CN109785965A - A kind of health evaluating method, health evaluating device and computer readable storage medium - Google Patents
A kind of health evaluating method, health evaluating device and computer readable storage medium Download PDFInfo
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Abstract
This application discloses a kind of health evaluating method, health evaluating device and computer readable storage mediums, are applied to prediction valuation field, and wherein method includes: to be directed to target disease, obtain target disease incidence table and the practical age of onset of target user；According to the expection age of onset of health evaluating method target disease incidence table projected health appraisal procedure target user；In the case where the practical age of onset of health evaluating method age of onset expected less than health evaluating method, adjustment health evaluating method target disease incidence table each age corresponding disease incident, so that expected age of onset is consistent with practical age of onset；The health point of health evaluating method target user is assessed according to the degree of adjustment.The application obtains the health point of target user by comparing the practical age of onset and expected age of onset of target user, to can reflect the quality of the health status of target user according to the size of health point.
Description
Technical field
This application involves risk assessment technology field more particularly to a kind of health evaluating methods, health evaluating device and meter
Calculation machine readable storage medium storing program for executing.
Background technique
The progress of medical technology is cured many diseases, but still having many chronic diseases is to be difficult to be cured
, and its incubation period be also it is very long, for the crowd of different constitutions, disease time by heredity and living habit
The influence of equal many factors, then specific disease time is not fixed, even if current body does not have disease that can not represent body
Body is healthy.
Then for the true physical condition of user is measured, can now be carried out at present by the physical function to user
Detection, to score the physical function of the various aspects of user, finally integrates all scores to obtain comprehensive score, so
User is assessed using the height of the comprehensive score afterwards certain specified disease will occur future or causes extremely because of certain specified disease
A possibility that dying, but also user can have an awareness and understanding substantially to own health by comprehensive score.
But the method that the physical condition of user is directly measured by the physical function to user is still less quasi-
Really, because unhealthful factor is too many, only assess the physical function of user that can not accurately to describe user true
Real physical condition then also lacks a kind of efficient and accurate health evaluating method.
Summary of the invention
The embodiment of the present application provides a kind of health evaluating method, can by by the physical condition of user with it is general same
Age, people compared, and efficiently and accurately assess to the health status of user.
In a first aspect, the embodiment of the present application provides a kind of health evaluating method, this method comprises:
It is directed to target disease, obtains target disease incidence table and the practical age of onset of target user, the mesh
Mark disease incident table describes corresponding disease incident of each age, and the practical age of onset is target use
It is actually in danger the age with the target disease at family；
According to the expection age of onset of the estimated target user of the target disease incidence table, the expected morbidity year
Age is that the target user of prediction may be in danger the age with the expection of the target disease；
In the case where the practical age of onset is less than the expected age of onset, the target disease incidence is adjusted
Table each age corresponding disease incident, until according to the estimated obtained expection of the target disease incidence table
Age of onset is consistent with the practical age of onset；
The health point of the target user is assessed according to the degree of adjustment.
With reference to first aspect, described according to the target disease incidence in the first implementation of first aspect
The expection age of onset of the estimated target user of table, comprising:
Target disease cumulative incidence table is calculated according to the target disease incidence meter, the target disease is accumulative to be occurred
Rate table has recorded corresponding accumulative disease incident of each age；
The accumulative disease incident is greater than or equal to the minimal ages of preset threshold as the expected age of onset.
With reference to first aspect, in second of implementation of first aspect, the adjustment target disease incidence
Table each age corresponding disease incident, comprising:
Age each in the target disease incidence table corresponding disease incident is amplified into identical adjustment ratio respectively
Example.
With reference to first aspect, in the third implementation of first aspect, it is described according to the degree of adjustment to assess
State the health point of target user, comprising:
The health point of the target user is assessed according to the adjustment ratio, the health point is with the adjustment ratio at just
Than.
With reference to first aspect, described to be assessed according to the adjustment ratio in the 4th kind of implementation of first aspect
The health of the target user point, comprising:
It calculates y=[x-1] × 100, to obtain the health point, the y is the health point, and the x is the adjustment
Ratio.
With reference to first aspect, in the 5th kind of implementation of first aspect, the acquisition target disease incidence table, packet
It includes；
Obtain the attribute of the target user；
Corresponding target disease incidence table is obtained according to the attribute of the target user.
With reference to first aspect to the 5th kind of implementation of first aspect, in the 6th kind of implementation of first aspect,
The target disease incidence table is the age of each user's illness in the medical big data for count medical insurance field, and obtains
Corresponding disease probability of happening of each age set.
Second aspect, the embodiment of the present application provide a kind of health evaluating device, which includes for holding
The unit of the health evaluating method of the above-mentioned first aspect of row, the health evaluating device include:
Acquiring unit obtains target disease incidence table and the practical hair of target user for being directed to target disease
Sick age, the target disease incidence table describe corresponding disease incident of each age, the practical morbidity year
Age is the target user being actually in danger the age with the target disease；
Predicting unit, for expecting the expection age of onset of the target user according to the target disease incidence table,
The expected age of onset is that the target user of prediction may be in danger the age with the expection of the target disease；
Adjustment unit is used in the case where the practical age of onset is less than the expected age of onset, described in adjustment
Target disease incidence table each age corresponding disease incident, until estimated according to the target disease incidence table
The obtained expected age of onset is consistent with the practical age of onset；
Assessment unit, for assessing the health point of the target user according to the degree of adjustment.
In conjunction with second aspect, in the first implementation of second aspect, the predicting unit is specifically used for:
Target disease cumulative incidence table is calculated according to the target disease incidence meter, the target disease is accumulative to be occurred
Rate table has recorded corresponding accumulative disease incident of each age；
The accumulative disease incident is greater than or equal to the minimal ages of preset threshold as the expected age of onset.
In conjunction with second aspect, in second of implementation of second aspect, the adjustment unit, being specifically used for will be described
Each age, corresponding disease incident amplified identical adjustment ratio respectively in target disease incidence table.
