CN109544357A - Data processing method and device based on medical insurance data - Google Patents
Data processing method and device based on medical insurance data Download PDFInfo
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- CN109544357A CN109544357A CN201811250289.7A CN201811250289A CN109544357A CN 109544357 A CN109544357 A CN 109544357A CN 201811250289 A CN201811250289 A CN 201811250289A CN 109544357 A CN109544357 A CN 109544357A
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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
Abstract
The embodiment of the present application provides a kind of data processing method and device based on medical insurance data, wherein, this method comprises: receiving the user data that target user sends, and extract the medical insurance data of the region where the target user, wherein, the user data includes the actual age of the target user；The basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user；According to the user data and the basic medical treatment expense, the target medical expense of the target user is calculated；According to the mapping relations between preset medical expense and physiological age, the real physiological age of the target user corresponding with the target medical expense is determined；According to the actual age and the real physiological age, the target risk grade of the target user is determined, with this, be able to ascend accuracy when determining consumer's risk grade.
Description
Technical field
This application involves technical field of data processing, and in particular to a kind of data processing method and dress based on medical insurance data
It sets.
Background technique
As social medical insurance (medical insurance) is gradually by public well-established, more and more Public choice purchase business doctors
Treat insurance.When the public buys and insures, insurance company needs to carry out the public core guarantor, and core guarantor is very heavy in reinsurance process
The step of one wanted controls risk, insurance company carries out core guarantor to client often through means such as health informings at this stage, sentences
Whether disconnected client meets the requirement of insuring of some insurance products.
Traditional medical class adjuster process, mainly by traditional clinical research experience, to the potential healthy wind of client
Danger is estimated, obtains the risk class of client, be easy to cause the accuracy in terms of the risk class judgement to client lower.
Summary of the invention
The embodiment of the present application provides a kind of data processing method and device based on medical insurance data, is able to ascend determining user
Accuracy when risk class.
The first aspect of the embodiment of the present application provides a kind of data processing method based on medical insurance data, the method packet
It includes:
The user data that target user sends is received, and extracts the medical insurance data of the region where the target user,
Wherein, the user data includes the actual age of the target user；
The basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user；
According to the user data and the basic medical treatment expense, the target medical expense of the target user is calculated；
According to the mapping relations between preset medical expense and physiological age, determine and the target medical expense phase
The real physiological age of the corresponding target user；
According to the actual age and the real physiological age, the target risk grade of the target user is determined.
The second aspect of the embodiment of the present application provides a kind of data processing equipment based on medical insurance data, described device packet
Include receiving unit, the first determination unit, computing unit, the second determination unit and third determination unit, wherein
The receiving unit, for receiving the user data of target user's transmission, and the extraction target user place
Region medical insurance data, wherein the user data includes the actual age of the target user；
First determination unit, for determining the target according to the medical insurance data of region where the target user
The basic medical treatment expense of user；
The computing unit, for calculating the target and using according to the user data and the basic medical treatment expense
The target medical expense at family；
Second determination unit, for determining according to the mapping relations between preset medical expense and physiological age
The real physiological age of the target user corresponding with the target medical expense out；
The third determination unit, for determining the mesh according to the actual age and the real physiological age
Mark the target risk grade of user.
The third aspect of the embodiment of the present application provides a kind of terminal, including processor, input equipment, output equipment and storage
Device, the processor, input equipment, output equipment and memory are connected with each other, wherein the memory is for storing computer
Program, the computer program include program instruction, and the processor is configured for calling described program instruction, are executed such as this
Apply for the step instruction in embodiment first aspect.
The fourth aspect of the embodiment of the present application provides a kind of computer readable storage medium, wherein above-mentioned computer can
Read the computer program that storage medium storage is used for electronic data interchange, wherein above-mentioned computer program executes computer
The step some or all of as described in the embodiment of the present application first aspect.
5th aspect of the embodiment of the present application provides a kind of computer program product, wherein above-mentioned computer program produces
Product include the non-transient computer readable storage medium for storing computer program, and above-mentioned computer program is operable to make to count
Calculation machine executes the step some or all of as described in the embodiment of the present application first aspect.The computer program product can be
One software installation packet.
