CN113990424A - Registration recommendation method and system based on electronic medical record - Google Patents

Registration recommendation method and system based on electronic medical record Download PDF

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CN113990424A
CN113990424A CN202111275506.XA CN202111275506A CN113990424A CN 113990424 A CN113990424 A CN 113990424A CN 202111275506 A CN202111275506 A CN 202111275506A CN 113990424 A CN113990424 A CN 113990424A
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doctor
department
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王海鸣
金震
伍朝晖
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Yiqun Dolphin Information Technology Shanghai Co ltd
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Abstract

The invention provides a registration recommendation method and system based on an electronic medical record, which comprises the following steps: step S1, analyzing according to a registration application and each visit record of the current patient input from outside to obtain at least one visit record matched with the registration application as a similar record, and extracting according to each similar record to obtain a corresponding visit department; step S2, counting according to the similar records to obtain a diagnosis rate for each department, and sequencing the departments in the order of the diagnosis rate from large to small to obtain a department sequence; and step S3, sequencing the doctors in the department according to the schedule of the doctors in the department and the working information of the doctors in the department to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and doctor. The medical registration system has the advantages that convenience is provided for the current patient to see a doctor, and registration efficiency of the patient is improved.

Description

Registration recommendation method and system based on electronic medical record
Technical Field
The invention relates to the technical field of medical information processing, in particular to a registration recommendation method and system based on an electronic medical record.
Background
At present, in order to orderly see a doctor for each patient, the patient needs to be registered before seeing a doctor, and the doctor can see the doctor according to the sequence of registration.
In the actual registration process, the patient needs to judge the department needing to be treated according to the disease of the patient, the medical knowledge of the patient is not enough, the situation that the disease of the patient is found to be not matched with the department needing to be treated after the patient is treated is caused, the patient often needs to be registered again and queued for treatment, the consumed time is long, on one hand, the problem that the patient cannot be treated in time exists, and on the other hand, the problem that medical resources are wasted due to repeated registration of the patient exists.
In addition, a plurality of doctors often exist in a department, the field of each doctor is different, in the registration process, because the patient has no deep relief for each doctor, only one doctor can be selected through subjective idea, and the defect that when the patient selects the doctor, objective suggestions are lacked to help the patient select the doctor exists.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a registration recommendation method based on electronic medical records, which is characterized in that a database is constructed in advance to store a plurality of electronic medical records, and each electronic medical record respectively comprises a treatment record generated after the treatment of a corresponding historical patient, and the registration recommendation method comprises the following steps:
step S1, analyzing and obtaining at least one clinic record matched with the registration application as a similar record according to a registration application of the current patient and each clinic record which are input externally, and extracting and obtaining a corresponding clinic according to each similar record;
step S2, counting according to the similarity records to obtain a diagnosis rate for each department, and sequencing the departments in the descending order of the diagnosis rate to obtain a department sequence;
step S3, sorting each doctor in the department according to the schedule of each doctor in the department and the working information of the doctor in the department to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and doctor.
Preferably, the step S1 includes:
step S11, extracting and obtaining current disease information of the current patient according to the registration application;
step S12 of calculating the similarity between the current medical condition information and the historical medical condition information included in each of the medical records, respectively;
step S13, when the similarity is greater than a preset threshold, outputting the corresponding history information as a similar information;
and step S14, acquiring the corresponding treatment record as the similar record according to the similar disease information, and extracting to obtain the treatment department according to the similar record.
Preferably, the step S12 includes:
step S121, extracting the features of the current disease information to obtain corresponding first feature fields, and respectively extracting the features of the historical disease information to obtain corresponding second feature fields;
and step S122, respectively carrying out similarity calculation on the first characteristic field and each second characteristic field to obtain the corresponding similarity.
