Information processing apparatus, information processing method, and program

Abstract

To provide an information processing apparatus, a method therefor, and a program therefor which recommend insurance to join and a contract period thereof based on risk of user health.SOLUTION: The present invention is directed to an information processing system formed of an information processing apparatus and a terminal connected to each other through a network and associated with at least one or more servers through the network. The information processing apparatus 101 specifies one or more diseases as factors for risk which is an object for compensation of a predetermined insurance, estimates, based on genetic information of a user, probability that the user suffers from each of the specified diseases, determines whether or not the user should join a predetermined insurance based on whether or no there is any disease whose affection probability exceeds a first threshold value, if it is determined by the determination that the user should join the predetermined insurance, determines, based on statistic information relating to disease occurrence timing of each of diseases whose affection probability exceeds the first threshold value, a timing when the user should join the predetermined insurance, and outputs the timing for joining the insurance as a result of the determination to the user.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present invention relates to a technology for recommending insurance that users should subscribe to.

Background Art

[0002] The average life expectancy in Japan has been increasing year by year. For example, according to the World Health Statistics 2023 edition, it is 84.3 years. On the other hand, according to the same statistics, the healthy life expectancy in Japan is 74.1 years. Here, the average life expectancy is the average of the periods of survival from birth to death. On the other hand, the healthy life expectancy is the period during which one can live without being restricted in daily life due to health problems. Therefore, there is an unhealthy period with restrictions in daily life over a period of about 10 years corresponding to the difference between the average life expectancy and the healthy life expectancy. The existence of such an unhealthy period is not only in Japan but also in a similar situation globally. That is, everyone has a risk that their daily life may be restricted due to some health problems for about 10 years during their lifetime. As a means to transfer such a risk, subscribing to an insurance service can be considered. Patent Document 1 describes a method by which a user can easily compare and consider insurance products provided by multiple companies via a network and select a desired insurance product.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The factors that cause the above-mentioned unhealthy periods vary from person to person. Therefore, the risks to be transferred also vary from person to person. However, generally, when a user selects an insurance product or service, based on their income, savings, etc., they make a selection based on the benefit details such as the amount of benefits paid in what circumstances and to what extent, the type and cost of insurance such as savings insurance or term insurance, and the coverage period such as term insurance or whole life insurance. As a result, an appropriate insurance may not be selected according to the potential of the user's personal health risks becoming apparent. Also, if the time to subscribe to insurance is too early, the insurance premium payment will be large, and if it is too late, there is a possibility of not meeting the subscription conditions.

[0005] The present invention provides a technology for recommending the insurance to be subscribed to and the subscription time according to the health risks of the user.

Means for Solving the Problems

[0006] An information processing apparatus according to an aspect of the present invention includes: a specifying means for specifying one or more diseases that are risk factors for a risk that is a compensation target of a predetermined insurance; an estimating means for estimating, based on the genetic information of the user, the probability of the user suffering from each of the diseases specified by the specifying means throughout their lifetime; a first determination means for making a subscription determination as to whether the user should subscribe to the predetermined insurance based on the presence or absence of a disease whose incidence probability exceeds a first threshold; a second determination means for making a determination of the subscription time at which the user should subscribe to the predetermined insurance based on the statistical information regarding the onset time of each of the diseases whose incidence probability exceeds the first threshold when the user is determined to should subscribe to the predetermined insurance by the subscription determination; and an output means for outputting the subscription time, which is the result of the determination, to the user.

Effects of the Invention

[0007] According to the present invention, it is possible to recommend the insurance to be subscribed to and the subscription time according to the health risks of the user.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Embodiments for Carrying Out the Invention

[0009] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the invention according to the claims. Although a plurality of features are described in the embodiments, not all of these plurality of features are essential for the invention, and the plurality of features may be arbitrarily combined. Further, in the accompanying drawings, the same or similar configurations are denoted by the same reference numerals, and duplicate descriptions are omitted.

[0010] (System Configuration) FIG. 1 shows a configuration example of an information processing system 100 according to the present embodiment. The information processing system 100 is a system that outputs insurance that a user should subscribe to and the time when the subscription should be made for a person who requests a proposal for insurance to subscribe to, a person for whom insurance subscription is recommended, a person who has registered a program including a proposal for insurance to subscribe to, etc. (hereinafter referred to as "user"). For example, the information processing system 100 can output an insurance subscription plan including one or more insurances that a user should subscribe to and the time when each insurance should be subscribed to. In the present embodiment, information about insurance output by the information processing system 100 to the user is called insurance recommendation information.

[0011] Insurance can be classified into public insurance (social insurance) and private insurance. For example, public medical insurance is insurance for which enrollment is mandatory, while private medical insurance is insurance that users can enroll in voluntarily and can cover medical expenses not covered by public medical insurance. In this embodiment, unless otherwise specified, the insurance recommended to users is private insurance that covers the scope not covered by public medical insurance. Also, there are various types of insurance offered by insurance companies. For example, private insurance can be broadly classified into three fields: life insurance, property insurance, and medical insurance, and can be further classified in more detail according to the benefit recipients (insured objects, compensation objects) of each insurance. Also, there can be subtle differences in the insurance products and insurance services offered by insurance companies. The information processing system 100 in this embodiment recommends the type of insurance according to the type of risk the user has. For example, the types of insurance can include advanced medical insurance (cancer insurance, medical insurance, etc. including advanced medical special contracts), unemployment insurance, long-term care insurance, dementia insurance, etc. The insurance products and insurance services offered by insurance companies can be classified into any of these types of insurance. Note that the insurance products and insurance services offered by insurance companies can include combinations of two or more of these types of insurance. In the following, an example will be used to describe the output of the type of insurance that the user should enroll in as the insurance recommended by the information processing system 100, but it is not limited to this. For example, the information processing system 100 may output the insurance products and insurance services that the user should enroll in as the recommended insurance. In this embodiment, the type of insurance may sometimes simply be referred to as insurance.