Implement the embodiment of the present application, at least has the following beneficial effects:
By the embodiment of the present application, the user data that target user sends is received, and extracts the target user place
Region medical insurance data, wherein the user data includes the actual age of the target user, according to the target user
The medical insurance data of place region determine the basic medical treatment expense of the target user, according to the user data and the basis
Medical expense calculates the target medical expense of the target user, according between preset medical expense and physiological age
Mapping relations determine the real physiological age of the target user corresponding with the target medical expense, according to described
Actual age and the real physiological age, determine the target risk grade of the target user, it therefore, can be according to reception
The user data that the target user arrived sends, the target user's that the medical insurance data of region in conjunction with where user are determined is true
Physiological age finally obtains the risk class of user according to the real physiological age of user and actual age, relative to existing side
The risk class of user is obtained in case by clinical experience, can be promoted to a certain extent risk class acquisition accuracy with
And intelligence.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of application for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 provides a kind of application scenarios schematic diagram of data processing method for the embodiment of the present application；
Fig. 2 provides a kind of flow diagram of data processing method based on medical insurance data for the embodiment of the present application；
Fig. 3 provides the flow diagram of another data processing method based on medical insurance data for the embodiment of the present application；
Fig. 4 provides the flow diagram of another data processing method based on medical insurance data for the embodiment of the present application；
Fig. 5 provides the flow diagram of another data processing method based on medical insurance data for the embodiment of the present application；
Fig. 6 provides the flow diagram of another data processing method based on medical insurance data for the embodiment of the present application；
Fig. 7 is a kind of structural schematic diagram of terminal provided by the embodiments of the present application；
Fig. 8 provides a kind of structural schematic diagram of data processing equipment based on medical insurance data for the embodiment of the present application.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of embodiments of the present application, instead of all the embodiments.It is based on
Embodiment in the application, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall in the protection scope of this application.
The description and claims of this application and term " first " in above-mentioned attached drawing, " second " etc. are for distinguishing
Different objects, are not use to describe a particular order.In addition, term " includes " and " having " and their any deformations, it is intended that
It is to cover and non-exclusive includes.Such as the process, method, system, product or equipment for containing a series of steps or units do not have
It is defined in listed step or unit, but optionally further comprising the step of not listing or unit, or optionally also wrap
Include other step or units intrinsic for these process, methods, product or equipment.
" embodiment " mentioned in this application is it is meant that a particular feature, structure, or characteristic described can be in conjunction with the embodiments
Included at least one embodiment of the application.The phrase, which occurs, in each position in the description might not each mean phase
Same embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art are explicitly
Implicitly understand, embodiments described herein can be combined with other embodiments.
Electronic device involved by the embodiment of the present application may include the various handheld devices with wireless communication function,
Mobile unit, wearable device calculate equipment or are connected to other processing equipments and various forms of radio modem
User equipment (user equipment, UE), mobile station (mobile station, MS), terminal device (terminal
Device) etc..For convenience of description, apparatus mentioned above is referred to as electronic device.
It is right first below in order to better understand the data processing method provided by the embodiments of the present application based on medical insurance data
The application scenarios of data processing method based on medical insurance data are briefly introduced.Referring to Fig. 1, Fig. 1 is the embodiment of the present application
A kind of application scenarios schematic diagram of data processing method is provided.As shown in Figure 1, target user can pass through electricity when applying for insurance
Sub-device 101 sends user information to medicare system 102, and user data includes the actual age of target user, medicare system 102
It receives target user and passes through the user data that electronic device 101 is sent, medicare system 102 extracts the region where target user
Medical insurance data, medicare system 102 determine the basis doctor of target user according to the medical insurance data of the region where target user
Treatment expense, basic medical treatment expense can be client similar with target user average health care costs, medicare system 102 according to
User data and basic medical treatment expense calculate the target medical expense of target user, and medicare system 102 is according to preset payment for medical care
With the mapping relations between physiological age, determine that the target user's corresponding with the target medical expense is true
Physiological age, finally, medicare system 102 is determined according to the actual age of target user and the real physiological age of target user
The target risk grade of target user out obtains user by clinical experience relative in existing scheme by the above method
Risk class, can be promoted to a certain extent risk class acquisition accuracy and intelligence.
Referring to Fig. 2, Fig. 2 provides a kind of process of data processing method based on medical insurance data for the embodiment of the present application
Schematic diagram.As shown in Fig. 2, data processing method includes step 201-205, it is specific as follows:
201, the user data that target user sends is received, and extracts the medical insurance number of the region where the target user
According to, wherein the user data includes the actual age of the target user.
Wherein, user data may include at least one data type, data type can include: actual age, gender, body
Whether whether high weight, smoke, drink, medical history, motion conditions, diet situation, the state of mind and family's medical history etc..Mesh
Region where marking user can be region belonging to city where target, ground belonging to province where can be target user
Domain, different regions have different medical insurance data.
Optionally, target user can send user data by electronic device when sending user data,
It can be carried out by providing user data template in medicare system, user data is filled in, and after the completion of filling in, is filled by electronics
It sets and sends medicare system for user data.
202, the basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user
With.
Optionally, a kind of method of possible determining basic medical treatment expense are as follows: according to the medical insurance of region where target user
Data calculate the average health care costs of crowd belonging to target user in the region, using the average health care costs of the crowd as
The basic medical treatment expense of target user.
