patient A when seeing him, he can directly search for any information of patient A in the dental software system to select and use. However, medical staff 1 may make an operational error (for example, not searching, or medical staff 1 mistakenly believes that patient A is seeing him for the first time in the dental software system). If the medical staff 3 fails to use the entered patient information (patient A information 1, patient A information 2, patient A information 3) due to a similar operational error during the next consultation for patient A, and repeatedly enters the patient A's information (patient A information 4) into the dental software system, the same applies to another medical staff 3. If the medical staff 3 fails to use the entered patient information (patient A information 1, patient A information 2, patient A information 3, patient A information 4) due to a similar operational error during the next consultation for patient A, it is possible that The information of patient A (patient A information 5) is repeatedly entered into the dental software system. In this way, during the subsequent consultation process for patient A, when other medical staff create dental orders for patient A, when searching for the patient information already entered for patient A (patient A information 1, patient A information 2, patient A information 3, patient A information 4, patient A information 5), there may be multiple duplicate patient information of patient A, which brings inconvenience to data selection and editing and reduces the efficiency of creating orders.

[0024] It is worth noting that the above introduction to the patient's medical record processing scenario is only an exemplary display. In actual application, other medical record processing scenarios are not excluded and are not specifically limited to this.

[0025] For example: the patient can be a physical examination person, a matching person, a patient or a patient; the medical staff can be a doctor, a nurse, a physical examination person, a health care person or a convalescent person; the medical record processing scenario can be a hospital (clinic), a physical examination center, a health care center, a sanatorium or a hospital (clinic) dental laboratory (technical laboratory) and other scenarios.

[0026] To address the above issues, this application provides a method for processing medical records that can improve the efficiency of creating medical records, and at the same time improve the efficiency of searching for patient information while ensuring a larger search range and making the search results more accurate. As shown in Figure 2, the method includes the following steps:

[0027] S201. When it is detected in the patient information database that a target patient is bound to multiple patient information, the target patient information is determined, where the target patient information is one of the multiple patient information.

[0028] The patient information database may have various specific implementations. For example, one implementation may include: the patient information database may be a pre-built database that can be configured to store patient information.

[0029] As an example, taking the dental scenario as an example, the patient information database can be a database belonging to the dental software system, and the database can be a local database or a cloud database.

[0030] It should be noted that the multiple patient information bound to the target patient can be multiple patient information pre-entered into the above-mentioned patient information database, or can be multiple patient information entered into the above-mentioned patient information database during the testing process. There is no specific limitation on the time point of entering the multiple patient information.

[0031] As an example, the target patient information can be determined based on the patient information selected by the user from the above-mentioned multiple patient information. For example, if the medical staff clicks on one of the patient information among the multiple patient information bound to the target patient, the clicked patient information can be determined as the above-mentioned target patient information.

[0032] It is worth noting that the above description of the method for determining the target patient information is only an example. In actual application, other determination methods are not excluded. For example, the amount of information contained in each piece of patient information can be determined among the multiple pieces of patient information mentioned above, and the patient information with the largest amount of information can be determined as the target patient information. Therefore, there is no specific limitation on the method for determining the target patient information.

[0033] S202. Based on the data associated with the target patient information, search the patient information database for patient information that matches the target patient information. The associated data includes data in the target patient information that can be used for fuzzy search.

[0034] As an example, taking the oral scanning scenario as an example, the data that can be used for fuzzy search in the target patient information may include the target patient's dental model data, and the target patient may be the same patient bound to multiple patient information. For different patients, if the patient information of multiple actually different patients is very similar, for example, the name, gender, contact information, birthday or medical history in the patient information of different patients are all the same, it is difficult to determine whether the corresponding patients are different patients based on these patient information alone. In this case, the dental model data associated with the patient information can be used to determine. Even if the patient information between two different patients is highly overlapping, there will be differences in the dental model data. The dental model data can play the role of uniquely identifying the patient. In the oral scanning scenario, the dental model data obtained by the oral scan can be used for fuzzy search and matching to further improve the search accuracy.

