CN112216372A - Intelligent medical hospital information display management platform based on big data - Google Patents
Intelligent medical hospital information display management platform based on big data Download PDFInfo
- Publication number
- CN112216372A CN112216372A CN202011084506.7A CN202011084506A CN112216372A CN 112216372 A CN112216372 A CN 112216372A CN 202011084506 A CN202011084506 A CN 202011084506A CN 112216372 A CN112216372 A CN 112216372A
- Authority
- CN
- China
- Prior art keywords
- doctor
- hospital
- module
- department
- information
- 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.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
- G06F16/287—Visualization; Browsing
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Computational Linguistics (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses an intelligent medical hospital information display management platform based on big data, which comprises a platform classification module, a doctor login module, an identity information screening module, a data extraction module, a data processing module, an analysis server, an information input module, a patient query module, an illness state analysis module, a display terminal and a storage database; the hospital information platform is classified into the plates through the platform classification module, the identity information of each doctor logging on the platform and the corresponding department are screened, the personal detailed information and the medical data of each doctor in each department are extracted, the comprehensive doctor rating influence coefficient of each doctor in each department is calculated, the doctor grades of each doctor in each department are contrastively screened, the corresponding department plate platform is entered, the department corresponding to the sick symptom of the patient is analyzed, and the introduction of each doctor in the doctor grade ranking list and the doctor grade ranking list of the department is displayed, so that the patient adhesion is enhanced, and the medical service quality of the hospital is improved.
Description
Technical Field
The invention relates to the field of medical information display management, in particular to an intelligent medical hospital information display management platform based on big data.
Background
With the development of information technology and the medical and health industry of China, the medical informatization process of China is also improved. Under the service idea of taking a patient as a center and taking improvement of medical service quality as a theme, a hospital medical information display platform is established in time, which is a subject faced by a hospital in competition.
At present, the existing hospital information display management platform generally has certain problems, the existing hospital information display management technology can not classify the hospital medical data, so that the query complexity of patients is high, unnecessary repeated query links are added, the time for inquiring the sick symptoms is greatly wasted, meanwhile, the medical level data of the hospital does not have the visual display function, so that the patient can not visually know the medical levels of doctors in various departments in the hospital, the patient adhesion is reduced, moreover, the existing hospital information display management platform is difficult to play the role of assisting doctors, so that patients cannot accurately analyze departments corresponding to own sick symptoms, and cannot obtain corresponding medical services in time, therefore, the medical service quality of the hospital is reduced, and in order to solve the problems, an intelligent medical hospital information display management platform based on big data is designed.
Disclosure of Invention
The invention aims to provide an intelligent medical hospital information display management platform based on big data, which classifies plates of a hospital information platform through a platform classification module, screens identity information of doctors logging in the platform and corresponding departments, extracts personal detailed information and medical data of doctors in the departments in the hospital, calculates comprehensive physician rating influence coefficients of the doctors in the departments in the hospital, contrasts and screens physician grades of the doctors in the departments in the hospital, records the ranked physician grade ranking lists of the departments into the corresponding department plate platform, screens and obtains the departments corresponding to sick symptoms of a patient through an illness state analysis module, and displays the physician grade ranking lists of the departments and introduction of the doctors in the physician grade ranking lists, so that the problem existing in the background technology is solved.
The purpose of the invention can be realized by the following technical scheme:
an intelligent medical hospital information display management platform based on big data comprises a platform classification module, a doctor login module, an identity information screening module, a data extraction module, a data processing module, an analysis server, an information input module, a patient query module, a disease state analysis module, a display terminal and a storage database;
the platform classification module is used for classifying the plates of the hospital information platform, dividing the hospital information platform into a plurality of department plate platforms according to different division modes of departments of the hospital, numbering the department plate platforms in sequence according to a set sequence, wherein the numbering is 1,2,.
