CN109377388B - Medical insurance application method, medical insurance application device, computer equipment and storage medium - Google Patents
Medical insurance application method, medical insurance application device, computer equipment and storage medium Download PDFInfo
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- CN109377388B CN109377388B CN201811068547.XA CN201811068547A CN109377388B CN 109377388 B CN109377388 B CN 109377388B CN 201811068547 A CN201811068547 A CN 201811068547A CN 109377388 B CN109377388 B CN 109377388B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
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- 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
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- 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
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The application relates to the field of big data analysis, in particular to a medical insurance application method, a medical insurance application device, computer equipment and a storage medium. The method comprises the following steps: receiving an application request sent by a user terminal, wherein the application request carries health information of an applicant; inputting the health information into a course matching model to obtain a first virtual course matched with the applicant; acquiring a medical insurance product corresponding to the first virtual course, and sending the acquired medical insurance product to the user terminal; receiving an insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal; and performing medical insurance application according to the insurance application instruction. By adopting the method, the virtual course can be predicted for the new applicant according to the analysis of a large amount of data of the historical applicant, so that the medical insurance product can be more accurately recommended for the applicant, and the medical insurance can be applied for the applicant.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a medical insurance application method, apparatus, computer device, and storage medium.
Background
In medical insurance, an applicant is generally required to provide health information such as recent medical history, clinic data and the like, so that a doctor of medical insurance can conveniently judge whether the applicant meets the participating conditions or not, and recommend proper medical insurance products for customers.
Traditionally, health information of an applicant is analyzed, typically through experience of medical professionals and expert rules formulated according to analysis of medical literature; however, since expert rules cannot accurately determine whether health information of an applicant changes within a medical insurance time, a problem that medical insurance products recommended for the applicant are inaccurate easily occurs.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a medical insurance application method, apparatus, computer device and storage medium capable of accurately recommending medical insurance products to an applicant.
A method of medical insurance application, the method comprising:
receiving an application request sent by a user terminal, wherein the application request carries health information of an applicant;
inputting the health information into a course matching model to obtain a first virtual course matched with the applicant;
acquiring a medical insurance product corresponding to the first virtual course, and sending the acquired medical insurance product to the user terminal;
Receiving an insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal;
and performing medical insurance application according to the insurance application instruction.
In one embodiment, after receiving the application request sent by the user terminal, the method further includes:
extracting diagnosis keywords and treatment keywords in the health information;
the inputting the health information into a course matching model to obtain a first virtual course matching the applicant comprises the following steps:
and inputting the diagnosis keywords and the treatment keywords into a disease simulation model to obtain a first virtual disease course matched with the applicant.
In one embodiment, the acquiring a medical insurance product corresponding to the first virtual course of disease includes:
acquiring an application period from the application;
calculating a first medical fee of the applicant within the guarantee period according to the first virtual course;
and acquiring a medical insurance product corresponding to the first medical expense.
In one embodiment, the acquiring a medical insurance product corresponding to the first virtual course of disease includes:
calculating a first medical fee of the applicant within an application period according to the first virtual course;
Inputting the health information into a trained expert analysis model to obtain a corresponding second medical expense of the applicant within the application period;
and acquiring medical insurance products corresponding to the first medical fee and the second medical fee.
In one embodiment, after the inputting the health information into the course matching model to obtain the first virtual course matching the applicant, the method further includes:
acquiring environment data corresponding to the applicant;
acquiring intervention histories corresponding to the first virtual disease course by the environmental data;
predicting the intervention condition of the environmental data on the first virtual disease course of the applicant according to the intervention history, and obtaining the second virtual disease course of the applicant according to the intervention condition;
the obtaining a medical insurance product corresponding to the first virtual course includes:
and obtaining a medical insurance product corresponding to the second virtual course.
In one embodiment, the generating method of the disease course matching model includes:
acquiring historical application data, wherein the historical application data carries historical health data;
acquiring corresponding course data in a preset time interval according to the historical health data;
And acquiring an initial model, and inputting the historical health data and the disease course data corresponding to the preset time interval into the initial model for training to obtain a disease course matching model.
In one embodiment, the method further comprises:
acquiring verification health data and a verification virtual disease course corresponding to the verification health data;
inputting the verification health data into the disease course matching model to obtain a third virtual disease course corresponding to the verification health data;
acquiring first course data of verification health data at preset time according to the verification virtual course, and acquiring second course data of verification health data at the preset time according to the third virtual course;
and calculating the difference value of the first course data and the second course data, and correcting the disease simulation model according to the verification virtual course when the difference value exceeds a preset value.
A medical insurance application device, the device comprising:
the information acquisition module is used for receiving an application request sent by the user terminal, wherein the application request carries health information of an applicant;
the disease course establishing module is used for inputting the health information into a disease course matching model to obtain a first virtual disease course matched with the applicant;
The medical insurance product acquisition module is used for acquiring medical insurance products corresponding to the first virtual disease course and sending the acquired medical insurance products to the user terminal;
the insurance application instruction acquisition module is used for receiving insurance application instructions corresponding to the acquired medical insurance products returned by the user terminal;
and the application module is used for performing medical insurance application according to the application instruction.