[0035] As an example, the above-mentioned tooth model data can be collected in the patient's oral cavity by an oral scanner. As a second example, the above-mentioned tooth model data can be collected in the patient's oral cavity by an oral scanner with an infrared light function. When scanning the teeth in the oral cavity, the visible light (such as laser or white light) emitted by the oral scanner can obtain external information of the teeth (such as the shape and color of the teeth) to reconstruct a three-dimensional model of the teeth. On the basis of visible light, the oral scanner with an infrared light function can also emit infrared light, which can obtain internal information of the teeth (such as caries information). Based on the oral image data collected by infrared light, relevant internal information (such as caries information, i.e., the number, shape, position and other information of caries) can be marked on the three-dimensional model of the teeth to make the collected tooth model data richer and more accurate.

[0036] As an example, the tooth model data may include dental arch size data, tooth texture data, individual tooth size data, missing tooth data, or tooth restoration material data or other data.

[0037] For example, when the data in the target patient information that can be used for fuzzy search includes the target patient's dental model data, one method of searching the patient information database for patient information that matches the target patient information may include: analyzing the difference between the target patient's dental model data and the dental model data associated with other patient information by using three-dimensional data abstract analysis on the dental model data, and determining the patient information with a difference value less than or equal to a threshold as the patient information that matches the target patient information. It is worth noting that the above description of the method of fuzzy matching using dental model data is merely an example. In actual application, other methods of fuzzy matching using dental model data are not excluded, and no specific limitation is imposed on this.

[0038] In one embodiment, oral image data captured by an oral scanner is obtained. In response to a user's operation of the oral scanner, the captured oral image data is preprocessed to obtain preprocessed oral image data, and the preprocessed oral image data is three-dimensionally reconstructed to obtain tooth model data.

[0039] The oral image data may be a two-dimensional image frame. User operations on the oral scanner may include, but are not limited to, activating specific functions of the oral scanner. Specific functions include, but are not limited to, filtering of miscellaneous data and gum information. Miscellaneous data may include, but are not limited to, oral impurities such as saliva, blood, fingers, and medical instruments.

[0040] Preprocessing corresponds to a specific function item. For example, if the specific function item is a filtering function for miscellaneous data, then the preprocessing includes filtering the miscellaneous data; if the specific function item is a filtering function for gum information, then the preprocessing includes filtering the gum information; if the specific function item is a filtering function for miscellaneous data and gum information, then the preprocessing includes filtering the miscellaneous data and gum information.

[0041] This embodiment implements preprocessing of the collected oral image data by responding to user operations, which not only reduces the interference of miscellaneous data, gum information, etc. on the oral image data, but also reduces the data information of the oral image data, and then performs three-dimensional reconstruction on the preprocessed oral image data. Since miscellaneous data, gum information, etc. are eliminated from the oral image data, the reconstruction accuracy of the tooth model data can be improved; at the same time, since the data information of the oral image data is reduced, the waste of storage space for the tooth model data can also be reduced.

[0042] In one embodiment, before compressing the tooth model data, the collected oral image data can be preprocessed to obtain preprocessed oral image data, including: identifying miscellaneous data and / or gum information from the collected oral image data, and removing miscellaneous data and / or gum information from the collected oral image data to obtain preprocessed oral image data.

[0043] The identification of the miscellaneous data and / or gum information can be obtained from the collected oral image data using a target detection algorithm. The target location of the miscellaneous data and / or gum information in the collected oral image data is determined, and the target location is blocked or the miscellaneous data and / or gum information at the target location is removed to obtain preprocessed oral image data.

[0044] This embodiment can accurately identify miscellaneous data and / or gum information from the collected oral image data through the target detection algorithm, and then by determining the target position, can accurately remove miscellaneous data and / or gum information from the collected oral image data, ensuring that the preprocessed oral image data does not include miscellaneous data, gum information and other information.

