CN116825265A - Treatment record processing method and device, electronic equipment and storage medium - Google Patents
Treatment record processing method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN116825265A CN116825265A CN202311103437.3A CN202311103437A CN116825265A CN 116825265 A CN116825265 A CN 116825265A CN 202311103437 A CN202311103437 A CN 202311103437A CN 116825265 A CN116825265 A CN 116825265A
- Authority
- CN
- China
- Prior art keywords
- information
- doctor
- target
- data
- consultants
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title abstract description 15
- 238000000034 method Methods 0.000 claims abstract description 46
- 238000012545 processing Methods 0.000 claims abstract description 19
- 230000008569 process Effects 0.000 claims abstract description 13
- 238000003745 diagnosis Methods 0.000 claims description 23
- 230000004044 response Effects 0.000 claims description 9
- 238000007408 cone-beam computed tomography Methods 0.000 claims description 7
- 238000012790 confirmation Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 4
- 230000036541 health Effects 0.000 description 5
- 210000000214 mouth Anatomy 0.000 description 5
- 230000000474 nursing effect Effects 0.000 description 4
- 239000013566 allergen Substances 0.000 description 3
- 208000002925 dental caries Diseases 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 206010020772 Hypertension Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000003446 ligand Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 230000026676 system process Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Landscapes
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The application discloses a treatment record processing method, a treatment record processing device, electronic equipment and a computer readable storage medium, wherein the treatment record processing method comprises the following steps: when the target doctor is detected to be bound with a plurality of pieces of doctor information in the doctor information base, determining the target doctor information, wherein the target doctor information is one piece of doctor information in the plurality of pieces of doctor information; searching the information of the doctor matched with the information of the target doctor in the information base of the doctor based on the data related to the information of the target doctor, wherein the related data comprises the data which can be used for fuzzy searching in the information of the target doctor; combining the matched information of the patients with the target information of the patients to process the records of the target patients and the records of the patients corresponding to the matched information of the patients according to the combined information of the patients. The method can improve the creation efficiency of the visit record, and ensure a larger search range while improving the information search efficiency of the visit person, so that the search result is more accurate.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method and apparatus for processing a diagnosis record, an electronic device, and a computer readable storage medium.
Background
When a doctor makes a doctor visit in a dental office, medical staff in the office needs to input information of the doctor when the doctor creates a dental order for the doctor, and the medical staff needs to input the information of the doctor in a dental software system.
For the same doctor, when creating a dental order for the doctor, if the information of the doctor does not exist in the dental software system, the medical staff is required to input the information of the doctor into the dental software system, and if the information of the doctor is already input in the dental software system, the information of the doctor can be directly searched out for selection and use. However, the medical staff may not use the entered information of the doctor due to misoperation and the like, but repeatedly enter the information of the same doctor into the dental software system, so that in the process of subsequently creating dental orders, when searching for the entered information of the doctor, multiple pieces of repeated information of the same doctor may exist, which brings inconvenience for data selection and editing and reduces the efficiency of creating orders.
Disclosure of Invention
In order to solve the technical problems, the application provides a treatment record processing method, a treatment record processing device, electronic equipment and a computer readable storage medium, wherein the technical scheme is as follows:
according to a first aspect of the present application, there is provided a method of processing a visit record, the method comprising:
when the target doctor is detected to be bound with a plurality of pieces of doctor information in the doctor information base, determining the target doctor information, wherein the target doctor information is one piece of doctor information in the plurality of pieces of doctor information;
searching the information of the target consultant in the consultant information base based on the data associated with the information of the target consultant, wherein the associated data comprises data which can be used for fuzzy searching in the information of the target consultant;
combining the matched information of the consultants to the target information of the consultants so as to process the records of the target consultants and the records of the consultants corresponding to the matched information of the consultants according to the combined information of the consultants.
According to a second aspect of the present application, there is provided a diagnosis record processing apparatus comprising:
the determining unit is used for determining target doctor information when the target doctor is detected to be bound with a plurality of pieces of doctor information in the doctor information base, wherein the target doctor information is one piece of doctor information in the plurality of pieces of doctor information;
a search unit, configured to search, in the visitor information base, visitor information that matches the target visitor information based on data associated with the target visitor information, where the associated data includes data that can be used for fuzzy search in the target visitor information;
the merging unit is used for merging the matched information of the consultants to the target information of the consultants so as to process the diagnosis records of the target consultants and the diagnosis records of the consultants corresponding to the matched information of the consultants according to the merged information of the consultants.
According to a third aspect of the present application, there is provided an electronic device comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to implement the method according to the first aspect.
According to a fourth aspect of the present application there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method according to the first aspect.
According to the technical scheme provided by the application, when multiple pieces of repeated doctor information aiming at the target doctor exist in the doctor information base, one piece of target doctor information is determined, and the doctor information matched with the target doctor information is combined under the target doctor information, so that the doctor record of the target doctor and the doctor record of the doctor corresponding to the matched doctor information are only required to be created or edited on the basis of the combined doctor information, the creation efficiency of the doctor record is improved, and meanwhile, when the doctor information matched with the target doctor information is searched in the doctor information base, fuzzy matching can be carried out in the doctor information base on the basis of the data which can be used for fuzzy searching in the target doctor information, the searching efficiency is improved, and meanwhile, the larger searching range is ensured, and the searching result is more accurate.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings required for the embodiments or the related technical descriptions will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to the drawings for those skilled in the art.
FIG. 1 is a schematic view of a related art treatment scenario for a doctor's visit record;
FIG. 2 is a flow chart of a method of treatment recording according to the present application;
FIG. 3 is a schematic diagram of a process scenario of a doctor's visit record according to one embodiment of the present application;
fig. 4 is a schematic structural view of a diagnosis record processing apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present specification.