The system comprises a doctor login module, an identity information screening module, a doctor information storage module and a data processing module, wherein the doctor login module is used for logging in identity information of each doctor in a hospital, and each doctor in the hospital inputs corresponding identity information into a hospital information platform for logging in and sends the identity information of each doctor in the login platform to the identity information screening module;
the identity information screening module is connected with the doctor login module and used for receiving the identity information of each doctor of the login platform sent by the doctor login module, extracting the standard identity information of each doctor in the hospital stored in the storage database, comparing the identity information of each doctor of the login platform with the stored standard identity information of each doctor in the hospital, screening the standard identity information of a plurality of doctors with the same name as that of the identity information of each doctor of the login platform, comparing the identity card number in the identity information of each doctor of the login platform with the standard identity information of a plurality of doctors with the same name, screening the identity information of each doctor of the login platform, and sending the screened identity information of each doctor of the login platform to the analysis server;
the analysis server is connected with the identity information screening module and used for receiving the identity information of each doctor of the screened login platform sent by the identity information screening module, extracting departments corresponding to the identity information of each doctor in the hospital stored in the storage database, screening departments corresponding to the identity information of each doctor of the screened login platform, counting the departments corresponding to each doctor of the login platform, jumping the hospital information platform login entrance of each doctor to the corresponding department plate platform, and sending the department plate platform corresponding to each doctor in the hospital to the data extraction module;
the data extraction module is connected with the analysis server and used for receiving department plate platforms corresponding to doctors in the hospital and sent by the analysis server, extracting and storing personal detailed information and medical data of the doctors in each department in the hospital and stored in the database, screening medical age in the personal detailed information of the doctors in each department in the hospital, outpatient service amount and successful operation amount of each level in each medical data, sending the personal detailed information and the medical data of the doctors in each department in the hospital to the information input module, and sending the outpatient service amount, successful operation amount of each level and medical age of the doctors in each department in the hospital to the data processing module;
the data processing module is connected with the data extraction module and used for receiving the outpatient service volume, the successful operation volume and the medical age of each doctor in each department in the hospital sent by the data extraction module, counting the outpatient service volume, the successful operation volume and the medical age of each doctor in each department in the hospital and forming each medical data set W of each doctor in each department in the hospitaliR(wi1r,wi2r,...,wijr,...,wimr)，wijr represents the r-th medical data of the jth doctor in the ith department in the hospital, and r is r1,r2,r3,r4,r5,r6，r1、r2、r3、r4、r5、r6Respectively representing the outpatient service volume, the first-level successful operation volume, the second-level successful operation volume, the third-level successful operation volume, the fourth-level successful operation volume and the medical age of the doctors, and sending each medical data set of each doctor in each department in the hospital to an analysis server;
the analysis server is connected with the data processing module and used for receiving each medical data set of each doctor in each department in the hospital sent by the data processing module, extracting a doctor rating influence weight coefficient corresponding to each medical data stored in the storage database, calculating a comprehensive doctor rating influence coefficient of each doctor in each department in the hospital, extracting a standard comprehensive doctor rating influence coefficient range corresponding to each doctor level stored in the storage database, comparing the calculated comprehensive doctor rating influence coefficient of each doctor in each department in the hospital with the stored standard comprehensive doctor rating influence coefficient range corresponding to each doctor level, screening the doctor level corresponding to the comprehensive doctor rating influence coefficient of each doctor in each department in the hospital, counting the doctor level corresponding to each doctor in each department in the hospital, and sending the doctor level corresponding to each doctor in each department in the hospital to the information input module;
the information recording module is connected with the data extraction module and the analysis server and used for receiving personal detailed information and medical data of doctors in each department in the hospital, which are sent by the data extraction module, receiving the doctor grades corresponding to the doctors in each department in the hospital, which are sent by the analysis server, sequentially arranging the doctor grades of the doctors in each department in the hospital from high to low, respectively recording the doctor grade ranking lists of the departments in the hospital into corresponding department edition platforms, respectively recording the personal detailed information and the medical data of the doctors in each department in the hospital into corresponding doctor descriptions in the doctor grade ranking lists of the corresponding departments, and respectively transmitting the doctor grade ranking lists of the departments in the hospital and the doctor descriptions in the corresponding doctor grade ranking lists to the display terminal;