[0045] In another embodiment, a gingival region is identified from the tooth model data and removed from the tooth model data to obtain tooth model data that does not include gingival information. In this embodiment, the tooth model data can be obtained by direct 3D reconstruction without undergoing a preprocessing step, or by 3D reconstruction after undergoing a preprocessing step to remove miscellaneous data but without undergoing a preprocessing step to remove gingival information.

[0046] This embodiment can reduce the data information in the tooth model data by filtering the gum model in the tooth model data, thereby reducing the space occupied by the tooth model data.

[0047] In another embodiment, the tooth model data is compressed based on the Huffman coding algorithm, and the compressed tooth model data is stored in the patient information database. The tooth model data in this embodiment can be: tooth model data including gum information, tooth model data excluding gum information. This embodiment compresses the tooth model data using the Huffman coding algorithm, which can ensure lossless compression of the tooth model data. At the same time, by compressing the tooth model data, it can further reduce the occupancy of the patient information database, improve the reading and writing efficiency of the compressed data, and improve the subsequent decompression efficiency of the tooth model data and the recognition efficiency of the tooth information. The compression step in this embodiment can be selectively enabled based on the user's input, or enabled after automatic recognition.

[0048] It is worth noting that the above description of the data that can be used for fuzzy search is only an example display. In actual application, other data are not excluded, and the specific implementation of the data that can be used for fuzzy search is not limited.

[0049] It is worth noting that the above description of the tooth model data collection method and specific implementation is only an example display. In actual application, other collection methods and specific implementations are not excluded and are not limited to this.

[0050] It is worth noting that the above description of the oral scanning scenario is only an exemplary display. In actual application, other application scenarios are not excluded, such as facial scanning scenarios. The above-mentioned associated data can also include facial data of the target patient. For example, in other medical scenarios, the above-mentioned associated data can also include medical information such as CBCT data, CT data and X-ray image information. Therefore, there is no specific limitation on the application scenario.

[0051] As an example, the data in the above-mentioned target patient information that can be used for fuzzy search may include an association identifier, which can indicate whether the data of a specified category in different patient information is associated; the target patient can be bound to the patient information of multiple patients, and the data of a specified category in the multiple bound patient information is associated. Through the association identifier contained in the target patient information, the patient information with the association identifier is searched in the patient information database, and the patient information is determined to be the patient information matching the target patient information. In some cases (for example, when the medical record is an order, for business strategy considerations, it is necessary to merge the patient information of twins and then create or edit the order. The twins are actually two different patients; for example, the patient information of a couple can be merged and then create or edit the order. The couple is actually two different patients. The above-mentioned merged patient information can facilitate medical staff to carry out commercial marketing activities such as order discount processing), when the user needs to merge the patient information of different patients with association, it can meet the user's need to merge different patients with associated data of specified categories in the patient information.

[0052] For example: assuming that the association identifier is a birthday identifier, then the data of the specified category is birthday data. Assuming that the birthday identifier only contains the date: January 1, 2000, then the birthday data contained in the patient information in the patient information database for January 1, 2000 is associated. The corresponding patients may be different patients, but there is an association between the patients, for example, the different patients are twins, triplets, etc. The association identifier can also be other identifiers, such as an address identifier. If the data of the specified category is address data, then the data with the same address data contained in the patient information in the patient information database is associated. The corresponding patients may be different patients, but there is an association between the patients, for example, multiple family members at the same address.

[0053] It is worth noting that the above description of the specific implementation of the association identifier and the specified category is only an exemplary display. In actual application, other specific implementations are not excluded. Therefore, there is no limitation on the specific implementation of the association identifier and the specified category.

[0054] As an example, the amount of data that can be used for fuzzy search in the target patient information can be greater than the other patient information in the above-mentioned multiple patient information. Among the multiple patient information bound to the target patient, the patient information with the largest amount of data that can be used for fuzzy search among the multiple patient information is determined as the target patient information, which can ensure that the data based on the fuzzy search is sufficient, further ensuring the scope and accuracy of the search. It is worth noting that the above description of the amount of data that can be used for fuzzy search in the target patient information is only an example display. In actual application, other data amounts are not excluded, and there is no specific limitation on this.