[0012] The information processing system 100 is configured to include, for example, an information processing device 101 and a terminal 111. The information processing device 101 and the terminal 111 can be connected via a network 131. Further, the information processing system 100 can cooperate with one or more servers via the network 131. The servers that can cooperate with the information processing system 100 may include an insurance information server 121, a disease risk information server 122, a genetic information server 123, a statistical information server 124, a health examination information server 125, an app cooperation server 126, and the like. Note that the information processing system 100 may include all or part of the functions provided by these servers. Also, the information processing system 100 may cooperate with each server to implement all or part of the functions provided by each server.

[0013] Based on a request from the terminal 111, the information processing device 101 determines the insurance that the user should subscribe to and outputs it to the terminal 111. Further, the information processing device 101 can determine the timing when the user should subscribe to the insurance that the user is determined to subscribe to and output it to the terminal 111. The information processing device 101 can determine the insurance that the user should subscribe to and the timing when the user should subscribe to each insurance by cooperating with each server via the network 131. Details of the operation of the information processing device 101 will be described later.

[0014] The terminal 111 is a terminal device used for a user of the information processing system 100 to receive the provision of insurance recommendation information. The terminal 111 can be, for example, a personal computer (PC), a tablet terminal, a smartphone, a mobile phone terminal, or the like. The terminal 111 can be operated by an insurance company that recommends insurance to the user. That is, the terminal 111 can be used not only by the user but also by an operator other than the user to receive information about the user and output insurance recommendation information to the user. The information about the user is information necessary for the information processing device 101 to create insurance recommendation information. For example, the information about the user may be input based on a predetermined input format, or may be input by communicating with other servers or the like using the user's identifier. Note that the insurance company is, for example, an insurance agency.

[0015] The insurance information server 121 is a server that provides information on multiple types of insurance. The insurance information server 121 can provide information classified by type of insurance. Also, the insurance information server 121 may provide information on insurance products and insurance services provided by insurance companies. For example, the insurance information server 121 provides information related to each of a plurality of types of insurance including insurance (advanced medical insurance) in which a benefit is paid when the insured person receives advanced medical treatment, insurance (employment disability insurance) in which a benefit is paid when the insured person becomes unable to work for a long period due to illness or injury, insurance (long-term care insurance) in which a benefit is paid when the insured person is certified as being in need of long-term care, and insurance (dementia insurance) in which a benefit is paid when the insured person is certified as having dementia. The information managed by the insurance information server 121 may be information that has been pre-analyzed and classified and accumulated as common content of insurance products and insurance services belonging to each type of insurance, or may be information generated by analyzing the content of insurance products and insurance services belonging to each type of insurance using machine learning or the like. For example, the insurance information server 121 can provide information such as benefit details (such as in what cases and to what extent benefits are paid), type and cost of insurance (such as savings-type insurance or term insurance), and coverage period (such as term insurance or whole life insurance) as information associated with each type of insurance, insurance product, and insurance service.

[0016] In addition, the insurance information server 121 can provide information for identifying diseases that are eligible for benefits under each type of insurance. For example, the insurance information server 121 can provide information associating the risks that are eligible for benefits under each type of insurance with the information on the diseases that are the causes of those risks. As an example, in cancer insurance and medical insurance (hereinafter sometimes referred to as advanced medical insurance) that includes a special contract for advanced medical treatment, when the insured develops cancer and undergoes predetermined proton beam therapy, heavy ion beam therapy, intravenous administration therapy, gene panel testing, etc., benefits can be paid. That is, when a user undergoes advanced medical treatment such as predetermined proton beam therapy, heavy ion beam therapy, or intravenous administration therapy that is not covered by public medical insurance, the user can receive benefits. In addition, gene panel testing is a test for examining gene mutations in cancer tissue for hundreds of genes related to cancer and searching for therapeutic drugs corresponding to those gene mutations. However, it may be a self-pay test for reasons such as being covered by insurance only when the standard treatment is ineffective. Thus, in advanced medical insurance, the risks of having to undergo treatments and tests that are not covered by public medical insurance are the objects of insurance coverage, and the diseases that are the objects of those treatments and tests can be associated. Note that for cancer insurance, the required treatment methods and test methods vary depending on the type of cancer such as pharyngeal cancer, esophageal cancer, gastric cancer, breast cancer, etc. FIG. 2 shows an example of the association between the type of cancer and the required treatment methods and test methods. Thus, advanced medical insurance can be subdivided according to the treatment methods and test methods that are the objects of its benefits and the diseases that are the objects. The insurance information server 121 can manage information such as the objects of benefits in association with each of these subdivided types of insurance. For example, by subscribing to a type of insurance that covers the types of cancer with a high risk of occurrence, a user can reduce the burden of insurance premiums compared to the case of subscribing to general cancer insurance. An example of the diseases associated with advanced medical insurance is pharyngeal cancer, esophageal cancer, gastric cancer, breast cancer, etc. In addition, the insurance information server 121 can manage information on medical institutions where advanced medical treatment can be received and their evaluations in association with the type of insurance. For example, the insurance information server 121 can provide the information processing device 101 with information on medical institutions that can provide treatment for the corresponding diseases and their evaluations as information associated with advanced medical insurance.

[0017] As an example, in the case of employment insurance, benefits can be paid when the insured person develops a myocardial infarction, a stroke, etc., and is unable to return to work even after undergoing rehabilitation or the like after discharge. That is, employment insurance covers the risks of undergoing rehabilitation that requires a certain period of time and the risk of covering living expenses during that period, and diseases that are the causes of these risks can be associated with it. An example of a disease associated with employment insurance is myocardial infarction or stroke.