In conjunction with second aspect, in the third implementation of second aspect, the assessment unit is specifically used for according to institute
The health point that adjustment ratio assesses the target user is stated, the health point is directly proportional to the adjustment ratio.
In conjunction with second aspect, in the 4th kind of implementation of second aspect, the assessment unit is specifically used for:
It calculates y=[x-1] × 100, to obtain the health point, the y is the health point, and the x is the adjustment
Ratio.
In conjunction with second aspect, in the 5th kind of implementation of second aspect, the acquiring unit is specifically used for:
Obtain the attribute of the target user；
Corresponding target disease incidence table is obtained according to the attribute of the target user.
In conjunction with the 5th kind of implementation of second aspect to second aspect, in the 6th kind of implementation of second aspect,
The target disease incidence table is the age of each user's illness in the medical big data for count medical insurance field, and obtains
Corresponding disease probability of happening of each age set.
The third aspect, the embodiment of the present application provides another health evaluating device, including processor and memory, described
Processor and memory are connected with each other, wherein the memory supports health evaluating device to execute above-mentioned health and comment for storing
Estimate the computer program of method, the computer program includes program instruction, and the processor is configured for calling the journey
Sequence instruction, to execute above-mentioned first aspect to first aspect any one implementation health evaluating method.
Fourth aspect, the embodiment of the present application provide a kind of computer readable storage medium, the computer storage medium
It is stored with computer program, the computer program includes program instruction, and described program instruction is when being executed by processor, to hold
The health evaluating method of any one implementation of the above-mentioned first aspect of row to first aspect.
The application first obtains the practical age of onset and target disease incidence table of target user, then according to target disease
Incidence table predicts the expection age of onset of target user, if the practical age of onset of target user is less than expected morbidity year
Age then illustrates the health status of health status contemporary not as good as of user, then passes through adjustment target disease incidence table
So that the expection age of onset of the target user reevaluated according to target disease incidence table adjusted and target are used
The practical age of onset at family is consistent, then can assess target according to the above-mentioned adjustment degree to target disease incidence table
The health of user point, to reflect the health status quality of target user by the size of health point.Then the application is with one
As contemporary health status on the basis of, the quality of the physical condition of Lai Hengliang user, relative to directly passing through assessment user
Physical function comes for the method for the physical condition of isolated assessment user, and the application is since to body, whether health is set
Assessment benchmark, therefore can more efficient and accurate evaluation user health status
Detailed description of the invention
Technical solution in ord to more clearly illustrate embodiments of the present application, below will be to needed in embodiment description
Attached drawing is briefly described.
Fig. 1 is a kind of schematic flow diagram of health evaluating method provided by the embodiments of the present application；
Fig. 2 is a kind of schematic flow diagram of health evaluating method provided by the embodiments of the present application；
Fig. 3 is a kind of example schematic of target disease incidence table provided by the embodiments of the present application；
Fig. 4 is a kind of example schematic of target disease cumulative incidence table provided by the embodiments of the present application；
Fig. 5 is a kind of schematic block diagram of health evaluating device provided by the embodiments of the present application；
Fig. 6 is a kind of structural diagram of health evaluating device provided by the embodiments 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 should be appreciated that ought use in this specification and in the appended claims, term " includes " and "comprising" instruction
Described feature, entirety, step, operation, the presence of element and/or component, but one or more of the other feature, whole is not precluded
Body, step, operation, the presence or addition of element, component and/or its set.
It is also understood that mesh of the term used in this present specification merely for the sake of description specific embodiment
And be not intended to limit the application.As present specification and it is used in the attached claims, unless on
Other situations are hereafter clearly indicated, otherwise " one " of singular, "one" and "the" are intended to include plural form.
It will be further appreciated that the term "and/or" used in present specification and the appended claims is
Refer to any combination and all possible combinations of one or more of associated item listed, and including these combinations.
As used in this specification and in the appended claims, term " if " can be according to context quilt
Be construed to " when ... " or " once " or " in response to determination " or " in response to detecting ".Similarly, phrase " if it is determined that " or
" if detecting [described condition or event] " can be interpreted to mean according to context " once it is determined that " or " in response to true
It is fixed " or " once detecting [described condition or event] " or " in response to detecting [described condition or event] ".
Terminal device described in the embodiment of the present application includes but is not limited to the equipment with communication function, smart phone, puts down
Plate computer, laptop, desktop computer, portable digital player, Intelligent bracelet and smartwatch etc..Work as terminal device
When health evaluating device into block chain sends data, record simultaneously the characteristic of data according to preset format
Transmission, wherein the characteristic of data includes time, place, type etc..
The application is mainly used in health evaluating device, which can be traditional health assessment device, clothes
Business device, large memory system, desktop computer, laptop, tablet computer, palm PC, smart phone, portable digital are broadcast
Device, smartwatch and Intelligent bracelet etc. are put, the application is without limitation.When health evaluating device is sent to other equipment
When data, the characteristic of data is recorded and transmitted according to preset format, wherein when the characteristic of data includes
Between, place, type etc..Wherein, above-mentioned other equipment include server, large memory system, desktop computer, laptop,
Tablet computer, palm PC, smart phone, portable digital player, smartwatch and Intelligent bracelet etc., the application couple
This is with no restrictions.
It is that the embodiment of the present application provides a kind of schematic flow diagram of health evaluating method referring to Fig. 1, it is healthy as shown in Figure 1
Appraisal procedure can include:
101: being directed to target disease, obtain target disease incidence table and the practical age of onset of target user.
In the embodiment of the present application, the age that acquisition target user suffers from target disease is used as practical age of onset, and obtains
Target disease incidence table is taken, which describes general user and suffer from the target disease at each age
Probability then describes corresponding disease incident of each age in target disease incidence table.
It should be noted that above-mentioned target user suffers from the disease time of the target disease user in medical insurance field
Be in danger record, contains the time of policy purchase of user being in danger in record, age at issue, is in danger time and the age of being in danger etc., then
It can that is to say that above-mentioned target is used according to being actually in danger the age with target disease recorded to determine user of being in danger of user
The practical age of onset at family.