Wherein, whole people of region where target user can divide multiple crowds, above-mentioned multiple crowds can include: poor
Crowd, general population, middle layer crowd or rich in crowd etc..General population for example can be the people that common wage-earners are constituted
Group, middle layer crowd for example can be the crowd that in company or enterprise etc. there is the people of certain position to be constituted, for example rich in crowd
It can be the crowd that the higher people that possesses wealth is constituted.Crowd can also be including teacher stratum, civil servant stratum etc., herein only
It is not specifically limited to illustrate.Judge that crowd belonging to target user can be according to the salary level of target user, occupation
Etc. being differentiated.
203, according to the user data and the basic medical treatment expense, the target payment for medical care of the target user is calculated
With.
Optionally, a kind of method of the possible target medical expense for calculating target user, which can be reported, includes step A1-A2, tool
Body is as follows:
A1, regulation coefficient group is determined according at least one described data type；
Wherein, whether at least one data type may include: actual age, gender, height, weight, smoke, drink
One or more of wine, medical history, motion conditions, diet situation, the state of mind and family's medical history.Each data type tool
There is different regulation coefficients, by taking weight as an example, according to the height and gender of target user, obtains the model of target user's normal type
It encloses, the weight in nomal body weight range, regulation coefficient 1.0, higher than the weight of nomal body weight range, then with every increase
15kg, regulation coefficient increase by 0.05, proportionally less than 15kg, increase regulation coefficient, for example, nomal body weight range is 50-
60kg, then the regulation coefficient that regulation coefficient when 75kg is 1.05,90kg is 1.1, by taking family's medical history as an example, in family's medical history such as
Fruit includes 9 big diseases, then it includes: cancer that regulation coefficient, which is 1.2,9 big diseases,；Heart disease；Hepatitis B；Hypertension；Diabetes；Cardiac muscle
More fill in；Rheumatoid cerebral thrombosis；Hemiplegia.Certainly there can also be other regulation coefficient setting means, herein by way of example only.
A2, using the regulation coefficient group, the basic medical treatment expense will be adjusted, obtain the target user's
Target medical expense.
Optionally, regulation coefficient in regulation coefficient group is multiplied with basic medical treatment expense respectively, and by the result phase of product
Add, obtains the target medical expense of target user.
It optionally, may include the type of disease in basic medical treatment expense, then the tune that can be mapped according to different disease types
Integral coefficient is adjusted basic medical treatment expense, obtains target medical expense.The mapping relations of disease type and regulation coefficient can
It is stored in advance by medicare system.
204, it according to the mapping relations between preset medical expense and physiological age, determines and the target payment for medical care
With the real physiological age of the corresponding target user.
Optionally, a kind of method at the real physiological age of possible determining target user may include step B1-B2, specifically
It is as follows:
B1, the medical insurance data according to the region where the target user, region where determining the target user
Expense-age curve；
Wherein it is determined that target user location can be extracted first when expense-age curve of region where target user
The medical expense of the people at each age in domain, then the average value of the medical expense of the people at each age is sought, by using average
It is worth method corresponding with the age, expense-age curve of region where drawing target user.
Optionally, model can also be determined using expense-age to determine that expense-age of target user place region is bent
Line, expense-age determines to be obtained after model learns sample data using machine learning, wherein machine learning model is
Supervised learning model, supervised learning model for example can be weight model etc. in artificial neural network method, health risk mould
A kind of method for building up of type are as follows: sample is subjected to feature extraction first, feature set is obtained, feature set is then inputted into training pattern
In, training pattern is learnt according to the algorithm in training pattern, the algorithm for example can be gradient descent method, Newton's algorithm,
Conjugate gradient algorithms etc., finally obtaining expense-age determines model, in this approach, by the study to a large amount of sample, finally
Obtaining expense-age determines model.By machine learning model, a large amount of sample is learnt, it can accurately really
Determining expense-age determines model, to improve the accuracy in expense-age curve acquisition.Wherein, sample be expense with
The real data at age.
B2, in the expense-age curve, determine the age corresponding with the target medical expense, will be described
Real physiological age of the age corresponding with the target medical expense as the target user.
Optionally, real physiological age corresponding with target medical expense, real physiological are searched in expense-age curve
Age can be understood as the new user due to environment or pervious case, and the year relevant to medical-risk actually shown
Age.For example, the actual age of new user is 30 years old, since its physical condition is poor, target medical expense is 3000 yuan/year,
But the medical expense of normal 30 years old people is 500 yuan/year, while the age of the corresponding normal people of 3000 yuan/year is 37
Year, then the real physiological age of the new user is 37 years old.