Preferably, before executing the step S12, the method further includes:
step S111, extracting the age value of the current patient according to the registration application;
step S112, classifying the treatment records according to preset age intervals and age values of the historical patients to obtain corresponding treatment record groups;
and step S113, screening the diagnosis record groups in the same age interval with the age value of the current patient according to the age interval, and outputting the diagnosis records corresponding to the screened diagnosis record groups.
Preferably, the calculation formula of the department visit rate in step 2 is as follows:
Figure BDA0003329205460000031
wherein, PiIs the visit rate, X, of the visit department iiAnd M is the statistic value of all the similar records aiming at the statistic value of the similar record corresponding to each clinic i.
Preferably, the registration application contains the position information of the current patient, and the step S3 includes:
step S31, acquiring the schedule of the doctor, wherein the schedule comprises a doctor time and a doctor place;
step S32, sequencing the treatment times in the order from morning to evening to generate a first sequence;
step S33, analyzing the position information and the treatment location to obtain a treatment distance, and sequencing the treatment doctors within the same treatment time in a sequence from near to far according to the treatment distances to generate a second sequence;
step S34, determining whether the same treatment distance exists in the second sequence;
if yes, go to step S35;
if not, processing according to the first sequence and the second sequence to obtain and output the doctor sequence, and then quitting;
step S35, extracting the physicians having the same treatment distances in the second sequence, and for each of the same treatment distances, sorting the extracted physicians according to the medical information to obtain a third sequence;
and step S36, processing according to the second sequence and the third sequence to obtain and output the doctor sequence.
Preferably, the step S35 includes:
step S351, aiming at each identical treatment distance, acquiring the working information corresponding to the doctor;
step S352, scoring the doctor for seeing a doctor according to the working information to obtain a scoring value;
step S353, for each identical treatment distance, sorting the score values in descending order, and generating the third sequence.
Preferably, a registration recommendation system based on an electronic medical record applies any one of the above registration recommendation methods, and the registration recommendation system includes:
the database is used for storing a plurality of electronic medical records, and each electronic medical record comprises a treatment record generated after the corresponding historical patient is treated;
the matching module is connected with the database and used for analyzing and obtaining at least one clinic record matched with the registration application as a similar record according to a registration application of a current patient and each clinic record which are input from the outside and extracting and obtaining a corresponding clinic according to each similar record;
the statistical module is connected with the matching module and used for counting according to the similarity records to obtain a diagnosis rate for each diagnosis department and sequencing the diagnosis departments in the descending order of the diagnosis rate to obtain a department sequence;
and the sequencing module is connected with the counting module and used for sequencing each doctor in the department according to the schedule of each doctor in the department and the working information of the doctor in the department to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and the doctor.
Preferably, the matching module includes:
the extracting unit is used for extracting and obtaining current disease information of the current patient according to the registration application;
the calculation unit is connected with the extraction unit and is used for respectively calculating the similarity between the current disease information and the historical disease information contained in each clinic record;
the matching unit is connected with the calculating unit and used for outputting the corresponding historical disease information as similar disease information when the similarity is greater than a preset threshold value;
and the first analysis unit is connected with the matching unit and used for acquiring the corresponding clinic records as the similar records according to the similar disease information and extracting and obtaining the clinic according to the similar records.
Preferably, the registration application contains location information of the current patient, and the ranking module comprises:
the acquisition unit is used for acquiring the schedule of the doctor, and the schedule comprises a doctor time and a doctor place;
the first sequencing unit is connected with the acquisition unit and used for sequencing the treatment times from morning to evening to generate a first sequence;
the second sequencing unit is connected with the first sequencing unit and used for analyzing the position information and the treatment place to obtain a treatment distance and sequencing the treatment doctors in the same treatment time from near to far according to the treatment distances to generate a second sequence;
the second analysis unit is connected with the second sequencing unit and used for generating a reordering signal when the same visit distance exists in the second sequence;
a third sorting unit, connected to the second analyzing unit, configured to, when the re-sorting signal is received, extract the physicians having the same treatment distances in the second sequence, and sort the extracted physicians according to the medical information for each of the same treatment distances to obtain a third sequence;
and the processing unit is connected with the third sequencing unit and used for processing according to the second sequence and the third sequence to obtain and output the doctor sequence.