Further, before obtaining target disease, before the acquisition target disease incidence table, it is big first to obtain medical treatment
Data are to establish above-mentioned target disease incidence table.Specifically, obtaining medical big data, medical big data includes at least one use
The medical data at family；The corresponding disease probability of happening of each age in medical big data is counted, to establish above-mentioned target disease
Sick incidence table.
In the embodiment of the present application, medical big data is first obtained, then counts in the medical treatment big data all users each
Sick ratio of a age, using corresponding number ratio of each age as the age corresponding disease incident.Wherein,
The medical data of multiple users is described in medical big data, especially each user suffers from the age of target disease.
For example, as shown in Figure 3, it is assumed that the medical data of 1000000 users is contained in above-mentioned medical treatment big data,
Through counting, the number for suffering from target disease in all users at 30 years old has 949 people, and the ratio for accounting for total number of persons is 0.000949, institute
There is the number for suffering from target disease at 31 years old in user to have 1009, the ratio for accounting for total number of persons is useful for 0.001078.......
The number for suffering from target disease at 44 years old in family has 4070, and the ratio for accounting for total number of persons is 0.004070.Thus according to above-mentioned each
Age corresponding number accounting distinguishes above-mentioned each age to establish target disease incidence table as shown in Figure 3
Corresponding number accounting is as corresponding disease incident of each age.
Optionally, each user in above-mentioned medical big data corresponds to one or more attribute, then above-mentioned according to doctor
It treats the user that big data is established target disease incidence table and be can be for different attribute and establishes different target disease incidences
Table.
In the application implementation, above-mentioned medical treatment big data includes the sick time of user and the attribute of user, the attribute
Including gender, area, occupation and/or interest etc., it is above-mentioned establish target disease incidence table when, can will the big number of medical treatment
User in is divided into different classes according to one or multiple attributes, then different according to being established by inhomogeneous user
Target disease incidence table.
For example, if including sick time, gender and the area of user in above-mentioned medical treatment big data, by above-mentioned medical treatment
The user for including in big data classifies according to its gender and regional two dimensions, such as gender includes male and female, area
It is divided into Beijing and Shanghai, then the user in above-mentioned medical big data is divided into four classes, the i.e. female user of Beijing area,
The male user of Beijing area, the female user of District of Shanghai and the male user of District of Shanghai are then directed to above-mentioned four respectively
Class user establishes a target disease incidence table, such as counts in the lady's family of above-mentioned Beijing area and suffer from target at each age
The ratio of the total number of persons of the female user of the number Zhan of disease total Beijing area, to obtain for for women of Beijing area
The target disease incidence table at family.
Further, before obtaining above-mentioned target disease incidence table, the attribute of target user is first obtained, is then obtained
The corresponding target disease incidence table of the attribute of target user, the different user of attribute correspond to different target disease incidences
Table；If target disease incidence table corresponding to the attribute of target user has not been obtained, medical big data is obtained, extracts the doctor
Multiple users identical with target user's attribute in big data are treated, then basis should multiple users identical with target user's attribute
To establish target disease incidence table.
Optionally, above-mentioned medical big data is the data based on medical insurance field, and above-mentioned target disease incidence table is
The age of each user's illness in the medical big data of statistics medical insurance field, and obtained corresponding disease of each age
The set of sick probability of happening.
In the application implementation, above-mentioned medical treatment big data derives from medical insurance data, as based on the doctor of medical insurance field
Treat big data.Specifically, the medical treatment big data derives from the record that is in danger of medical insurance field, wherein be in danger and be recorded as user
After target disease purchase insurance, the record just pursued a claim to insurance company when user suffers from target disease, then
Being in danger the time for user, the i.e. sick time of user can be recorded in this is in danger and records.
102: according to the expection age of onset of the estimated above-mentioned target user of above-mentioned target disease incidence table.
In the embodiment of the present application, it can determine that the disease of the target disease is high-incidence according to above-mentioned target disease incidence table
Age, when not knowing about under the health condition of target user, using the disease high incidence age as the expection age of onset of target user,
It is expected that age of onset is that the target user of prediction may suffer from the age of target disease.Wherein, target disease incidence table comes from
The ratio of target disease occurs at each age for the user being in danger in statistics medical field, occurs thus according to target disease
The expection age of onset that rate table determines that is to say that the expection of target user is in danger the age.
Specifically, the above-mentioned expection age of onset according to target disease incidence table scheduled target user, refers to first root
Target disease cumulative incidence table is calculated according to target disease incidence meter, target disease cumulative incidence table has recorded each age
Corresponding accumulative disease incident；Then using accumulative disease incident be greater than or equal to preset threshold minimal ages as
Above-mentioned expected age of onset.
For example, the accumulative generation of target disease as shown in Figure 4 is obtained by target disease incidence table as shown in Figure 3
Rate table, i.e. each age corresponding accumulative disease incident in calculating target disease incidence table, 30 years old corresponding accumulative
Disease incident is 30 years old corresponding disease incident, i.e. target user's probability that target disease was suffered from 30 years old, 31 years old correspondence
Accumulative disease probability of happening be 30 years old, the sum of 31 years old corresponding disease incident, i.e., target user was at 30 years old to 31 years old
Between to suffer from probability ... 44 years old corresponding accumulative disease incident of target disease be 30 years old, 31 years old ... to 43 years old point
The probability that the sum of not corresponding disease incident, i.e. target user suffer from target disease between 30 years old to 43 years old.It obtains above-mentioned
It after accumulative target disease incidence table, takes in the accumulative target disease incidence table, adds up disease incident and be greater than default threshold
The minimal ages of value are as expected age of onset, it is assumed that preset threshold 0.02, then it can be seen that target disease cumulative incidence
42 years old in table is the minimal ages for adding up disease incident and being more than 0.02, then is used as above-mentioned expected age of onset for 42 years old.