Optionally, target medical expense may include multiple sub-goal medical expenses, the alternatively possible user that sets the goal really
The method at real physiological age may include step C1-C2, it is specific as follows:
C1, according to the mapping relations between preset medical expense and physiological age, determine and the multiple sub-goal
Each sub-goal medical expense is corresponding in medical expense refers to physiological age；
Wherein, sub-goal medical expense can be formed according to the expense in target medical expense and be divided, and expense composition can
Think the corresponding consumption cost etc. of hospitalization cost, drug categories.Corresponding with hospitalization cost by hospitalization cost determination
, can be according in hospitalization cost when with reference to physiological age, the expense of expense forms to determine, expense, which forms, includes, length of stay,
Hospitalization cost, nursing expense when being hospitalized, the expense of medical apparatus used when being hospitalized, when being hospitalized due to the people of all ages and classes,
Its number of days being hospitalized, in hospital when nursing expense, expense of medical apparatus for using etc. can have differences when being hospitalized, then can unite
Above-mentioned difference is counted, so that it is determined that each sub-goal medical expense is corresponding out refers to physiological age.Corresponding by consumption cost
Drug type when determining with reference to physiological age, since the drug that the people of different age group uses can have differences, then can be used logical
The method of excessive data statistics obtains the age of the people using certain drug, then can be drug class according to sub-goal medical expense
Not corresponding consumption cost determines corresponding reference physiological age.
C2, the real physiological age of the target user is obtained by following formula:
Wherein, aiPhysiological age, k are referred to for sub-goal medical expense is correspondingjFor with aiCorresponding preset weights, i, j
For positive integer, h is the real physiological age of target user.Above-mentioned formula is that each sub-goal medical expense is corresponding with reference to life
The age is managed multiplied by weight corresponding with the sub-goal medical expense, product addition is then obtained into the reference physiology of target user
Age.Wherein, preset weights kjThere can be system to be set, can also be set by system manager, may be used also certainly
To there is other setting means, herein without limitation.
205, according to the actual age and the real physiological age, the target risk etc. of the target user is determined
Grade.
Optionally, a kind of method of the target risk grade of possible determining target user includes step D1-D2, specifically such as
Under:
D1, according to the actual age and the real physiological age, target is calculated and divides age death rate；
Wherein, it a point age death rate calculation formula can be used obtains target and divide age death rate.When actual age and really
When physiological age is identical, then divide age death rate using the corresponding death rate of actual age as target.
D2, according to the mapping relations between preset point of age death rate and risk class, determine and the target point
The target risk grade of the corresponding target user of age death rate.
Optionally, presetting the mapping relations divided between age death rate and risk class can be deposited in advance by medicare system
Storage, risk class may include the first risk class, the second risk class, third risk class and the 4th risk class, first to
The relative risk of 4th risk class successively increases, the relative risk highest of the 4th risk class.
Optionally, the method for the target risk grade of the alternatively possible user that sets the goal really are as follows: by the actual age
It is input in preset risk class confirmation model with the real physiological age, obtains the target risk etc. of the target user
Grade.Wherein, the mode of establishing of preset risk class confirmation model can refer to expense-age and determine that model is established.
In a possible mode, the data processing method based on medical insurance data may also include step E1-E3, specifically such as
Under:
E1, formula is sought by preset relative risk, seeks corresponding first relative risk of the actual age, and seek
Real physiological age corresponding second relative risk；
Optionally, relative risk algorithm for example can be by the pre-stored some relative risk algorithms of system, for example, unit
The percentage of the number Zhan of occurrence risk total number in time, unit time for example can be 1 year, first quarter etc., and wind occurs
Danger can be understood as that Claims Resolution event etc. occurs.
E2, using first relative risk and second relative risk, pass through preset risk score formula and obtain institute
State target user's risk score value；
Wherein, risk score formula is preset are as follows:
Wherein, wherein h is target user's risk score value, and p1 is the first relative risk, and p2 is the second relative risk；
If E3, according to target user's risk score value of the target risk grade and the target user, institute is determined
It states target user and meets requirement of insuring, then send a notification message to the target user.
Optionally, meet requirement of insuring it is to be understood that target risk grade is lower than preset risk class and target is used
When family risk score value is lower than default score value, that is, determine that target user meets requirement of insuring.Wherein, preset risk class and
Default score value can have default, can also be set by user according to according to different geographical, not limited specifically herein
It is fixed.
Optionally, send a notification message to target user can be for by disappearing to the electronic device of target user transmission notice
Breath, notification message may include that target user meets requirement etc. of insuring.