[0055] For example, data within the target patient information that can be used for fuzzy search can include one or more of the patient's name, gender, contact information, birthday, medical history (e.g., hypertension, diabetes), CBCT data, CT data, or X-ray image information. It should be noted that the description of data that can be used for fuzzy search is merely illustrative; in actual applications, other data, such as the patient's address, may also be used. The specific implementation of data that can be used for fuzzy search is not limited.

[0056] As an example, after searching for patient information that matches the target patient information in the patient information database, the matching relationship can be stored in the patient information database. When adding new patient information or modifying the entered patient information in the future, the matching relationship can be directly used to determine whether the changed (newly added or modified) patient information matches.

[0057] S203: Merge the matched patient information into the target patient information, and process the target patient's medical records and the medical records of the patient corresponding to the matched patient information according to the merged patient information.

[0058] In another embodiment, when a target patient is detected in a patient information database as having multiple patient records associated with them, the electronic device displays an information merging interface that includes the target patient's medical records and the medical records of similar patients. In response to a user's confirmation operation on the information merging interface, the electronic device searches the patient information database for dental model data of similar patients and compares it with the target patient's dental model data to determine dental similarity. If the dental similarity is greater than or equal to a preset threshold, the medical records of the similar patients are merged into the medical records of the target patient. If the dental similarity is less than the preset threshold, a prompt message is generated.

[0059] The information merging interface may further include a control indicating information merging, for example, a "Merge Patient" button. Confirmation may include a click operation, etc. The preset threshold may be set based on actual needs, for example, 80%. The prompt may be configured to indicate that similar patients are not the same user as the target patient.

[0060] When this embodiment detects that a target patient is bound to multiple patient information in the patient information database, it displays an information merging interface to intuitively display the relevant information of the target patient and similar patients. Then, when a user's confirmation operation is detected, the dental model data of similar patients is compared with the dental model data of the target patient. When the dental similarity is greater than or equal to a preset threshold, the medical records of similar patients are merged into the medical records of the target patient, thereby improving the rationality of the merging of medical records.

[0061] In another embodiment, before searching for tooth model data of similar patients in the patient information database and comparing the tooth model data with the tooth model data of the target patient, the electronic device decompresses the tooth model data searched from the patient information database.

[0062] In this embodiment, since the tooth model data stored in the patient information database is compressed data, the reading efficiency of the tooth model data is improved.

[0063] The "medical record" of this application refers to all files containing patient information. Medical records can have multiple specific forms and specific sources. For example, a medical record can be a medical file (such as a diagnosis file, physical examination file, health care file or convalescent file, etc.) or scan data created by medical staff for the patient when the patient is seeing the doctor; a medical record can also be a medical record file (such as historical medical records, allergy records, etc.) and medical data (such as scan models, CBCT data, CT data or X-ray image information, etc.) retained in other hospitals provided by the patient to the hospital (clinic), physical examination center, health care center, sanatorium, etc. when the patient is seeing the doctor; a medical record can also be a medical record provided by a cooperating hospital when multiple hospitals make a joint diagnosis. The patient's medical records (such as historical medical records, allergy records, etc.) and medical data (such as scan models, CBCT data, CT data or X-ray image information) sent to the main hospital; the medical records can also be the orders (such as dental mold orders, orthodontic appliance orders, retainer orders, etc.) created by the dental laboratory for the patient after the patient's visit to the hospital. The medical records can also be the patient's medical records (such as historical medical records, allergy records, etc.) and medical data (such as scan models, CBCT data, CT data or X-ray image information) retained by the hospital (clinic), physical examination center, health center, sanatorium or dental laboratory. Therefore, this application does not limit the specific form and specific source of the medical records.