Detailed Description
In order that those skilled in the art will better understand the technical solutions of the present application, the following detailed description of the technical solutions of the embodiments of the present application will be given with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the application, shall fall within the scope of protection of the application.
Referring to fig. 1, a scenario of a treatment record of a doctor in the related art is described, taking a dental scenario as an example, and taking a doctor's treatment record as an example of an order of the doctor, when the doctor is in a dental office or a hospital, and a doctor's medical staff creates a dental order for the doctor, the dental order needs to include information of the doctor, the medical staff needs to input the information of the doctor in a dental software system, the input information of the doctor belongs to the dental office or the hospital, and different medical staff in the same office or the hospital may share the information of the doctor already input by the dental software system when creating the order for the doctor.
For the same doctor, when creating a dental order for the doctor, if the information of the doctor does not exist in the dental software system, the medical staff is required to input the information of the doctor into the dental software system, and if the information of the doctor is already input in the dental software system, the information of the doctor can be directly searched out for selection and use. However, the medical staff may not use the entered information of the same doctor due to misoperation and the like, but repeatedly enter the information of the same doctor into the dental software system, and when the information of the same doctor is entered into the dental software system, only the information of the name, the contact mode and the like of the same doctor are entered, the identification of the name, the contact mode and the like can be changed, and in view of protecting privacy, the privacy data of the same doctor can not be uniquely identified, such as an identity card number and the like, so the entered information of the doctor is not unique, and the dental software system cannot judge whether the information of the same doctor which is entered for multiple times belongs to the same doctor or not actually, and can only be regarded as different doctor information for recording. In the subsequent process of creating dental orders, when the information of the entered doctor is searched, multiple pieces of repeated doctor information of the same doctor may exist, so that inconvenience in data selection and editing is brought, and the efficiency of creating the doctor record is reduced.
Taking fig. 1 as an example, the above scenario is described exemplarily:
assuming that there is a doctor B, if there is no information of the doctor B in the dental software system, a medical staff who needs to visit the doctor B first inputs the doctor information of the doctor B to the dental software system, for example, for the medical staff 1, if the doctor B is a first visit at a clinic where the medical staff 1 is located, there may be no information of the doctor B in the dental software, and the medical staff 1 needs to input the information of the doctor B (doctor B information 1) first when the doctor B is at a visit; assuming that there is a doctor a, if the doctor information of the doctor a has been entered in the dental software system, for example, three pieces of the doctor information in fig. 1: for the medical staff 2, if a dental order needs to be created for the patient a when the patient a is in the doctor, any piece of information of the patient a can be directly searched in the dental software system to select the user, however, the medical staff 1 may not use the entered patient information (the patient a information 1, the patient a information 2, the patient a information 3) because of misoperation (for example, the medical staff 1 misjudges that the patient a is in the local doctor for the first time) and the like, and repeatedly enter the information (the patient a information 1, the patient a information 2, the patient a information 3) of the patient a into the dental software system, and if the patient 3 is in the next doctor of the patient a, the information a (the patient a information 1, the patient a information 2, the patient a 3, the patient a information 4) is not used for similar operation errors, the information a can be repeatedly input into the dental software system, and the information a can be repeatedly input into the dental software system (the patient a information a) when the order is not created by the patient a, the patient a is in the system, and the patient a is 5, and the information a can be repeatedly input into the system (the patient a information a is in the system, and the patient a is 5) when the order is in the patient a system, and the patient a is in the patient has the system is in the patient a need of the information a is in the system, and the patient a is in the patient b is in the patient information is in the patient a system, and the patient is in the patient a patient is in the patient system and the patient a system.
It should be noted that the above description of the scenario of the doctor's recording process is only exemplary, and in practical application, the existence of other scenarios of the doctor's recording process is not excluded, which is not limited in particular.
For example: the consultant may be a physical examination, a ligand, a patient, or a patient; the medical staff can be doctors, nurses, physical examination staff, health care staff or nursing staff; the treatment recording processing scene may be a scene of a hospital (clinic), a physical examination center, a health care center, a nursing home, or a dental laboratory (mechanic) of a hospital (clinic), or the like.
In view of the above problems, the present application provides a treatment method for a diagnosis record, which can improve the creation efficiency of the diagnosis record, and ensure a larger search range while improving the information search efficiency of the diagnosis person, so that the search result is more accurate. As shown in fig. 2, the method comprises the steps of:
s201, when the fact that a plurality of pieces of information of the target doctor are bound in a doctor information base is detected, determining the target doctor information, wherein the target doctor information is one piece of information of the plurality of pieces of information of the doctor;
the physician information base may have a variety of specific implementations, one of which may include, by way of example: the physician information base may be a pre-built database that can be used to store the physician information.
By way of example, taking the dental scenario as an example, the interviewee information base may be a database that is assigned to a dental software system, which may be a local database or a cloud database.
The plurality of pieces of patient information bound to the target patient may be the plurality of pieces of patient information previously recorded in the patient information base, or the plurality of pieces of patient information may be recorded in the patient information base only during the detection process, and the recording time point of the plurality of pieces of patient information is not particularly limited.
As an example, the target doctor information may be determined according to one piece of doctor information selected by the user from the plurality of pieces of doctor information, for example, if the medical staff clicks one piece of doctor information among the plurality of pieces of doctor information bound to the target doctor, the clicked piece of doctor information may be determined as the target doctor information.
It should be noted that the above description of the determination manner of the target doctor information is merely exemplary, and in practical applications, other determination manners are not excluded, for example, the information amount included in each piece of doctor information may be determined from the pieces of doctor information, and the doctor information with the largest information amount may be determined as the target doctor information, so the determination manner of the target doctor information is not specifically limited.