the patient query module is used for querying the sick symptoms of the patient, the patient inputs the relevant information of the sick symptoms of the patient by logging in a query entrance of a hospital information platform, and the relevant information of the sick symptoms input by the patient is sent to the illness state analysis module;
the disease condition analysis module is connected with the patient query module and used for receiving the relevant information of the patient input diseased symptom sent by the patient query module, extracting the symptom keywords in the received relevant information of the patient input diseased symptom, extracting the keywords of each medical symptom in each department in the hospital stored in the storage database, comparing the symptom keywords in the received relevant information of the patient input diseased symptom with the stored keywords of each medical symptom in each department in the hospital, screening to obtain a department corresponding to the diseased symptom of the patient, and sending the department corresponding to the diseased symptom of the patient to the display terminal;
the display terminal is respectively connected with the information entry module and the disease condition analysis module, and is used for receiving doctor grade leaderboards of all departments in the hospital and doctor introductions in corresponding doctor grade leaderboards sent by the information entry module, receiving departments corresponding to the patient disease symptoms sent by the disease condition analysis module, and displaying the doctor grade leaderboards of the departments and the doctor grade leaderboards of all doctors according to the received departments corresponding to the patient disease symptoms;
the storage database is respectively connected with the platform classification module, the identity information screening module, the analysis server, the data extraction module and the disease condition analysis module, and is used for receiving the serial numbers of the plate block platforms of all departments sent by the platform classification module, simultaneously storing the standard identity information of all doctors in the hospital and departments corresponding to the identity information of all doctors, storing the personal detailed information and all medical data of all doctors in all departments in the hospital, and storing outpatient service volume, primary successful operation volume, secondary successful operation volume, tertiary successful operation volume, quaternary successful operation volume and physician rating influence weight coefficients corresponding to medical ages in all medical data, which are respectively expressed as lambda1、λ2、λ3、λ4、λ5、λ6Storing standard comprehensive physician rating influence coefficient ranges corresponding to the physician grades, and storing keywords of medical symptoms in each department in the hospital;
further, the identity information of the doctor comprises a doctor name and a doctor identity card number;
further, the personal details of the doctor include job title, contact address, sex, photograph, belonging position, brief introduction, excellence, daily working hours and medical age;
furthermore, the various levels of operations comprise a first level operation, a second level operation, a third level operation and a fourth level operation, wherein the first level operation is various operations with lower technical difficulty, simple operation process and lower risk; the secondary operation is various operations with common technical difficulty, uncomplicated operation process and moderate risk; the three-level operation is various operations with higher technical difficulty, more complex operation process and higher risk; the four-stage operation is an operation with great technical difficulty, complex operation process and great risk;
further, the calculation formula of the comprehensive physician rating influence coefficient of each physician in each department in the hospital is
，ζwijExpressed as the comprehensive physician rating influence coefficient, lambda, of the jth physician in the ith department of the hospital1、λ2、λ3、λ4、λ5、λ6Respectively expressed as the outpatient service volume, the first-level successful operation volume, the second-level successful operation volume, the third-level successful operation volume, the fourth-level successful operation volume and the physician rating influence weight coefficient corresponding to the medical age in the medical data, wijr represents the r-th medical data of the jth doctor in the ith department in the hospital, and r is r1,r2,r3,r4,r5,r6，r1、r2、r3、r4、r5、r6Respectively representing the outpatient service volume, the first-level successful operation volume, the second-level successful operation volume, the third-level successful operation volume, the fourth-level successful operation volume and the medical age of the doctor, wherein e is a natural number and is equal to 2.718;
further, the physician grades include assistant physicians, resident physicians, attending physicians, subordinate chief physicians, and the physician grades are sequentially increased.
Has the advantages that:
(1) the intelligent medical hospital information display management platform based on big data, provided by the invention, classifies the plates of the hospital information platform through the platform classification module, reduces the query complexity of patients, thereby avoiding unnecessary repeated query links, saving a large amount of time for querying sick symptoms, simultaneously screening the identity information of each doctor logged on the platform and the corresponding department, extracting the personal detailed information and each medical data of each doctor in each department in the hospital, providing reliable reference data for later-stage calculation of the comprehensive physician rating influence coefficient of each doctor in each department in the hospital, simultaneously calculating the comprehensive physician rating influence coefficient of each doctor in each department in the hospital, comparing and screening the physician grades of each doctor in each department in the hospital, and inputting the ranked physician grade ranking list of each department in the hospital into the corresponding department plate platform, therefore, the medical level data of the hospital has a visual display function, the patient can visually know the medical level of doctors in each department in the hospital, and the adhesion degree of the patient is enhanced.