The technical scheme has the following advantages or beneficial effects:
(1) the registration recommendation list is obtained by processing according to the registration application of the current patient and the treatment records of the historical patients stored in the database, the current patient can visually see the treatment department and the doctor in a sitting treatment more suitable for the current patient according to the registration recommendation list, the registration recommendation method provides convenience for the current patient to see the doctor, and the registration efficiency of the patient is improved;
(2) the registration recommendation method provides registration recommendation corresponding to registration application for the current patient from an objective angle, reduces the condition that the corresponding doctor and doctor need to register again because the corresponding doctor and department are not suitable for the current patient's symptoms when the current patient is registered for the first time, and further plays the roles of improving the medical efficiency and saving medical resources;
(3) and screening the electronic medical records of the historical patients according to the age interval of the age value of the current patient, so that the number of the historical disease information needing to be added in the calculation when the similarity between the historical disease information and the current disease information is calculated is reduced, and the processing efficiency is improved.
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FIG. 1 is a flow chart of a registration recommendation method in accordance with a preferred embodiment of the present invention;
FIG. 2 is a flowchart illustrating the detailed procedure of step S1 in the registration recommendation method according to the preferred embodiment of the present invention;
FIG. 3 is a flowchart illustrating the detailed procedure of step S12 in the registration recommendation method according to the preferred embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps S111, S112 and S113 before step S12 is executed in the registration recommendation method according to the preferred embodiment of the present invention;
FIG. 5 is a flowchart illustrating the detailed procedure of step S3 in the registration recommendation method according to the preferred embodiment of the present invention;
FIG. 6 is a flowchart illustrating the detailed procedure of step S35 in the registration recommendation method according to the preferred embodiment of the present invention;
FIG. 7 is a control schematic diagram of a registration recommendation system in a preferred embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present invention is not limited to the embodiment, and other embodiments may be included in the scope of the present invention as long as the gist of the present invention is satisfied.
In a preferred embodiment of the present invention, based on the above problems in the prior art, there is provided a registration recommendation method based on electronic medical records, in which a database 1 is pre-constructed to store a plurality of electronic medical records, each electronic medical record includes a treatment record generated after a corresponding history patient has been treated, as shown in fig. 1, the registration recommendation method includes:
step S1, analyzing according to a registration application and each visit record of the current patient input from outside to obtain at least one visit record matched with the registration application as a similar record, and extracting according to each similar record to obtain a corresponding visit department;
step S2, counting according to the similar records to obtain a diagnosis rate for each department, and sequencing the departments in the order of the diagnosis rate from large to small to obtain a department sequence;
and step S3, sequencing the doctors in the department according to the schedule of the doctors in the department and the working information of the doctors in the department to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and doctor.
Specifically, in this embodiment, after each patient visits, the medical information system in the hospital stores the corresponding visit record into the database 1, on one hand, the visit record is stored as a file for subsequent review and calling, and on the other hand, the data analysis and mining are performed on each visit record to assist in medical research.
In the registration recommendation method, an objective registration recommendation list is provided for the current patient by analyzing the treatment record, so that the situation that the current patient has no way when selecting a treatment department and a doctor for sitting treatment is reduced, and the treatment efficiency of the current patient is improved.
In a preferred embodiment of the present invention, as shown in fig. 2, step S1 includes:
step S11, extracting current disease information of the current patient according to the registration application;
step S12, respectively calculating the similarity between the current disease information and the historical disease information contained in each visit record;
step S13, outputting corresponding historical disease information as a similar disease information when the similarity is greater than a preset threshold;
and step S14, acquiring corresponding treatment records as similar records according to the similar disease information, and extracting treatment departments according to the similar records.