103: in the case where above-mentioned practical age of onset is less than above-mentioned expected age of onset, adjusting above-mentioned target disease hair
Life rate table each age corresponding disease incident, until according to the estimated obtained expected morbidity of target disease incidence table
Age is consistent with practical age of onset.
In the embodiment of the present application, if the practical age of onset of above-mentioned target user is less than above-mentioned expected age of onset,
Illustrate that the physical condition of user is not so good as the physical condition of general user, then adjusts above-mentioned target disease incidence table
In corresponding disease incident of each age, then obtained further according to the target disease incidence table after adjustment new
Target disease cumulative incidence table so that the expection age of onset and target that are obtained according to the new target disease incidence table
The practical age of onset of user is consistent.
Optionally, can to age each in above-mentioned target disease incidence table corresponding disease incident respectively into
The amplification of the non-equal proportion of row, alternatively, age each in target disease incidence table corresponding disease incident is amplified phase respectively
Same adjustment ratio.
In the embodiment of the present application, the corresponding disease of each age in above-mentioned target disease incidence table is occurred
Rate is adjusted, and can carry out the adjustment of non-equal proportion to corresponding target disease incidence table of each age, or wait
The adjustment of ratio.
For example, different ratios is adjusted separately to each age in target disease incidence table as shown in Figure 3,
Such as 101% was adjusted separately to 30 years old, 31 years old, 44 years old 32 years old ... corresponding disease incident, 103%,
106%......120%, or to the unification of each age all adjust identical adjustment ratio, such as 105%.
104: the health point of above-mentioned target user is assessed according to the degree of adjustment.
In the embodiment of the present application, according to the degree of above-mentioned adjustment target disease incidence, to assess above-mentioned target user
Health point.Specifically, just being calculated above-mentioned each if having adjusted separately different ratios to each age during above-mentioned adjustment
The mean value for the ratio that a age adjusts separately, using the mean value as total adjustment ratio, alternatively, if during above-mentioned adjustment, it is right
Each age has adjusted separately identical ratio, then using the identical ratio as adjustment ratio.According to the size of adjustment ratio
The degree that can reflect out above-mentioned adjustment, is then adjusted after ratio, and the strong of target user is assessed according to adjustment ratio
Health point, specifically, the health of target user point is set to 0 point when the ratio of adjustment is less than or equal to 1, when adjustment ratio is greater than 1
When, adjustment ratio is bigger, and health point is bigger.Wherein, health is divided into 0 point of expression health, and health point is bigger to indicate target user's
Physical condition is poorer compared to general contemporary.
It should be noted that being said if the practical age of onset of above-mentioned target user is more than or equal to expected age of onset
The health of bright target user then directly enables the health of target user be divided into 0 point, represents the health of target user,
It is similar with the health status of general contemporary, or it is better than general contemporary.
Further, the above-mentioned health for calculating target user according to above-mentioned adjustment ratio is divided into, and calculating y=[x-1] ×
100, to obtain health point, wherein y is health point, and the x is adjustment ratio.
For example, if above-mentioned adjustment ratio is 105%, the calculation formula of above-mentioned y=[x-1] × 100 is good for
5 points of health point.
In the embodiment of the present application, it has been carried out according to expection age of onset of the target disease incidence table to target user pre-
Survey, then the practical age of onset of the expection age of onset and target user is compared, if practical age of onset greater than etc.
In expected age of onset, then the health of target user is enabled to be divided into 0 point, indicate target user health status and general contemporary one
Sample is better than general contemporary, if practical age of onset is less than expected age of onset, carries out to target disease incidence table
Adjustment, until the expection age of onset estimated according to target disease incidence table is consistent with practical age of onset, further according to
Corresponding disease incident of each age in target disease incidence is adjusted, finally according to the amplitude of adjustment come
Determine the health point of target user, the amplitude of adjustment is bigger, then health point is bigger.As can be seen that the embodiment of the present application is based on mesh
Disease is marked, the health status of target user is compared with general contemporary, then obtains the health point of target user, then
The embodiment of the present application by general contemporary as healthy benchmark, relative to directly according to the health data of target user come to mesh
For the health status of mark user scores, more objective health evaluating more effectively can be carried out to target user.
It referring to fig. 2, is that the embodiment of the present application provides the schematic flow diagram of another health evaluating method, it is strong as shown in Figure 2
Health appraisal procedure can include:
201: obtaining the attribute of target user, and be directed to target disease, obtain the practical age of onset of target user.
In the embodiment of the present application, the age that acquisition target user suffers from target disease is used as practical age of onset, and obtains
Take the attribute of target user, wherein attribute includes gender, area, occupation and/or interest etc..
It should be noted that above-mentioned target user suffers from the disease time of the target disease user in medical insurance field
Be in danger record, contains the time of policy purchase of user being in danger in record, age at issue, is in danger time and the age of being in danger etc., then
It can that is to say that above-mentioned target is used according to being actually in danger the age with target disease recorded to determine user of being in danger of user
The practical age of onset at family.
202: corresponding target disease incidence table is obtained according to the attribute of target user.
In the embodiment of the present application, corresponding target disease incidence table, the target are obtained according to the attribute of target user
Disease incident table describes the probability that general user suffers from the target disease at each age, then in target disease incidence
Corresponding disease incident of each age is described in table.
Further, before obtaining target disease, before the acquisition target disease incidence table, it is big first to obtain medical treatment
Data are to establish above-mentioned target disease incidence table.Specifically, obtaining medical big data, medical big data includes at least one use
The medical data at family, wherein medical data includes illness age and attribute；By the user in medical big data according to above-mentioned attribute
Different user's set are divided into, the corresponding disease probability of happening of each age in each user's set are counted, to be directed to
Different attributes establishes different target disease incidence tables.
In the application implementation, medical big data is first obtained, then will include the user of same alike result in medical big data
It is divided in same user's set, to obtain different user's set for different attributes, then each user is collected
The illness age of user in conjunction counts, to be directed to attribute, obtains corresponding target disease of each age and occurs
Rate table, the attribute include gender, area, occupation and/or interest etc..