(2) According to the medical service platform, the departments corresponding to the sick symptoms of the patient are obtained through screening of the disease condition analysis module, and the doctor grade ranking list of the department and the introduction of each doctor in the doctor grade ranking list are displayed through the display terminal, so that the platform plays a role in assisting the doctor, the problem that the patient cannot obtain corresponding medical service in time is avoided, and the medical service quality of a hospital is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic view of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an intelligent medical hospital information display management platform based on big data comprises a platform classification module, a doctor login module, an identity information screening module, a data extraction module, a data processing module, an analysis server, an information entry module, a patient query module, a disease analysis module, a display terminal and a storage database;
the platform classification module is used for classifying the plates of the hospital information platform, dividing the hospital information platform into a plurality of department plate platforms according to different division modes of departments of the hospital, numbering the department plate platforms in sequence according to a set sequence, wherein the numbering is 1,2, 1, i, n, so that the inquiry complexity of a patient is reduced, unnecessary repeated inquiry links are avoided, a large amount of time for inquiring sick symptoms is saved, and the numbering of each department plate platform is sent to a storage database;
the system comprises a doctor login module, an identity information screening module, a doctor information display module and a doctor information display module, wherein the doctor login module is used for logging in identity information of each doctor in a hospital, the identity information of the doctor comprises a doctor name and a doctor identity card number, and each doctor in the hospital inputs corresponding identity information into a hospital information platform for logging in and sends the identity information of each doctor in the login platform to the identity information screening module;
the identity information screening module is connected with the doctor login module and used for receiving the identity information of each doctor of the login platform sent by the doctor login module, extracting the standard identity information of each doctor in the hospital stored in the storage database, comparing the identity information of each doctor of the login platform with the stored standard identity information of each doctor in the hospital, screening the standard identity information of a plurality of doctors with the same name as that of the identity information of each doctor of the login platform, comparing the identity card number in the identity information of each doctor of the login platform with the standard identity information of a plurality of doctors with the same name, screening the identity information of each doctor of the login platform, and sending the screened identity information of each doctor of the login platform to the analysis server;
the analysis server is connected with the identity information screening module and used for receiving the identity information of each doctor of the screened login platform sent by the identity information screening module, extracting departments corresponding to the identity information of each doctor in the hospital stored in the storage database, screening departments corresponding to the identity information of each doctor of the screened login platform, counting the departments corresponding to each doctor of the login platform, jumping the hospital information platform login entrance of each doctor to the corresponding department plate platform, and sending the department plate platform corresponding to each doctor in the hospital to the data extraction module;
the data extraction module is connected with the analysis server and used for receiving department plate platforms corresponding to doctors in the hospital and sent by the analysis server, extracting and storing personal detailed information and medical data of the doctors in the departments in the hospital and stored in the database, screening medical ages in the personal detailed information of the doctors in the departments in the hospital, outpatient service amount in the medical data and successful operation amount of each level, and providing reliable reference data for later-stage calculation of comprehensive physician rating influence coefficients of the doctors in the departments in the hospital, wherein each level of operations comprises a first-level operation, a second-level operation, a third-level operation and a fourth-level operation, and the first-level operation is various operations with low technical difficulty, simple operation process and low risk; the secondary operation is various operations with common technical difficulty, uncomplicated operation process and moderate risk; the three-level operation is various operations with higher technical difficulty, more complex operation process and higher risk; the four-stage operation is an operation with high technical difficulty, complex operation process and high risk, simultaneously sends the personal detailed information and the medical data of each doctor in each department in the hospital to the information input module, and sends the screened outpatient service volume, the successful operation volume of each department and the medical age of each doctor in each department in the hospital to the data processing module;
the data processing module is connected with the data extraction module and used for receiving the outpatient service volume, the successful operation volume and the medical age of each doctor in each department in the hospital sent by the data extraction module, counting the outpatient service volume, the successful operation volume and the medical age of each doctor in each department in the hospital and forming each medical data set W of each doctor in each department in the hospitaliR(wi1r,wi2r,...,wijr,...,wimr)，wijr represents the r-th medical data of the jth doctor in the ith department in the hospital, and r is r1,r2,r3,r4,r5,r6，r1、r2、r3、r4、r5、r6Respectively representing the outpatient service volume, the first-level successful operation volume, the second-level successful operation volume, the third-level successful operation volume, the fourth-level successful operation volume and the medical age of the doctors, and sending each medical data set of each doctor in each department in the hospital to an analysis server;
the analysis server is connected with the data processing module and used for receiving each medical data set of each doctor in each department in the hospital sent by the data processing module, extracting the doctor rating influence weight coefficient corresponding to each medical data stored in the storage database, calculating the comprehensive doctor rating influence coefficient of each doctor in each department in the hospital, and the calculation formula of the comprehensive doctor rating influence coefficient of each doctor in each department in the hospital is
The information recording module is connected with the data extraction module and the analysis server and used for receiving the personal detailed information and the medical data of each doctor in each department in the hospital sent by the data extraction module, receiving the doctor grades corresponding to each doctor in each department in the hospital sent by the analysis server, sequentially arranging the doctor grades of each doctor in each department in the hospital from high to low, respectively recording the doctor grade ranking lists of each department in the hospital into the corresponding department edition platform, and respectively recording the personal detailed information and the medical data of each doctor in each department in the hospital into the corresponding doctor introduction in the doctor grade ranking lists of the corresponding department, so that the medical level data of the hospital has a visual display function, the patient can visually know the medical level of each doctor in each department in the hospital, and the patient adhesion degree is enhanced, and sending the doctor grade ranking list of each department in the hospital and the introduction of each doctor in the corresponding doctor grade ranking list to a display terminal;
the patient query module is used for querying the sick symptoms of the patient, the patient inputs the relevant information of the sick symptoms of the patient by logging in a query entrance of a hospital information platform, and the relevant information of the sick symptoms input by the patient is sent to the illness state analysis module;
the disease condition analysis module is connected with the patient query module and used for receiving the relevant information of the patient input diseased symptom sent by the patient query module, extracting the symptom keywords in the received relevant information of the patient input diseased symptom, extracting the keywords of each medical symptom in each department in the hospital stored in the storage database, comparing the symptom keywords in the received relevant information of the patient input diseased symptom with the stored keywords of each medical symptom in each department in the hospital, screening to obtain a department corresponding to the diseased symptom of the patient, and sending the department corresponding to the diseased symptom of the patient to the display terminal;
the display terminal is respectively connected with the information entry module and the disease condition analysis module and used for receiving doctor grade ranking lists of all departments in the hospital and doctor introduction in the corresponding doctor grade ranking lists sent by the information entry module, receiving departments corresponding to the patient disease symptoms sent by the disease condition analysis module, and displaying the doctor grade ranking lists of the departments and the doctor introduction in the doctor grade ranking lists according to the received departments corresponding to the patient disease symptoms, so that the platform plays a role of assisting doctors, the problem that the patient cannot obtain corresponding medical services in time is avoided, and the medical service quality of the hospital is improved.
The storage database is respectively connected with the platform classification module, the identity information screening module, the analysis server, the data extraction module and the disease condition analysis module, and is used for receiving the serial numbers of the plate block platforms of each department sent by the platform classification module, simultaneously storing the standard identity information of each doctor in the hospital and departments corresponding to the identity information of each doctor, storing the personal detailed information and each medical data of each doctor in each department in the hospital, wherein the personal detailed information of the doctor comprises a title, a contact way, a sex, a picture, a belonging position, a brief introduction, a good strength, daily working time and medical age, and storing outpatient service amount, first-level successful operation amount, second-level successful operation amount, third-level successful operation amount, fourth-level successful operation amount and physician rating influence weight coefficients corresponding to the medical age in each medical data, which are respectively expressed as lambda1、λ2、λ3、λ4、λ5、λ6And storing standard comprehensive physician rating influence coefficient ranges corresponding to all physician grades, wherein all physician grades comprise assistant physicians, resident physicians, main treating physicians, subordinate main physicians and main physicians, all the physician grades are sequentially increased, and keywords of medical symptoms in all departments in the hospital are stored.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (6)
1. The utility model provides an wisdom medical hospital information-based show management platform based on big data which characterized in that: the system comprises a platform classification module, a doctor login module, an identity information screening module, a data extraction module, a data processing module, an analysis server, an information input module, a patient query module, an illness state analysis module, a display terminal and a storage database;
the platform classification module is used for classifying the plates of the hospital information platform, dividing the hospital information platform into a plurality of department plate platforms according to different division modes of departments of the hospital, numbering the department plate platforms in sequence according to a set sequence, wherein the numbering is 1,2,.
The system comprises a doctor login module, an identity information screening module, a doctor information storage module and a data processing module, wherein the doctor login module is used for logging in identity information of each doctor in a hospital, and each doctor in the hospital inputs corresponding identity information into a hospital information platform for logging in and sends the identity information of each doctor in the login platform to the identity information screening module;
the identity information screening module is connected with the doctor login module and used for receiving the identity information of each doctor of the login platform sent by the doctor login module, extracting the standard identity information of each doctor in the hospital stored in the storage database, comparing the identity information of each doctor of the login platform with the stored standard identity information of each doctor in the hospital, screening the standard identity information of a plurality of doctors with the same name as that of the identity information of each doctor of the login platform, comparing the identity card number in the identity information of each doctor of the login platform with the standard identity information of a plurality of doctors with the same name, screening the identity information of each doctor of the login platform, and sending the screened identity information of each doctor of the login platform to the analysis server;
the analysis server is connected with the identity information screening module and used for receiving the identity information of each doctor of the screened login platform sent by the identity information screening module, extracting departments corresponding to the identity information of each doctor in the hospital stored in the storage database, screening departments corresponding to the identity information of each doctor of the screened login platform, counting the departments corresponding to each doctor of the login platform, jumping the hospital information platform login entrance of each doctor to the corresponding department plate platform, and sending the department plate platform corresponding to each doctor in the hospital to the data extraction module;
the data extraction module is connected with the analysis server and used for receiving department plate platforms corresponding to doctors in the hospital and sent by the analysis server, extracting and storing personal detailed information and medical data of the doctors in each department in the hospital and stored in the database, screening medical age in the personal detailed information of the doctors in each department in the hospital, outpatient service amount and successful operation amount of each level in each medical data, sending the personal detailed information and the medical data of the doctors in each department in the hospital to the information input module, and sending the outpatient service amount, successful operation amount of each level and medical age of the doctors in each department in the hospital to the data processing module;
the data processing module is connected with the data extraction module and used for receiving the outpatient service volume, the successful operation volume and the medical age of each doctor in each department in the hospital sent by the data extraction module, counting the outpatient service volume, the successful operation volume and the medical age of each doctor in each department in the hospital and forming each medical data set W of each doctor in each department in the hospitaliR(wi1r,wi2r,...,wijr,...,wimr)，wijr represents the r-th medical data of the jth doctor in the ith department in the hospital, and r is r1,r2,r3,r4,r5,r6，r1、r2、r3、r4、r5、r6Respectively representing the outpatient service volume, the first-level successful operation volume, the second-level successful operation volume, the third-level successful operation volume, the fourth-level successful operation volume and the medical age of the doctors, and sending each medical data set of each doctor in each department in the hospital to an analysis server;
the analysis server is connected with the data processing module and used for receiving each medical data set of each doctor in each department in the hospital sent by the data processing module, extracting a doctor rating influence weight coefficient corresponding to each medical data stored in the storage database, calculating a comprehensive doctor rating influence coefficient of each doctor in each department in the hospital, extracting a standard comprehensive doctor rating influence coefficient range corresponding to each doctor level stored in the storage database, comparing the calculated comprehensive doctor rating influence coefficient of each doctor in each department in the hospital with the stored standard comprehensive doctor rating influence coefficient range corresponding to each doctor level, screening the doctor level corresponding to the comprehensive doctor rating influence coefficient of each doctor in each department in the hospital, counting the doctor level corresponding to each doctor in each department in the hospital, and sending the doctor level corresponding to each doctor in each department in the hospital to the information input module;
the information recording module is connected with the data extraction module and the analysis server and used for receiving personal detailed information and medical data of doctors in each department in the hospital, which are sent by the data extraction module, receiving the doctor grades corresponding to the doctors in each department in the hospital, which are sent by the analysis server, sequentially arranging the doctor grades of the doctors in each department in the hospital from high to low, respectively recording the doctor grade ranking lists of the departments in the hospital into corresponding department edition platforms, respectively recording the personal detailed information and the medical data of the doctors in each department in the hospital into corresponding doctor descriptions in the doctor grade ranking lists of the corresponding departments, and respectively transmitting the doctor grade ranking lists of the departments in the hospital and the doctor descriptions in the corresponding doctor grade ranking lists to the display terminal;
the patient query module is used for querying the sick symptoms of the patient, the patient inputs the relevant information of the sick symptoms of the patient by logging in a query entrance of a hospital information platform, and the relevant information of the sick symptoms input by the patient is sent to the illness state analysis module;
the disease condition analysis module is connected with the patient query module and used for receiving the relevant information of the patient input diseased symptom sent by the patient query module, extracting the symptom keywords in the received relevant information of the patient input diseased symptom, extracting the keywords of each medical symptom in each department in the hospital stored in the storage database, comparing the symptom keywords in the received relevant information of the patient input diseased symptom with the stored keywords of each medical symptom in each department in the hospital, screening to obtain a department corresponding to the diseased symptom of the patient, and sending the department corresponding to the diseased symptom of the patient to the display terminal;
the display terminal is respectively connected with the information entry module and the disease condition analysis module, and is used for receiving doctor grade leaderboards of all departments in the hospital and doctor introductions in corresponding doctor grade leaderboards sent by the information entry module, receiving departments corresponding to the patient disease symptoms sent by the disease condition analysis module, and displaying the doctor grade leaderboards of the departments and the doctor grade leaderboards of all doctors according to the received departments corresponding to the patient disease symptoms;
the storage database is respectively connected with the platform classification module, the identity information screening module, the analysis server, the data extraction module and the disease condition analysis module, and is used for receiving the serial numbers of the plate block platforms of all departments sent by the platform classification module, simultaneously storing the standard identity information of all doctors in the hospital and departments corresponding to the identity information of all doctors, storing the personal detailed information and all medical data of all doctors in all departments in the hospital, and storing outpatient service volume, primary successful operation volume, secondary successful operation volume, tertiary successful operation volume, quaternary successful operation volume and physician rating influence weight coefficients corresponding to medical ages in all medical data, which are respectively expressed as lambda1、λ2、λ3、λ4、λ5、λ6And storing standard comprehensive physician rating influence coefficient ranges corresponding to the physician grades, and storing keywords of medical symptoms in each department in the hospital.
2. The intelligent medical hospital information display management platform based on big data according to claim 1, characterized in that: the doctor identity information comprises a doctor name and a doctor identity card number.
3. The intelligent medical hospital information display management platform based on big data according to claim 1, characterized in that: the personal details of the doctor include job title, contact address, sex, photograph, belonging position, introduction, excellence, daily work time, and medical age.
4. The intelligent medical hospital information display management platform based on big data according to claim 1, characterized in that: the first-level operation is various operations with lower technical difficulty, simple operation process and lower risk; the secondary operation is various operations with common technical difficulty, uncomplicated operation process and moderate risk; the three-level operation is various operations with higher technical difficulty, more complex operation process and higher risk; the four-stage operation is an operation with great technical difficulty, complex operation process and great risk.
5. The intelligent medical hospital information display management platform based on big data according to claim 1, characterized in that: the calculation formula of the comprehensive physician rating influence coefficient of each doctor in each department in the hospital is
，ζwijExpressed as the comprehensive physician rating influence coefficient, lambda, of the jth physician in the ith department of the hospital1、λ2、λ3、λ4、λ5、λ6Respectively expressed as the outpatient service volume, the first-level successful operation volume, the second-level successful operation volume, the third-level successful operation volume, the fourth-level successful operation volume and the physician rating influence weight coefficient corresponding to the medical age in the medical data, wijr represents the r-th medical data of the jth doctor in the ith department in the hospital, and r is r1,r2,r3,r4,r5,r6，r1、r2、r3、r4、r5、r6Respectively expressed as the doctor's outpatient service volume, primary successful operation volume, secondary successful operation volume, tertiary successful operation volume, quaternary successful operation volume and medical age, and e is expressed as a natural number and is equal to 2.718.
6. The intelligent medical hospital information display management platform based on big data according to claim 1, characterized in that: the physician grades include assistant physicians, resident physicians, treating physicians, subordinate chief physicians, and the physician grades are sequentially increased.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011084506.7A CN112216372A (en) | 2020-10-12 | 2020-10-12 | Intelligent medical hospital information display management platform based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011084506.7A CN112216372A (en) | 2020-10-12 | 2020-10-12 | Intelligent medical hospital information display management platform based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112216372A true CN112216372A (en) | 2021-01-12 |
Family
ID=74053269
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011084506.7A Withdrawn CN112216372A (en) | 2020-10-12 | 2020-10-12 | Intelligent medical hospital information display management platform based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112216372A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113239279A (en) * | 2021-06-10 | 2021-08-10 | 武汉轻派壳子数码有限公司 | Chronic disease medical data acquisition, analysis and management method based on data analysis and cloud computing and cloud platform |
| CN113496774A (en) * | 2021-07-22 | 2021-10-12 | 河北北方学院 | Digital medical information management method and related device |
| CN113642821A (en) * | 2021-01-29 | 2021-11-12 | 武汉威尔莱博科技有限公司 | Intelligent analysis ranking system for subject construction |
| CN114220537A (en) * | 2022-02-18 | 2022-03-22 | 橙意家人科技（天津）有限公司 | AI intelligent online diagnosis method based on Internet hospital and cloud system |
| CN115132307A (en) * | 2022-06-23 | 2022-09-30 | 张利萍 | Method for accessing medical institution system to smart medical cloud service platform |
-
2020
- 2020-10-12 CN CN202011084506.7A patent/CN112216372A/en not_active Withdrawn
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113642821A (en) * | 2021-01-29 | 2021-11-12 | 武汉威尔莱博科技有限公司 | Intelligent analysis ranking system for subject construction |
| CN113239279A (en) * | 2021-06-10 | 2021-08-10 | 武汉轻派壳子数码有限公司 | Chronic disease medical data acquisition, analysis and management method based on data analysis and cloud computing and cloud platform |
| CN113239279B (en) * | 2021-06-10 | 2022-08-05 | 四川聚典新业科技有限公司 | Chronic disease medical data acquisition, analysis and management method and cloud platform |
| CN113496774A (en) * | 2021-07-22 | 2021-10-12 | 河北北方学院 | Digital medical information management method and related device |
| CN114220537A (en) * | 2022-02-18 | 2022-03-22 | 橙意家人科技（天津）有限公司 | AI intelligent online diagnosis method based on Internet hospital and cloud system |
| CN115132307A (en) * | 2022-06-23 | 2022-09-30 | 张利萍 | Method for accessing medical institution system to smart medical cloud service platform |
| CN115132307B (en) * | 2022-06-23 | 2023-09-12 | 浙江和仁科技股份有限公司 | Method for accessing medical institution system to intelligent medical cloud service platform |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112216372A (en) | Intelligent medical hospital information display management platform based on big data | |
| CN114171176A (en) | Hospital triage data processing method and system based on Internet | |
| CN111475713A (en) | Doctor information recommendation method and device, electronic equipment, system and storage medium | |
| CN114639479A (en) | Intelligent diagnosis auxiliary system based on medical knowledge map | |
| CN113838577B (en) | Convenient layered old people MODS early death risk assessment model, device and establishment method | |
| CN107767960A (en) | Data processing method, device and the electronic equipment of clinical detection project | |
| CN106919804A (en) | Medicine based on clinical data recommends method, recommendation apparatus and server | |
| Wang et al. | Predictive classification of ICU readmission using weight decay random forest | |
| CN117476217B (en) | Chronic heart disease state of illness trend prediction system | |
| CN109192312B (en) | Intelligent management system and method for adverse events of heart failure patients | |
| WO2022141925A1 (en) | Intelligent medical service system and method, and storage medium | |
| CN109584086A (en) | Be hospitalized rational method and Related product are predicted based on prediction model | |
| Rathi et al. | Early Prediction of Diabetes Using Machine Learning Techniques | |
| CN113643814A (en) | Health management scheme recommendation method, device, equipment and storage medium | |
| CN113744877A (en) | Chronic disease assessment and intervention system with disease related factor extraction module | |
| CN112967803A (en) | Early mortality prediction method and system for emergency patients based on integrated model | |
| CN112151174A (en) | User health information analysis method and system based on physical examination data | |
| CN116564521A (en) | Chronic disease risk assessment model establishment method, medium and system | |
| CN116434899A (en) | Health record information platform establishment method based on multi-source data | |
| US20230005603A1 (en) | Intelligent emergency triage system | |
| Ieva et al. | Network analysis of comorbidity patterns in heart failure patients using administrative data | |
| CN114842975A (en) | Health management method and system for unit group | |
| CN116936082A (en) | Quantitative assessment method, system and device for physical health risk | |
| CN113948171A (en) | Matching system for automatically matching hospital grade according to patient condition | |
| CN113096127A (en) | System and method for generating brain network evolution model |
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 | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210112 |