S202, searching out the information of the doctor matched with the information of the target doctor in the information base of the doctor based on the associated data of the information of the target doctor, wherein the associated data comprises the data which can be used for fuzzy searching in the information of the target doctor;
as an example, taking an oral scan scenario as an example, the data that can be used for fuzzy search in the target visitor information may include tooth model data of the target visitor, which may be the same visitor to which multiple pieces of visitor information are bound. For different visitors, if the degree of similarity of the information of the visitors among a plurality of actual different visitors is very high, for example, the names, sexes, contact ways, birthdays or past medical histories in the information of the visitors of the different visitors are all consistent, whether the corresponding visitors are different visitors or not is difficult to judge by the information of the visitors alone, the judgment can be carried out by means of the tooth model data related to the information of the visitors at the moment, even if the information of the visitors among two different visitors is highly overlapped, the difference exists in the tooth model data, the tooth model data can play the role of uniquely identifying the visitors, and the fuzzy search matching can be carried out by the tooth model data obtained by oral scanning under an oral scanning scene, so that the search precision is further improved.
By way of example, the dental model data may be collected by an oral scanner within the mouth of the practitioner. As a second example, the dental model data may be acquired in the mouth of the patient by an oral scanner having an infrared light function. When teeth in the oral cavity are scanned, visible light (such as laser or white light) emitted by an oral cavity scanner can acquire external information (such as shape, color and the like of the teeth) of the teeth so as to reconstruct a three-dimensional model of the teeth, on the basis of the visible light, the oral cavity scanner with an infrared light function can also emit infrared light, can acquire internal information (such as caries and the like) of the teeth through the infrared light, and can mark relevant internal information (such as caries information, namely the number, shape, position and the like of the caries) on the three-dimensional model of the teeth based on the tooth picture acquired by the infrared light so that the acquired tooth model data is richer and more accurate.
By way of example, the tooth model data may include arch size data, tooth texture data, individual tooth size data, missing tooth data, or dental restorative material data, or other data.
As an example, when the data that can be used for the fuzzy search in the target visitor information includes tooth model data of the target visitor, one of the ways of searching the visitor information library for the visitor information that matches the target visitor information may include: and analyzing the difference value of the tooth model data of the target doctor and the tooth model data related to other doctor information by adopting a three-dimensional data abstraction analysis mode of the tooth model data, and determining the doctor information with the difference value smaller than or equal to a threshold value as the doctor information matched with the target doctor information. It should be noted that the foregoing description of the manner of performing fuzzy matching through the tooth model data is merely exemplary, and in practical application, other manners of performing fuzzy matching through the tooth model data are not excluded, which is not limited in particular.
It should be noted that the foregoing description of the data that can be used for the fuzzy search is merely exemplary, and in practical applications, other data are not excluded, and the specific implementation of the data that can be used for the fuzzy search is not limited.
It should be noted that the foregoing description of the collection manner and the specific implementation of the tooth model data is merely illustrative, and in practical application, other collection manners and specific implementations are not excluded, which are not limited thereto.
It should be noted that the above description of the oral scan scenario is only exemplary, and in practical application, other application scenarios, such as a face scan scenario, are not excluded, the associated data may also include five-sense organ data of the target patient, such as other medical scenarios, and the associated data may also include medical information, such as CBCT data, CT data, and X-ray picture information, which is not limited specifically to the application scenario.
As an example, the data in the target doctor information that can be used for fuzzy search may include an association identifier, where the association identifier may characterize whether the data in the specified category in the different doctor information has an association; the target reviewer may be bound with reviewer information for multiple reviewers, with the data of a specified category in the bound pieces of reviewer information having an association. Through the association identifier contained in the target doctor information, the doctor information with the association identifier is searched in the doctor information base, the doctor information is determined to be the doctor information matched with the target doctor information, in some cases (for example, when the doctor information is recorded as an order, the doctor information of two twins needs to be combined and then subjected to order creation or editing processing in terms of business strategies and the like, and the twins are actually two different consultants, for example, the doctor information of a pair of lovers can be combined and then subjected to order creation or editing processing, and the lovers are also actually two different consultants, so that the combined doctor information can be convenient for medical staff to perform business marketing activities such as order discount processing and the like), and the user can meet the combined requirement of the user on the different consultants with association on the specific type of data in the doctor information.
Illustrating: assuming that the association identifier is a birthday identifier, the data of the designated category is birthday data, and assuming that the birthday identifier only comprises date: the date of birth data included in the information base of the doctor information is 1 st 2000, and the date of birth data included in the information base of the doctor information is 1 st 2000, and the corresponding doctor may be different doctor, but the doctor has relevance, for example, the different doctor is twins, triplet, etc. The association identifier may be other identifiers, for example, an address identifier, and if the data of the specified category is address data, the data of the same address data included in the information of the doctor in the doctor information base has an association, and the corresponding doctor may be different doctor, but the doctor has an association, for example, a plurality of family members of the same address.
It should be noted that the foregoing description of specific implementations of the association identifier and the specified category is merely exemplary, and in practical application, other specific implementations are not excluded, and thus, the specific implementations of the association identifier and the specified category are not limited.
As an example, the data amount of the data that can be used for the fuzzy search in the target visitor information may be larger than other visitor information in the above-described pieces of visitor information. Among the multiple pieces of the patient information bound by the target patient, the patient information with the largest data volume of the data which can be used for fuzzy search in the multiple pieces of the patient information is determined as the target patient information, so that the data which is based on the target patient information is enough during fuzzy search, and the search range and the search precision are further ensured. It should be noted that the above description of the data size of the data that can be used for the fuzzy search in the target doctor information is only exemplary, and in practical application, other data sizes are not excluded, which is not limited in particular.