Referring to Fig. 3, Fig. 3 provides the stream of another data processing method based on medical insurance data for the embodiment of the present application
Journey schematic diagram.As shown in figure 3, data processing method includes step 301-306, it is specific as follows:
301, the user data that target user sends is received, and extracts the medical insurance number of the region where the target user
According to, wherein the user data includes at least one data type, and the data type includes the practical year of the target user
Age；
302, the basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user
With；
303, regulation coefficient group is determined according at least one described data type；
304, using the regulation coefficient group, the basic medical treatment expense will be adjusted, the target user is obtained
Target medical expense；
305, it according to the mapping relations between preset medical expense and physiological age, determines and the target payment for medical care
With the real physiological age of the corresponding target user；
306, according to the actual age and the real physiological age, the target risk etc. of the target user is determined
Grade.
In this example, regulation coefficient group is determined according to the data type of user data, and according to regulation coefficient group to base
Plinth medical expense is adjusted to obtain target medical expense, determines adjustment by the data type in the user data of target user
Coefficient sets can be adjusted basic medical treatment expense according to the actual conditions of user, so that target medical expense is obtained, it can
It is promoted to a certain extent and obtains the accuracy of target medical expense, and then can also promoted to a certain extent and obtain target user
Target risk grade accuracy.
Referring to Fig. 4, Fig. 4 provides the stream of another data processing method based on medical insurance data for the embodiment of the present application
Journey schematic diagram.As shown in figure 4, data processing method includes step 401-406, it is specific as follows:
401, the user data that target user sends is received, and extracts the medical insurance number of the region where the target user
According to, wherein the user data includes the actual age of the target user；
402, the basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user
With；
403, according to the user data and the basic medical treatment expense, the target payment for medical care of the target user is calculated
With；
404, according to the medical insurance data of the region where the target user, region where determining the target user
Expense-age curve；
405, in the expense-age curve, the age corresponding with the target medical expense is determined, it will be described
Real physiological age of the age corresponding with the target medical expense as the target user；
406, according to the actual age and the real physiological age, the target risk etc. of the target user is determined
Grade.
In this example, expense-age curve is determined by the medical insurance data of region where target user, and according to taking
The real physiological age of target user is obtained with-age curve, expense-age curve was able to reflect out between expense and age
Change curve so as to more accurately predict the expense when non-integer age, and then can promote acquisition to a certain extent
The accuracy at real physiological age, to can also promote the accurate of the target risk grade for obtaining target user to a certain extent
Property.
Referring to Fig. 5, Fig. 5 provides the stream of another data processing method based on medical insurance data for the embodiment of the present application
Journey schematic diagram.As shown in figure 5, data processing method includes step 501-506, it is specific as follows:
501, the user data that target user sends is received, and extracts the medical insurance number of the region where the target user
According to, wherein the user data includes the actual age of the target user；
502, the basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user
With；
503, according to the user data and the basic medical treatment expense, the target payment for medical care of the target user is calculated
With；
504, it according to the mapping relations between preset medical expense and physiological age, determines and the target payment for medical care
With the real physiological age of the corresponding target user；
505, according to the actual age and the real physiological age, target is calculated and divides age death rate；
506, it according to the mapping relations between preset point of age death rate and risk class, determines and the target point
The target risk grade of the corresponding target user of age death rate.
In this example, the target risk grade of target user is determined by dividing age death rate, due to dividing age death
Rate can accurately reflect the probability of the occurrence risk of target user, so as to promote acquisition target to a certain extent
Accuracy when risk class.
Referring to Fig. 6, Fig. 6 provides the stream of another data processing method based on medical insurance data for the embodiment of the present application
Journey schematic diagram.As shown in fig. 6, data processing method includes step 601-606, it is specific as follows:
601, the user data that target user sends is received, and extracts the medical insurance number of the region where the target user
According to, wherein the user data includes the actual age of the target user；
602, the basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user
With；
603, according to the user data and the basic medical treatment expense, the target payment for medical care of the target user is calculated
With；
604, it according to the mapping relations between preset medical expense and physiological age, determines and the target payment for medical care
With the real physiological age of the corresponding target user；
605, according to the actual age and the real physiological age, the target risk etc. of the target user is determined
Grade；
606, formula is sought by preset relative risk, seeks corresponding first relative risk of the actual age, Yi Jiqiu
Take the real physiological age corresponding second relative risk；
607, using first relative risk and second relative risk, institute is obtained by preset risk score formula
State target user's risk score value；
If 608, determining institute according to target user's risk score value of the target risk grade and the target user
It states target user and meets requirement of insuring, then send a notification message to the target user.
In this example, in the target risk grade of determining target user and then secondary by seeking target user's reality
Age and be really physiological age relative risk, obtain target user's risk score value, then by target user's risk score value and
Target risk grade differentiates whether target user meets requirement of insuring, satisfaction insure require when, sent to target user logical
Know message, it, can be by introducing risk score value with this, and wanted in conjunction with risk class to differentiate whether target user meets to insure
It asks, can be promoted to a certain extent and determine whether target user meets the accuracy insured when requiring.
