JP2017117393A - Calculation device, calculation method and calculation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide proper information related to a future design.SOLUTION: A calculation device related to the present application comprises an acquisition part and a calculation part. The acquisition part acquires risk information which indicates a risk related to a wellness of a user. The calculation part calculates a medical expense in the future which is assumed to the user based on medical expense information which indicates a medical expense corresponding to the risk information, and a degree of a risk which is indicated by the risk information acquired by the acquisition part. For example, the calculation part uses the medical expense information which indicates a preset medical expense for every kind of a disease, for calculating the medical expense in the future which is assumed to the user.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a calculation device, a calculation method, and a calculation program.

  There is a service that introduces asset management methods suitable for users or introduces insurance products suitable for users by analyzing information related to users regarding individual asset management and insurance.

  As an example of a technique related to such a service, a technique related to a system that determines a user's disease risk based on information such as calories consumed by the user and introduces medical insurance products according to the determination result is known. .

JP 2014-132402 A

  However, it is difficult to provide appropriate information regarding the future design with the above-described conventional technology. For example, in the above-described conventional technology, the user can only receive an introduction of insurance products according to the risk. For this reason, users may not be able to plan for future asset formation, such as how much medical expenses should be provided or whether they should be allocated to investment rather than as medical expenses. .

  The present application has been made in view of the above, and an object thereof is to provide a calculation device, a calculation method, and a calculation program capable of providing appropriate information regarding future design.

  The calculation device according to the present application includes an acquisition unit that acquires risk information that is information indicating a risk related to a user's health, medical cost information that indicates a medical cost corresponding to the risk information, and risk information acquired by the acquisition unit. And a calculation unit that calculates a future medical cost assumed for the user based on the degree of risk indicated by.

  According to one aspect of the embodiment, there is an effect that it is possible to provide appropriate information regarding the future design.

FIG. 1 is a diagram illustrating an example of a calculation process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the calculation apparatus according to the embodiment. FIG. 3 is a diagram illustrating an example of a genetic test result table according to the embodiment. FIG. 4 is a diagram illustrating an example of a medical cost information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of the definition information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of notification processing according to the embodiment. FIG. 7 is a flowchart illustrating a processing procedure according to the embodiment. FIG. 8 is a diagram illustrating an example of calculation processing according to the modification. FIG. 9 is a diagram illustrating a configuration example of a calculation apparatus according to a modification. FIG. 10 is a diagram illustrating an example of a user behavior table according to the modification. FIG. 11 is a diagram illustrating an example of a medical cost information storage unit according to the modification. FIG. 12 is a diagram illustrating an example of a lifestyle table according to the modification. FIG. 13 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the calculation apparatus.

  Hereinafter, a mode for carrying out a calculation device, a calculation method, and a calculation program according to the present application (hereinafter referred to as “embodiment”) will be described in detail with reference to the drawings. Note that the calculation device, the calculation method, and the calculation program according to the present application are not limited by this embodiment. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description is omitted.

[1. Example of calculation process)
First, an example of calculation processing according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a calculation process according to the embodiment. In FIG. 1, an example of a calculation process according to the present application will be described using the calculation system 1 as an example. Specifically, in FIG. 1, the calculation device 100 that is a server device included in the calculation system 1 calculates a future medical cost assumed for the user, and relates to the user's behavior based on the calculated medical cost. An example of processing for generating proposal information that is information including a proposal will be described.

  As shown in FIG. 1, the calculation system 1 includes a user terminal 10 and a calculation device 100. Each device included in the calculation system 1 is connected to be communicable with each other via a communication network (not shown) (for example, the Internet). The number of devices included in the calculation system 1 is not limited to the example illustrated in FIG. For example, the calculation system 1 may include a plurality of user terminals 10.

  The user terminal 10 is an information processing device used by a user. Specifically, the user terminal 10 is used for transmitting predetermined information to the calculation device 100 and receiving information transmitted from the calculation device 100. The user terminal 10 is realized by, for example, a mobile terminal such as a smartphone, a tablet terminal, or a PDA (Personal Digital Assistant), a desktop PC (Personal Computer), a notebook PC, or the like. In the example of FIG. 1, the user terminal 10 is assumed to be a smartphone used by the user U01. In the following description, the user terminal 10 may be referred to as a user U01. That is, in the following, the user U01 can be read as the user terminal 10.

  The calculation device 100 is a server device that generates a proposal (recommendation) for an action that the user U01 can take based on information received from the user terminal 10 and provides the generated proposal to the user U01. Specifically, the calculation device 100 acquires risk information that is information transmitted from the user terminal 10 and indicates information indicating a risk that the user U01 develops some disease. And the calculation apparatus 100 calculates the future medical expenses assumed with respect to the user U01 based on the acquired risk information and the medical expenses data corresponding to the risk information. Subsequently, the calculation apparatus 100 generates proposal information that is information including a proposal for the user U01 based on the calculated future medical expenses.

  The calculation apparatus 100 generates a proposal regarding an action that the user U01 can take in the future in order to cover an expected future medical cost as a proposal included in the proposal information. For example, the calculation device 100 may purchase insurance in advance when the user U01 is highly likely to develop a specific disease and the amount required as medical expenses for the specific disease is high, Generate proposals that recommend actions such as saving the required amount. As described above, the calculation apparatus 100 can provide the user U01 with information on the future design by giving the user U01 a certain guideline regarding provision of future medical expenses with high uncertain factors. Hereinafter, the calculation process by the calculation apparatus 100 will be described along the flow with reference to FIG.

  In the calculation process according to the present application, the user U01 provides risk information acquired by the user U01 in advance to the calculation apparatus 100. In the example illustrated in FIG. 1, the user terminal 10 transmits, as an example of risk information, the result of the genetic test that the user U01 has previously consulted to the calculation device 100 (step S11). In the genetic test, a type of disease that is likely to develop by the user U01 and a risk value that is a numerical value indicating the possibility of developing for each type of disease are shown. In the example of FIG. 1, the genetic test result of the user U01 indicates that the risk value for developing “diabetes” is “1.7” and the risk value for developing “hypertension” is “2.9”. Including. If the risk value corresponding to the type of the disease exceeds “2.0” in the genetic test result that the user U01 consulted, the possibility of developing the disease is determined to be “high”. . This means that the risk of developing the disease is high, that is, the probability of developing it is high. Further, in the genetic test result, when the risk value is between “1.5” and “2.0”, the possibility of developing the disease is determined as “medium”. This means that the risk of developing the disease is moderate and not as high as the disease determined to be “high” risk, but the probability of developing the disease is relatively high.

  The calculation device 100 receives the genetic test result transmitted from the user terminal 10 and stores it in the genetic test result table 122. In addition, the calculation apparatus 100 acquires medical cost information corresponding to the risk information in order to calculate the medical cost assumed for the user U01. For example, the calculation apparatus 100 acquires medical cost information by referring to statistical information on medical costs for each disease published by a public institution or accessing a predetermined medical cost database. The calculation apparatus 100 stores the acquired information related to medical costs in the medical cost information storage unit 125.

  And the calculation apparatus 100 calculates the medical expenses assumed with respect to the user U01 based on the acquired information (step S12). For example, the calculation device 100 corresponds to a disease having a relatively high risk of developing the user U01 (for example, a disease determined as a risk “high” or a risk “medium”) among the risk information transmitted from the user terminal 10. The amount of medical expenses to be calculated is calculated.

  In the example of FIG. 1, the calculation apparatus 100 extracts “diabetes” and “hypertension” from the genetic test results as diseases with a relatively high possibility that the user U01 will develop. Subsequently, the calculation apparatus 100 refers to how much medical expenses are required for each disease of “diabetes” and “hypertension” from the acquired medical expenses information. In the example of FIG. 1, the calculation apparatus 100 refers to the fact that a user having a “diabetes” disease needs a medical fee of “24,000 yen” per month on average. In addition, the calculation apparatus 100 refers to the fact that a user with a “high blood pressure” disease needs an average medical cost of “16000 yen” per month.

  Therefore, the calculation device 100 is necessary for each of “diabetes” and “hypertension” as a future medical cost for the user U01 who has a relatively high risk of developing “diabetes” and “hypertension”. Calculate the total amount of medical expenses. In the example of FIG. 1, the calculation apparatus 100 calculates a monthly fee of 40000 yen, which is a total amount of a monthly fee of 24,000 yen and a monthly fee of 16000 yen, as a medical cost assumed for the user U01. In the example of FIG. 1, only two types of diseases with a high risk of developing the user U01 are listed for explanation. However, the calculation device 100 has other diseases with a relatively high risk of developing the user U01. If so, add up the medical expenses for the disease.