[0064] The matched patient information can be merged into the target patient information in a variety of ways. For example, one of the ways may include: merging the matched patient information into the above-mentioned target patient information in response to a user confirmation instruction. The user confirmation instruction may be issued after the user confirms the above-mentioned matched patient information. For example: after searching for patient information that matches the target patient information, the matched patient information may be sent to the user, and the user is requested to confirm the matched patient information and confirm whether to merge. When the user confirms the matched patient information and confirms that it needs to be merged, a user confirmation instruction may be issued, and in response to the instruction, the matched patient information is merged into the target patient information. It is worth noting that the above description of the merging method is only an exemplary display. In actual application, other merging methods are not excluded. For example, after searching for patient information that matches the target patient information, the matched patient information is automatically merged into the target patient information without user confirmation. Therefore, there is no specific limitation on the merging method.

[0065] As an example, the medical record processing method of any of the above embodiments may be executed in response to a user's trigger request, which may include a request for creating new patient information for a target patient or a request for merging multiple patient information.

[0066] As an example, the above-mentioned user may be a medical staff who is treating a patient, or may be other users, and there is no specific limitation on this.

[0067] As an example, taking the above-mentioned user as a medical staff who is treating a patient, the new patient information request for the target patient can be a new patient information request issued by the medical staff when creating a treatment record for the target patient while treating the target patient.

[0068] As an example, the request to merge multiple patient information may be a request issued by a user after the user finds multiple duplicate patient information during a consultation or non-consultation period for the patient.

[0069] It is worth noting that the above description of the execution conditions of the medical record processing method of any of the above embodiments is only an example display. In actual application, other execution conditions are not excluded and are not specifically limited to this.

[0070] As an example, the medical record processing method of any of the above embodiments can be applied to a distributed system, which may include several clients. The medical record processing method of any of the above embodiments can be executed by the distributed system in response to a user's trigger request (for example, a request for new patient information for a target patient or a request to merge multiple copies of patient information). If the distributed system receives user trigger requests sent by multiple clients at the same time, that is, when it receives multiple trigger requests at the same time, it can respond to the multiple trigger requests one by one and execute the medical record processing method of any of the above embodiments, thereby ensuring that the distributed system executes serially to achieve the uniqueness of the execution, ensuring the atomicity of the merged transaction, and thus ensuring the stability of the system's execution transactions.

[0071] For example: when the distributed system receives two trigger requests at the same time, it can respond to and execute one of the trigger requests first and then respond to the other trigger request based on the priority and other judgment principles; when the distributed system receives two trigger requests at the same time, it can also respond to and execute only one of the trigger requests based on the priority and other judgment principles, and prompt the client that the response to the other trigger request failed.

[0072] It should be noted that the distributed system may only include a number of clients, which receive trigger requests sent by each other, respond to the trigger requests, and execute the medical record processing method of any of the above embodiments.

[0073] The distributed system may also include a main control center located locally or in the cloud, which receives the trigger request sent by the client, responds to the trigger request, and executes the medical record processing method of any of the above embodiments.

[0074] It is worth noting that the above description of the system applicable to the medical record processing method of any of the above embodiments is only an exemplary display. In actual application, other applicable systems are not excluded and are not specifically limited to this.

[0075] As an example, the medical record processing method of any of the above embodiments can be applied to a distributed system, which may include a cloud and several clients. Upon receiving the above-mentioned trigger request sent by any client, the cloud can be configured to execute the steps in the medical record processing method of any of the above embodiments and synchronize the execution results to all clients.

[0076] As an example, if the above-mentioned cloud successfully merges the patient information, it can attribute the historical medical records of the patient corresponding to the merged patient information to the medical records of the above-mentioned target patient, and send a prompt of the successful merger to the above-mentioned client; if the above-mentioned cloud system fails to merge the patient information successfully (for example, when the sending network is abnormal, or the cloud system is in data maintenance status, or the cloud system is serially processing multiple merge requests initiated simultaneously), it can send a prompt of the merge failure to the above-mentioned client.

[0077] It is worth noting that the above description of the execution subject is only an example. In actual application, other execution subjects are not excluded and no specific limitation is made to this.

[0078] For example, before determining the target patient information, the patient information database may be searched for patient information related to the target patient at preset intervals. If the patient information database actually contains multiple duplicate patient information related to the target patient, and the user has not discovered the duplicates, the system can automatically search for similar patient information related to the target patient at regular intervals. If the system detects that the target patient is associated with multiple copies of patient information in the patient information database, the system triggers execution of the medical record processing method of any of the above embodiments.