[0018] As an example, in the case of long-term care insurance, benefits can be paid when the insured person develops a myocardial infarction, a stroke, etc., and is certified as being in need of long-term care. That is, long-term care insurance covers the risks of becoming bedridden or living in a wheelchair, etc., and diseases that are the causes of these risks can be associated with it. An example of a disease associated with long-term care insurance is myocardial infarction or stroke.

[0019] As an example, in the case of dementia insurance, benefits can be paid when the insured person develops Alzheimer's disease, etc., and is certified as having dementia, or when damage occurs due to dementia. That is, dementia insurance covers the risks of developing dementia and the decline of brain function, memory, physical function, etc., and diseases that are the causes of these risks can be associated with it. An example of a disease associated with dementia insurance is Alzheimer's disease.

[0020] The disease risk information server 122 provides information on the correlation between genetic information and the onset of diseases. For example, the disease risk information server 122 may provide information associating mutations in a predetermined gene with the susceptibility to a predetermined disease. As an example, the disease risk information server 122 may provide that there are mutations in the BRCA1 gene or the BRCA2 gene as genetic information highly correlated with the onset of diseases such as ovarian cancer and breast cancer. Also, the disease risk information server 122 may provide that there is a mutation in the APOE gene as genetic information highly correlated with the onset of Alzheimer's disease. The APOE gene is an abbreviation for the gene that produces apolipoprotein E. Further, the disease risk information server 122 may associate multiple gene mutations with one disease. For example, regarding the correlation with the onset risk of stroke, when it can be stratified by a polygenic risk score (a method of predicting the onset risk of a disease by scoring hundreds of thousands of gene mutations that increase the onset risk of a specific disease possessed by an individual), the disease risk information server 122 may provide the user's polygenic risk score for the target disease instead of the presence or absence of genes. Note that the disease risk information server 122 may provide information obtained by processing the polygenic risk score instead of or in addition to the polygenic risk score. For example, the disease risk information server 122 may provide information such as which rank the user's polygenic risk score corresponds to from the highest risk in a predetermined population or the probability of developing a disease calculated from the polygenic risk score.

[0021] The genetic information server 123 manages the genetic information of users. The genetic information can be the results of genetic tests or information indicating the physical constitution of users obtained based on such results. For example, the genetic information can be obtained by a genotyping vendor analyzing the blood of a user collected at a hospital or the like. The genetic information server 123 can provide the genetic information of the user to the information processing device 101. Since the genetic information is highly confidential information, the genetic information server 123 can provide the genetic information of the user to the information processing device 101 based on the permission of the user. For example, when the genetic information server 123 is requested by the information processing device 101 to provide the genetic information of a specific user, it can communicate with the contact information of the pre-associated user to seek permission. As an example, the genetic information server 123 may notify an application installed on a terminal (not shown) owned by the user that there is a request for genetic information and seek permission for the provision. The genetic information server 123 may provide all of the genetic information of the user to the information processing device 101, or may provide only a predetermined range of genetic information to the information processing device 101. By providing only a predetermined range of genetic information to the information processing device 101, the risk of information leakage can be suppressed. For example, the genetic information server 123 can provide only the genetic information of the user related to genes highly correlated with a disease specified by the information processing device 101 to the information processing device 101.

[0022] The statistical information server 124 provides statistical information regarding the onset of a predetermined disease. For example, the statistical information server 124 can provide statistical information regarding the number of people who have developed a predetermined disease for each age, age group, a predetermined age range, etc. As an example, the statistical information server 124 can show the ratio of the number of people who have developed a disease within a predetermined age range to the total number of people who have developed the disease. Also, the statistical information server 124 can provide information obtained by aggregating the number of people who have developed a predetermined disease per unit number for each predetermined age range. Such statistical information can be obtained and provided through an epidemiological survey. Note that the integrated information server 124 can provide statistical information divided by gender. Since the age trends and probabilities of onset can vary significantly between men and women, more accurate information can be provided.

[0023] The health check information server 125 manages the biometric information (health check data) of the user obtained through a health check. The health check data is data indicating health problems, precautions, etc. that can be detected from the user's health condition, and can be generated based on information indicating the results of the user's health check. For example, in the health check data, in the data of the user's health check, data outside the range of standard values in the user's attributes (age, gender, etc.) can be identified as abnormal values. The health check information server 125 may manage and provide the information in the medical questionnaire submitted when the user undergoes a health check, included in the health check data. For example, since the information in the medical questionnaire may include the user's lifestyle habits (such as alcohol intake and smoking status), it can be used for estimating the probability of disease, similar to the abnormal values in the health check data. As an example, when there is data indicating that a user with a specific genotype of alcohol metabolism has a 189-fold increased probability of developing pharyngeal cancer due to drinking and smoking, the health check information server 125 can provide the user's medical questionnaire data on drinking and smoking as health check data associated with pharyngeal cancer. The health check information server 125 can provide the user's health check data to the information processing device 101. Since the user's health check data is highly confidential like genetic information, the health check information server 125 can provide the user's health check data to the information processing device 101 based on the user's permission. Note that the health check information server 125 may provide all of the user's health check data to the information processing device 101, or may provide only the predetermined health check data or abnormal values specified by the information processing device 101 to the information processing device. The health check information server 125 can provide only the user's health check data related to health check items highly correlated with the disease specified by the information processing device 101 to the information processing device 101.