  Subsequently, the calculation device 100 generates proposal information for the user U01 based on the calculated medical expenses (step S13). The calculation apparatus 100 generates proposal information for the user U01 according to the amount of medical expenses assumed for the user U01 in the future and the degree of risk of developing each disease. As will be described in detail later, the calculation apparatus 100 accepts the setting of the action definition proposed to the user in advance according to the medical cost and the degree of risk corresponding to the medical cost. Generate proposal information. For example, when the assumed medical cost is relatively high and the risk of developing a disease corresponding to the medical cost is high, the calculation device 100 follows the contents defined according to the situation. Proposal information about user behavior is generated. Specifically, in the case of the above situation, the calculation device 100 recommends enrollment in insurance corresponding to a disease or saves for the future from the present time so that necessary medical expenses can be surely secured. Or suggest. Alternatively, even if the calculated medical cost is relatively high, the calculation device 100 is not limited to saving, as long as it has a moderate risk of developing the disease. Proposal information including such a proposal may be generated.

  Proposal information generated by the calculation device 100 includes user U01, such as the above-mentioned proposal to the action related to the asset of the user U01, the estimated amount of medical expenses calculated by the calculation device 100, and the determination of the degree of disease risk. Consists of multiple communication items. In the example of FIG. 1, the calculation apparatus 100 includes information indicating that the amount of medical expenses that the user U01 is expected to need in the future is “24,000 yen + 16000 yen” as one piece of information included in the proposal information. Generate. Further, the calculation device 100 generates a proposal that recommends that the cost of hypertension is “high” as a proposal to the user U01 included in the proposal information, and that the cost is saved and secured from now on. In addition, the calculation device 100 generates a proposal that recommends investing for the future when the risk of diabetes is “medium”. Then, the calculation device 100 transmits to the user terminal 10 proposal information including the calculated amount of medical expenses and a proposal to the user U01. In other words, the calculation device 100 notifies the user U01 of the proposal generated by itself (step S14). By referring to the proposal displayed on the user terminal 10, the user U01 can confirm the medical expenses required in the future, and can obtain a guideline for actions that can be taken to secure the medical expenses. .

  As described above, the calculation device 100 according to the embodiment acquires a genetic test result that is information indicating a risk related to the health of the user U01. Then, the calculation device 100 calculates a future medical cost assumed for the user U01 based on medical cost information indicating the medical cost corresponding to the genetic test result and the degree of risk indicated by the genetic test result. . Furthermore, the calculation device 100 generates proposal information including a proposal regarding the action of the user U01 based on the calculated future medical expenses.

  As described above, the calculation device 100 according to the embodiment uses the genetic test result acquired from the user U01 and the medical cost information corresponding to the genetic test result to accurately calculate the medical cost expected in the future of the user U01. Can be calculated. Furthermore, the calculation apparatus 100 can present a certain guideline regarding the future design of the user U01 by generating a proposal for the user U01 based on the calculated medical cost and the degree of risk. Therefore, according to the calculation device 100, the user U01 can accurately grasp the action to be taken by the user U01 with respect to an uncertain element such as medical expenses in the future design. Specifically, the user U01 refrains from joining insurance for low-risk diseases, or actively purchases insurance for high-risk diseases, or saves medical expenses that may be required in advance. Various measures can be taken. Thus, the calculation apparatus 100 can provide the user U01 with appropriate information regarding the future design.

[2. Configuration of calculation device]
Next, the configuration of the calculation apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the calculation apparatus 100 according to the embodiment. As illustrated in FIG. 2, the calculation device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The calculation device 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator who uses the calculation device 100, and an output unit (for example, a liquid crystal display) for outputting various types of information. You may have.

(About the communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to a communication network by wire or wirelessly and transmits / receives information to / from the user terminal 10 via the communication network.

(About the storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 according to the embodiment includes a risk information storage unit 121, a medical cost information storage unit 125, and a definition information storage unit 127. Hereinafter, each storage unit will be described in order.

(Risk information storage unit 121)
The risk information storage unit 121 stores risk information indicating a risk related to the user. In the embodiment, the risk information storage unit 121 includes a genetic test result table 122 as one of data tables that store risk information.

(Regarding the genetic test result table 122)
The genetic test result table 122 stores information on the genetic test result. Here, FIG. 3 shows an example of the genetic test result table 122 according to the embodiment. As illustrated in FIG. 3, the genetic test result table 122 includes items such as “user ID”, “analysis item”, “risk value”, and “risk degree”.

  “User ID” indicates identification information for identifying a user. In the embodiment, it is assumed that the user ID is common with a reference symbol used in the description. For example, a user whose user ID is “U01” indicates “user U01”.