[0079] As an example, the target patient and the patient corresponding to the matched patient information may be the same patient or different patients, and there is no specific limitation on this.

[0080] For example, after the matched patient information is merged into the target patient information, the patient information contained in any medical record of the target patient can be updated to the target patient information, which can further ensure the uniformity of the merged multiple patient information.

[0081] For example, if it is detected that the patient information contained in any medical record of the target patient is different from the target patient information, an update prompt can be issued to the user to remind the user to update the patient information. If the user agrees to the update, the patient information that is different from the target patient information can be updated to the target patient information in response to the user's instructions; if the user does not agree to the update, the patient information that is different from the target patient information can be set to read-only in response to the user's instructions. It is worth noting that the description of the triggering conditions for updating patient information is only an example. In actual application, other triggering conditions are not excluded and are not specifically limited to this.

[0082] Please refer to FIG3 , and the specific application scenario of processing the patient's medical records according to an embodiment of the present application is exemplarily described below:

[0083] Assume that there are two patients A and B, and the patient information bound to patient A has been entered in the patient information database, such as the three patient information in Figure 3: patient A information 1, patient A information 2, and patient A information 3. Then, for the medical staff who subsequently sees patient A, taking the patient's medical record as the patient's order as an example, when it is necessary to create a dental order for patient A, it may not be found that there are multiple duplicate information of patient A in the patient information database. Then, when the medical staff sends a request for new patient information for patient A through the client, the cloud system can respond to the request. When it is detected in the patient information database that there are multiple copies of patient information bound to patient A (for example, when it is detected that patient A has multiple copies of patient information), Patient A information 1, patient A information 2; or patient A information 1, patient A information 3 are detected), target patient information is determined (for example, when patient A information 1 and patient A information 2 are detected, patient A information 1 is determined as target patient information), assuming that the target patient information is patient A information 1, based on the data in patient A information 1 that can be used for fuzzy search, patient information that matches patient A information 1 is searched for in the patient information database (such as patient A information 2, patient A information 3), and patient A information 2 and patient A information 3 are merged into patient A information 1 to obtain the merged patient information, so as to process the order of patient A according to the merged patient information.

[0084] If patient A and patient B are related patients and there is the same association identifier in their respective patient information, then patient B's patient information can also be merged, as shown in Figure 3, patient B information 1, patient A information 2, and patient A information 3 are merged into patient A information 1.

[0085] The technical solution provided by the embodiment of the present application determines a target patient information when there are multiple duplicate patient information for a target patient in the patient information database, and merges all the patient information matching the target patient information into the target patient information. This allows the creation or editing of the target patient's medical records and the medical records of the patients corresponding to the matched patient information only based on the merged patient information, thereby improving the efficiency of medical record creation. At the same time, when searching for patient information matching the target patient information in the patient information database, fuzzy matching can be performed in the patient information database based on the data in the target patient information that can be used for fuzzy search, thereby improving the search efficiency while ensuring a larger search range and making the search results more accurate.

[0086] Corresponding to the above method embodiment, the present application embodiment further provides a medical record processing device, as shown in FIG4 , which may include:

[0087] The determining unit 401 is configured to determine the target patient information when it is detected in the patient information database that the target patient is bound to multiple patient information, where the target patient information is one of the multiple patient information;

[0088] A search unit 402 is configured to search the patient information database for patient information that matches the target patient information based on data associated with the target patient information, wherein the associated data includes data in the target patient information that can be used for fuzzy search;

[0089] Merging unit 403 is configured to merge the matched patient information with the target patient information, and process the target patient's medical records and the medical records of the patient corresponding to the matched patient information based on the merged patient information. For example, when the above-described medical record processing device is applied to an oral scanning scenario, the data in the target patient information that can be used for fuzzy search includes the target patient's dental model data, and the target patient is the same patient with multiple sets of patient information associated with them.