For example, if including sick time, gender and the area of user in above-mentioned medical treatment big data, by above-mentioned medical treatment
The user for including in big data classifies according to its gender and regional two dimensions, such as gender includes male and female, area
It is divided into Beijing and Shanghai, then the user in above-mentioned medical big data is divided into four classes, the i.e. female user of Beijing area,
The male user of Beijing area, the female user of District of Shanghai and the male user of District of Shanghai are then directed to above-mentioned four respectively
Class user establishes a target disease incidence table, such as counts in the lady's family of above-mentioned Beijing area and suffer from target at each age
The ratio of the total number of persons of the female user of the number Zhan of disease total Beijing area, to obtain for for women of Beijing area
The target disease incidence table at family.Assuming that obtaining attribute is that women and Pekinese user gather, then gathered according to the user to build
Corresponding target disease incidence table is found, as shown in Figure 3, it is assumed that in above-mentioned medical treatment big data with containing 1000000 Beijing
The medical data of the female user in area, through counting, the number for suffering from target disease in all users at 30 years old has 949 people, and Zhan is total
The ratio of number is 0.000949, and the number that target disease was suffered from 31 years old in all users has 1009, accounts for the ratio of total number of persons
Number to suffer from target disease at 44 years old in all users of 0.001078....... has 4070, and the ratio for accounting for total number of persons is
0.004070.Occur thus according to corresponding number accounting of above-mentioned each age to establish target disease as shown in Figure 3
Rate table, and using corresponding number accounting of above-mentioned each age as corresponding disease incident of each age.
Further, if target disease incidence table corresponding to the attribute of target user has not been obtained, medical treatment is obtained
Big data extracts multiple users identical with target user's attribute in the medical treatment big data, and then basis is somebody's turn to do and target user belongs to
Property identical multiple users establish target disease incidence table.
Optionally, above-mentioned medical big data is the data based on medical insurance field, and above-mentioned target disease incidence table is
The age of each user's illness in the medical big data of statistics medical insurance field, and obtained corresponding disease of each age
The set of sick probability of happening.
In the application implementation, above-mentioned medical treatment big data derives from medical insurance data, as based on the doctor of medical insurance field
Treat big data.Specifically, the medical treatment big data derives from the record that is in danger of medical insurance field, wherein be in danger and be recorded as user
After target disease purchase insurance, the record just pursued a claim to insurance company when user suffers from target disease, then
Being in danger the time for user, the i.e. sick time of user can be recorded in this is in danger and records.
203: according to the expection age of onset of the estimated above-mentioned target user of above-mentioned target disease incidence table.
It should be noted that the user that target disease incidence table has been in danger in statistics medical field is in each year
The ratio of target disease occurs for age, and the expection age of onset determined thus according to target disease incidence table that is to say target user
Expection be in danger the age.
204: in the case where above-mentioned practical age of onset is less than above-mentioned expected age of onset, the target disease being occurred
Each age, corresponding disease incident amplified identical adjustment ratio respectively in rate table, until according to target disease incidence table
It is expected that obtained expection age of onset is consistent with practical age of onset.
In the embodiment of the present application, if the practical age of onset of above-mentioned target user is less than above-mentioned expected age of onset,
Illustrate that the physical condition of user is not so good as the physical condition of general user, then adjusts above-mentioned target disease incidence table
In corresponding disease incident of each age so that corresponding disease incident of each age adjust separately it is identical
Adjustment ratio, new target disease cumulative incidence is then obtained further according to the target disease incidence table after adjustment
Table, so that the practical age of onset one of the expection age of onset and target user obtained according to the new target disease incidence table
It causes.
For example, identical adjustment is adjusted separately to each age in target disease incidence table as shown in Figure 3
Ratio, such as adjusting separately to 30 years old, 31 years old, 44 years old 32 years old ... corresponding disease incident is original 105%.
205: the health point of target user is assessed according to the size of above-mentioned adjustment ratio.
In the embodiment of the present application, according to the degree of above-mentioned adjustment target disease incidence, to assess above-mentioned target user
Health point.Specifically, identical ratio has been adjusted separately to each age during above-mentioned adjustment, then it is this is identical
Ratio is as adjustment ratio.The degree that can reflect out above-mentioned adjustment according to the size of adjustment ratio, is then adjusted ratio
Later, the health point of target user is assessed according to adjustment ratio, specifically, using target when the ratio of adjustment is less than or equal to 1
The health at family point is set to 0 point, and when the ratio of adjustment is greater than 1, adjustment ratio is bigger, and health point is bigger.Wherein, health is divided into 0 point
Indicate health, health point is bigger, and the physical condition for indicating target user is poorer compared to general contemporary.
Further, the above-mentioned health for calculating target user according to above-mentioned adjustment ratio is divided into, and calculating y=[x-1] ×
100, to obtain health point, wherein y is health point, and the x is adjustment ratio.
For example, if above-mentioned adjustment ratio is 105%, the calculation formula of above-mentioned y=[x-1] × 100 is good for
5 points of health point.
For upper application embodiment, more detailed description acquisition target disease occurs the embodiment of the present application
Rate table adjusts target disease incidence table and assesses target user according to the amplitude adjusted to target disease incidence table and is good for
The processes such as health point.Wherein, when obtaining above-mentioned target disease incidence table, before first obtaining target disease incidence table, first
The attribute for obtaining target user, then obtains corresponding target disease incidence table according to the attribute of user, when not obtaining
Corresponding to attribute to target user when target disease incidence table, comprising target user in available medical treatment big data
The user of attribute gathers to form user, then gathers again for the user to establish the corresponding target disease of attribute of target user
Sick incidence table.As can be seen that the embodiment of the present application divides the user for including in medical big data according to the attribute of user
Then class establishes different target disease incidence tables for different attributes, this is because the user of different attribute is actually
Different in the probability that each age suffers from target disease, then the embodiment of the present application is by obtaining not the attribute for target
Same target disease incidence table, so as to more accurately predict the expection age of onset of target user, thus more quasi-
The really health point of assessment target user.
It should be noted that tending to emphasize the difference between each embodiment to the description of each embodiment above
Place, same or similar place can refer to mutually, for sake of simplicity, repeats no more herein.
The embodiment of the present application also provides a kind of health evaluating device, which is used to execute any one of aforementioned
The unit of health evaluating method.It specifically, is a kind of signal of health evaluating device provided by the embodiments of the present application referring to Fig. 5
Block diagram.The health evaluating device of the present embodiment includes acquiring unit 510, predicting unit 520, adjustment unit 530 and assessment unit
540:
Acquiring unit 510 obtains target disease incidence table and the reality of target user for being directed to target disease
Border age of onset, the target disease incidence table describe corresponding disease incident of each age, the practical hair
The sick age is the target user being actually in danger the age with the target disease；
Specifically, acquiring unit 510, for obtaining the attribute of the target user；According to the attribute of the target user
Obtain corresponding target disease incidence table.
Predicting unit 520, for the expected morbidity year according to the estimated target user of the target disease incidence table
Age, the expected age of onset are that the target user of prediction may be in danger the age with the expection of the target disease.
Specifically, predicting unit is used to calculate target disease cumulative incidence table according to the target disease incidence meter,
The target disease cumulative incidence table has recorded corresponding accumulative disease incident of each age；By the accumulative disease
Incidence is greater than or equal to the minimal ages of preset threshold as the expected age of onset.
Adjustment unit 530, for adjusting institute in the case where the practical age of onset is less than the expected age of onset
Target disease incidence table each age corresponding disease incident is stated, until pre- according to the target disease incidence table
It is consistent with the practical age of onset to count the obtained expected age of onset.
Specifically, adjustment unit 530, for age each in the target disease incidence table corresponding disease to be occurred
Rate amplifies identical adjustment ratio respectively.
Assessment unit 540 assesses the health point of the target user according to the degree of adjustment.
Specifically, assessment unit 540, specifically for assessing the health point of the target user according to the adjustment ratio,
The health point is directly proportional to the adjustment ratio.
More specifically, assessment unit 540, for calculating y=[x-1] × 100, to obtain the health point, the y is institute
Health point is stated, the x is the adjustment ratio.
Optionally, target disease incidence table is each user's illness in the medical big data for count medical insurance field
Age, and the set of obtained corresponding disease probability of happening of each age.
Further, above-mentioned health evaluating device further includes receiving unit 550, for receiving the transmission of other terminal devices
Medical big data.
Further, above-mentioned acquiring unit 510 is also used to obtain above-mentioned medical big data, correspondingly, above-mentioned health evaluating
Device further includes statistic unit 560, the corresponding disease probability of happening of each age in medical big data is counted, on establishing
State target disease incidence table.
In the embodiment of the present application, target disease incidence table is obtained by acquiring unit and target user is practical suffers from
The practical age of onset of upper target disease, then predicting unit predicts that the expected of target user sends out according to target disease incidence table
At the sick age, then adjustment unit adjusts target disease incidence in the case where the expection age of onset is less than practical age of onset
Each age corresponding disease incident in table, until expected age of onset is consistent with practical age of onset, to assess
Unit is assessed according to the amplitude of above-mentioned adjustment come the health to target user point.It will thus be seen that present application example is logical
It crosses and compares the expection age of onset of target user with practical age of onset, thus to the physical condition of target user
Effectively assessed.
It is a kind of health evaluating device schematic block diagram that another embodiment of the application provides referring to Fig. 6.Sheet as shown in the figure
Health evaluating device in embodiment may include: one or more processors 610 and memory 620.Above-mentioned 610 He of processor
Memory 620 is connected by bus 630.For memory 620 for storing computer program, computer program includes program instruction,
Processor 610 is used to execute the program instruction of the storage of memory 620.
Processor 610, for being directed to target disease, obtains target disease hair for executing the function of acquiring unit 510
Raw rate table and the practical age of onset of target user, the target disease incidence table describe each age and respectively correspond
Disease incident, the practical age of onset is that the target user being actually in danger the age with the target disease；
Specifically, the attribute for obtaining the target user；Corresponding mesh is obtained according to the attribute of the target user
Mark disease incident table.
It is also used to execute the function of predicting unit 520, for according to the estimated target of the target disease incidence table
The expection age of onset of user, the expected age of onset are that the target user of prediction may suffer from the target disease
It is expected that being in danger the age.
Specifically, for calculating target disease cumulative incidence table, the target according to the target disease incidence meter
Disease cumulative incidence table has recorded corresponding accumulative disease incident of each age；The accumulative disease incident is big
In or equal to preset threshold minimal ages as the expected age of onset.
It is also used to execute the function of adjustment unit 530, for being less than the expected morbidity year in the practical age of onset
In the case where age, target disease incidence table each age corresponding disease incident is adjusted, until according to
The estimated obtained expected age of onset of target disease incidence table is consistent with the practical age of onset.
Specifically, for age each in the target disease incidence table corresponding disease incident to be amplified phase respectively
Same adjustment ratio.
It is also used to execute the function of assessment unit 540, the health point of the target user is assessed according to the degree of adjustment.
Specifically, the health point for assessing the target user according to the adjustment ratio, the health point with it is described
Adjustment ratio is directly proportional.
More specifically, for calculating y=[x-1] × 100, to obtain the health point, the y is the health point, institute
Stating x is the adjustment ratio.
Optionally, target disease incidence table is each user's illness in the medical big data for count medical insurance field
Age, and the set of obtained corresponding disease probability of happening of each age.