As examples, the data in the target visitor information that can be used for the fuzzy search may include one or more of visitor name, visitor gender, visitor contact, visitor birthday or visitor prior history (e.g., hypertension, diabetes, etc.), CBCT data, CT data, or X-ray picture information. It should be noted that the description of the data that can be used for the fuzzy search is merely an exemplary illustration, and in practical applications, other data, such as the address of the doctor, etc., are not excluded, and the specific implementation of the data that can be used for the fuzzy search is not limited.
As an example, after the information of the doctor matching with the target doctor information is searched in the doctor information base, the matching relationship may be stored in the doctor information base, and when the doctor information is newly added later or the registered doctor information is modified, the matching relationship may be directly used to determine whether the changed (newly added or modified) doctor information is matched.
S203, merging the matched information of the patients to the target information of the patients, so as to process the records of the target patients and the records of the patients corresponding to the matched information of the patients according to the merged information of the patients.
The application relates to a diagnosis record which refers to all files containing information of a doctor, and can have various specific expression forms and specific sources, and the diagnosis record can be a diagnosis file (such as a diagnosis file, a physical examination file, a health care file, a sanitarian file, etc.) or scan data which are created by medical staff for the doctor when the doctor makes a diagnosis;
the diagnosis record may also be a medical record file (such as a history diagnosis record, an allergen record, etc.) and medical data (such as scan model, CBCT data, CT data or X-ray picture information, etc.) which are provided by the diagnosis person to a hospital (clinic), a physical examination center, a health care center, a nursing home, etc.;
the diagnosis record can also be a medical record (such as a historical diagnosis record, an allergen record and the like) and medical data (such as a scanning model, CBCT data, CT data or X-ray picture information) of a doctor sent to a main hospital by a matched hospital when a plurality of hospitals are used for joint diagnosis;
the doctor records can also be that after the doctor makes a doctor visit in a hospital, the hospital transmits relevant doctor information to a dental laboratory (technical institute), and orders (such as dental model orders, appliance orders, retainer orders and the like) created by the technical staff for the doctor;
the medical records may also be medical records (e.g., historical medical records, allergen records, etc.) associated with a medical practitioner (e.g., scan model, CBCT data, CT data, or X-ray picture information) maintained by a hospital (clinic), physical examination center, health care center, nursing home, or dental laboratory (mechanic's office).
Accordingly, the specific form and specific source of the present application for the visit record are not limited.
The matching physician information may be incorporated into the target physician information in a variety of ways, one of which may include, by way of example: the matched information of the patient may be combined with the target information of the patient in response to a user confirmation instruction, which may be issued after the user confirms the matched information of the patient, for example: after searching out the doctor information matched with the target doctor information, the matched doctor information can be sent to the user, the user is requested to confirm the matched doctor information and confirm whether the matched doctor information is combined or not, when the user confirms the matched doctor information and confirms that the combination is needed, a user confirmation instruction can be sent out, and then the matched doctor information is combined to the target doctor information in response to the instruction. It should be noted that the above description of the merging mode is only exemplary, and in practical application, other merging modes are not excluded, for example, after the information of the patient who matches the target patient information is searched, the matched patient information is automatically merged into the target patient information without confirmation of the user, so the merging mode is not limited specifically.
As an example, the treatment record processing method described in any of the above embodiments may be performed in response to a trigger request from a user, where the trigger request may include a new-built-up-doctor information request for a target doctor or a request to combine multiple pieces of doctor information.
The user may be a medical staff member for a doctor to visit, or may be another user, and the specific example is not limited thereto.
As an example, taking the medical staff taking the user as the doctor for the doctor as an example, the new doctor information request for the target doctor may be the new doctor information request sent by the medical staff when the doctor is taking the doctor for the target doctor and creating the doctor record for the target doctor.
As an example, the request to merge multiple pieces of reviewer information may be a request issued by a user to merge multiple pieces of reviewer information after multiple repeated pieces of reviewer information are found during or during review for the reviewer.
It should be noted that the foregoing description of the execution conditions of the treatment recording processing method according to any of the foregoing embodiments is merely illustrative, and in practical application, other execution conditions are not excluded, which is not limited in particular.
As an example, the treatment record processing method described in any of the foregoing embodiments may be applied to a distributed system, where the distributed system may include a plurality of clients, where the treatment record processing method described in any of the foregoing embodiments may be executed by the distributed system in response to a trigger request of a user (for example, a new doctor information request for a target doctor or a request for merging multiple pieces of doctor information), where if the distributed system receives trigger requests of users sent by a plurality of clients at the same time, that is, when receiving multiple trigger requests at the same time, the treatment record processing method described in any of the foregoing embodiments may be executed in response to multiple trigger requests one by one, so as to ensure that the distributed system performs serially to implement the uniqueness of execution, and ensure atomicity of merged transactions, thereby ensuring stability of executing transactions of the system.
Illustrating: when the distributed system receives two trigger requests at the same time, one trigger request is responded and executed firstly according to the judging principles of priority and the like, and then the other trigger request is responded; when the distributed system receives two trigger requests at the same time, only one trigger request can be responded and executed according to the judging principles of priority and the like, and the other trigger request is prompted to fail to respond by the client.
It should be noted that the distributed system may only include a plurality of clients, where the clients mutually receive the trigger request sent by the client, respond to the trigger request, and execute the treatment record processing method described in any embodiment above.