Specifically, in this embodiment, in step S11, when the patient submits a registration request, the patient needs to fill in current disease condition information, where the current disease condition information includes: the current body parts where patients feel discomfort and the corresponding discomfort manifestations, including but not limited to: pain in the body part, soreness and numbness in the body part, and swelling in the body part.
In step S12, when the current disease state information and the historical disease state information included in each visit record are calculated, a pearson similarity calculation method is used.
In a preferred embodiment of the present invention, as shown in fig. 3, step S12 includes:
step S121, extracting the characteristics of the current disease information to obtain corresponding first characteristic fields, and respectively extracting the characteristics of the historical disease information to obtain corresponding second characteristic fields;
and step S122, respectively carrying out similarity calculation on the first characteristic field and each second characteristic field to obtain corresponding similarity.
Specifically, in this embodiment, pearson similarity calculation is performed on each first feature field and each second feature field corresponding to the historical disease information in each visit record to obtain the similarity between the current disease information and one visit record, the similarity between the current disease information and each other visit record is calculated by traversing all the visit records, and then, each similarity is screened according to the threshold value to obtain each similarity greater than the threshold value. And taking the visit record corresponding to the screened similarity as a similar record.
In a preferred embodiment of the present invention, as shown in fig. 4, before executing step S12, the method further includes:
step S111, extracting the age value of the current patient according to the registration application;
step S112, classifying the treatment records according to the preset age intervals and the age values of the historical patients to obtain corresponding treatment record groups;
and step S113, screening the diagnosis record groups in the same age interval with the age value of the current patient according to the age interval, and outputting the diagnosis records corresponding to the screened diagnosis record groups.
Specifically, in this embodiment, each visit record is screened once based on each preset age interval, and the screening of the similarity according to the threshold is a secondary screening, and through the two screens, the sample size of the similar records is reduced, so as to improve the processing efficiency of the registration recommendation method.
In a preferred embodiment of the present invention, the calculation formula of the department visit rate in step 2 is:
Figure BDA0003329205460000111
wherein, PiFor the visit rate of visit department i, XiFor the statistical value of the similar records corresponding to each visit department i, M is the statistical value of all similar records.
Specifically, in the present embodiment, the higher the visit rate of the visit department, the more patients with similar diseases select the visit department.
The treatment departments are sorted according to the sequence of the treatment rate from large to small, and the current patient can select the treatment department with the most front sorting so as to improve the treatment efficiency.
In a preferred embodiment of the present invention, the registration application contains the current position information of the patient, as shown in fig. 5, step S3 includes:
step S31, collecting the schedule of the doctor, wherein the schedule comprises a doctor time and a doctor place;
step S32, sequencing the treatment times in the order from morning to evening to generate a first sequence;
step S33, analyzing the position information and the treatment location to obtain a treatment distance, and sequencing the treatment doctors in the same treatment time from near to far according to the treatment distances to generate a second sequence;
step S34, judging whether the same treatment distance exists in the second sequence;
if yes, go to step S35;
if not, processing according to the first sequence and the second sequence to obtain and output a doctor sequence, and then quitting;
step S35, extracting the doctors with the same treatment distance in the second sequence, and sequencing the extracted doctors according to the working information to obtain a third sequence according to each identical treatment distance;
and step S36, processing according to the second sequence and the third sequence to obtain and output a doctor sequence.
Specifically, in this embodiment, in the schedule of each doctor, if the same time exists between the doctors, before the ordering the times, the method further includes:
step A1, randomly selecting a first visit time from all the visit times, and adding the first visit time into a to-be-sorted set;
step A2, randomly selecting a second visit time from the rest visit times, and judging whether the second visit time is the same as the first visit time;
if yes, the second visit time is not added with the waiting sorting set, and then the step A4 is executed;
if not, adding the second visit time into the set to be sorted, and then executing the step A4;
step A4, judging whether all the treatment time is extracted;
if yes, go to step S32;
if not, executing the step A2;
in step S32, the visit times in the set to be sorted are sorted to obtain a first sequence.