It is consistent with above-described embodiment, referring to Fig. 7, Fig. 7 is that a kind of structure of terminal provided by the embodiments of the present application is shown
It is intended to, as shown, including processor, input equipment, output equipment and memory, the processor, input equipment, output are set
Standby and memory is connected with each other, wherein for the memory for storing computer program, the computer program includes that program refers to
It enables, the processor is configured for calling described program instruction, and above procedure includes the instruction for executing following steps；
The user data that target user sends is received, and extracts the medical insurance data of the region where the target user,
Wherein, the user data includes the actual age of the target user；
The basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user；
According to the user data and the basic medical treatment expense, the target medical expense of the target user is calculated；
According to the mapping relations between preset medical expense and physiological age, determine and the target medical expense phase
The real physiological age of the corresponding target user；
According to the actual age and the real physiological age, the target risk grade of the target user is determined.
In this example, the region where the user data that target user sends, and the extraction target user is received
Medical insurance data, wherein the user data includes the actual age of the target user, according to region where the target user
Medical insurance data determine the basic medical treatment expense of the target user, taken according to the user data and the basic medical treatment
With, calculate the target medical expense of the target user, according between preset medical expense and physiological age mapping close
System, determines the real physiological age of the target user corresponding with the target medical expense, according to the practical year
Age and the real physiological age, determine the target risk grade of the target user, it therefore, can be according to the mesh received
Mark the user data that user sends, the real physiological year for the target user that the medical insurance data of region in conjunction with where user are determined
Age finally obtains the risk class of user according to the real physiological age of user and actual age, leads to relative in existing scheme
Clinical experience is crossed to obtain the risk class of user, the accuracy and intelligence of risk class acquisition can be promoted to a certain extent
Property.
It is above-mentioned that mainly the scheme of the embodiment of the present application is described from the angle of method side implementation procedure.It is understood that
, in order to realize the above functions, it comprises execute the corresponding hardware configuration of each function and/or software module for terminal.This
Field technical staff should be readily appreciated that, in conjunction with each exemplary unit and algorithm of embodiment description presented herein
Step, the application can be realized with the combining form of hardware or hardware and computer software.Some function actually with hardware also
It is the mode of computer software driving hardware to execute, the specific application and design constraint depending on technical solution.Profession
Technical staff can specifically realize described function to each using distinct methods, but this realization should not be recognized
For beyond scope of the present application.
The embodiment of the present application can carry out the division of functional unit according to above method example to terminal, for example, can be right
The each functional unit of each function division is answered, two or more functions can also be integrated in a processing unit.
Above-mentioned integrated unit both can take the form of hardware realization, can also realize in the form of software functional units.It needs
Illustrate, is schematical, only a kind of logical function partition to the division of unit in the embodiment of the present application, it is practical to realize
When there may be another division manner.
Consistent with the above, referring to Fig. 8, Fig. 8 provides a kind of data based on medical insurance data for the embodiment of the present application
The structural schematic diagram of processing unit, described device include receiving unit 801, the first determination unit 802, computing unit 803, second
Determination unit 804 and third determination unit 805, wherein
The receiving unit 801, for receiving the user data of target user's transmission, and the extraction target user institute
Region medical insurance data, wherein the user data includes the actual age of the target user；
First determination unit 802, it is described for being determined according to the medical insurance data of region where the target user
The basic medical treatment expense of target user；
The computing unit 803, for calculating the target according to the user data and the basic medical treatment expense
The target medical expense of user；
Second determination unit 804, for according to the mapping relations between preset medical expense and physiological age, really
Make the real physiological age of the target user corresponding with the target medical expense；
The third determination unit 805, it is described for determining according to the actual age and the real physiological age
The target risk grade of target user.
As can be seen that receiving the user data that target user sends in this example, and extract the target user place
Region medical insurance data, wherein the user data includes the actual age of the target user, according to the target user
The medical insurance data of place region determine the basic medical treatment expense of the target user, according to the user data and the basis
Medical expense calculates the target medical expense of the target user, according between preset medical expense and physiological age
Mapping relations determine the real physiological age of the target user corresponding with the target medical expense, according to described
Actual age and the real physiological age, determine the target risk grade of the target user, it therefore, can be according to reception
The user data that the target user arrived sends, the target user's that the medical insurance data of region in conjunction with where user are determined is true
Physiological age finally obtains the risk class of user according to the real physiological age of user and actual age, relative to existing side
The risk class of user is obtained in case by clinical experience, can be promoted to a certain extent risk class acquisition accuracy with
And intelligence.
Optionally, the user data includes at least one data type, described according to the user data and described
Basic medical treatment expense calculates the target medical expense aspect of the target user, and the computing unit 803 is specifically used for:
Regulation coefficient group is determined according at least one described data type；
Using the regulation coefficient group, the basic medical treatment expense will be adjusted, the mesh of the target user is obtained
Mark medical expense.