[0090] As an example, the data in the target patient information that can be used for fuzzy search includes association identifiers, which indicate whether data of a specified category in different patient information is associated; the target patient is bound to the patient information of multiple patients, and the data of a specified category in the multiple bound patient information is associated.

[0091] As an example, the amount of data that can be used for fuzzy search in the target patient information is greater than that of other patient information in the plurality of patient information.

[0092] For example, the data in the target patient information that can be used for fuzzy search includes one or more of the patient's name, gender, contact information, birthday, medical history, CBCT data, CT data, or X-ray image information. For example, the determination unit 401 is further configured to search the patient information database for patient information specific to the target patient at predetermined intervals.

[0093] As an example, the merging unit 403 is further configured to update the patient information included in any consultation record of the target patient to the target patient information.

[0094] As an example, the storage unit 404 is configured to compress the tooth model data based on the Huffman coding algorithm, and store the compressed tooth model data in the patient information database.

[0095] As an example, before compressing the tooth model data, the acquisition unit 405 is configured to obtain the oral image data acquired by the oral scanner; the preprocessing unit 406 is configured to respond to the user's operation of the oral scanner, preprocess the acquired oral image data, and obtain preprocessed oral image data; the reconstruction unit 407 is configured to perform three-dimensional reconstruction on the preprocessed oral image data to obtain the tooth model data.

[0096] As an example, the preprocessing unit 406 is specifically configured to: identify miscellaneous data and / or gum information from the collected oral image data; remove the miscellaneous data and / or gum information from the collected oral image data to obtain preprocessed oral image data.

[0097] As an example, before compressing the tooth model data, the identification unit 408 is configured to identify the gum area from the tooth model data; the deletion unit 409 is configured to remove the gum area from the tooth model data to obtain the tooth model data without gum information.

[0098] As an example, the display unit 410 is configured to display an information merging interface when it is detected in the patient information database that the target patient is bound to multiple patient information. The information merging interface includes the medical records of the target patient and the medical records of similar patients; the search unit 402 is also configured to respond to the user's confirmation operation on the information merging interface, search for the tooth model data of similar patients from the patient information database and compare it with the tooth model data of the target patient to obtain the tooth similarity; the merging unit 403 is also configured to merge the medical records of similar patients into the medical records of the target patient if the tooth similarity is greater than or equal to a preset threshold; the generation unit 411 is configured to generate a prompt message if the tooth similarity is less than a preset threshold.

[0099] The present application also provides an electronic device, as shown in FIG5 , which includes:

[0100] Processor 501;

[0101] a memory 502 configured to store processor-executable instructions;

[0102] The processor 501 is configured to implement the medical record processing method described in any of the above embodiments.

[0103] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the medical record processing method described in any one of the above embodiments is implemented.

[0104] The above is only a specific implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application. Industrial Applicability

[0105] When there are multiple duplicate patient information for the target patient in the patient information database, one target patient information is determined, and all patient information matching the target patient information is merged into the target patient information. This allows the target patient's medical records and the patient's medical records corresponding to the matched patient information to be created or edited based on the merged patient information, thereby improving the efficiency of medical record creation. At the same time, when searching for patient information matching the target patient information in the patient information database, fuzzy matching can be performed in the patient information database based on data in the target patient information that can be used for fuzzy search. This improves search efficiency while ensuring a larger search range, making search results more accurate and having strong industrial applicability.

Claims

1. A method for processing medical records, wherein: include: When it is detected in the patient information database that a target patient is bound to multiple patient information, the target patient information is determined, where the target patient information is one of the multiple patient information; Based on the data associated with the target patient information, searching the patient information database for patient information matching the target patient information, wherein the associated data includes data in the target patient information that can be used for fuzzy search; The matched patient information is merged into the target patient information, so as to process the medical records of the target patient and the medical records of the patient corresponding to the matched patient information according to the merged patient information.

2. The method according to claim 1, wherein: The step of merging the matched patient information into the target patient information includes: In response to a user confirmation instruction, the matched patient information is merged into the target patient information, and the user confirmation instruction is issued after the user confirms the matched patient information.