The distributed system may further include a local or cloud master control center, where the local or cloud master control center receives the trigger request sent by the client, responds to the trigger request, and executes the treatment record processing method described in any embodiment above.
It should be noted that the above description of the system applicable to the treatment record processing method described in any of the foregoing embodiments is merely illustrative, and in practical application, other applicable systems are not excluded, which is not limited in particular.
As an example, the treatment record processing method described in any of the above embodiments may be applied to a distributed system, where the distributed system may include a cloud end and a plurality of clients, where the cloud end may be configured to execute the steps in the treatment record processing method described in any of the above embodiments and synchronize the execution result to all the clients when receiving the trigger request sent by any of the clients.
As an example, if the cloud end succeeds in merging the successful doctor information, the historical doctor records of the doctor corresponding to the merged doctor information may be attributed to the doctor records of the target doctor, and a prompt of successful merging may be sent to the client; if the cloud system fails to combine the successful doctor information (for example, if a network is abnormal, or the cloud system is in a data maintenance state, or the cloud system processes multiple simultaneous combining requests in series), a prompt of combining failure can be sent to the client.
It should be noted that the foregoing description of the execution subject is merely an exemplary illustration, and in practical application, other execution subjects are not excluded, which is not limited in particular.
As an example, before determining the target doctor information, the doctor information for the target doctor may be searched in the doctor information base at every predetermined time. The method for processing the diagnosis record according to any of the embodiments can be triggered to be executed when the target doctor information base actually has a plurality of pieces of repeated doctor information for the target doctor, and when the user does not find the repetition, similar doctor information for the target doctor is automatically searched periodically and when the target doctor is detected to be bound with a plurality of pieces of doctor information in the doctor information base.
As an example, the target doctor and the doctor corresponding to the matched doctor information may be the same doctor or different ones, and the specific is not limited.
As an example, after the matched doctor information is combined with the target doctor information, the doctor information included in any one of the doctor records of the target doctor may be updated to the target doctor information. The uniformity of the combined plurality of the doctor information can be further ensured.
As an example, if it is detected that the information of the target doctor included in any one of the doctor records of the target doctor is different from the information of the target doctor, an update prompt may be issued to the user to remind the user that the information of the target doctor may be updated, and if the user agrees to update, the information of the doctor different from the information of the target doctor may be updated to the information of the target doctor in response to the instruction of the user; if the user does not agree with the update, the doctor information different from the target doctor information may be set to a read-only state in response to an instruction of the user. It should be noted that the above description of the trigger condition of the update of the doctor information is only exemplary, and in practical application, other trigger conditions are not excluded, which is not limited in particular.
Referring to fig. 3, the following illustrates a specific application scenario of the treatment record processing of a doctor according to an embodiment of the present application:
assuming that there are two reviewers A, B, reviewer information for reviewer A binding has been entered into the reviewer information base, such as three pieces of reviewer information in FIG. 3: the medical staff who subsequently carries out the diagnosis for the patient a, such as the patient a, the patient a information 1, the patient a information 2 and the patient a information 3, when the patient a needs to create a dental order for the patient a, a plurality of pieces of repeated information of the patient a existing in the patient information base may not be found, the medical staff can respond to the request when sending a newly built patient information request for the patient a through the client, the cloud system can search for the information of the patient a based on the information of the patient a, and can obtain the information of the patient a by combining the information of the patient a with the information of the patient a (such as the patient a information 1 and the patient a information 2 are detected, or the patient a information 1 and the patient a information 3 are detected), the target patient information (such as the patient a information 1 and the patient a information 1 are determined to be the target patient information when the patient a is detected, the patient a information 1 is determined to be the target patient information), the target patient information is the patient a is determined, the patient a information is searched for the patient a based on the information a 1, and the information a is combined with the information of the patient a 2 based on the information of the patient a, and the patient a is combined with the information of the patient a 1 (such as the patient a information 1 is found by the patient b information).
If the doctor A and the doctor B are associated with each other, and the same associated identification exists in the respective doctor information, the doctor information of the doctor B can also participate in merging, such as merging the doctor B information 1, the doctor A information 2 and the doctor A information 3 into the doctor A information 1 in fig. 3.
According to the technical scheme provided by the embodiment of the application, when multiple pieces of repeated doctor information aiming at the target doctor exist in the doctor information base, one piece of target doctor information is determined, and the doctor information matched with the target doctor information is combined under the target doctor information, so that the doctor record of the target doctor and the doctor record of the doctor corresponding to the matched doctor information are only required to be created or edited on the basis of the combined doctor information, the creation efficiency of the doctor record is improved, and meanwhile, when the doctor information matched with the target doctor information is searched in the doctor information base, fuzzy matching can be carried out in the doctor information base on the basis of the data which can be used for fuzzy searching in the target doctor information, so that the searching efficiency is improved, and meanwhile, a larger searching range is ensured, and the searching result is more accurate.
Corresponding to the above method embodiment, the embodiment of the present application further provides a treatment record processing device, as shown in fig. 4, where the device may include:
a determining unit 401, configured to determine target doctor information when it is detected in a doctor information base that a target doctor is bound with a plurality of pieces of doctor information, where the target doctor information is one piece of doctor information in the plurality of pieces of doctor information;
a search unit 402, configured to search, in the visitor information base, visitor information that matches the target visitor information based on data associated with the target visitor information, where the associated data includes data that can be used for fuzzy search in the target visitor information;
and a merging unit 403, configured to merge the matched information of the patients with the target information of the patients, so as to process the record of the patients with the target information of the patients and the record of the patients corresponding to the matched information of the patients according to the merged information of the patients.
As an example, when the above-mentioned treatment record processing device is applied to an oral scanning scene, the data that can be used for fuzzy search in the target treatment person information includes tooth model data of the target treatment person, and the target treatment person is the same treatment person to which a plurality of treatment person information is bound.