A computer device comprising a memory storing a computer program and a processor implementing the steps of any one of the methods described above when the processor executes the computer program.
A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of any of the preceding claims.
According to the medical insurance application method, the medical insurance application device, the computer equipment and the storage medium, the health information of the applicant is analyzed through the trained illness state simulation model, the change condition of the applicant in a period of time is simulated, namely, a first virtual illness course, and then a medical insurance scheme corresponding to the applicant is selected according to the first virtual illness course, namely, whether the applicant can participate in insurance or a strategy for high-price insurance can be analyzed. The finally obtained medical insurance scheme is more in line with the treatment scheme of the applicant in the future participating time, and medical insurance products are more accurately recommended to the applicant, and medical insurance is applied to the applicant.
Drawings
FIG. 1 is an application scenario diagram of a traditional Chinese medicine insurance application method according to one embodiment;
FIG. 2 is a flow diagram of a method of medical insurance application in one embodiment;
FIG. 3 is a flow diagram of a model training regimen in one embodiment;
FIG. 4 is a flow diagram of a model verification scheme in one embodiment;
FIG. 5 is a block diagram of a medical insurance application device according to one embodiment;
fig. 6 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The medical insurance application method provided by the application can be applied to an application environment shown in figure 1. The terminal and the server communicate through a network. The server acquires an insuring request of an insuring user from a user terminal, inputs health information of the user in the insuring request into a course matching model to match a first virtual course corresponding to the insuring user, and recommends medical insurance products for the insuring user according to the first virtual course of the insuring user. The user terminal may be, but not limited to, various personal computers, notebook computers, smartphones, tablet computers and portable wearable devices, and the server may be implemented by a separate server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a medical insurance application method is provided, and the method is applied to the server in fig. 1 for illustration, and includes the following steps:
s202, receiving an insurance application request sent by a user terminal, wherein the insurance application request carries health information of an applicant.
The user terminal is mobile terminal equipment of the applicant, the applicant sends an insurance application request to the server through the user terminal, for example, a user performs insurance selection operation on the user terminal and fills in health information of the corresponding applicant, and the user terminal generates the insurance application request according to the user selection operation. The application request is request information sent by the applicant to the server through the user terminal and is used for informing the server that the applicant has a tendency of purchasing medical insurance products, wherein the request information comprises health information capable of reflecting the physical condition of the applicant. The applicant may fill in an application installed on the user terminal with an application request, which the user terminal sends to the server.
Specifically, the server receives an insurance application request sent to the server by the applicant through the user terminal, the insurance application request comprises health information capable of reflecting the physical condition of the applicant, and the server can judge whether the applicant can participate in insurance or recommend proper medical insurance products for the applicant through the health information of the applicant in the insurance application request.
Optionally, the server provides an application program installed on the user terminal and capable of performing data interaction with the server for the applicant, the applicant can fill in health information of the applicant through the application program installed on the user terminal to form an application request, the user terminal sends the application request to the server, and the server performs the next operation after receiving the application request of the applicant.
S204, inputting the health information into a course matching model to obtain a first virtual course matched with the applicant.
The disease course matching model is used for establishing a first virtual disease course of the applicant according to the health information of the applicant, and is used for establishing a medical expense condition prediction model of the applicant in the future corresponding medical expense condition according to the health information of the applicant in the historical application data. Since the cost of one type of disorder is regular, the medical cost condition of a customer suffering from the disorder in the future can be simulated by the historical health data of the patients suffering from the disorder; if the applicant who initiates the application for insurance is diagnosed as suffering from diabetes for one year, the change of the medical expense condition of the disease course of the second year and the third year after the diabetes is suffered from diabetes can be predicted according to the historical application data, and a first virtual disease course is established for the applicant.
The first virtual course is the change condition of the medical expense condition of the applicant in the future after the server inputs the health information of the applicant into the course matching model. The first virtual course can establish medical expense conditions corresponding to the applicant in a future period according to the years of the applicant needing to be attended. Specifically, the server inputs health information of the applicant in the application request acquired from the user terminal to a course matching model trained according to historical application data to obtain a change trend of medical expense conditions of the applicant in the future, so as to establish a first virtual course corresponding to the applicant, wherein the first virtual course can be a graph of the change of the medical expense conditions of the applicant each year.
S206, acquiring a medical insurance product corresponding to the first virtual course, and sending the acquired medical insurance product to the user terminal.
Specifically, after the first virtual course obtained in step S204, the server may recommend an appropriate medical insurance product for this purpose according to the medical expense condition of the applicant in the future, and then send the medical insurance product to the user terminal.
For example, the case where the applicant recommends a suitable medical insurance product for this purpose may be: if the corresponding first virtual course of the applicant indicates that the applicant's application has a certain risk, the applicant's application may be denied. Or when the disease of the applicant is known to be chronic disease, such as diabetes, arthritis and the like according to the health information of the applicant, the doctor-insurance product for continuous years can be recommended to the applicant according to the change of the medical spending condition of the applicant for continuous years in the first virtual disease course; in addition, the risk of the insurance applicant participating in insurance can be analyzed according to the medical expense condition of the insurance applicant, and the policy of high-price insurance can be applied to the insurance applicant participating in insurance.