3. The method according to claim 1, wherein: When the method is applied to an oral scanning scenario, the data in the target patient information that can be used for fuzzy search includes the tooth model data of the target patient, and the target patient is the same patient to which multiple patient information is bound.

4. The method according to claim 1, wherein: The data in the target patient information that can be used for fuzzy search includes an association identifier, which indicates whether data of a specified category in different patient information is associated; the target patient is bound to the patient information of multiple patients, and the data of a specified category in the bound multiple pieces of patient information are associated.

5. The method according to claim 1, wherein: The amount of data in the target patient information that can be used for fuzzy search is greater than that of other patient information in the multiple pieces of patient information.

6. The method according to claim 1, wherein: The data in the target patient information that can be used for fuzzy search includes one or more of the patient's name, the patient's gender, the patient's contact information, the patient's birthday, the patient's medical history, CBCT data, CT data or X-ray image information.

7. The method according to claim 1, wherein: The method is executed in response to a trigger request from a user, wherein the trigger request includes a request for creating new patient information for the target patient or a request for merging multiple copies of patient information.

8. The method according to claim 7, wherein: The method is applicable to a distributed system, which includes a plurality of clients. When the trigger requests sent by a plurality of clients are received at the same time, the method responds to the trigger requests one by one.

9. The method according to claim 7, wherein: The method is applicable to a distributed system, which includes a cloud and several clients. When the cloud receives the trigger request sent by any client, it is configured to execute the steps in the method and synchronize the execution results to all clients.

10. The method according to claim 1, wherein: Before determining the target patient information, the method further includes: At preset time intervals, the patient information database is searched for the patient information of the target patient.

11. The method according to claim 1, wherein: After merging the matched patient information into the target patient information, the method further includes: The patient information contained in any medical record of the target patient is updated to the target patient information.

12. The method according to claim 3, wherein: The method further comprises: The tooth model data is compressed based on a Huffman coding algorithm, and the compressed tooth model data is stored in the patient information database.

13. The method according to claim 3, wherein: The method further comprises: Acquire oral image data collected by an oral scanner; In response to the user's operation on the oral scanner, preprocessing the collected oral image data to obtain preprocessed oral image data; The preprocessed oral image data is three-dimensionally reconstructed to obtain the tooth model data.

14. The method according to claim 13, wherein: The preprocessing of the collected oral image data to obtain preprocessed oral image data includes: Identifying miscellaneous data and / or gum information from the collected oral image data; The miscellaneous data and / or the gum information are removed from the collected oral image data to obtain the preprocessed oral image data.

15. The method according to claim 3, wherein: The method further comprises: identifying a gingival region from the tooth model data; The gum area is removed from the tooth model data to obtain the tooth model data without gum information.

16. The method according to claim 1, wherein: The method further comprises: When it is detected in the patient information database that the target patient is bound to multiple patient information, an information merging interface is displayed, and the information merging interface includes the medical records of the target patient and the medical records of similar patients; In response to the user's confirmation operation on the information merging interface, searching the patient information database for the tooth model data of the similar patient and comparing the tooth model data of the target patient to obtain the tooth similarity; If the tooth similarity is greater than or equal to a preset threshold, the medical records of the similar patients are merged into the medical records of the target patient; If the tooth similarity is less than the preset threshold, a prompt message is generated.

17. A medical record processing device, wherein: include: A determination unit is configured to determine target patient information when it is detected in the patient information database that a target patient is bound to multiple patient information, wherein the target patient information is one of the multiple patient information; A search unit is configured to search for patient information matching the target patient information in the patient information database based on data associated with the target patient information, wherein the associated data includes data in the target patient information that can be used for fuzzy search; The merging unit is configured to merge the matched patient information into the target patient information, so as to process the medical records of the target patient and the medical records of the patient corresponding to the matched patient information according to the merged patient information.

18. An electronic device, wherein: include: processor; a memory configured to store processor-executable instructions; The processor is configured to implement the method according to any one of claims 1 to 16.

19. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are implemented.

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