[0024] The application cooperation server 126 manages the biometric information of the user obtained by the device carried by the user and provides it to the information processing device. For example, the device carried by the user may be a wearable device such as a watch-type measuring device like a smartwatch, a ring-type measuring device, an earphone-type measuring device, a clothing-type measuring device, etc. For example, the device carried by the user (hereinafter sometimes referred to as a wearable device) can transmit the biometric information of the user to the application cooperation server 126 using the communication function provided in the device itself. Also, the wearable device can transmit the biometric information of the user to the application cooperation server 126 via a device with a communication function such as a smartphone carried by the user. In this case, the wearable device cooperates with the application installed on the user's smartphone or the like, regularly provides the biometric information of the user measured by the device itself to the application, and the application can transmit the biometric information of the user to the application cooperation server 126 using the communication function of the smartphone or the like. When the device such as a smartphone carried by the user has data generation means such as a camera function, the wearable device may include the smartphone. For example, the application can measure the biometric information of the user using the sensor function (including data generation means such as a camera) of the smartphone and provide it to the application cooperation server 126. The application cooperation server 126 accumulates the biometric information of the user received from the wearable device. The application cooperation server 126 can provide the biometric information (monitoring data) of the user to the information processing device 101 in response to a request from the information processing device 101. The application cooperation server 126 may provide all of the biometric information of the user measured by the wearable device to the information processing device, or may provide only the predetermined monitoring data specified by the information processing device to the information processing device. Note that the application cooperation server 126 may be included in the user's smartphone. In this case, the monitoring data accumulated in the user's smartphone can be provided to the information processing device 101.

[0025] According to such a configuration, the information processing apparatus 101 can identify diseases that are risk factors for a risk covered by a predetermined insurance, estimate the probability of a user contracting each of the identified diseases during their lifetime based on the user's genetic information, and determine whether the user should subscribe to the insurance based on the presence or absence of diseases whose incidence probability exceeds a predetermined threshold. Then, when it is determined that the user should subscribe to the insurance, the information processing apparatus 101 can determine the time when the user should subscribe to the insurance based on the statistical information regarding the onset time of each disease whose incidence probability exceeds the predetermined threshold. In addition, the information processing apparatus 101 can further determine the time when the user should subscribe to the insurance based on the user's biological information. By executing such processing for each insurance to be determined, the information processing apparatus 101 can output to the user the insurance that the user should subscribe to and the time when the user should subscribe to each insurance. Hereinafter, the information processing system 100 of an embodiment having such an effect will be described in more detail.

[0026] (Device Configuration) FIG. 3 shows an example of the hardware configuration of the information processing apparatus 101. In one example, the information processing apparatus 101 includes a processor 301, a ROM 302, a RAM 303, a storage device 304, and a communication circuit 305. The processor 301 is a computer including one or more processing circuits such as a general-purpose CPU (Central Processing Unit) or an ASIC (Application Specific Integrated Circuit). The processor 301 reads and executes programs stored in the ROM 302 and the storage device 304 to execute the overall processing of the apparatus and each of the above-described processes. The ROM 302 is a read-only memory in which information such as programs and various parameters related to the processes executed by the information processing apparatus 101 are recorded. The RAM 303 functions as a workspace when the processor 301 executes a program and is a random access memory in which temporary information is recorded. The storage device 304 is configured by, for example, a removable external storage device or the like. The communication circuit 305 includes, for example, a circuit for communicating with other devices.

[0027] (Functional Configuration) FIG. 3 is a diagram showing a functional configuration example of the information processing apparatus 101. The information processing apparatus 101 includes, as its functions, for example, a disease identification unit 401, a morbidity probability estimation unit 402, an enrollment necessity determination unit 403, an enrollment timing determination unit 404, and an insurance recommendation information output unit 405. FIG. 3 shows the functional configuration of the information processing apparatus 101 according to the present embodiment, and for example, the general configuration of the information processing apparatus 101 is omitted. These functional units can be realized, for example, by the processor 301 executing programs stored in the ROM 302 and the storage device 304 and controlling the communication circuit 305 as necessary. However, the present invention is not limited thereto, and for example, dedicated hardware for realizing each function may be prepared.

[0028] The disease-specific part 401 associates each of one or more types of insurance with one or more diseases that are risk factors for the risks covered by that type of insurance. For example, the disease-specific part 401 obtains information regarding each type of insurance from the insurance information server 121 and identifies one or more diseases that are risk factors for the risks covered by each type of insurance. As an example, the types of insurance may include advanced medical insurance, employment disability insurance, long-term care insurance, dementia insurance, etc. Also, the types of insurance may include major disease protection insurance, specific injury insurance, physical disability protection insurance, etc. Furthermore, the types of insurance may include cancer insurance for women that can cover breast reconstruction surgery, types of insurance that can cover diseases prone to long hospital stays, treatment actual cost type cancer insurance that is also applicable when a cancer panel test (advanced medical treatment) is performed when suffering from cancer and the anticancer drugs that match the identified mutant genes are subject to out-of-pocket medical treatment, etc. And various cancers, etc. are associated with advanced medical insurance, cancer, myocardial infarction, stroke, etc. are associated with employment disability insurance, myocardial infarction, stroke, osteoporosis, Parkinson's disease, etc. are associated with long-term care insurance, Alzheimer's, etc. are associated with dementia insurance, cancer, myocardial infarction, stroke are associated with major disease protection insurance, osteoporosis, etc. are associated with specific injury insurance, glaucoma, hearing loss, rheumatoid arthritis, etc. are associated with physical disability protection insurance, breast cancer, etc. are associated with cancer insurance for women, schizophrenia, cerebral infarction, mood disorders, etc. are associated with types of insurance that can cover diseases prone to long hospital stays, respectively. The diseases associated with each insurance are not limited to the above. For example, the disease-specific part 401 obtains the risks covered by each type of insurance and identifies one or more diseases that are the risk factors for those risks for each type of insurance. In this case, the disease-specific part 401 pre-stores the diseases that can cause each risk and associates them with the obtained risks covered by insurance to associate the type of insurance with the disease. Also, the disease-specific part 401 can obtain from the insurance information server 121 the risks covered by each type of insurance and one or more diseases that are the risk factors for those risks from the insurance information server 121. In this case, the disease-specific part 401 can associate each type of insurance with one or more diseases based on the obtained information. Note that, as described above, one disease can be associated with multiple types of insurance.