As an example, the data in the target doctor information that can be used for fuzzy search includes an association identifier, where the association identifier characterizes whether the data in the specified category in the different doctor information has association; the target consultant is bound with the consultant information of a plurality of consultants, and the data of the specified category in the bound plurality of consultant information has relevance.
As an example, the amount of data that can be used for the fuzzy search in the target visitor information is larger than other visitor information in the plurality of pieces of visitor information.
As an example, the data in the target visitor information that can be used for the fuzzy search includes one or more of visitor name, visitor gender, visitor contact, visitor birthday, visitor prior history, CBCT data, CT data, or X-ray picture information.
As an example, the determining unit 401 is further configured to search the information base of the patients for the target patients at preset time intervals.
As an example, the merging unit 403 is further configured to update the information of the target doctor included in any one of the doctor records of the target doctor to the information of the target doctor.
The present application also provides an electronic device, as shown in fig. 5, including:
a processor 501;
a memory 502 for storing processor-executable instructions;
wherein the processor 501 is configured to implement the method of treatment record processing described in any of the embodiments above.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of treatment record processing described in any of the embodiments above.
The foregoing is merely illustrative of the embodiments of this application and it will be appreciated by those skilled in the art that variations and modifications may be made without departing from the principles of the application, and it is intended to cover all modifications and variations as fall within the scope of the application.
Claims (14)
1. A method of processing a visit record, comprising:
when the target doctor is detected to be bound with a plurality of pieces of doctor information in the doctor information base, determining the target doctor information, wherein the target doctor information is one piece of doctor information in the plurality of pieces of doctor information;
searching the information of the target consultant in the consultant information base based on the data associated with the information of the target consultant, wherein the associated data comprises data which can be used for fuzzy searching in the information of the target consultant;
combining the matched information of the consultants to the target information of the consultants so as to process the records of the target consultants and the records of the consultants corresponding to the matched information of the consultants according to the combined information of the consultants.
2. The method of claim 1, wherein the merging the matched-up visit information into the target visit information comprises:
and combining the matched information of the consultants to the target information of the consultants in response to a user confirmation instruction, wherein the user confirmation instruction is sent after the user confirms the matched information of the consultants.
3. The method of claim 1, wherein the data in the target attendant information that can be used for fuzzy searching when the method is applied to an oral scanning scenario comprises tooth model data of the target attendant, the target attendant being the same attendant to which multiple attendant information pieces are bound.
4. The method of claim 1, wherein the data in the target visitor information that can be used for the fuzzy search includes an association identifier that characterizes whether the specified category of data in the different visitor information has an association; the target consultant is bound with the consultant information of a plurality of consultants, and the data of the specified category in the bound plurality of consultant information has relevance.
5. The method of claim 1, wherein the amount of data in the target reviewer information that can be used for the fuzzy search is greater than other reviewer information in the plurality of pieces of reviewer information.
6. The method of claim 1, wherein the data in the target visitor information that can be used for the fuzzy search includes one or more of visitor name, visitor gender, visitor contact, visitor date, visitor prior history, CBCT data, CT data, or X-ray picture information.
7. The method of claim 1, wherein the method is performed in response to a user's trigger request, the trigger request comprising a request for new-built reviewer information for the target reviewer or a request to merge multiple reviewer information.
8. The method according to claim 7, wherein the method is applied to a distributed system, and the distributed system comprises a plurality of clients, and the trigger requests are responded one by one when the trigger requests sent by a plurality of clients are received simultaneously.
9. The method according to claim 7, wherein the method is applied to a distributed system, the distributed system comprises a cloud and a plurality of clients, and the cloud is used for executing steps in the method and synchronizing execution results to all clients when receiving the trigger request sent by any client.
10. The method of claim 1, wherein prior to the determining the target visit information, the method further comprises:
and searching the information of the consultants aiming at the target consultants in the information base of the consultants at preset time intervals.
11. The method of claim 1, wherein after the merging of the matched-up visit information into the target visit information, the method further comprises:
and updating the information of the target consultant contained in any one of the consultation records of the target consultant into the information of the target consultant.
12. A visit record processing device, characterized by comprising:
the determining unit is used for determining target doctor information when the target doctor is detected to be bound with a plurality of pieces of doctor information in the doctor information base, wherein the target doctor information is one piece of doctor information in the plurality of pieces of doctor information;
a search unit, configured to search, in the visitor information base, visitor information that matches the target visitor information based on data associated with the target visitor information, where the associated data includes data that can be used for fuzzy search in the target visitor information;
the merging unit is used for merging the matched information of the consultants to the target information of the consultants so as to process the diagnosis records of the target consultants and the diagnosis records of the consultants corresponding to the matched information of the consultants according to the merged information of the consultants.
13. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to implement the method of any one of claims 1 to 11.
14. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 11.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311103437.3A CN116825265A (en) | 2023-08-29 | 2023-08-29 | Treatment record processing method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311103437.3A CN116825265A (en) | 2023-08-29 | 2023-08-29 | Treatment record processing method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116825265A true CN116825265A (en) | 2023-09-29 |
Family
ID=88126149
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311103437.3A Pending CN116825265A (en) | 2023-08-29 | 2023-08-29 | Treatment record processing method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116825265A (en) |
Citations (28)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020007284A1 (en) * | 1999-12-01 | 2002-01-17 | Schurenberg Kurt B. | System and method for implementing a global master patient index |
| JP2006087669A (en) * | 2004-09-24 | 2006-04-06 | Toshiba Corp | Image inspecting device, image inspection program and image inspection method |
| CN103488783A (en) * | 2013-09-29 | 2014-01-01 | 方正国际软件有限公司 | Patient information matching system and patient information matching method |
| CN103544148A (en) * | 2012-07-09 | 2014-01-29 | 首都医科大学宣武医院 | Patient indexing method and system |
| CN104657248A (en) * | 2013-11-21 | 2015-05-27 | 中国移动通信集团山东有限公司 | Java thread stack analysis method and system |
| CN204814653U (en) * | 2015-08-21 | 2015-12-02 | 翟凯 | Novel supplementary reproduction section hospital outpatient service case history |
| CN106295182A (en) * | 2016-08-10 | 2017-01-04 | 依据数据（湖南）科技有限公司 | A kind of personal identification method based on patient biological information |
| CN106650259A (en) * | 2016-12-22 | 2017-05-10 | 深圳中兴网信科技有限公司 | Patient information management method and management system |
| US20180046679A1 (en) * | 2015-02-27 | 2018-02-15 | Koninklijke Philips N.V | Efficient integration of de-identified records |
| CN110709027A (en) * | 2017-06-08 | 2020-01-17 | 美多斯国际有限公司 | User interface system for sterile field and other work environments |
| CN111091884A (en) * | 2019-12-24 | 2020-05-01 | 无锡识凌科技有限公司 | Patient main index matching system and method of hospital information integration platform |
| CN112311887A (en) * | 2020-11-02 | 2021-02-02 | 陕西医链区块链集团有限公司 | Medical health file establishing method based on block chain technology |
| JP2021051394A (en) * | 2019-09-20 | 2021-04-01 | キヤノンメディカルシステムズ株式会社 | Medical information processing apparatus and program |
| WO2021202490A1 (en) * | 2020-03-31 | 2021-10-07 | Zoll Medical Corporation | Systems and methods of producing patient encounter records |
| CN113688135A (en) * | 2021-08-25 | 2021-11-23 | 四川互慧软件有限公司 | Hospital information integration method based on patient main index technology |
| WO2021233348A1 (en) * | 2020-05-20 | 2021-11-25 | 中山大学肿瘤防治中心 | Medical role-based instant messaging method and apparatus, system, and electronic device |
| CN113934895A (en) * | 2021-09-29 | 2022-01-14 | 浪潮云信息技术股份公司 | Method for assisting in establishing patient main index |
| CN114201968A (en) * | 2021-11-29 | 2022-03-18 | 上海保链科技有限公司 | Data normalization processing method and device based on medical scene and Chinese character combination |
| CN114329208A (en) * | 2021-12-29 | 2022-04-12 | 深圳市轱辘车联数据技术有限公司 | Search method, search device, server and storage medium |
| CN114490642A (en) * | 2021-12-31 | 2022-05-13 | 上海柯林布瑞信息技术有限公司 | Patient master index generation method, apparatus and medium |
| CN114741384A (en) * | 2021-12-22 | 2022-07-12 | 深圳市巨鼎医疗股份有限公司 | Patient information processing method and device and computer readable storage medium |
| CN115132308A (en) * | 2022-07-04 | 2022-09-30 | 佳缘科技股份有限公司 | Patient identity information processing method |
| CN115269613A (en) * | 2022-09-27 | 2022-11-01 | 四川互慧软件有限公司 | Patient main index construction method, system, equipment and storage medium |
| CN115331763A (en) * | 2022-08-09 | 2022-11-11 | 康键信息技术（深圳）有限公司 | Personal health record management method and device, computer equipment and storage medium |
| CN115840800A (en) * | 2023-02-27 | 2023-03-24 | 江苏曼荼罗软件股份有限公司 | Patient information matching method, system, computer and readable storage medium |
| CN115910387A (en) * | 2022-11-08 | 2023-04-04 | 北京健康在线技术开发有限公司 | Data processing method, device and equipment based on time sequence and storage medium |
| KR20230064694A (en) * | 2021-11-03 | 2023-05-11 | 서울대학교산학협력단 | Patient information enrollment device, server for analyzing data of patient and system for analyzing data of patient |
| CN116189911A (en) * | 2023-04-24 | 2023-05-30 | 江西莱普特信息技术有限公司 | Hospital information system intercommunication method and system based on blockchain side chain technology |
-
2023
- 2023-08-29 CN CN202311103437.3A patent/CN116825265A/en active Pending
Patent Citations (28)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020007284A1 (en) * | 1999-12-01 | 2002-01-17 | Schurenberg Kurt B. | System and method for implementing a global master patient index |
| JP2006087669A (en) * | 2004-09-24 | 2006-04-06 | Toshiba Corp | Image inspecting device, image inspection program and image inspection method |
| CN103544148A (en) * | 2012-07-09 | 2014-01-29 | 首都医科大学宣武医院 | Patient indexing method and system |
| CN103488783A (en) * | 2013-09-29 | 2014-01-01 | 方正国际软件有限公司 | Patient information matching system and patient information matching method |
| CN104657248A (en) * | 2013-11-21 | 2015-05-27 | 中国移动通信集团山东有限公司 | Java thread stack analysis method and system |
| US20180046679A1 (en) * | 2015-02-27 | 2018-02-15 | Koninklijke Philips N.V | Efficient integration of de-identified records |