Optionally, in the mapping relations according between preset medical expense and physiological age, determine with it is described
In terms of the real physiological age of the corresponding target user of target medical expense, second determination unit 804 is specifically used
In:
The medical insurance data of region where the target user, the expense of region where determining the target user
With-age curve；
In the expense-age curve, the age corresponding with the target medical expense is determined, it will described and institute
State real physiological age of the target medical expense corresponding age as the target user.
Optionally, the target medical expense includes multiple sub-goal medical expenses, described according to preset payment for medical care
With the mapping relations between physiological age, determine that the target user's corresponding with the target medical expense is true
In terms of physiological age, second determination unit 804 also particularly useful for:
According to the multiple sub-goal medical expense, each sub-goal doctor in the multiple sub-goal medical expense is determined
Treatment expense is corresponding to refer to physiological age；
The real physiological age of the target user is obtained by following formula:
Wherein, aiPhysiological age, k are referred to for sub-goal medical expense is correspondingjFor with aiCorresponding preset weights, i, j
For positive integer, h is the real physiological age of target user.
Optionally, determine the target user's according to the actual age and the real physiological age described
In terms of target risk grade, the third determination unit 805 is specifically used for:
According to the actual age and the real physiological age, target is calculated and divides age death rate；
According to the mapping relations between preset point of age death rate and risk class, determine to divide the age with the target
The target risk grade of the corresponding target user of the death rate.
Optionally, determine the target user's according to the actual age and the real physiological age described
In terms of target risk grade, the third determination unit 805 also particularly useful for:
The actual age and the real physiological age are input in preset risk class confirmation model, institute is obtained
State the target risk grade of target user.
Optionally, the data processing equipment of the medical insurance data is also used to:
Formula is sought by preset relative risk, seeks corresponding first relative risk of the actual age, and seek institute
State real physiological age corresponding second relative risk；
Using first relative risk and second relative risk, the mesh is obtained by preset risk score formula
Mark consumer's risk score value；
If determining the mesh according to target user's risk score value of the target risk grade and the target user
Mark user meets requirement of insuring, then sends a notification message to the target user.
The embodiment of the present application also provides a kind of computer storage medium, wherein computer storage medium storage is for electricity
The computer program of subdata exchange, it is as any in recorded in above method embodiment which execute computer
A kind of some or all of the data processing method based on medical insurance data step.
The embodiment of the present application also provides a kind of computer program product, and the computer program product includes storing calculating
The non-transient computer readable storage medium of machine program, the computer program make computer execute such as above method embodiment
Some or all of any data processing method based on medical insurance data of middle record step.
It should be noted that for the various method embodiments described above, for simple description, therefore, it is stated as a series of
Combination of actions, but those skilled in the art should understand that, the application is not limited by the described action sequence because
According to the application, some steps may be performed in other sequences or simultaneously.Secondly, those skilled in the art should also know
It knows, the embodiments described in the specification are all preferred embodiments, related actions and modules not necessarily the application
It is necessary.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, there is no the portion being described in detail in some embodiment
Point, reference can be made to the related descriptions of other embodiments.
In several embodiments provided herein, it should be understood that disclosed device, it can be by another way
It realizes.For example, the apparatus embodiments described above are merely exemplary, such as the division of the unit, it is only a kind of
Logical function partition, there may be another division manner in actual implementation, such as multiple units or components can combine or can
To be integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Coupling, direct-coupling or communication connection can be through some interfaces, the indirect coupling or communication connection of device or unit,
It can be electrical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, applying for that each functional unit in bright each embodiment can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also be realized in the form of software program module.
If the integrated unit is realized in the form of software program module and sells or use as independent product
When, it can store in a computer-readable access to memory.Based on this understanding, the technical solution of the application substantially or
Person says that all or part of the part that contributes to existing technology or the technical solution can body in the form of software products
Reveal and, which is stored in a memory, including some instructions are used so that a computer equipment
(can be personal computer, server or network equipment etc.) executes all or part of each embodiment the method for the application
Step.And memory above-mentioned includes: USB flash disk, read-only memory (read-only memory, ROM), random access memory
The various media that can store program code such as (random access memory, RAM), mobile hard disk, magnetic or disk.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can store in a computer-readable memory, memory
It may include: flash disk, read-only memory, random access device, disk or CD etc..
The embodiment of the present application is described in detail above, specific case used herein to the principle of the application and
Embodiment is expounded, the description of the example is only used to help understand the method for the present application and its core ideas；
At the same time, for those skilled in the art can in specific embodiments and applications according to the thought of the application
There is change place, in conclusion the contents of this specification should not be construed as limiting the present application.