[0029] The disease probability estimation unit 402 estimates the probability that the user will contract the disease identified by the disease identification unit 401 during their lifetime. For example, the disease probability estimation unit 402 can obtain the user's genetic information from the genetic information server 123 and estimate the probability of contracting the disease based on whether the user's genetic information contains mutations in genes that are highly correlated with the onset of the disease identified by the disease identification unit 401. Note that the disease probability estimation unit 402 can pre-obtain information on mutations in genes that are highly correlated with the onset of a predetermined disease from the disease risk information server 122 and estimate the probability of contracting the disease based on whether the user's genetic information contains such mutations in the gene.

[0030] The insurance enrollment necessity determination unit 403 determines whether the user should enroll in a predetermined insurance by comparing the probability of contracting each disease estimated by the disease probability estimation unit 402 with a predetermined threshold. The predetermined threshold may vary for each disease or may be the same for all diseases. By using different thresholds for each disease, it is possible to make a determination considering the impact (such as mortality rate, severity of health problems, etc.) on the user when each disease develops. For example, when there is one or more diseases with a probability of contracting higher than the predetermined threshold, the insurance enrollment necessity determination unit 403 may determine that the user should enroll in the insurance associated with that disease. The insurance enrollment necessity determination unit 403 may also determine that the user should enroll in the insurance associated with that disease when the number of diseases with a probability of contracting higher than the predetermined threshold is equal to or greater than a predetermined threshold. Note that when one disease is associated with multiple types of insurance, if the probability of contracting that disease exceeds the predetermined threshold, multiple types of insurance may be determined as the insurance that should be enrolled in. The insurance enrollment necessity determination unit 403 can output one or more types of insurance determined as the insurance that should be enrolled in.

[0031] When the necessity determination unit 403 determines that the user should subscribe to a predetermined insurance, the subscription timing determination unit 404 determines the timing when the user should subscribe to the predetermined insurance based on the statistical information regarding the disease that was the factor in that determination. For example, the subscription timing determination unit 404 acquires statistical information regarding the onset of the disease from the statistical information server 124. As an example, the subscription timing determination unit 404 acquires from the statistical information server 124 statistical information in which the number of people who developed the disease is tabulated for each age, age group, or range of a predetermined age. Then, the subscription timing determination unit 404 identifies the age at which the cumulative number of people who developed the disease exceeds a predetermined threshold. The subscription timing determination unit 404 may identify the age at which the ratio of the cumulative number of people who developed the disease to the total number of people who developed the disease exceeds a predetermined threshold. The subscription timing determination unit 404 determines the age calculated based on the identified age as the timing when the user should subscribe to the insurance. As an example, the subscription timing determination unit 404 may output, as the timing when the user should subscribe to the insurance, the age at which the cumulative number of people who developed the disease, or the ratio of the cumulative number of people who developed the disease to the total number of people who developed the disease, exceeds a predetermined threshold. Also, the subscription timing determination unit 404 may output, as the timing when the user should subscribe to the insurance, the age obtained by adding or subtracting a predetermined fixed value to or from those ages. For example, if the age at which the likelihood of developing a predetermined disease increases (the cumulative number of people who developed the disease exceeds a predetermined threshold) is 50 years old, and the user's age at the time of determination is 30 years old, the user has a low need to immediately subscribe to the insurance, and rather, the period for paying the insurance premium may be longer. On the other hand, if the recommended subscription timing for the user is set at 50 years old, there is a risk that the user will develop the disease by then. Therefore, the subscription timing determination unit 404 may recommend to the user a timing that is a predetermined period earlier than the age at which the likelihood of developing a predetermined disease increases. Also, as will be described later, depending on the user's health condition, the risk of developing a disease may increase or decrease. Therefore, the subscription timing determination unit 404 may output, as the timing when the user should subscribe to the insurance, the age obtained by making a predetermined adjustment based on the age determined based on the statistical information. As an example, the subscription timing determination unit 404 may make a predetermined adjustment based on the biometric information of the user acquired from the health examination information server 125 or the application cooperation server 126.For example, when the abnormal value in the user's biometric information is within the range of values that are evaluated to have a high probability of the onset of the disease, the enrollment timing determination unit 404 can adjust the timing for the user to enroll in the insurance to be earlier. Also, when there is no abnormal value in items correlated with the onset of the disease, the enrollment timing determination unit 404 can adjust the timing for the user to enroll in the insurance to be later.

[0032] Based on the respective determination results of the insurance recommendation information output unit 405, the enrollment necessity determination unit 403, and the enrollment timing determination unit 404, one or more types of insurance that the user should enroll in and the timing for enrolling in each type of insurance are output. Note that when the type of insurance that the user should enroll in is advanced medical insurance, the insurance recommendation information output unit 405 may provide information on medical institutions that can perform advanced medical treatment for diseases with a high probability of the user being affected. For example, the information on medical institutions that can perform advanced medical treatment can be provided by the insurance information server 121.