| CN204814653U (en) * | 2015-08-21 | 2015-12-02 | 翟凯 | Novel supplementary reproduction section hospital outpatient service case history |
| CN106295182A (en) * | 2016-08-10 | 2017-01-04 | 依据数据（湖南）科技有限公司 | A kind of personal identification method based on patient biological information |
| CN106650259A (en) * | 2016-12-22 | 2017-05-10 | 深圳中兴网信科技有限公司 | Patient information management method and management system |
| CN110709027A (en) * | 2017-06-08 | 2020-01-17 | 美多斯国际有限公司 | User interface system for sterile field and other work environments |
| JP2021051394A (en) * | 2019-09-20 | 2021-04-01 | キヤノンメディカルシステムズ株式会社 | Medical information processing apparatus and program |
| CN111091884A (en) * | 2019-12-24 | 2020-05-01 | 无锡识凌科技有限公司 | Patient main index matching system and method of hospital information integration platform |
| WO2021202490A1 (en) * | 2020-03-31 | 2021-10-07 | Zoll Medical Corporation | Systems and methods of producing patient encounter records |
| WO2021233348A1 (en) * | 2020-05-20 | 2021-11-25 | 中山大学肿瘤防治中心 | Medical role-based instant messaging method and apparatus, system, and electronic device |
| CN112311887A (en) * | 2020-11-02 | 2021-02-02 | 陕西医链区块链集团有限公司 | Medical health file establishing method based on block chain technology |
| CN113688135A (en) * | 2021-08-25 | 2021-11-23 | 四川互慧软件有限公司 | Hospital information integration method based on patient main index technology |
| CN113934895A (en) * | 2021-09-29 | 2022-01-14 | 浪潮云信息技术股份公司 | Method for assisting in establishing patient main index |
| KR20230064694A (en) * | 2021-11-03 | 2023-05-11 | 서울대학교산학협력단 | Patient information enrollment device, server for analyzing data of patient and system for analyzing data of patient |
| CN114201968A (en) * | 2021-11-29 | 2022-03-18 | 上海保链科技有限公司 | Data normalization processing method and device based on medical scene and Chinese character combination |
| CN114741384A (en) * | 2021-12-22 | 2022-07-12 | 深圳市巨鼎医疗股份有限公司 | Patient information processing method and device and computer readable storage medium |
| CN114329208A (en) * | 2021-12-29 | 2022-04-12 | 深圳市轱辘车联数据技术有限公司 | Search method, search device, server and storage medium |
| CN114490642A (en) * | 2021-12-31 | 2022-05-13 | 上海柯林布瑞信息技术有限公司 | Patient master index generation method, apparatus and medium |
| CN115132308A (en) * | 2022-07-04 | 2022-09-30 | 佳缘科技股份有限公司 | Patient identity information processing method |
| CN115331763A (en) * | 2022-08-09 | 2022-11-11 | 康键信息技术（深圳）有限公司 | Personal health record management method and device, computer equipment and storage medium |
| CN115269613A (en) * | 2022-09-27 | 2022-11-01 | 四川互慧软件有限公司 | Patient main index construction method, system, equipment and storage medium |
| CN115910387A (en) * | 2022-11-08 | 2023-04-04 | 北京健康在线技术开发有限公司 | Data processing method, device and equipment based on time sequence and storage medium |
| CN115840800A (en) * | 2023-02-27 | 2023-03-24 | 江苏曼荼罗软件股份有限公司 | Patient information matching method, system, computer and readable storage medium |
| CN116189911A (en) * | 2023-04-24 | 2023-05-30 | 江西莱普特信息技术有限公司 | Hospital information system intercommunication method and system based on blockchain side chain technology |
Non-Patent Citations (3)
| Title |
|---|
| 周镇宏等著: "《新学科之林》", 广东科技出版社, pages: 405 * |
| 张新隆;徐亦鹏;邵燕;吴晓燕;: "医院客户关系管理(HCRM)应用", 中国伤残医学, no. 09, pages 393 - 395 * |
| 缪姝妹;王忠民;景慎旗;张小亮;章娣;郭建军;寇建秋;刘云;: "医院患者主索引系统的设计与探索", 中国数字医学, no. 07, pages 61 - 66 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| RU2565506C2 (en) | Autonomous linkage of patient information records stored at different entities | |
| JP5498579B2 (en) | Medical support system and medical support method | |
| US20060178913A1 (en) | Medical and other consent information management system | |
| US20060155579A1 (en) | Medical image viewing management and status system | |
| US20050215867A1 (en) | Treatment data processing and planning system | |
| KR20140096092A (en) | Methods and techniques for collecting, reporting, and managing information about medical diagnostic procedures | |
| US20100021027A1 (en) | Image data management systems | |
| US20070143142A1 (en) | Patient Medication History Management System | |
| CN104364787A (en) | System and method for generating textual report content using macros | |
| JP2008200373A (en) | Similar case retrieval apparatus and its method and program and similar case database registration device and its method and program | |
| CN108352185A (en) | For with the longitudinal healthy patients profile found | |
| US8892577B2 (en) | Apparatus and method for storing medical information | |
| US20070162312A1 (en) | Physician Treatment Ordering System | |
| CN114300079A (en) | Case discussion report acquisition method, electronic device and storage medium | |
| JP2008234309A (en) | Case collection system | |
| JP5616859B2 (en) | Medical support system and program | |
| CN113808762A (en) | Internet hospital remote consultation system | |
| CN102955901A (en) | Medical presentation creator | |
| JP2009244980A (en) | Medical practice support device and computer program | |
| US20150248527A1 (en) | Prompting medication safety technology | |
| EP3039590A2 (en) | System and method for reporting multiple medical procedures | |
| CN116825265A (en) | Treatment record processing method and device, electronic equipment and storage medium | |
| JP5753986B2 (en) | Identity confirmation support system | |
| JP4390606B2 (en) | Information processing apparatus, information processing terminal, program, and method | |
| KR102130098B1 (en) | Method and apparatus for generating medical data which is communicated between equipments related a medical image |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |