A health assessment method, a health assessment device and a computer readable storage medium

Abstract

The present application discloses a health assessment method, a health assessment device and a computer-readable storage medium, which are applied to the field of prediction and valuation, wherein the method includes: for a target disease, obtaining a target disease incidence table and the actual onset age of a target user; estimating the expected onset age of the target user of the health assessment method according to the target disease incidence table of the health assessment method; when the actual onset age of the health assessment method is less than the expected onset age of the health assessment method, adjusting the disease incidence rates corresponding to each age in the target disease incidence table of the health assessment method so that the expected onset age is consistent with the actual onset age; and evaluating the health score of the target user of the health assessment method according to the degree of adjustment. The present application obtains the health score of the target user by comparing the actual onset age of the target user with the expected onset age, so that the health status of the target user can be reflected according to the size of the health score.

Description

Technical Field

[0001] The present application relates to the technical field of risk assessment, and in particular to a health assessment method, a health assessment device, and a computer-readable storage medium. Background Art

[0002] Advances in medical technology have made many diseases curable, but there are still many chronic diseases that are difficult to cure and have a long incubation period. For people with different physical conditions, the onset time is affected by many factors such as genetics and lifestyle habits, so the specific onset time is not fixed. Even if there is no disease in the current body, it does not mean that the body is healthy.

[0003] Therefore, in order to measure the user's true physical health status, it is now possible to test the user's physical functions, thereby scoring the user's physical functions in various aspects, and finally combining all scores to obtain a comprehensive score. The comprehensive score is then used to assess the user's likelihood of developing a specific disease or dying from a specific disease in the future. The user can also have a general understanding of his or her own health through the comprehensive score.

[0004] However, the method of directly measuring the user's physical health by evaluating the user's physical functions is still not very accurate, because there are too many factors that affect health. Simply evaluating the user's physical functions cannot accurately describe the user's true physical health status. Therefore, there is still a lack of an efficient and accurate health assessment method. Summary of the invention

[0005] The embodiment of the present application provides a health assessment method, which can efficiently and accurately assess the health status of a user by comparing the user's physical health status with that of general peers.

[0006] In a first aspect, an embodiment of the present application provides a health assessment method, the method comprising:

[0007] For the target disease, obtain a target disease incidence table and the actual onset age of the target user, wherein the target disease incidence table records the disease incidence rates corresponding to different ages, and the actual onset age is the actual risk age of the target user suffering from the target disease;

[0008] Predicting the expected age of onset of the target user according to the target disease incidence table, where the expected age of onset is the predicted age at which the target user may suffer from the target disease;

[0009] When the actual onset age is younger than the expected onset age, the disease incidence rates corresponding to the respective ages in the target disease incidence rate table are adjusted until the expected onset age estimated according to the target disease incidence rate table is consistent with the actual onset age;

[0010] The health score of the target user is evaluated according to the degree of adjustment.

[0011] In combination with the first aspect, in a first implementation of the first aspect, estimating the expected onset age of the target user according to the target disease incidence table includes:

[0012] Calculating a target disease cumulative incidence table according to the target disease incidence table, wherein the target disease cumulative incidence table records the cumulative disease incidence corresponding to each age;

[0013] The minimum age at which the cumulative disease incidence is greater than or equal to a preset threshold is taken as the expected age of onset.

[0014] In combination with the first aspect, in a second implementation of the first aspect, adjusting the disease incidence rates corresponding to each age in the target disease incidence table includes:

[0015] The disease incidence rates corresponding to each age in the target disease incidence rate table are respectively enlarged by the same adjustment ratio.

[0016] In combination with the first aspect, in a third implementation of the first aspect, evaluating the health score of the target user according to the degree of adjustment includes:

[0017] The health score of the target user is evaluated according to the adjustment ratio, and the health score is proportional to the adjustment ratio.

[0018] In combination with the first aspect, in a fourth implementation of the first aspect, evaluating the health score of the target user according to the adjustment ratio includes:

[0019] Calculate y=[x-1]×100 to obtain the health score, where y is the health score and x is the adjustment ratio.

[0020] In combination with the first aspect, in a fifth implementation of the first aspect, obtaining the target disease incidence table includes:

[0021] Obtaining attributes of the target user;

[0022] The corresponding target disease incidence table is obtained according to the attributes of the target user.

[0023] In combination with the first aspect to the fifth implementation method of the first aspect, in the sixth implementation method of the first aspect, the target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by statistically analyzing the ages of each user suffering from the disease in the medical big data in the medical insurance field.

[0024] In a second aspect, an embodiment of the present application provides a health assessment device, the health assessment device comprising a unit for executing the health assessment method of the first aspect, the health assessment device comprising:

[0025] an acquisition unit, for acquiring, for a target disease, a target disease incidence table and an actual onset age of a target user, wherein the target disease incidence table records the disease incidences corresponding to different ages, and the actual onset age is the actual risk age of the target user suffering from the target disease;

[0026] A prediction unit, configured to predict the expected age of onset of the target user according to the target disease incidence table, wherein the expected age of onset is the predicted age at which the target user may suffer from the target disease;

[0027] An adjusting unit, configured to adjust the disease incidence rates corresponding to the respective ages in the target disease incidence rate table, when the actual onset age is younger than the expected onset age, until the expected onset age estimated according to the target disease incidence rate table is consistent with the actual onset age;

[0028] An evaluation unit is used to evaluate the health score of the target user according to the degree of adjustment.

[0029] In conjunction with the second aspect, in a first implementation manner of the second aspect, the prediction unit is specifically configured to:

[0030] Calculating a target disease cumulative incidence table according to the target disease incidence table, wherein the target disease cumulative incidence table records the cumulative disease incidence corresponding to each age;

[0031] The minimum age at which the cumulative disease incidence is greater than or equal to a preset threshold is taken as the expected age of onset.

[0032] In combination with the second aspect, in a second implementation of the second aspect, the adjustment unit is specifically used to amplify the disease incidence rates corresponding to each age in the target disease incidence table by the same adjustment ratio.

[0033] In combination with the second aspect, in a third implementation manner of the second aspect, the evaluation unit is specifically used to evaluate the health score of the target user according to the adjustment ratio, and the health score is proportional to the adjustment ratio.

[0034] In combination with the second aspect, in a fourth implementation of the second aspect, the evaluation unit is specifically configured to:

[0035] Calculate y=[x-1]×100 to obtain the health score, where y is the health score and x is the adjustment ratio.

[0036] In combination with the second aspect, in a fifth implementation manner of the second aspect, the acquiring unit is specifically configured to:

[0037] Obtaining attributes of the target user;

[0038] The corresponding target disease incidence table is obtained according to the attributes of the target user.

[0039] In combination with the second aspect to the fifth implementation method of the second aspect, in the sixth implementation method of the second aspect, the target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by statistically analyzing the ages of each user suffering from the disease in the medical big data in the field of medical insurance.

[0040] In a third aspect, an embodiment of the present application provides another health assessment device, comprising a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program that supports the health assessment device to execute the above-mentioned health assessment method, and the computer program includes program instructions. The processor is configured to call the program instructions to execute the health assessment method of any one of the implementation methods of the above-mentioned first aspect to the first aspect.

[0041] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer storage medium stores a computer program, wherein the computer program includes program instructions, and wherein the program instructions, when executed by a processor, are used to execute a health assessment method of any one of the implementation methods of the first aspect to the first aspect above.

[0042] This application first obtains the actual onset age of the target user and the target disease incidence table, and then predicts the expected onset age of the target user based on the target disease incidence table. If the actual onset age of the target user is lower than the expected onset age, it means that the user's health condition is not as good as that of his or her peers. Therefore, the target disease incidence table is adjusted so that the expected onset age of the target user re-estimated based on the adjusted target disease incidence table is consistent with the actual onset age of the target user. Then, the health score of the target user can be evaluated based on the above adjustment degree of the target disease incidence table, thereby reflecting the health condition of the target user through the size of the health score. Therefore, this application uses the health condition of general peers as a benchmark to measure the user's physical condition. Compared with the method of directly evaluating the user's physical health condition in isolation by evaluating the user's physical function, this application sets an evaluation benchmark for whether the body is healthy, so it can more efficiently and accurately evaluate the user's health condition. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments.

[0044] Figure 1 is a schematic flow chart of a health assessment method provided in an embodiment of the present application;

[0045] Figure 2 is a schematic flow chart of a health assessment method provided in an embodiment of the present application;

[0046] Figure 3 is an example schematic diagram of a target disease incidence table provided in an embodiment of the present application;

[0047] Figure 4 This is an example schematic diagram of a cumulative incidence table of a target disease provided in an embodiment of the present application;

[0048] Figure 5 is a schematic block diagram of a health assessment device provided in an embodiment of the present application;

[0049] Figure 6 It is a structural block diagram of a health assessment device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0051] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0052] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0053] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0054] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0055] The terminal devices described in the embodiments of the present application include but are not limited to devices with communication functions, smart phones, tablet computers, laptop computers, desktop computers, portable digital players, smart bracelets, and smart watches. When the terminal device sends data to the health assessment device in the blockchain, the characteristics of the data are recorded and transmitted in a preset format, wherein the characteristics of the data include time, location, type, etc.

[0056] This application is mainly used for health assessment devices, which can be traditional health assessment devices, servers, large storage systems, desktop computers, laptops, tablet computers, PDAs, smart phones, portable digital players, smart watches and smart bracelets, etc., and this application does not limit this. When the health assessment device sends data to other devices, the characteristics of the data are recorded and transmitted according to a preset format, wherein the characteristics of the data include time, location, type, etc. Among them, the above-mentioned other devices include servers, large storage systems, desktop computers, laptops, tablet computers, PDAs, smart phones, portable digital players, smart watches and smart bracelets, etc., and this application does not limit this.

[0057] See also Figure 1 , is a schematic flow chart of a health assessment method provided by an embodiment of the present application, such as Figure 1 The health assessment methods shown may include:

[0058] 101: For the target disease, obtain the target disease incidence table and the actual onset age of the target user.

[0059] In an embodiment of the present application, the age at which the target user develops the target disease is obtained as the actual age of onset, and a target disease incidence table is obtained, which records the probability of an average user developing the target disease at each age. The target disease incidence table then records the disease incidence rates corresponding to each age.

[0060] It should be noted that the onset time of the target disease of the above-mentioned target user comes from the user's insurance record in the medical insurance field, which includes the user's insurance time, insurance age, insurance time and insurance age, etc. Therefore, the user's actual insurance age of suffering from the target disease can be determined based on the user's insurance record, that is, the actual onset age of the above-mentioned target user.

[0061] Furthermore, before obtaining the target disease, before obtaining the target disease incidence table, medical big data is first obtained to establish the target disease incidence table. Specifically, medical big data is obtained, and the medical big data includes medical data of at least one user; the disease occurrence probability corresponding to each age in the medical big data is statistically analyzed to establish the target disease incidence table.

[0062] In the embodiment of the present application, medical big data is first obtained, and then the proportion of all users in the medical big data who are sick at each age is counted, and the proportion of people corresponding to each age is used as the disease incidence rate corresponding to the age. The medical big data records the medical data of multiple users, especially the age at which each user suffers from the target disease.

[0063] For example, if Figure 3 As shown in the figure, assuming that the above medical big data contains the medical data of 1,000,000 users, according to statistics, 949 users suffer from the target disease at the age of 30, accounting for 0.000949 of the total number of users, 1,009 users suffer from the target disease at the age of 31, accounting for 0.001078 of the total number of users... 4,070 users suffer from the target disease at the age of 44, accounting for 0.004070 of the total number of users. Therefore, according to the proportion of the number of people corresponding to each age, the following is established: Figure 3 The target disease incidence table is shown, and the proportion of the number of people corresponding to each age group mentioned above is taken as the disease incidence rate corresponding to each age group.

[0064] Optionally, each user in the above medical big data corresponds to one or more attributes, so the above target disease incidence table established based on the medical big data may be to establish different target disease incidence tables for users with different attributes.

[0065] In the implementation of this application, the above-mentioned medical big data includes the user's illness time and the user's attributes, which include gender, region, occupation and / or interests, etc. When establishing the above-mentioned target disease incidence table, the users in the medical big data can be divided into different categories according to one or more of their attributes, and then different target disease incidence tables are established according to the users of different categories.

[0066] For example, if the above medical big data includes the user's illness time, gender and region, the users contained in the above medical big data are classified according to the two dimensions of their gender and region. For example, gender includes male and female, and the region is divided into Beijing and Shanghai. Therefore, the users in the above medical big data can be divided into four categories, namely female users in Beijing, male users in Beijing, female users in Shanghai and male users in Shanghai. Then, a target disease incidence table is established for the above four categories of users respectively. For example, the proportion of the number of female users in Beijing who suffer from the target disease at each age to the total number of female users in Beijing is counted, so as to obtain the target disease incidence table for female users in Beijing.

[0067] Furthermore, before obtaining the above-mentioned target disease incidence table, the attributes of the target user are first obtained, and then the target disease incidence table corresponding to the attributes of the target user is obtained, and users with different attributes correspond to different target disease incidence tables; if the target disease incidence table corresponding to the attributes of the target user is not obtained, medical big data is obtained, and multiple users with the same attributes as the target user are extracted from the medical big data, and then the target disease incidence table is established based on the multiple users with the same attributes as the target user.

[0068] Optionally, the above-mentioned medical big data is data based on the field of medical insurance, and the above-mentioned target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by statistically analyzing the ages of each user suffering from the disease in the medical big data in the field of medical insurance.

[0069] In the implementation of this application, the above-mentioned medical big data comes from medical insurance data, that is, medical big data based on the field of medical insurance. Specifically, the medical big data comes from the accident records in the field of medical insurance, where the accident record is a record of the user purchasing insurance for the target disease and making a claim to the insurance company when the user suffers from the target disease. Therefore, the accident record will record the user's accident time, that is, the user's illness time.

[0070] 102: Estimate the expected age of onset of the above target users based on the above target disease incidence table.

[0071] In the embodiment of the present application, the high-risk age of the target disease can be determined according to the above target disease incidence table. When the health of the target user is unknown, the high-risk age of the disease is used as the expected age of the target user. The expected age of onset is the predicted age at which the target user may suffer from the target disease. The target disease incidence table is derived from the statistical medical field. The proportion of users who have suffered accidents and have the target disease at each age, so the expected age of onset determined according to the target disease incidence table is also the expected age of the target user.

[0072] Specifically, the above-mentioned estimating the expected onset age of the target user based on the target disease incidence table refers to first calculating the target disease cumulative incidence table based on the target disease incidence table, where the target disease cumulative incidence table records the cumulative disease incidence rates corresponding to each age; and then taking the minimum age whose cumulative disease incidence rate is greater than or equal to a preset threshold as the above-mentioned expected onset age.

[0073] For example, Figure 3 The target disease incidence table shown is obtained as follows Figure 4 The target disease cumulative incidence table shown is to calculate the cumulative disease incidence corresponding to each age in the target disease incidence table. The cumulative disease incidence corresponding to 30 years old is the disease incidence corresponding to 30 years old, that is, the probability of the target user suffering from the target disease at the age of 30. The cumulative disease incidence corresponding to 31 years old is the sum of the disease incidence corresponding to 30 years old and 31 years old, that is, the probability of the target user suffering from the target disease between 30 and 31 years old... The cumulative disease incidence corresponding to 44 years old is the sum of the disease incidence corresponding to 30 years old, 31 years old... to 43 years old, that is, the probability of the target user suffering from the target disease between 30 and 43 years old. After obtaining the above cumulative target disease incidence table, the minimum age in the cumulative target disease incidence table with a cumulative disease incidence greater than the preset threshold is taken as the expected onset age. Assuming the preset threshold is 0.02, it can be seen that 42 years old in the target disease cumulative incidence table is the minimum age with a cumulative disease incidence exceeding 0.02, and 42 years old is taken as the above expected onset age.

[0074] 103: When the actual age of onset is lower than the expected age of onset, adjust the disease incidence rates corresponding to the respective ages in the target disease incidence table until the expected age of onset estimated according to the target disease incidence table is consistent with the actual age of onset.

[0075] In an embodiment of the present application, if the actual onset age of the target user is younger than the expected onset age, it means that the user's physical health is not as good as that of an average user. Therefore, the disease incidence rates corresponding to each age in the target disease incidence table are adjusted, and then a new target disease cumulative incidence table is obtained based on the adjusted target disease incidence table, so that the expected onset age obtained based on the new target disease incidence table is consistent with the actual onset age of the target user.

[0076] Optionally, the disease incidence rates corresponding to each age in the above target disease incidence table may be amplified by non-equal proportions, or the disease incidence rates corresponding to each age in the target disease incidence table may be amplified by the same adjustment proportion.

[0077] In an embodiment of the present application, the disease incidence rates corresponding to the respective ages in the above-mentioned target disease incidence rate table are adjusted. The target disease incidence rate table corresponding to the respective ages may be adjusted non-proportionally or proportionally.

[0078] For example, Figure 3 Different proportions are adjusted for each age group in the target disease incidence table shown. For example, the disease incidence rates corresponding to 30, 31, 32, ... 44 years old are adjusted to 101%, 103%, 106%, ... 120%, respectively, or the same adjustment proportion is uniformly adjusted for each age group, for example, 105%.

[0079] 104: Evaluate the health score of the target user according to the degree of adjustment.

[0080] In an embodiment of the present application, the health score of the target user is evaluated according to the degree of adjustment of the incidence of the target disease. Specifically, if different proportions are adjusted for each age during the adjustment process, the mean of the proportions adjusted for each age is calculated, and the mean is used as the total adjustment ratio. Alternatively, if the same proportion is adjusted for each age during the adjustment process, the same proportion is used as the adjustment ratio. The degree of the adjustment can be reflected according to the size of the adjustment ratio. After the adjustment ratio is obtained, the health score of the target user is evaluated according to the adjustment ratio. Specifically, when the adjustment ratio is less than or equal to 1, the health score of the target user is set to 0 points. When the adjustment ratio is greater than 1, the larger the adjustment ratio, the larger the health score. Among them, a health score of 0 indicates health, and a larger health score indicates that the physical health of the target user is worse than that of the average peer.

[0081] It should be noted that if the actual age of onset of the above-mentioned target user is greater than or equal to the expected age of onset, it means that the target user is in good health. Therefore, the health score of the target user is directly set to 0, which means that the target user is in good health, which is similar to or better than that of the average peers.

[0082] Furthermore, the health score of the target user is calculated according to the adjustment ratio, and y=[x-1]×100 is calculated to obtain the health score, wherein y is the health score and x is the adjustment ratio.

[0083] For example, if the above adjustment ratio is 105%, then the above calculation formula y=[x-1]×100 will give a health score of 5 points.

[0084] In the embodiment of the present application, the expected onset age of the target user is predicted according to the target disease incidence table, and then the expected onset age is compared with the actual onset age of the target user. If the actual onset age is greater than or equal to the expected onset age, the health score of the target user is set to 0, indicating that the health status of the target user is the same as or better than that of the average peers. If the actual onset age is less than the expected onset age, the target disease incidence table is adjusted until the expected onset age estimated according to the target disease incidence table is consistent with the actual onset age, and then the disease incidence corresponding to each age in the target disease incidence is adjusted. Finally, the health score of the target user is determined according to the adjustment range. The larger the adjustment range, the larger the health score. It can be seen that the embodiment of the present application compares the health status of the target user with that of the average peers based on the target disease, and then obtains the health score of the target user. Therefore, the embodiment of the present application uses the average peers as the health benchmark. Compared with directly scoring the health status of the target user based on the health data of the target user, it can be more objective and effective to evaluate the health of the target user.

[0085] See also Figure 2 , is a schematic flow chart of another health assessment method provided by an embodiment of the present application, such as Figure 2 The health assessment methods shown may include:

[0086] 201: Obtain the attributes of the target user, and for the target disease, obtain the actual onset age of the target user.

[0087] In an embodiment of the present application, the age at which the target user develops the target disease is obtained as the actual age of onset, and the attributes of the target user are obtained, where the attributes include gender, region, occupation and / or interests, etc.

[0088] It should be noted that the onset time of the target disease of the above-mentioned target user comes from the user's insurance record in the medical insurance field, which includes the user's insurance time, insurance age, insurance time and insurance age, etc. Therefore, the user's actual insurance age of suffering from the target disease can be determined based on the user's insurance record, that is, the actual onset age of the above-mentioned target user.

[0089] 202: Obtain the corresponding target disease incidence table according to the attributes of the target user.

[0090] In an embodiment of the present application, a corresponding target disease incidence table is obtained based on the attributes of the target user. The target disease incidence table records the probability of an average user suffering from the target disease at each age, and the disease incidence corresponding to each age is then recorded in the target disease incidence table.

[0091] Furthermore, before obtaining the target disease, before obtaining the target disease incidence table, medical big data is first obtained to establish the above target disease incidence table. Specifically, medical big data is obtained, and the medical big data includes medical data of at least one user, wherein the medical data includes the age and attributes of the disease; the users in the medical big data are divided into different user sets according to the above attributes, and the disease occurrence probability corresponding to each age in each user set is counted, so as to establish different target disease incidence tables for different attributes.

[0092] In the implementation of this application, medical big data is first obtained, and then users with the same attributes in the medical big data are divided into the same user set, so as to obtain different user sets for different attributes, and then the disease ages of users in each user set are counted, so as to obtain a target disease incidence table corresponding to each age for the attribute, and the attribute includes gender, region, occupation and / or interest, etc.

[0093] For example, if the above medical big data contains the user's illness time, gender and region, then the users contained in the above medical big data are classified according to the two dimensions of gender and region. For example, gender includes male and female, and the region is divided into Beijing and Shanghai. Therefore, the users in the above medical big data can be divided into four categories, namely female users in Beijing, male users in Beijing, female users in Shanghai and male users in Shanghai. Then, a target disease incidence table is established for the above four categories of users respectively. For example, the proportion of the number of female users in Beijing who suffer from the target disease at each age to the total number of female users in Beijing is counted, so as to obtain the target disease incidence table for female users in Beijing. Assuming that a user set with the attributes of female and Beijing is obtained, a corresponding target disease incidence table is established based on the user set, such as Figure 3As shown in the figure, assuming that the above medical big data contains the medical data of 1,000,000 female users in Beijing, according to statistics, 949 users suffer from the target disease at the age of 30, accounting for 0.000949 of the total number of users, 1009 users suffer from the target disease at the age of 31, accounting for 0.001078 of the total number of users... 4070 users suffer from the target disease at the age of 44, accounting for 0.004070 of the total number of users. Therefore, according to the proportion of the number of people corresponding to each age, the following is established: Figure 3 The target disease incidence table is shown, and the proportion of the number of people corresponding to each age group mentioned above is taken as the disease incidence rate corresponding to each age group.

[0094] Furthermore, if the target disease incidence table corresponding to the target user's attributes is not obtained, medical big data is obtained, multiple users with the same attributes as the target user are extracted from the medical big data, and then the target disease incidence table is established based on the multiple users with the same attributes as the target user.

[0095] Optionally, the above-mentioned medical big data is data based on the field of medical insurance, and the above-mentioned target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by statistically analyzing the ages of each user suffering from the disease in the medical big data in the field of medical insurance.

[0096] In the implementation of this application, the above-mentioned medical big data comes from medical insurance data, that is, medical big data based on the field of medical insurance. Specifically, the medical big data comes from the accident records in the field of medical insurance, where the accident record is a record of the user purchasing insurance for the target disease and making a claim to the insurance company when the user suffers from the target disease. Therefore, the accident record will record the user's accident time, that is, the user's illness time.

[0097] 203: Estimate the expected onset age of the above target users based on the above target disease incidence table.

[0098] It should be noted that the target disease incidence table is derived from the statistical proportion of users who have suffered accidents in the medical field who develop the target disease at each age. Therefore, the expected age of onset determined based on the target disease incidence table is also the expected age of accident for the target user.

[0099] 204: When the actual onset age is lower than the expected onset age, the disease incidence rates corresponding to the respective ages in the target disease incidence table are respectively amplified by the same adjustment ratio until the expected onset age estimated according to the target disease incidence table is consistent with the actual onset age.

[0100] In an embodiment of the present application, if the actual age of onset of the target user is younger than the expected age of onset, it means that the user's physical health is not as good as that of an average user. Therefore, the disease incidence rates corresponding to each age in the target disease incidence table are adjusted so that the disease incidence rates corresponding to each age are adjusted by the same adjustment ratio. Then, a new target disease cumulative incidence table is obtained based on the adjusted target disease incidence table, so that the expected age of onset obtained based on the new target disease incidence table is consistent with the actual age of onset of the target user.

[0101] For example, Figure 3 Each age in the target disease incidence table shown is adjusted at the same ratio. For example, the disease incidence corresponding to 30, 31, 32, ..., 44 years old is adjusted to 105% of the original respectively.

[0102] 205: Evaluate the health score of the target user according to the size of the above adjustment ratio.

[0103] In an embodiment of the present application, the health score of the target user is evaluated according to the degree of adjustment of the incidence rate of the target disease. Specifically, in the above adjustment process, the same proportion is adjusted for each age, and the same proportion is used as the adjustment proportion. The degree of the above adjustment can be reflected according to the size of the adjustment proportion. Therefore, after the adjustment proportion is obtained, the health score of the target user is evaluated according to the adjustment proportion. Specifically, when the adjustment proportion is less than or equal to 1, the health score of the target user is set to 0 points. When the adjustment proportion is greater than 1, the larger the adjustment proportion, the larger the health score. Among them, a health score of 0 points indicates health, and a larger health score indicates that the physical health of the target user is worse than that of the average peers.

[0104] Furthermore, the health score of the target user is calculated according to the adjustment ratio, and y=[x-1]×100 is calculated to obtain the health score, wherein y is the health score and x is the adjustment ratio.

[0105] For example, if the above adjustment ratio is 105%, then the above calculation formula y=[x-1]×100 will give a health score of 5 points.

[0106] Compared with the previous embodiment of the application, the embodiment of the present application describes in more detail the process of obtaining the target disease incidence table, adjusting the target disease incidence table, and evaluating the target user's health score according to the adjustment range of the target disease incidence table. Among them, when obtaining the above-mentioned target disease incidence table, before obtaining the target disease incidence table, first obtain the attributes of the target user, and then obtain the corresponding target disease incidence table according to the user's attributes. When the target disease incidence table corresponding to the target user's attributes is not obtained, the user containing the attributes of the target user in the medical big data can be obtained to form a user set, and then the target disease incidence table corresponding to the attributes of the target user is established for the user set. It can be seen that the embodiment of the present application classifies the users contained in the medical big data according to the user's attributes, and then establishes different target disease incidence tables for different attributes. This is because users with different attributes actually have different probabilities of suffering from the target disease at each age. Therefore, the embodiment of the present application obtains different target disease incidence tables for the attributes used for the target, so that the expected age of onset of the target user can be more accurately predicted, thereby more accurately evaluating the health score of the target user.

[0107] It should be noted that the above description of the various embodiments tends to emphasize the differences between the various embodiments, and the same or similar aspects can be referenced to each other. For the sake of brevity, they will not be repeated herein.

[0108] The present application also provides a health assessment device, which is used to perform any of the above health assessment methods. Figure 5 , is a schematic block diagram of a health assessment device provided in an embodiment of the present application. The health assessment device of this embodiment includes an acquisition unit 510, a prediction unit 520, an adjustment unit 530 and an assessment unit 540:

[0109] The acquisition unit 510 is used to acquire, for a target disease, a target disease incidence table and an actual onset age of a target user, wherein the target disease incidence table records the disease incidences corresponding to different ages, and the actual onset age is the actual risk age of the target user suffering from the target disease;

[0110] Specifically, the acquisition unit 510 is used to acquire the attributes of the target user; and acquire the corresponding target disease incidence table according to the attributes of the target user.

[0111] The prediction unit 520 is used to predict the expected age of onset of the target user according to the target disease incidence table, where the expected age of onset is the predicted age at which the target user may suffer from the target disease.

[0112] Specifically, the prediction unit is used to calculate a target disease cumulative incidence table based on the target disease incidence table, wherein the target disease cumulative incidence table records the cumulative disease incidence rates corresponding to each age; and the minimum age at which the cumulative disease incidence rate is greater than or equal to a preset threshold is taken as the expected onset age.

[0113] The adjustment unit 530 is used to adjust the disease incidence rates corresponding to each age in the target disease incidence table when the actual onset age is younger than the expected onset age, until the expected onset age estimated according to the target disease incidence table is consistent with the actual onset age.

[0114] Specifically, the adjustment unit 530 is used to amplify the disease incidence rates corresponding to each age in the target disease incidence rate table by the same adjustment ratio.

[0115] The evaluation unit 540 evaluates the health score of the target user according to the degree of adjustment.

[0116] Specifically, the evaluation unit 540 is specifically configured to evaluate the health score of the target user according to the adjustment ratio, where the health score is proportional to the adjustment ratio.

[0117] More specifically, the evaluation unit 540 is used to calculate y=[x-1]×100 to obtain the health score, where y is the health score and x is the adjustment ratio.

[0118] Optionally, the target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by counting the ages of each user suffering from illness in the medical big data in the field of medical insurance.

[0119] Furthermore, the above health assessment device also includes a receiving unit 550 for receiving medical big data sent by other terminal devices.

[0120] Furthermore, the acquisition unit 510 is also used to acquire the medical big data. Accordingly, the health assessment device further includes a statistical unit 560 for statistically analyzing the disease occurrence probabilities corresponding to each age in the medical big data to establish the target disease incidence table.

[0121] In the embodiment of the present application, the target disease incidence table and the actual onset age of the target user who actually suffers from the target disease are obtained by the acquisition unit, and then the prediction unit predicts the expected onset age of the target user based on the target disease incidence table, and then the adjustment unit adjusts the disease incidence corresponding to each age in the target disease incidence table when the expected onset age is less than the actual onset age, until the expected onset age is consistent with the actual onset age, so that the evaluation unit evaluates the health score of the target user according to the above adjustment range. It can be seen that the example of the present application effectively evaluates the physical health status of the target user by comparing the expected onset age of the target user with the actual onset age.

[0122] See also Figure 6 , is a schematic block diagram of a health assessment device provided by another embodiment of the present application. As shown in the figure, the health assessment device in this embodiment may include: one or more processors 610 and a memory 620. The above-mentioned processor 610 and memory 620 are connected via a bus 630. The memory 620 is used to store a computer program, the computer program includes program instructions, and the processor 610 is used to execute the program instructions stored in the memory 620.

[0123] The processor 610 is used to execute the function of the acquisition unit 510, and is used to acquire, for the target disease, a target disease incidence table and an actual onset age of the target user, wherein the target disease incidence table records the disease incidence rates corresponding to different ages, and the actual onset age is the actual risk age of the target user suffering from the target disease;

[0124] Specifically, it is used to obtain the attributes of the target user; and obtain the corresponding target disease incidence table according to the attributes of the target user.

[0125] It is also used to execute the function of the prediction unit 520, which is used to predict the expected onset age of the target user based on the target disease incidence table, and the expected onset age is the predicted expected age at which the target user may suffer from the target disease.

[0126] Specifically, it is used to calculate a target disease cumulative incidence table based on the target disease incidence table, wherein the target disease cumulative incidence table records the cumulative disease incidence corresponding to each age; and the minimum age at which the cumulative disease incidence is greater than or equal to a preset threshold is taken as the expected onset age.

[0127] It is also used to execute the function of the adjustment unit 530, which is used to adjust the disease incidence rates corresponding to each age in the target disease incidence table when the actual onset age is younger than the expected onset age, until the expected onset age estimated according to the target disease incidence table is consistent with the actual onset age.

[0128] Specifically, it is used to amplify the disease incidence rates corresponding to each age in the target disease incidence rate table by the same adjustment ratio.

[0129] It is also used to execute the function of the evaluation unit 540 to evaluate the health score of the target user according to the degree of adjustment.

[0130] Specifically, it is used to evaluate the health score of the target user according to the adjustment ratio, and the health score is proportional to the adjustment ratio.

[0131] More specifically, it is used to calculate y=[x-1]×100 to obtain the health score, where y is the health score and x is the adjustment ratio.

[0132] Optionally, the target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by counting the ages of each user suffering from illness in the medical big data in the field of medical insurance.

[0133] Optionally, the memory 620 stores medical big data, which includes medical data of at least one user, wherein the medical data includes the age at which the user suffers from the target disease.

[0134] Optionally, the health assessment device further includes a communication interface 640, which is used to perform the function of the receiving unit 550 and to interact with other terminal devices. Specifically, in the embodiment of the present application, the communication interface is used to receive medical big data sent by other terminal devices.

[0135] Furthermore, the processor 610 is also used to obtain the medical big data. Accordingly, the processor 610 is also used to execute the function of the statistical unit 560 to count the disease occurrence probabilities corresponding to each age in the medical big data to establish the target disease incidence table.

[0136] It should be understood that in the embodiment of the present application, the processor 610 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0137] The memory 620 may include a read-only memory and a random access memory, and provide instructions and data to the processor 610. A portion of the memory 620 may also include a nonvolatile random access memory. For example, the memory 620 may also store information on the device type.

[0138] In a specific implementation, the processor 610 described in the embodiments of the present application can execute the implementation methods described in the first embodiment, the second embodiment, the third embodiment and the fourth embodiment of the health assessment method provided in the embodiments of the present application, and can also execute the implementation methods of the health assessment device described in the embodiments of the present application, which will not be repeated here.

[0139] In another embodiment of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the program instructions are executed by a processor.

[0140] The computer-readable storage medium may be an internal storage unit of the health assessment device of any of the foregoing embodiments, such as a hard disk or memory of the health assessment device. The computer-readable storage medium may also be an external storage device of the health assessment device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the health assessment device. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the health assessment device. The computer-readable storage medium is used to store computer programs and other programs and data required by the health assessment device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0141] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different health assessment methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0142] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the health assessment device and unit described above can refer to the corresponding process in the aforementioned health assessment method embodiment, and will not be repeated here.

[0143] In the several embodiments provided in the present application, it should be understood that the disclosed health assessment device and health assessment method can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0144] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0145] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0146] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or partly contributed to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a health assessment device, or a network device, etc.) to perform all or part of the steps of the health assessment method of each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

Claims

1. A health assessment method, characterized in that: include: For the target disease, obtain a target disease incidence table and the target user's actual onset age. The target disease incidence table records the disease incidence rates corresponding to different ages. The actual onset age is the actual age at which the target user develops the target disease. Estimating the expected age of onset of the target user based on the target disease incidence table, the expected age of onset being the predicted age at which the target user may be at risk of contracting the target disease; wherein estimating the expected age of onset of the target user based on the target disease incidence table comprises: calculating a target disease cumulative incidence table based on the target disease incidence table, the target disease cumulative incidence table recording the cumulative disease incidence corresponding to each age; and taking the minimum age at which the cumulative disease incidence is greater than or equal to a preset threshold as the expected age of onset; If the actual age of onset is younger than the expected age of onset, adjust the disease incidence rates corresponding to the respective ages in the target disease incidence table until the expected age of onset estimated according to the target disease incidence table is consistent with the actual age of onset; The health score of the target user is evaluated according to the degree of adjustment; the degree of adjustment is determined by the adjustment ratio. When the adjustment ratio is less than or equal to 1, the health score of the target user is 0 points. When the adjustment ratio is greater than 1, the larger the adjustment ratio, the larger the corresponding health score. The larger the health score, the worse the physical health of the target user is compared with his peers. The health score is evaluated as follows: Calculation , to obtain the health score, the For the health score, the The ratio is adjusted as described above.

2. The method according to claim 1, wherein adjusting the disease incidence rate corresponding to each age group in the target disease incidence rate table comprises: The disease incidence rates corresponding to each age group in the target disease incidence table are respectively amplified by the same adjustment ratio.

3. The method according to claim 1, characterized in that The obtaining of the target disease incidence table includes: Obtaining attributes of the target user; Obtain a corresponding target disease incidence table according to the attributes of the target user.

4. The method according to any one of claims 1 to 3, characterized in that The target disease incidence table is a set of disease occurrence probabilities corresponding to each age obtained by statistically analyzing the ages of each user suffering from illness in the medical big data in the medical insurance field.

5. A health assessment device, characterized in that: include: an acquisition unit, configured to acquire, for a target disease, a target disease incidence table recording the disease incidence rates corresponding to respective ages, and an actual onset age of a target user, wherein the target disease incidence table records the disease incidence rates corresponding to respective ages, and the actual onset age is the actual age at which the target user becomes ill with the target disease; a prediction unit, configured to predict an expected age of onset of the target user based on the target disease incidence table, the expected age of onset being the predicted age at which the target user may develop the target disease; wherein predicting the expected age of onset of the target user based on the target disease incidence table comprises: calculating a target disease cumulative incidence table based on the target disease incidence table, the target disease cumulative incidence table recording the cumulative disease incidence corresponding to each age; and taking the minimum age for which the cumulative disease incidence is greater than or equal to a preset threshold as the expected age of onset; an adjusting unit, configured to adjust the disease incidence rates corresponding to respective ages in the target disease incidence table, if the actual age of onset is younger than the expected age of onset, until the expected age of onset estimated according to the target disease incidence table is consistent with the actual age of onset; The evaluation unit is used to evaluate the health score of the target user according to the degree of adjustment; the degree of adjustment is determined by the adjustment ratio. When the adjustment ratio is less than or equal to 1, the health score of the target user is 0 points. When the adjustment ratio is greater than 1, the larger the adjustment ratio, the larger the corresponding health score. The larger the health score, the worse the physical health of the target user is compared with that of his peers. The health score is evaluated as follows: Calculate , to obtain the health score, the For the health score, the The ratio is adjusted as described above.

6. A health assessment device, characterized in that: The method comprises a processor and a memory, wherein the processor and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions. When the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 4.

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