[0033] (Processing flow) FIG. 5 shows an example of a flow of operations when the information processing apparatus 101 in the present embodiment determines the types of insurance that the user should subscribe to and determines the timing when the user should subscribe to each type of insurance. The information processing apparatus 101 can start this process when there is a request from the user or the operator via the terminal 111. First, the information processing apparatus 101 acquires the types of insurance to be determined and identifies one or more diseases that are risk factors for the risks covered by each type of insurance (S501). For example, the information processing apparatus 101 acquires information regarding a predetermined type of insurance to be determined from the insurance information server 121. The predetermined type of insurance to be determined may be all types of insurance recorded in the insurance information server 121, or may be a type of insurance designated by the user, the operator, or the like. Also, in the information processing apparatus 101, the types of insurance to be determined may be preset in advance. For example, the types of insurance to be determined may include advanced medical insurance, employment disability insurance, dementia insurance, long-term care insurance, and the like. Then, the information processing apparatus 101 identifies one or more diseases that are risk factors for the risks covered by each type of insurance to be determined. For example, the information processing apparatus 101 can identify diseases based on the information associated with each type of insurance acquired from the insurance information server 121 and the benefit contents associated with the insurance products and insurance services belonging thereto. For example, in cancer insurance, which is a type of advanced medical insurance, when a benefit is paid based on the insured having received advanced medical treatment such as proton beam therapy, heavy ion beam therapy, or intravenous administration therapy for the treatment of cancer, cancer can be a disease to be identified. Also, in employment disability insurance, when a benefit is paid based on the insured having suffered a myocardial infarction or a stroke and being unable to work for a period exceeding a predetermined period, myocardial infarction and stroke can be diseases to be identified. Note that in long-term care insurance, when a benefit is paid based on the insured having suffered a myocardial infarction or a stroke and having been certified as requiring long-term care, myocardial infarction and stroke can be diseases to be identified. Furthermore, in dementia insurance, when a benefit is paid based on the onset of Alzheimer's disease and the insured having been certified as having dementia, Alzheimer's disease can be a disease to be identified. Each type of insurance to be determined is not limited to these types of insurance.In addition, when associating insurance types with diseases, when using the benefit details of insurance products and insurance services belonging to that insurance type, there may be multiple insurance products and insurance services used. In this case, the diseases associated with each of the multiple insurance products and insurance services belonging to the same insurance type may be different. Also, in multiple insurance types, some of the diseases associated with them may be the same. In other words, multiple types of insurance may be associated with one disease. In this way, the information processing apparatus 101 can reduce the number of diseases to be analyzed in subsequent processing by specifying one or more corresponding diseases for each insurance type to be determined. As a result, the information processing apparatus 101 does not need to analyze diseases that are not covered by insurance or genetic information highly correlated with the onset of those diseases, and thus can determine the insurance that the user should subscribe to and the timing for such subscription in a short time.

[0034] Subsequently, the information processing apparatus 101 identifies the probability that the user has each of the identified diseases (S502). For example, the information processing apparatus 101 can identify the probability of contracting each disease based on the user's genetic information. The probability of contracting a disease is, for example, the probability that the user will develop the disease during their lifetime. As an example, the information processing apparatus 101 obtains information regarding mutations of genes that are highly correlated with the onset of the identified disease from the disease risk information server 122. Further, the information processing apparatus 101 obtains the user's genetic information from the genetic information server 123. Note that the information processing apparatus 101 can obtain only the user's genetic information corresponding to mutations of genes that are highly correlated with the onset of the identified disease. By restricting the information obtained by the information processing apparatus 101 from the genetic information server 123, it is possible to avoid handling the user's personal information that does not need to be exchanged between devices. Then, the information processing apparatus 101 estimates the probability that the user will develop the disease based on whether there is a mutation of a gene that is highly correlated with the onset of the identified disease in the user's genetic information. For example, the information processing apparatus 101 can calculate the probability of contracting the disease by multiplying the ratio of the number of people who have contracted the disease in the entire population within a predetermined range by the relative probability of contracting the disease based on the genetic information. For example, the information processing apparatus 101 can use the number of people having the mutation of the gene among the total number of people who have developed the disease as the probability of contracting the disease. The method for calculating the probability of contracting a disease is not limited to these methods. Also, among the diseases, there may be those that are correlated with mutations of multiple genes. In this case, the information processing apparatus 101 can determine the probability of contracting the disease based on the presence or absence of mutations of each gene. For example, a weight coefficient can be assigned to each gene mutation, and the probability of contracting the disease can be calculated based on the total value where 1 is used when there is a gene mutation and 0 is used when there is no gene mutation.

[0035] Subsequently, the information processing apparatus 101 identifies the types of insurance that the user should subscribe to (S503). For example, for each identified disease, the information processing apparatus 101 compares the user's probability of contracting the disease with a predetermined threshold. If there is a disease with a probability of contracting that exceeds the predetermined threshold (YES in S503), the insurance associated with that disease is identified as the insurance that the user should subscribe to (S504). On the other hand, if the probability of contracting any disease does not exceed the predetermined threshold (NO in S503), the information processing apparatus 101 may output that there is no insurance that the user should subscribe to (S507). The predetermined threshold may be common for all diseases or may vary for each disease. For example, among diseases, there may be some for which a certain correlation with a mutation of a predetermined gene is confirmed, but the probability of contracting is calculated to be lower compared to other diseases. Based on such differences in the probability of contracting between diseases, a predetermined threshold may be set. For example, in a population within a predetermined range, if there is a first disease with a probability of contracting of 50% and a second disease with a probability of contracting of 20%, and if the probability of contracting the first disease when having a mutation of the first gene is 70% and the probability of contracting the second disease when having a mutation of the second gene is 40%, the threshold for the first disease may be set to 60% and the threshold for the second disease may be set to 30%. Also, depending on the method of calculating the probability of contracting, the probability of contracting may be different even for the same disease. For example, the probability of contracting may be different depending on whether the population is a population within a predetermined range or the number of people who have developed the disease within that population. Based on such differences in the method of calculating the probability of contracting, a predetermined threshold may be set. Furthermore, among diseases, there may be some with a low probability of contracting but a large impact on the user if they develop. For example, if the user develops myocardial infarction or stroke, it may be necessary to secure living expenses and nursing care expenses over a long period. By setting a low predetermined threshold for such diseases, it may be possible to surely recommend insurance subscription to the user. Also, the information processing apparatus 101 may determine whether the user should subscribe to a predetermined insurance based on the presence or absence of a mutation of a predetermined gene. For example, when there is statistical information that the probability of contracting Alzheimer's is 10 times higher when having a mutation of the APOE gene, the information processing apparatus 101 checks whether the user has a mutation of the APOE gene.And, when the user has a gene mutation of APOE, the information processing apparatus 101 may determine that the user should subscribe to dementia insurance. Note that when the information processing apparatus 101 can obtain the polygenic risk score of the user for a predetermined disease from the disease risk information server 122, it can determine the possibility that the user suffers from the disease based on the obtained polygenic risk score, and determine whether the user should subscribe to insurance. For example, when the polygenic risk score is greater than a predetermined threshold associated with the disease, the information processing apparatus 101 may determine that the user has a high possibility of suffering from the disease and should subscribe to insurance. Further, when the information processing apparatus 101 can obtain information obtained by processing the polygenic risk score from the disease risk information server 122, it can determine whether the user should subscribe to insurance based on the information.

[0036] Subsequently, for each insurance that the information processing apparatus 101 determines that the user should subscribe to, it determines the timing when the user should subscribe (S505). For example, the information processing apparatus 101 acquires statistical information regarding the onset of diseases from the statistical information server 124. The information processing apparatus 101 may acquire statistical information on diseases determined in S503 that the user's probability of contracting exceeds a predetermined threshold, or diseases determined to have a high likelihood of contracting based on gene mutations possessed by the user. For example, the statistical information may be statistical information obtained by aggregating the number of people who have developed the disease for each age, age group, or a predetermined age range. The information processing apparatus 101 can identify the age at which the cumulative number of people who have developed the disease exceeds a predetermined threshold, or the age at which the ratio of the cumulative number of people who have developed the disease to the total number of people who have developed the disease exceeds a predetermined threshold, as the age at which the probability of the disease developing is high. Then, based on the identified age, the information processing apparatus 101 can determine the timing when the user should subscribe to the insurance. For example, the information processing apparatus 101 can determine the age at which the probability of the disease developing is high as the timing when the user should subscribe to the insurance. FIG. 6 shows an example of statistics obtained by aggregating the age of onset of a predetermined disease A every five years. The horizontal axis in FIG. 6 indicates the age at which the disease A has developed, and the vertical axis indicates the number of people who have developed the disease per 100,000 population. For example, if a predetermined threshold is set to 100 people (cumulative) per 100,000 population, the cumulative number of people exceeds the predetermined threshold at the age of 55 - 59 years. In this case, the information processing apparatus 101 can determine that the user should subscribe to the insurance by the age of 55, which is the lower limit of this age range. Further, the information processing apparatus 101 can determine the timing when the user should subscribe to the insurance by applying the age at which the probability of the disease developing is high to a predetermined calculation formula. For example, the information processing apparatus 101 can determine the age obtained by adding or subtracting a predetermined fixed value from the age at which the probability of the disease developing is high as the timing when the user should subscribe to the insurance. The statistical information can be aggregated based on parameters regarding the user's attributes (such as gender) other than age. For example, it may be aggregated for each gender. Generally, the age of onset and the probability of contracting a predetermined disease may differ between men and women. Also, the statistical information may be aggregated for each ethnicity. The age of onset and the probability of contracting a predetermined disease may differ between ethnicities. By aggregating for each gender and ethnicity, more accurate determination based on the user's attributes can be performed.

[0037] The information processing device 101 may adjust the timing when the user should subscribe to insurance based on the user's biological information. The biological information can be information emitted by a living body such as body temperature, blood pressure, heart rate, electromyogram, electroencephalogram, blood volume, etc. For example, when determining the timing when the user should subscribe to insurance based on the statistical information of the age at which a disease occurred as described above, the user's health condition at the time of determination is not considered. On the other hand, among diseases, there are some for which the risk of onset can be estimated based on the user's biological information. For example, in the case of a stroke mentioned above, the risk of onset can be detected by measuring the presence or absence of an abnormal heart rate or an irregular disturbance of the heart rate (atrial fibrillation). The user can measure the heart rate and atrial fibrillation by undergoing a medical check-up. For example, when the user's medical examination data is managed in the medical examination information server 125, the information processing device 101 can obtain information on the user's heart rate and atrial fibrillation from the medical examination information server 125, and based on the abnormal values in the heart rate and the presence or absence of atrial fibrillation, adjust the timing when the user should subscribe to insurance. For example, the information processing device 101 can determine that the user should subscribe to insurance promptly based on the presence of abnormal values in the heart rate or atrial fibrillation.

[0038] On the other hand, among diseases, there are some for which the risk of onset cannot be accurately detected by a medical check-up. For example, the heart rate and atrial fibrillation for detecting the risk of a stroke may not be detected by short-term measurement in some cases. As an example, in the case of asymptomatic or paroxysmal atrial fibrillation, it may not be detected by short-term measurement. In this case, the user can detect atrial fibrillation by observing changes in blood volume using an optical sensor provided in a wearable device. Such a measurement method can be called a photoplethysmograph (PPG). When the biological information measured by the user using a wearable device is managed in the app cooperation server 126, the information processing device 101 can obtain information on the user's heart rate and atrial fibrillation from the app cooperation server 126, and based on the abnormal values in the heart rate and the presence or absence of atrial fibrillation, adjust the timing when the user should subscribe to insurance. For example, the information processing device 101 can determine that the user should subscribe to insurance promptly based on the presence of abnormal values in the heart rate or atrial fibrillation.