S208, receiving an insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal.
The insurance application instruction is an instruction for receiving the medical insurance product sent by the server and requesting to participate in the medical insurance product.
Specifically, after the server sends the medical insurance product corresponding to the first virtual course to the user terminal of the applicant, if the applicant agrees to participate in the medical insurance product, an insurance application instruction is fed back to the server through the user terminal.
Optionally, when the server sends the medical insurance product to the user terminal through the application program, the server may include product information, participation price, participation contract and other information of the medical insurance product, and provide corresponding data interfaces in the application program to collect feedback information of the applicant, after the user terminal receives the information about the medical insurance product, the applicant may select participation approval in the application program, and sign an electronic participation contract, and the application program returns an insurance instruction to the server to inform the server that the applicant agrees to participation approval.
And S210, medical insurance application is conducted according to the application instruction.
Specifically, after receiving the insurance application instruction sent by the user terminal, the server executes the insurance operation for the insurance applicant according to the information in the insurance application instruction, the electronic insurance application and the like, and the insurance applicant successfully purchases the medical insurance product.
According to the medical insurance application method, the health information of the applicant is analyzed through the trained course matching model, the change condition of the physical condition of the applicant in a period of time, namely the first virtual course, is simulated, and then the medical insurance scheme corresponding to the health information of the applicant is selected according to the first virtual course, namely whether the applicant can participate in insurance or the policy that the applicant can participate in insurance with high price is analyzed, so that the finally obtained medical insurance scheme is more in accordance with the treatment scheme of the applicant in future participation time, medical insurance products are recommended to the applicant more accurately, and medical insurance application is performed to the applicant.
In one embodiment, after step S202 in the above medical insurance policy receives the insurance request sent by the user terminal, the method may further include: extracting diagnosis keywords and treatment keywords in the health information; the step S204 of inputting the health information into the course matching model to obtain the first virtual course matching with the applicant may include: the diagnosis keywords and the treatment keywords are input into a disease simulation model to obtain a first virtual disease course matched with the applicant.
The diagnosis keywords are information which can reflect the physical condition of the applicant in the health information of the applicant, and can be diagnosis data of doctors during inquiry or symptoms in cases of the applicant. The treatment keyword is information representing a treatment regimen adopted by the physical condition of the applicant, such as an operation, a medicine for treating a disorder, and the like, corresponding to the diagnosis keyword of the applicant.
Specifically, after receiving an application request sent by a user terminal, a server firstly extracts a diagnosis keyword reflecting the physical condition of an applicant and a treatment keyword corresponding to the diagnosis keyword of the applicant and representing a treatment scheme adopted by the physical condition of the applicant from health information carried by the application request, inputs the diagnosis keyword and the treatment keyword into a disease course matching model, and the disease course matching model can identify the input diagnosis keyword and treatment keyword according to trained logic and establish a first virtual disease course corresponding to the diagnosis keyword and the treatment keyword.
Alternatively, the server may recognize the diagnosis keywords and the treatment keywords in the health information according to the semantic recognition program; health information can also be identified by trained keyword extraction rules.
In the embodiment, the diagnosis keywords and the treatment keywords in the health information are extracted through the server and then input into the disease course matching model for analysis, the model does not need to identify all the health information, only the keywords in the health information are needed to be analyzed, and the analysis efficiency of the disease course matching model on the health information is improved.
In one embodiment, obtaining a medical insurance product corresponding to a first virtual course of disease includes: acquiring an application period from an application; calculating a first medical fee of the applicant in the guarantee period according to the first virtual course; and acquiring a medical insurance product corresponding to the first medical expense.
The insurance coverage is the time the insurance applicant wants to participate in, and when the insurance applicant inputs an insurance request through the user terminal, the insurance coverage can be selected simultaneously, such as one year insurance coverage, two years insurance coverage, ten years insurance coverage and the like.
The first medical expense is that the server predicts the medical expense condition in the insurance duration after analyzing the first virtual course of the applicant, and the applicant spends in medical treatment; if a certain applicant who has suffered from diabetes for one year requires medical insurance for one year, the medical expense of the applicant in the second year of suffering from diabetes can be predicted through the first virtual course of disease of the applicant.
Specifically, when the medical insurance staff selects the medical insurance scheme for the applicant through the server, the medical expense condition of the applicant in the participation period is mainly considered, so after the first virtual course of the applicant is obtained, the medical expense of the applicant can be predicted according to the change of the health condition of the applicant in the insurance period, and a proper medical insurance scheme is recommended for the applicant.
According to the embodiment, after the first virtual course of the applicant is obtained, the prediction of the first medical expense of the applicant in the guarantee period is introduced, and the medical insurance scheme is recommended to the applicant more accurately.
In one embodiment, step S206 in the medical insurance application method described above obtains a medical insurance product corresponding to the first virtual course, which may include: calculating a first medical fee of the applicant in the guarantee period according to the first virtual course; inputting the health information into a trained expert analysis model to obtain a corresponding second medical expense of the applicant within the guarantee period; and acquiring medical insurance products corresponding to the first medical expense and the second medical expense.
The expert analysis model is trained according to long-term clinical analysis and clinical experience summarized by medical research, and can predict other medical expenses of the applicant except the first virtual course possibly occurring in the future according to the health information of the applicant; such as medical habits of the applicant, frequent hospitals, whether to pay out physiotherapy costs regularly, etc. The second medical expense is that after the expert analysis model analyzes the health information of the applicant, other medical expense possibly caused by the applicant in the guarantee period is obtained, and then the total medical expense of the applicant in the guarantee period is predicted. The second medical fee is obtained, for example, based on the first medical fee being fluctuated by the applicant's cost in the guarantee period.
Specifically, after obtaining the first virtual course of the applicant, the server may predict the medical expense of the applicant according to the change of the medical expense condition of the applicant within the applicant's guarantee period, so as to obtain a first medical expense; and then the server predicts whether the applicant has other medical expense in the insurance period according to the expert analysis model, adjusts the first medical expense according to the expert analysis model to obtain the second medical expense, and is used as a supplementary analysis for selecting a medical insurance scheme for the object to be analyzed.
According to the embodiment, besides the first medical cost of the applicant in the guarantee period in the previous embodiment, the second medical cost obtained after the expert analysis model analyzes the health information of the applicant is introduced, so that the server is more practical when recommending the medical insurance scheme for the applicant, and the medical insurance scheme can be more accurately recommended for the applicant.
In one embodiment, after the step S204 of the medical insurance application method inputs the health information into the course matching model to obtain the first virtual course matching with the applicant, the method may further include: acquiring environment data corresponding to an applicant; acquiring intervention histories corresponding to the first virtual disease course by the environmental data; predicting the intervention condition of the environmental data on the first virtual course of the applicant according to the intervention history, and obtaining the second virtual course of the applicant according to the intervention condition; step S206 of obtaining a medical insurance product corresponding to the first virtual course may include: and obtaining a medical insurance product corresponding to the second virtual course.
The environmental data corresponding to the applicant may include working environment, living environment or living habit of the object to be analyzed, such as whether the object is in smoke environment or radiation environment for a long time, or whether there are factors such as smoking, drinking, etc. that may affect medical cost of the applicant.
The intervention history corresponding to the first virtual course by the environmental data is the influence trend of the environmental data, which is obtained by analyzing the history application data or other medical systems and medical data, on the medical expense of the applicant by the server, and is known by data analysis: the smoke environment exacerbates the condition of bronchitis, and the medical costs of bronchitis patients in this environment tend to vary from those of patients in this environment.
Specifically, the server introduces environmental variables of the object to be analyzed, and supplements and corrects the virtual course obtained by model analysis; the server analyzes the environmental data of the applicant, predicts the intervention condition of the environmental data on the first virtual course of the applicant through the intervention history, and adjusts the first virtual course to obtain the second virtual course of the applicant.
According to the embodiment, the intervention of the environmental factors on the medical expense condition of the applicant is introduced, so that the influence of the environmental data on the physical condition of the applicant is considered when the server recommends the medical insurance scheme for the applicant, and the medical insurance scheme can be more accurately recommended for the applicant.
In one embodiment, the medical insurance application method further includes a generation mode of the course matching model, and the mode may include:
s302, acquiring historical application data, wherein the historical application data carries historical health data.
The historical application data are a large amount of historical application information of the applicant, which is acquired from the medical insurance system by the server; the historical insurance data may be the insurance data of one or more years above the medical insurance product, or the insurance data of several years above the medical insurance product similar to or related to the medical insurance product of the application.
The historical health data is health data corresponding to the physical condition of the applicant and carried in the historical insurance application data, the health data of the applicant needs to be provided every time the applicant purchases the medical insurance product, so that the medical insurance system can evaluate the participation risk of the applicant conveniently, and the historical health data is the data reflecting the medical expense condition provided by the applicant who purchases the medical insurance product before.
Specifically, the server acquires historical application data of the previously-participating applicant from the medical insurance system, wherein the historical application data comprises historical health data of the corresponding applicant.
S304, acquiring corresponding disease course data in a preset time interval according to the historical health data.
The preset time interval is a time interval corresponding to the guarantee time of the medical insurance product, if the guarantee period of the medical insurance product provided by the applicant is one, three or five years, the server can acquire the disease course data of a certain disease in each year from the historical health data, so that the change of the medical expense condition of the disease in each year after the disease is obtained.
The course data is a change in medical spending for a condition extracted from the historical health data over a preset time interval. A change in medical spending condition; specifically, after the server acquires the historical application data carrying the historical health data, the server sequentially extracts the disease course data of a certain disease in a preset time interval so as to know the change of the medical expense condition of the disease in each preset time interval.
Optionally, after the server obtains the historical health data, the keywords of the historical health data, which can represent the symptoms of the corresponding applicant, are identified, then the historical health data are grouped according to the keywords, the applicant suffering from the same symptoms is taken as a group, and then the suffering time of each applicant in each group and the medical expense condition of the corresponding applicant in each preset time interval are obtained. S306, acquiring an initial model, and inputting the history health data and the course data corresponding to the preset time interval into the initial model for training to obtain a course matching model.
The initial model is a blank model for training a course matching model, and the form of the initial model is consistent with the course matching model to be trained.
Specifically, through historical health data in a large number of historical administration data of the same disease, a corresponding change trend of medical expense of a single person corresponding to the historical health data in each preset time interval can be obtained, especially for some chronic diseases, through searching cases of the same or related diseases, medical expense data in a past period in the historical administration data corresponding to the cases is used as a virtual disease course of the disease corresponding to the disease, and a model of a first virtual disease course of a corresponding applicant in a future period can be obtained according to the input health information through training, namely the disease course matching model.
For example, the change of the diabetes in each year after the diabetes is affected can be analyzed by the change (deterioration or cure, etc.) of the medical spending condition of a plurality of diabetics (such as 6-year diabetes history of patient A/3-year diabetes history of patient B/1-year diabetes history of patient C), and if it is desired to obtain the change of the medical spending condition of the patient who just suffers from diabetes in the first year, the medical spending condition data of patient C and the medical spending condition of patient A and patient B in the first year can be used as the virtual course of the diabetes in the first year; if it is desired to obtain a change in the medical cost condition of the previous 3 years, the actual medical cost condition of the previous three years of the patient A and the medical cost condition of the previous three years of the patient B can be analyzed to form a corresponding virtual course of the previous three years of the diabetic patient, and the like.
According to the model training mode in the embodiment, the history application data is used as the basis for training the course matching model, so that the obtained course matching model can obtain the first virtual course more accurately according to the input health information of the applicant.
In one embodiment, the medical insurance application method further includes a model verification mode, and the mode may include:
s402, acquiring verification health data and verification virtual disease course corresponding to the verification health data.
The health data verification module is used for verifying the health data of the course matching model; a certain proportion can be selected from the historical health data as verification health data.
The verification virtual course is to verify the progress of the course corresponding to the health data, the disease condition corresponding to the health data can be obtained, and the change of the medical expense condition of the disease condition in a continuous preset time period is established to verify the virtual course.
Specifically, when verifying the course matching model, the server acquires verification health data and a verification virtual course corresponding to the verification health data.
S404, inputting the verification health data into the course matching model to obtain a third virtual course corresponding to the verification health data.
The third virtual course is a virtual course obtained according to rules trained in the course matching model after the verification health data are input into the course matching model.
Specifically, after acquiring verification health data, the server inputs the verification health data into a disease course matching model, analyzes the verification health data according to rules trained by the model, identifies symptoms in the verification health data, predicts changes of the symptoms in future medical expense conditions, and obtains a third virtual disease course.
S406, acquiring first course data of the verification health data at a preset time according to the verification virtual course, and acquiring second course data of the verification health data at the preset time according to the third virtual course.
The preset time is used for judging and verifying the difference between the virtual disease course and the third virtual disease course, and the selection of the preset time can be selected according to clinical experience.
Specifically, after the server acquires the verification virtual disease course and the third virtual disease course corresponding to the verification health data, the difference between the two needs to be compared to verify the accuracy of the disease course matching model. Since the validation virtual course and the third virtual course are variations in the medical costs of a condition over a period of time (typically a longer period of time, such as ten years), a point in time may be selected for comparison that validation health data is first course data in the validation virtual course and second course data in the third virtual course.
S408, calculating a difference value between the first course data and the second course data, and correcting the course matching model according to the verified virtual course when the difference value exceeds a preset value.
Specifically, the server compares the first course data with the second course data, calculates the difference value between the first course data and the second course data, and when the secondary difference value is larger than a preset value, the result obtained by the course matching model is larger than the course change in reality, and the course matching model needs to be corrected.
According to the embodiment, the disease course matching model is corrected by verifying the health data, so that the disease course matching model is more accurate.
It should be understood that, although the steps in the flowcharts of fig. 2 to 4 are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily occur in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps or stages of other steps.
In one embodiment, as shown in FIG. 5, there is provided a medical insurance application apparatus comprising: an information acquisition module 100, a course creation module 200, a medical insurance product acquisition module 300, an insurance application instruction acquisition module 400, and an insurance application module 500, wherein:
the information obtaining module 100 is configured to receive an application request sent by a user terminal, where the application request carries health information of an applicant.
The course setting module 200 is configured to input the health information into a course matching model to obtain a first virtual course matching with the applicant.
The medical insurance product obtaining module 300 is configured to obtain a medical insurance product corresponding to the first virtual disease course, and send the obtained medical insurance product to the user terminal.
And the insurance application instruction acquisition module 400 is used for receiving the insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal.
The application module 500 is used for performing medical insurance application according to the application instruction.
In one embodiment, the medical insurance application device further includes:
and the keyword extraction module is used for extracting diagnosis keywords and treatment keywords in the health information.
The disease course establishing module is further configured to input a diagnosis keyword and a treatment keyword into the disease simulation model to obtain a first virtual disease course matched with the applicant.
In one embodiment, the medical insurance product acquisition module in the medical insurance application device may include:
and the expense calculation unit is used for calculating the first medical expense of the applicant in the guarantee period according to the first virtual course.
And the medical insurance product acquisition unit is used for acquiring medical insurance products corresponding to the first medical expense.
In one embodiment, the medical insurance product obtaining module in the medical insurance application device may further include:
and the insurance duration acquisition unit is used for acquiring the insurance duration from the insurance application.
And the first expense calculation unit is used for calculating the first medical expense of the applicant in the guarantee period according to the first virtual course.
The first expense calculation unit is used for inputting the health information into the trained expert analysis model to obtain the corresponding second medical expense of the applicant in the application period.
And the medical insurance product calculation unit is used for acquiring medical insurance products corresponding to the first medical expense and the second medical expense.
In one embodiment, the medical insurance application device may further include:
the environment analysis module is used for acquiring environment data corresponding to the applicant.
And the history intervention module is used for acquiring intervention histories corresponding to the first virtual disease course by the environmental data.
The intervention course module is used for predicting the intervention condition of the environmental data on the first virtual course of the applicant according to the intervention history and obtaining the second virtual course of the applicant according to the intervention condition.
The medical insurance product acquisition module may be further configured to acquire a medical insurance product corresponding to the second virtual disease course.
In one embodiment, the medical insurance application device may further include:
the historical data acquisition module is used for acquiring historical application data, wherein the historical application data carries historical health data.
And the disease course acquisition module is used for acquiring corresponding disease course data in a preset time interval according to the historical health data.
The model training module is used for acquiring an initial model, inputting the history health data and the disease course data corresponding to the preset time interval into the initial model, and training to obtain a disease course matching model.
In one embodiment, the medical insurance application device may further include:
and the verification course module is used for acquiring verification health data and verification virtual courses corresponding to the verification health data.
And the model analysis module is used for inputting the verification health data into the disease course matching model to obtain a third virtual disease course corresponding to the verification health data.
The timing extraction module is used for acquiring first course data of the verification health data in preset time according to the verification virtual course and acquiring second course data of the verification health data in preset time according to the third virtual course.
And the correction module is used for calculating the difference value between the first course data and the second course data, and correcting the course matching model according to the verification virtual course when the difference value exceeds a preset value.
Specific limitations regarding the medical insurance application device may be found in the above limitations on the medical insurance application method, and will not be described in detail herein. The various modules in the medical insurance application device described above may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing medical insurance application data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a medical insurance application method.
It will be appreciated by those skilled in the art that the structure shown in FIG. 6 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of: receiving an insurance application request sent by a user terminal, wherein the insurance application request carries health information of an insurance applicant; inputting the health information into a course matching model to obtain a first virtual course matched with the applicant; acquiring a medical insurance product corresponding to the first virtual course, and sending the acquired medical insurance product to a user terminal; receiving an insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal; medical insurance application is conducted according to the application instruction.
In one embodiment, after the processor executes the computer program, the method further includes: extracting diagnosis keywords and treatment keywords in the health information; inputting the health information into the course matching model to obtain a first virtual course matching the applicant, the first virtual course being implemented when the processor executes the computer program, the processor being implemented when the processor executes the computer program, may include: the diagnosis keywords and the treatment keywords are input into a disease simulation model to obtain a first virtual disease course matched with the applicant.
In one embodiment, obtaining a medical insurance product corresponding to a first virtual course of disease, which is implemented when the processor executes the computer program, may include: acquiring an application period from an application; calculating a first medical fee of the applicant in the guarantee period according to the first virtual course; and acquiring a medical insurance product corresponding to the first medical expense.
In one embodiment, obtaining a medical insurance product corresponding to a first virtual course of disease implemented when a processor executes a computer program includes: calculating a first medical fee of the applicant in the guarantee period according to the first virtual course; inputting the health information into a trained expert analysis model to obtain a corresponding second medical expense of the applicant within the guarantee period; and acquiring medical insurance products corresponding to the first medical expense and the second medical expense.
In one embodiment, after inputting the health information into the course matching model to obtain the first virtual course matching the applicant, the processor, when executing the computer program, further comprises: acquiring environment data corresponding to an applicant; acquiring intervention histories corresponding to the first virtual disease course by the environmental data; predicting the intervention condition of the environmental data on the first virtual course of the applicant according to the intervention history, and obtaining the second virtual course of the applicant according to the intervention condition; acquiring the medical insurance product corresponding to the first virtual course as implemented when the processor executes the computer program may include: and obtaining a medical insurance product corresponding to the second virtual course.
In one embodiment, the medical insurance application method implemented when the processor executes the computer program further includes a manner of generating a course matching model, the manner including: acquiring historical application data, wherein the historical application data carries historical health data; acquiring corresponding course data in a preset time interval according to the historical health data; and acquiring an initial model, and inputting the historical health data and the disease course data corresponding to the preset time interval into the initial model for training to obtain a disease course matching model.