In a preferred embodiment of the present invention, as shown in fig. 6, step S35 includes:
step S351, aiming at each same treatment distance, acquiring working information corresponding to a doctor;
step S352, scoring the doctor according to the working information to obtain a scoring value;
and S353, sequencing the scoring values from large to small according to the same treatment distance to generate a third sequence.
Specifically, in this embodiment, the medical information includes the years of work of the doctor and the ability to treat each disease, and a higher score value indicates that the longer the years of work of the doctor, the stronger the ability to treat similar diseases.
In the registration process, a patient firstly submits a registration application, then a department with the first order is selected according to a registration recommendation list generated by a registration recommendation method, then proper treatment time and treatment distance are selected according to own schedule, and after the treatment time and the treatment distance are selected, when a plurality of corresponding doctors with the previous treatment exist, the previously arranged doctors with the previous treatment are selected. The more anterior the arrangement, the greater the ability of the treating physician to treat the similar condition.
In a preferred embodiment of the present invention, there is further provided a registration recommendation system based on an electronic medical record, which applies any one of the above registration recommendation methods, as shown in fig. 7, the registration recommendation system includes:
the database 1 is used for storing a plurality of electronic medical records, and each electronic medical record comprises a treatment record generated after the treatment of a corresponding historical patient;
the matching module 2 is connected with the database 1 and used for analyzing and obtaining at least one clinic record matched with the registration application as a similar record according to the externally input registration application and each clinic record of the current patient and extracting and obtaining a corresponding clinic according to each similar record;
the statistical module 3 is connected with the matching module 2 and used for obtaining a treatment rate according to the similar records for each treatment department through statistics and sequencing the treatment departments in the descending order of the treatment rate to obtain a department sequence;
and the sequencing module 4 is connected with the statistical module 3 and is used for sequencing all the doctors for sitting diagnosis according to the schedule arrangement of all the doctors for sitting diagnosis in the department and the working information of the doctors for sitting diagnosis in the department sequence to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and doctor for sitting diagnosis.
In a preferred embodiment of the present invention, the matching module 2 comprises:
the extracting unit 21 is used for extracting and obtaining current disease information of the current patient according to the registration application;
a calculating unit 22 connected to the extracting unit 21, for calculating the similarity between the current disease information and the historical disease information contained in each visit record;
the matching unit 23 is connected with the calculating unit 22 and is used for outputting the corresponding historical disease information as similar disease information when the similarity is greater than a preset threshold value;
and the first analysis unit 24 is connected with the matching unit 23, and is used for acquiring the corresponding treatment record as a similar record according to the similar disease information, and extracting the treatment department according to the similar record.
In a preferred embodiment of the present invention, the registration application contains information of the current patient's location, and the ranking module 4 comprises:
an acquisition unit 41, configured to acquire a schedule of a doctor, where the schedule includes a doctor time and a doctor place;
the first sequencing unit 42 is connected with the acquisition unit 41 and is used for sequencing the treatment times in the order from morning to evening to generate a first sequence;
the second sequencing unit 43 is connected to the first sequencing unit 42, and is configured to analyze the position information and the treatment location to obtain a treatment distance, and sequence the treatment doctors within the same treatment time in a sequence from near to far according to the treatment distances to generate a second sequence;
a second analyzing unit 44, connected to the second sorting unit 43, for generating a re-sorting signal when the same visit distance exists in the second sequence;
a third sorting unit 45, connected to the second analyzing unit 44, for extracting the physicians having the same treatment distance in the second sequence when receiving the re-sorting signal, and sorting the extracted physicians according to the medical information for each of the same treatment distance to obtain a third sequence;
and the processing unit 46 is connected with the third sequencing unit 45, and is used for processing according to the second sequence and the third sequence to obtain and output the doctor sequence.