[0039] In general, among diseases, there are those strongly influenced by genetic information and those strongly influenced by lifestyle habits. For example, in diseases such as ovarian cancer and breast cancer, there is a high correlation with mutations in the BRCA1 gene and BRCA2 gene, and there is statistical information indicating a low correlation with lifestyle habits. In such cases, for diseases with a high correlation with such genetic information, the information processing device 101 may not adjust the enrollment timing based on biometric information, and may only execute the adjustment of the enrollment timing based on biometric information for diseases with a higher correlation with lifestyle habits than genetic information. Thereby, while avoiding handling the user's personal information more than necessary, it is possible to maintain the determination accuracy of the timing when the user should enroll in the recommended insurance. For example, based on the statistical information, the information processing device 101 may quantify the degree of correlation with genetic information or the degree of correlation with lifestyle habits in each disease, and when the degree of correlation with genetic information exceeds a threshold value, it may determine not to adjust the enrollment timing.

[0040] The information processing device 101 outputs the insurance that the user should enroll in and the timing when the user should enroll (S506). For example, the information processing device 101 may output insurance recommendation information composed of the type of insurance determined in S504 that the user should enroll in and the timing when the user should enroll in each type of insurance determined in S505. The insurance recommendation information output by the information processing device 101 is notified to the terminal 111 via the network 131 and can be displayed on the display device possessed by the terminal 111. The display device can be a display, a printer, or the like.

[0041] As described above, according to this embodiment, the information processing apparatus 101 identifies diseases that are risk factors for risks covered by a predetermined insurance, estimates for each of the identified diseases the probability of the user contracting them during their lifetime based on the user's genetic information, and determines whether the user should subscribe to the insurance based on the presence or absence of diseases whose incidence probability exceeds a predetermined threshold. Then, the information processing apparatus 101 determines the timing when the user should subscribe to the insurance based on statistical information regarding the onset timing of each of the diseases whose incidence probability exceeds a predetermined threshold and the user's biological information. As a result, the user can select the insurance to which they should subscribe according to their health risks, and by subscribing to the insurance by the age when the probability of the disease that is the risk factor for those risks increases, it becomes possible to efficiently transfer the risks during the unhealthy period.

[0042] The invention is not limited to the above-described embodiment, and various modifications and changes are possible within the scope of the gist of the invention.

Explanation of Reference Numerals

[0043] 101: Information processing apparatus, 111: Terminal, 121: Insurance information server, 122: Disease risk information server, 123: Genetic information server, 124: Statistical information server, 125: Health examination information server, 126: Application cooperation server, 131: Network

Claims

1. specific means for identifying one or more diseases that are risk factors for the risks covered by a predetermined insurance; estimating means for estimating, based on the genetic information of the user, the probability of the user developing each of the diseases identified by the specific means during their lifetime; first determination means for determining whether the user should subscribe to the predetermined insurance based on whether there is a disease whose incidence probability exceeds a predetermined threshold; second determination means for determining the subscription time when the user should subscribe to the predetermined insurance based on statistical information regarding the onset time of the disease whose incidence probability exceeds a predetermined threshold when it is determined by the subscription determination that the user should subscribe to the predetermined insurance; output means for outputting the determined subscription time to the user, and having an information processing apparatus characterized by the above.

2. The second determination means makes the determination of the subscription time based further on the biological information of the user. The information processing apparatus according to claim 1, characterized by the above.

3. The information processing apparatus according to claim 2, wherein the biological information is the biological information of the user measured in a health check.

4. The information processing apparatus according to claim 2, wherein the biological information is the biological information of the user measured by a device carried by the user.

5. When, in the subscription determination, it is determined that the user should subscribe to the predetermined insurance and there are two or more diseases whose incidence probabilities exceed the predetermined threshold, the second determination means determines a first subscription time when the user should subscribe to the predetermined insurance based on statistical information regarding the onset time of a first disease included in the two or more diseases, determines a second subscription time when the user should subscribe to the predetermined insurance based on statistical information regarding the onset time of a second disease different from the first disease included in the two or more diseases, and when the first subscription time is earlier than the second subscription time, determines the first subscription time as the subscription time when the user should subscribe to the predetermined insurance. The information processing apparatus according to claim 1, characterized by the above.

6. The information processing apparatus according to claim 1, wherein the predetermined insurance is an insurance associated with any one of advanced medical treatment, inability to work, nursing care, or dementia.

7. An information processing method executed by an information processing apparatus, comprising: a specific step of identifying one or more diseases that are risk factors for the risks covered by a predetermined insurance; An estimation step of estimating, based on the genetic information of the user, the probability of the user suffering from each of the diseases specified by the specific process throughout their life; A first determination step of performing an enrollment determination as to whether the user should enroll in the predetermined insurance based on the presence or absence of a disease whose incidence probability exceeds a predetermined threshold; When it is determined by the enrollment determination that the user should enroll in the predetermined insurance, a second determination step of determining the enrollment time when the user should enroll in the predetermined insurance based on statistical information regarding the onset time of a disease whose incidence probability exceeds a predetermined threshold; An output step of outputting the enrollment time, which is the result of the determination, to the user, and having An information processing method characterized by this.

8. In a computer included in an information processing apparatus, Cause one or more diseases that are risk factors for risks covered by a predetermined insurance to be specified; Cause the probability of the user suffering from each of the specified diseases throughout their life to be estimated based on the genetic information of the user; Cause an enrollment determination to be made as to whether the user should enroll in the predetermined insurance based on the presence or absence of a disease whose incidence probability exceeds a predetermined threshold; When it is determined by the enrollment determination that the user should enroll in the predetermined insurance, cause a determination of the enrollment time when the user should enroll in the predetermined insurance to be made based on statistical information regarding the onset time of a disease whose incidence probability exceeds a predetermined threshold; Cause the enrollment time, which is the result of the determination, to be output to the user A program for this.

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