In one embodiment, the medical insurance application method implemented when the processor executes the computer program may further include: acquiring verification health data and a verification virtual disease course corresponding to the verification health data; inputting the verification health data into a disease course matching model to obtain a third virtual disease course corresponding to the verification health data; acquiring first course data of the verification health data at preset time according to the verification virtual course, and acquiring second course data of the verification health data at preset time according to the third virtual course; and calculating a difference value between the first course data and the second course data, and correcting the disease simulation model according to the verified virtual course when the difference value exceeds a preset value.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: receiving an insurance application request sent by a user terminal, wherein the insurance application request carries health information of an insurance applicant; inputting the health information into a course matching model to obtain a first virtual course matched with the applicant; acquiring a medical insurance product corresponding to the first virtual course, and sending the acquired medical insurance product to a user terminal; receiving an insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal; medical insurance application is conducted according to the application instruction.
In one embodiment, after receiving the application request sent by the user terminal, the implementation of the computer program when executed by the processor may further include: extracting diagnosis keywords and treatment keywords in the health information; inputting the health information into the course matching model to obtain a first virtual course matching the applicant, which is implemented when the computer program is executed by a processor, may include: the diagnosis keywords and the treatment keywords are input into a disease simulation model to obtain a first virtual disease course matched with the applicant.
In one embodiment, the obtaining of the medical insurance product corresponding to the first virtual course of disease, which is implemented when the computer program is executed by the processor, may include: acquiring an application period from the application; calculating a first medical fee of the applicant in the guarantee period according to the first virtual course; and acquiring a medical insurance product corresponding to the first medical expense.
In one embodiment, obtaining a medical insurance product corresponding to a first virtual course of disease, the computer program when executed by a processor, comprises: calculating a first medical fee of the applicant in the guarantee period according to the first virtual course; inputting the health information into a trained expert analysis model to obtain a corresponding second medical expense of the applicant within the guarantee period; and acquiring medical insurance products corresponding to the first medical expense and the second medical expense.
In one embodiment, after inputting the health information into the course matching model to obtain the first virtual course matching the applicant, the implementation when the computer program is executed by the processor may further include: acquiring environment data corresponding to an applicant; acquiring intervention histories corresponding to the first virtual disease course by the environmental data; predicting the intervention condition of the environmental data on the first virtual course of the applicant according to the intervention history, and obtaining the second virtual course of the applicant according to the intervention condition; acquiring the medical insurance product corresponding to the first virtual course, which is implemented when the computer program is executed by the processor, may include: and obtaining a medical insurance product corresponding to the second virtual course.
In one embodiment, the medical insurance application method implemented when the computer program is executed by the processor may further include a manner of generating a course matching model, the manner including: acquiring historical application data, wherein the historical application data carries historical health data; acquiring corresponding course data in a preset time interval according to the historical health data; and acquiring an initial model, and inputting the historical health data and the disease course data corresponding to the preset time interval into the initial model for training to obtain a disease course matching model.
In one embodiment, the medical insurance application method implemented when the computer program is executed by the processor may further include: acquiring verification health data and a verification virtual disease course corresponding to the verification health data; inputting the verification health data into a disease course matching model to obtain a third virtual disease course corresponding to the verification health data; acquiring first course data of the verification health data at preset time according to the verification virtual course, and acquiring second course data of the verification health data at preset time according to the third virtual course; and calculating a difference value between the first course data and the second course data, and correcting the disease simulation model according to the verified virtual course when the difference value exceeds a preset value.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A method of medical insurance application, the method comprising:
receiving an application request sent by a user terminal, wherein the application request carries health information of an applicant;
inputting the health information into a course matching model to obtain a first virtual course matched with the applicant; the first virtual course is the change condition of the medical expense condition of the applicant in the future after the health information of the applicant is input into a course matching model;
Acquiring a medical insurance product corresponding to the first virtual course, and sending the acquired medical insurance product to the user terminal;
receiving an insurance application instruction corresponding to the acquired medical insurance product returned by the user terminal;
medical insurance application is carried out according to the application instruction;
the obtaining a medical insurance product corresponding to the first virtual course includes:
calculating a first medical fee of the applicant within an application period according to the first virtual course; the first medical expense is that the server predicts the medical expense condition in the insurance coverage after analyzing the first virtual course of the insurance applicant;
inputting the health information into a trained expert analysis model to obtain a second medical fee corresponding to the applicant within the application period; the expert analysis model is a model trained according to clinical experience summarized by long-term clinical analysis and medical research; the second medical expense is medical expense except the first virtual course possibly caused by the applicant in the guarantee period after the expert analysis model analyzes the health information of the applicant;
acquiring a medical insurance product corresponding to the first medical fee and the second medical fee;
After the health information is input into the course matching model to obtain the first virtual course matched with the applicant, the method further comprises the following steps:
acquiring environment data corresponding to the applicant;
acquiring intervention histories corresponding to the first virtual disease course by the environmental data;
predicting the intervention condition of the environmental data on a first virtual disease course of the applicant according to the intervention history, and adjusting the first virtual disease course according to the intervention condition to obtain a second virtual disease course of the applicant;
the obtaining a medical insurance product corresponding to the first virtual course includes:
and obtaining a medical insurance product corresponding to the second virtual course.