In summary, currently, a patient sends a registration application to a registration recommendation system to obtain a registration recommendation list output by a registration recommendation platform, and objective registration suggestions are obtained based on the ranking of each doctor and doctor in the registration recommendation list.
The registration recommendation method is used for facilitating the medical treatment of the current patient and improving the registration efficiency of the patient;
in addition, registration recommendation corresponding to registration application is provided for the current patient from an objective angle, the situation that when the current patient is registered for the first time, corresponding office and doctor of seeing a doctor are not suitable for the symptoms of the current patient and need to be registered again is reduced, and the effects of improving the medical efficiency and saving medical resources are achieved.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.

Claims (10)

1. A registration recommendation method based on electronic medical records is characterized in that a database is constructed in advance to store a plurality of electronic medical records, and each electronic medical record comprises a treatment record generated after a corresponding historical patient has treated, and the registration recommendation method comprises the following steps:
step S1, analyzing and obtaining at least one clinic record matched with the registration application as a similar record according to a registration application of the current patient and each clinic record which are input externally, and extracting and obtaining a corresponding clinic according to each similar record;
step S2, counting according to the similarity records to obtain a diagnosis rate for each department, and sequencing the departments in the descending order of the diagnosis rate to obtain a department sequence;
step S3, sorting each doctor in the department according to the schedule of each doctor in the department and the working information of the doctor in the department to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and doctor.
2. The registration recommendation method according to claim 1, wherein the step S1 comprises:
step S11, extracting and obtaining current disease information of the current patient according to the registration application;
step S12 of calculating the similarity between the current medical condition information and the historical medical condition information included in each of the medical records, respectively;
step S13, when the similarity is greater than a preset threshold, outputting the corresponding history information as a similar information;
and step S14, acquiring the corresponding treatment record as the similar record according to the similar disease information, and extracting to obtain the treatment department according to the similar record.
3. The registration recommendation method according to claim 2, wherein the step S12 comprises:
step S121, extracting the features of the current disease information to obtain corresponding first feature fields, and respectively extracting the features of the historical disease information to obtain corresponding second feature fields;
and step S122, respectively carrying out similarity calculation on the first characteristic field and each second characteristic field to obtain the corresponding similarity.
4. The registration recommendation method according to claim 2, wherein the step S12 is further performed before the step of:
step S111, extracting the age value of the current patient according to the registration application;
step S112, classifying the treatment records according to preset age intervals and age values of the historical patients to obtain corresponding treatment record groups;
and step S113, screening the diagnosis record groups in the same age interval with the age value of the current patient according to the age interval, and outputting the diagnosis records corresponding to the screened diagnosis record groups.
5. The registration recommendation method according to claim 1, wherein the department visit rate in step 2 is calculated by the formula:
Figure FDA0003329205450000021
wherein, PiIs the visit rate, X, of the visit department iiAnd M is the statistic value of all the similar records aiming at the statistic value of the similar record corresponding to each clinic i.
6. The registration recommendation method of claim 1, wherein the registration application contains location information of the current patient, and the step S3 comprises:
step S31, acquiring the schedule of the doctor, wherein the schedule comprises a doctor time and a doctor place;
step S32, sequencing the treatment times in the order from morning to evening to generate a first sequence;
step S33, analyzing the position information and the treatment location to obtain a treatment distance, and sequencing the treatment doctors within the same treatment time in a sequence from near to far according to the treatment distances to generate a second sequence;
step S34, determining whether the same treatment distance exists in the second sequence;
if yes, go to step S35;
if not, processing according to the first sequence and the second sequence to obtain and output the doctor sequence, and then quitting;
step S35, extracting the physicians having the same treatment distances in the second sequence, and for each of the same treatment distances, sorting the extracted physicians according to the medical information to obtain a third sequence;
and step S36, processing according to the second sequence and the third sequence to obtain and output the doctor sequence.