Claims (10)
1. a kind of data processing method based on medical insurance data, which is characterized in that the described method includes:
The user data that target user sends is received, and extracts the medical insurance data of the region where the target user, wherein
The user data includes the actual age of the target user；
The basic medical treatment expense of the target user is determined according to the medical insurance data of region where the target user；
According to the user data and the basic medical treatment expense, the target medical expense of the target user is calculated；
According to the mapping relations between preset medical expense and physiological age, determine corresponding with the target medical expense
The target user the real physiological age；
According to the actual age and the real physiological age, the target risk grade of the target user is determined.
2. the method according to claim 1, wherein the user data includes at least one data type, institute
State the target medical expense that the target user is calculated according to the user data and the basic medical treatment expense, comprising:
Regulation coefficient group is determined according at least one described data type；
Using the regulation coefficient group, the basic medical treatment expense will be adjusted, obtain the target doctor of the target user
Treatment expense.
3. according to the method described in claim 2, it is characterized in that, described according between preset medical expense and physiological age
Mapping relations, determine the real physiological age of the target user corresponding with the target medical expense, comprising:
The medical insurance data of region where the target user, expense-year of region where determining the target user
Age curve；
In the expense-age curve, the age corresponding with the target medical expense is determined, it will the described and mesh
Mark real physiological age of the medical expense corresponding age as the target user.
4. method according to claim 1 or 2, which is characterized in that the target medical expense includes multiple sub-goal doctors
Treatment expense, the mapping relations according between preset medical expense and physiological age are determined and the target payment for medical care
With the real physiological age of the corresponding target user, comprising:
According to the mapping relations between preset medical expense and physiological age, determine and the multiple sub-goal medical expense
In each sub-goal medical expense it is corresponding refer to physiological age；
The real physiological age of the target user is obtained by following formula:
Wherein, aiPhysiological age, k are referred to for sub-goal medical expense is correspondingjFor with aiCorresponding preset weights, i, j are positive
Integer, h are the real physiological age of target user.
5. method according to any one of claims 1 to 3, which is characterized in that described according to the actual age and described
The real physiological age determines the target risk grade of the target user, comprising:
According to the actual age and the real physiological age, target is calculated and divides age death rate；
According to the mapping relations between preset point of age death rate and risk class, determine to divide age death with the target
The target risk grade of the corresponding target user of rate.
6. method according to any one of claims 1 to 3, which is characterized in that described according to the actual age and described
The real physiological age determines the target risk grade of the target user, comprising:
The actual age and the real physiological age are input in preset risk class confirmation model, the mesh is obtained
Mark the target risk grade of user.
7. the method according to claim 1, wherein the method also includes:
Formula is sought by preset relative risk, seeks corresponding first relative risk of the actual age, and is sought described true
Corresponding second relative risk of real physiological age；
Using first relative risk and second relative risk, the target is obtained by preset risk score formula and is used
Family risk score value；
If determining that the target is used according to target user's risk score value of the target risk grade and the target user
Family meets requirement of insuring, then sends a notification message to the target user.
8. a kind of data processing equipment based on medical insurance data, which is characterized in that described device includes:
Receiving unit for receiving the user data of target user's transmission, and extracts region where the target user
Medical insurance data, wherein the user data includes the actual age of the target user；
First determination unit, for determining the base of the target user according to the medical insurance data of region where the target user
Plinth medical expense；
Computing unit, for calculating the target of the target user according to the user data and the basic medical treatment expense
Medical expense；
Second determination unit, for according to the mapping relations between preset medical expense and physiological age, determine with it is described
The real physiological age of the corresponding target user of target medical expense；
Third determination unit, for determining the target user's according to the actual age and the real physiological age
Target risk grade.
9. a kind of terminal, which is characterized in that the processor, defeated including processor, input equipment, output equipment and memory
Enter equipment, output equipment and memory to be connected with each other, wherein the memory is for storing computer program, the computer
Program includes program instruction, and the processor is configured for calling described program instruction, is executed such as any one of claim 1-7
The method.
10. a kind of computer readable storage medium, which is characterized in that the computer storage medium is stored with computer program,
The computer program includes program instruction, and described program instruction makes the processor execute such as right when being executed by a processor
It is required that the described in any item methods of 1-7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811250289.7A CN109544357A (en) | 2018-10-25 | 2018-10-25 | Data processing method and device based on medical insurance data |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811250289.7A CN109544357A (en) | 2018-10-25 | 2018-10-25 | Data processing method and device based on medical insurance data |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109325869A (en) * | 2018-09-10 | 2019-02-12 | 平安科技（深圳）有限公司 | User's insurance risk appraisal procedure, device, computer equipment and storage medium |
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2018
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109325869A (en) * | 2018-09-10 | 2019-02-12 | 平安科技（深圳）有限公司 | User's insurance risk appraisal procedure, device, computer equipment and storage medium |
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