2. The method according to claim 1, wherein after receiving the application request sent by the user terminal, the method comprises:
extracting diagnosis keywords and treatment keywords in the health information;
the inputting the health information into a course matching model to obtain a first virtual course matching the applicant comprises the following steps:
and inputting the diagnosis keywords and the treatment keywords into a disease simulation model to obtain a first virtual disease course matched with the applicant.
3. The method of claim 1, wherein the acquiring a medical insurance product corresponding to the first virtual course of disease comprises:
acquiring an application period from the application;
calculating a first medical fee of the applicant within the guarantee period according to the first virtual course;
and acquiring a medical insurance product corresponding to the first medical expense.
4. The method of claim 1, wherein the course matching model is generated in a manner that includes:
acquiring historical application data, wherein the historical application data carries historical health data;
acquiring corresponding course data in a preset time interval according to the historical health data; the course data is the change of medical spending condition of a certain disease extracted from the historical health data within a preset time interval;
and acquiring an initial model, and inputting the historical health data and the disease course data corresponding to the preset time interval into the initial model for training to obtain a disease course matching model.
5. The method according to claim 1, wherein the method further comprises:
acquiring verification health data and a verification virtual disease course corresponding to the verification health data;
Inputting the verification health data into the disease course matching model to obtain a third virtual disease course corresponding to the verification health data; the third virtual course is a virtual course obtained according to rules trained in the course matching model after the verification health data are input into the course matching model;
acquiring first course data of verification health data at preset time according to the verification virtual course, and acquiring second course data of verification health data at the preset time according to the third virtual course;
and calculating a difference value between the first course data and the second course data, and correcting the course matching model according to the verification virtual course when the difference value exceeds a preset value.
6. A medical insurance application device, the device comprising:
the information acquisition module is used for receiving an application request sent by the user terminal, wherein the application request carries health information of an applicant;
the disease course establishing module is used for inputting the health information into a disease course matching model to obtain a first virtual disease course matched with the applicant; the first virtual course is the change condition of the medical expense condition of the applicant in the future after the health information of the applicant is input into a course matching model;
The medical insurance product acquisition module is used for acquiring medical insurance products corresponding to the first virtual disease course and sending the acquired medical insurance products to the user terminal;
the insurance application instruction acquisition module is used for receiving insurance application instructions corresponding to the acquired medical insurance products returned by the user terminal;
the application module is used for performing medical insurance application according to the application instruction;
the medical insurance product acquisition module comprises:
a first fee calculation unit for calculating a first medical fee of the applicant within an application period according to the first virtual course; the first medical expense is that the server predicts the medical expense condition in the insurance coverage after analyzing the first virtual course of the insurance applicant;
the second expense calculation unit is used for inputting the health information into a trained expert analysis model to obtain a second medical expense corresponding to the applicant in the application period; the expert analysis model is a model trained according to clinical experience summarized by long-term clinical analysis and medical research; the second medical expense is medical expense except the first virtual course possibly caused by the applicant in the guarantee period after the expert analysis model analyzes the health information of the applicant;
A medical insurance product calculation unit, configured to obtain a medical insurance product corresponding to the first medical fee and the second medical fee;
the device further comprises:
the environment analysis unit is used for acquiring environment data corresponding to the applicant;
the history intervention module is used for acquiring intervention histories corresponding to the first virtual disease course by the environmental data;
the intervention course module is used for predicting the intervention condition of the environmental data on the first virtual course of the applicant according to the intervention history, and adjusting the first virtual course according to the intervention condition to obtain the second virtual course of the applicant;
the medical insurance product acquisition module is further used for acquiring medical insurance products corresponding to the second virtual disease course.
7. The apparatus of claim 6, wherein the apparatus further comprises:
the keyword extraction module is used for extracting diagnosis keywords and treatment keywords in the health information;
the course establishing module is further used for inputting diagnosis keywords and treatment keywords into the illness state simulation model to obtain a first virtual course matched with the applicant.
8. The apparatus of claim 6, wherein the medical insurance product acquisition module comprises:
The insurance duration acquisition unit is used for acquiring the insurance duration from the insurance application;
a fee calculation unit for calculating a first medical fee of the applicant within the guarantee period according to the first virtual course;
and the medical insurance product acquisition unit is used for acquiring the medical insurance product corresponding to the first medical expense.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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| CN108520444A (en) * | 2018-04-12 | 2018-09-11 | 中国平安人寿保险股份有限公司 | Insurance products recommend method, unit and computer readable storage medium |
| CN108510402A (en) * | 2018-06-06 | 2018-09-07 | 中国平安人寿保险股份有限公司 | Insurance kind information recommendation method, device, computer equipment and storage medium |
| CN109003193A (en) * | 2018-09-10 | 2018-12-14 | 平安科技（深圳）有限公司 | Insurance risk prediction technique, device, computer equipment and storage medium |
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