Optionally, above-mentioned memory 620 is stored with medical big data, including at least one user in the medical treatment big data
Medical data, wherein medical data includes the age for suffering from target disease of user
Optionally, above-mentioned health evaluating device further includes communication interface 640, and the communication interface 640 is for executing reception
The function of unit 550, for carrying out data interaction with other terminal devices.Specifically, in the application application embodiment, communication
Interface is used to receive the medical big data of other terminal devices transmission.
Further, above-mentioned processor 610 is also used to obtain above-mentioned medical big data, correspondingly, processor 610 is also used to
The function of statistic unit 560 is executed, the corresponding disease probability of happening of each age in medical big data is counted, on establishing
State target disease incidence table.
It should be appreciated that in the embodiment of the present application, alleged processor 610 can be central processing unit (Central
Processing Unit, CPU), which can also be other general processors, digital signal processor (Digital
Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit,
ASIC), ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic
Device, discrete gate or transistor logic, discrete hardware components etc..General processor can be microprocessor or this at
Reason device is also possible to any conventional processor etc..
The memory 620 may include read-only memory and random access memory, and to processor 610 provide instruction and
Data.The a part of of memory 620 can also include nonvolatile RAM.For example, memory 620 can also be deposited
Store up the information of device type.
In the specific implementation, provided by the embodiments of the present application be good for can be performed in processor 610 described in the embodiment of the present application
Implementation described in the first embodiment of health appraisal procedure, second embodiment, 3rd embodiment and fourth embodiment,
The implementation of health evaluating device described in executable the embodiment of the present application, details are not described herein.
A kind of computer readable storage medium is provided in another embodiment of the application, computer readable storage medium is deposited
Computer program is contained, computer program includes program instruction, and program instruction is executed by processor.:
Computer readable storage medium can be the internal storage unit of the health evaluating device of aforementioned any embodiment, example
Such as the hard disk or memory of health evaluating device.The external storage that computer readable storage medium is also possible to health evaluating device is set
Plug-in type hard disk that is standby, such as being equipped on health evaluating device, intelligent memory card (Smart Media Card, SMC), safe number
Word (Secure Digital, SD) card, flash card (Flash Card) etc..Further, computer readable storage medium may be used also
With the internal storage unit both including health evaluating device or including External memory equipment.Computer readable storage medium is for depositing
Other programs and data needed for storing up computer program and health evaluating device.Computer readable storage medium can be also used for
Temporarily store the data that has exported or will export.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware
With the interchangeability of software, each exemplary composition and step are generally described according to function in the above description.This
A little functions are implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Specially
Industry technical staff can realize described function to each specific application using different health evaluating methods, but this
Kind is realized it is not considered that exceeding scope of the present application.
It is apparent to those skilled in the art that for convenience of description and succinctly, foregoing description is good for
Health assesses the specific work process of device and unit, can refer to the corresponding process in aforementioned health evaluating embodiment of the method,
This is repeated no more.
In several embodiments provided herein, it should be understood that disclosed health evaluating device and health are commented
Estimate method, may be implemented in other ways.For example, the apparatus embodiments described above are merely exemplary, for example,
The division of unit, only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units
Or component can be combined or can be integrated into another system, or some features can be ignored or not executed.In addition, showing
Show or the mutual coupling, direct-coupling or communication connection that discusses can be through some interfaces, between device or unit
Coupling or communication connection are connect, electricity, mechanical or other form connections are also possible to.
Unit may or may not be physically separated as illustrated by the separation member, shown as a unit
Component may or may not be physical unit, it can and it is in one place, or may be distributed over multiple networks
On unit.It can select some or all of unit therein according to the actual needs to realize the mesh of the embodiment of the present application scheme
's.
It, can also be in addition, each functional unit in each embodiment of the application can integrate in one processing unit
It is that each unit physically exists alone, is also possible to two or more units and is integrated in one unit.It is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.
It, can if integrated unit is realized in the form of SFU software functional unit and when sold or used as an independent product
To be stored in a computer readable storage medium.Based on this understanding, the technical solution of the application substantially or
Say that all or part of the part that contributes to existing technology or the technical solution can embody in the form of software products
Out, which is stored in a storage medium, including some instructions are used so that a computer equipment
(can be personal computer, health evaluating device or the network equipment etc.) executes each embodiment health evaluating side of the application
The all or part of the steps of method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can store journey
The medium of sequence code.
Claims (10)
1. a kind of health evaluating method characterized by comprising
It is directed to target disease, obtains target disease incidence table and the practical age of onset of target user, the target disease
Sick incidence table describes corresponding disease incident of each age, and the practical age of onset is target user trouble
There is actually being in danger the age for the target disease；
According to the expection age of onset of the estimated target user of the target disease incidence table, the expected age of onset is
The target user of prediction may be in danger the age with the expection of the target disease；
In the case where the practical age of onset is less than the expected age of onset, it is each to adjust the target disease incidence table
A age corresponding disease incident, until according to the target disease incidence table it is estimated obtain described expected fall ill
Age is consistent with the practical age of onset；
The health point of the target user is assessed according to the degree of adjustment.
2. according to right to require 1 described in method, which is characterized in that it is described according to the estimated institute of the target disease incidence table
State the expection age of onset of target user, comprising:
Target disease cumulative incidence table, the target disease cumulative incidence table are calculated according to the target disease incidence meter
Have recorded corresponding accumulative disease incident of each age；
The accumulative disease incident is greater than or equal to the minimal ages of preset threshold as the expected age of onset.
3. according to the method described in claim 1, adjustment target disease incidence table each age is corresponding
Disease incident, comprising:
Age each in the target disease incidence table corresponding disease incident is amplified into identical adjustment ratio respectively.
4. according to the method described in claim 3, it is characterized in that, described assess the target user according to the degree of adjustment
Health point, comprising:
The health point of the target user is assessed according to the adjustment ratio, the health point is directly proportional to the adjustment ratio.
5. according to the method described in claim 4, it is characterized in that, described assess the target use according to the adjustment ratio
The health at family point, comprising:
It calculates y=[x-1] × 100, to obtain the health point, the y is the health point, and the x is the adjustment ratio.
6. the method according to claim 1, wherein the acquisition target disease incidence table, including；
Obtain the attribute of the target user；
Corresponding target disease incidence table is obtained according to the attribute of the target user.
7. according to claim 1 to method described in 6 any one, which is characterized in that the target disease incidence table is system
It counts the age of each user's illness in the medical big data of medical insurance field, and obtained corresponding disease of each age
The set of probability of happening.
8. a kind of health evaluating device characterized by comprising
Acquiring unit obtains target disease incidence table and the practical morbidity year of target user for being directed to target disease
Age, the target disease incidence table describe corresponding disease incident of each age, and the practical age of onset is
The target user is actually in danger the age with the target disease；
Predicting unit, it is described for the expection age of onset according to the estimated target user of the target disease incidence table
It is expected that the target user that age of onset is prediction may be in danger the age with the expection of the target disease；
Adjustment unit, for adjusting the target in the case where the practical age of onset is less than the expected age of onset
Disease incident table each age corresponding disease incident is obtained until according to the target disease incidence table is estimated
The expected age of onset it is consistent with the practical age of onset；
Assessment unit, for assessing the health point of the target user according to the degree of adjustment.
9. a kind of health evaluating device, which is characterized in that including processor and memory, the processor is mutually interconnected with memory
It connects, wherein the memory is for storing computer program, and the computer program includes program instruction, the processor quilt
It is configured to call described program instruction, to execute the method according to claim 1 to 7.
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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| CN201811530546.2A CN109785965A (en) | 2018-12-13 | 2018-12-13 | A kind of health evaluating method, health evaluating device and computer readable storage medium |
| PCT/CN2019/099776 WO2020119151A1 (en) | 2018-12-13 | 2019-08-08 | Health evaluation method, health evaluation device, and computer readable storage medium |
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| CN201811530546.2A CN109785965A (en) | 2018-12-13 | 2018-12-13 | A kind of health evaluating method, health evaluating device and computer readable storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020119151A1 (en) * | 2018-12-13 | 2020-06-18 | 平安医疗健康管理股份有限公司 | Health evaluation method, health evaluation device, and computer readable storage medium |
| CN116092681A (en) * | 2023-03-28 | 2023-05-09 | 北京嘉和海森健康科技有限公司 | Method, system, electronic device and storage medium for determining health index score |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106326654A (en) * | 2016-08-24 | 2017-01-11 | 北京辛诺创新科技有限公司 | Big data cloud analysis-based health prediction system, intelligent terminal and server |
| CN107153774A (en) * | 2017-05-24 | 2017-09-12 | 山东大学 | The disease forecasting system of the structure and application of chronic disease risk assessment the hyperbolic model model |
| CN107506606A (en) * | 2017-09-13 | 2017-12-22 | 温州悦康信息技术有限公司 | Common disease Risk Forecast Method and system |
| CN107767959A (en) * | 2017-11-15 | 2018-03-06 | 平安健康保险股份有限公司 | Health risk assessment method, apparatus and equipment based on character trait |
| CN108206058A (en) * | 2016-12-19 | 2018-06-26 | 平安科技（深圳）有限公司 | Human body comprehensive health risk Forecasting Methodology and system |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105184107A (en) * | 2015-10-20 | 2015-12-23 | 沈阳国际旅行卫生保健中心 | Health risk pre-warning system for human body circulatory system |
| CN105528526B (en) * | 2016-01-15 | 2018-03-30 | 胡广芹 | A kind of life cycle dynamical health management system excavated based on traditional Chinese medicine succession with big data |
| US20180308569A1 (en) * | 2017-04-25 | 2018-10-25 | S Eric Luellen | System or method for engaging patients, coordinating care, pharmacovigilance, analysis or maximizing safety or clinical outcomes |
| CN108573752A (en) * | 2018-02-09 | 2018-09-25 | 上海米因医疗器械科技有限公司 | A kind of method and system of the health and fitness information processing based on healthy big data |
| CN109712712A (en) * | 2018-12-13 | 2019-05-03 | 平安医疗健康管理股份有限公司 | A kind of health evaluating method, health evaluating device and computer readable storage medium |
| CN109785965A (en) * | 2018-12-13 | 2019-05-21 | 平安医疗健康管理股份有限公司 | A kind of health evaluating method, health evaluating device and computer readable storage medium |
-
2018
- 2018-12-13 CN CN201811530546.2A patent/CN109785965A/en active Pending
-
2019
- 2019-08-08 WO PCT/CN2019/099776 patent/WO2020119151A1/en active Application Filing
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106326654A (en) * | 2016-08-24 | 2017-01-11 | 北京辛诺创新科技有限公司 | Big data cloud analysis-based health prediction system, intelligent terminal and server |
| CN108206058A (en) * | 2016-12-19 | 2018-06-26 | 平安科技（深圳）有限公司 | Human body comprehensive health risk Forecasting Methodology and system |
| CN107153774A (en) * | 2017-05-24 | 2017-09-12 | 山东大学 | The disease forecasting system of the structure and application of chronic disease risk assessment the hyperbolic model model |
| CN107506606A (en) * | 2017-09-13 | 2017-12-22 | 温州悦康信息技术有限公司 | Common disease Risk Forecast Method and system |
| CN107767959A (en) * | 2017-11-15 | 2018-03-06 | 平安健康保险股份有限公司 | Health risk assessment method, apparatus and equipment based on character trait |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020119151A1 (en) * | 2018-12-13 | 2020-06-18 | 平安医疗健康管理股份有限公司 | Health evaluation method, health evaluation device, and computer readable storage medium |
| CN116092681A (en) * | 2023-03-28 | 2023-05-09 | 北京嘉和海森健康科技有限公司 | Method, system, electronic device and storage medium for determining health index score |
| CN116092681B (en) * | 2023-03-28 | 2023-08-08 | 北京嘉和海森健康科技有限公司 | Method, system, electronic device and storage medium for determining health index score |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020119151A1 (en) | 2020-06-18 |
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