7. The registration recommendation method according to claim 6, wherein the step S35 comprises:
step S351, aiming at each identical treatment distance, acquiring the working information corresponding to the doctor;
step S352, scoring the doctor for seeing a doctor according to the working information to obtain a scoring value;
step S353, for each identical treatment distance, sorting the score values in descending order, and generating the third sequence.
8. A registration recommendation system based on electronic medical record, which is characterized in that the registration recommendation method according to any one of claims 1-7 is applied, and the registration recommendation system comprises:
the database is used for storing a plurality of electronic medical records, and each electronic medical record comprises a treatment record generated after the corresponding historical patient is treated;
the matching module is connected with the database and used for analyzing and obtaining at least one clinic record matched with the registration application as a similar record according to a registration application of a current patient and each clinic record which are input from the outside and extracting and obtaining a corresponding clinic according to each similar record;
the statistical module is connected with the matching module and used for counting according to the similarity records to obtain a diagnosis rate for each diagnosis department and sequencing the diagnosis departments in the descending order of the diagnosis rate to obtain a department sequence;
and the sequencing module is connected with the counting module and used for sequencing each doctor in the department according to the schedule of each doctor in the department and the working information of the doctor in the department to generate a doctor sequence, and processing the doctor sequence and the department sequence to generate and output a registration recommendation list for the current patient to select the corresponding department and the doctor.
9. The registration recommendation system of claim 8, wherein the matching module comprises:
the extracting unit is used for extracting and obtaining current disease information of the current patient according to the registration application;
the calculation unit is connected with the extraction unit and is used for respectively calculating the similarity between the current disease information and the historical disease information contained in each clinic record;
the matching unit is connected with the calculating unit and used for outputting the corresponding historical disease information as similar disease information when the similarity is greater than a preset threshold value;
and the first analysis unit is connected with the matching unit and used for acquiring the corresponding clinic records as the similar records according to the similar disease information and extracting and obtaining the clinic according to the similar records.
10. The registration recommendation system of claim 8, wherein the registration application contains location information of the current patient, the ranking module comprising:
the acquisition unit is used for acquiring the schedule of the doctor, and the schedule comprises a doctor time and a doctor place;
the first sequencing unit is connected with the acquisition unit and used for sequencing the treatment times from morning to evening to generate a first sequence;
the second sequencing unit is connected with the first sequencing unit and used for analyzing the position information and the treatment place to obtain a treatment distance and sequencing the treatment doctors in the same treatment time from near to far according to the treatment distances to generate a second sequence;
the second analysis unit is connected with the second sequencing unit and used for generating a reordering signal when the same visit distance exists in the second sequence;
a third sorting unit, connected to the second analyzing unit, configured to, when the re-sorting signal is received, extract the physicians having the same treatment distances in the second sequence, and sort the extracted physicians according to the medical information for each of the same treatment distances to obtain a third sequence;
and the processing unit is connected with the third sequencing unit and used for processing according to the second sequence and the third sequence to obtain and output the doctor sequence.
CN202111275506.XA 2021-10-29 2021-10-29 Registration recommendation method and system based on electronic medical record Pending CN113990424A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116844732A (en) * 2023-07-27 2023-10-03 北京中益盛启科技有限公司 Hypertension diagnosis and treatment data distributed regulation and control system and method based on big data analysis
CN118098535A (en) * 2024-04-16 2024-05-28 旭辉卓越健康信息科技有限公司 Visual medical procedure active recommendation method and system

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116844732A (en) * 2023-07-27 2023-10-03 北京中益盛启科技有限公司 Hypertension diagnosis and treatment data distributed regulation and control system and method based on big data analysis
CN116844732B (en) * 2023-07-27 2024-02-02 北京中益盛启科技有限公司 Hypertension diagnosis and treatment data distributed regulation and control system and method based on big data analysis
CN118098535A (en) * 2024-04-16 2024-05-28 旭辉卓越健康信息科技有限公司 Visual medical procedure active recommendation method and system

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