  “Analysis item” indicates an item to be analyzed in the genetic test. For example, the item to be analyzed is indicated using a disease name or the like. “Risk value” indicates a value obtained by quantifying the risk of developing a disease corresponding to an analysis item.

  The “risk degree” indicates a result of determining the risk of developing a disease based on the risk value. In the embodiment, it is assumed that an analysis item having a risk value lower than “1.5” is determined to have a risk level of “low”. This indicates that the risk that the user develops a disease corresponding to the analysis item is lower than the risk degree “high” or “medium”. An analysis item having a risk value higher than “2.0” is determined to have a high risk level. This indicates that the risk of the user developing a disease corresponding to the analysis item is extremely high. Further, an analysis item having a risk value between “1.5” and “2.0” is determined to have a medium risk level. This indicates that the risk of the user developing a disease corresponding to the analysis item is higher than “low” and lower than “high”.

  That is, in FIG. 3, as an example of the genetic test result, the genetic test result received by the user U01 identified by the user ID “U01” is shown. In the test, “diabetes”, “hypertension”, “hay fever” , “Gout” is analyzed, and the risk values are “1.7”, “2.9”, “1.4”, and “1.2”, respectively. “Medium”, “High”, “Low”, and “Low” are shown.

  For the degree of risk shown in FIG. 3, the calculation device 100 may adopt a standard indicated by the business operator who has performed the genetic test, or the calculation device 100 independently sets the risk value of the genetic test result. You may employ | adopt the criteria determined based on. For example, the calculation device 100 may determine the degree of risk by acquiring the risk value of the genetic test result and the statistical information of the number of users who actually developed the disease, and learning the relationship between them.

(About medical expenses information storage unit 125)
The medical cost information storage unit 125 stores information related to medical costs. Here, FIG. 4 shows an example of the medical cost information storage unit 125 according to the embodiment. As illustrated in FIG. 4, the medical cost information storage unit 125 includes items such as “type of disease” and “monthly medical cost”.

  “Disease type” indicates the type of the disease corresponding to the medical cost. “Monthly medical expenses” indicates the amount of medical expenses required for one month. Note that the monthly medical expenses may be statistical data of average medical expenses of general users published by public institutions, or may be values independently calculated on the calculation device 100 side. For example, the calculation device 100 may calculate monthly medical expenses for each disease by acquiring information about medical expenses actually required from the user who generated the proposal information and counting the acquired information.

  That is, FIG. 4 shows that, as an example of information related to medical expenses, if the disease type is “diabetes”, the average medical expenses for one month are only “24000”.

  In addition, although the medical cost information storage part 125 showed the example which memorize | stores the medical cost required for one month for every kind of disease, the amount of the medical cost memorize | stored is not restricted to this. For example, the medical cost information storage unit 125 may store an average amount of medical expenses necessary for the year, or may store an average amount of medical expenses required throughout the lifetime. The medical cost information storage unit 125 may store information related to a period until the disease is completely cured. In this case, the medical cost information storage unit 125 stores, for example, an average amount of medical expenses necessary for a period until the disease is completely cured.

(About the definition information storage unit 127)
The definition information storage unit 127 stores definition information related to generation processing that is used when generating a proposal to the user. Here, FIG. 5 illustrates an example of the definition information storage unit 127 according to the embodiment. As illustrated in FIG. 5, the definition information storage unit 127 includes items such as “risk degree”, “assumed medical expenses”, and “proposed action”.

  The “risk degree” corresponds to the same item shown in FIG. “Assumed medical cost” is a medical cost assumed for the user to be processed, and indicates the total amount of monthly medical cost for each degree of risk. “Proposed action” indicates the type of action to be proposed to the user based on the risk level and the assumed medical cost.

  That is, in FIG. 5, “insurance” and “savings” are performed simultaneously or “savings” for a user whose medical cost assumed in a disease with a high risk level is “30000” or more. The example of the definition information of producing | generating the proposal which recommends either of doing only is shown.

  Note that the definition information shown in FIG. 5 may be changed or corrected as appropriate by the administrator of the calculation apparatus 100, or may be changed or corrected by learning by the calculation apparatus 100. In the example shown in FIG. 5, when the medical cost assumed in a disease with a high risk level is “30000” or more, it is highly likely that it will be difficult to pay the medical cost in the future. , Proposed actions are set. The calculation apparatus 100 may make an appropriate adjustment for these settings according to the age and annual income of the user to be processed. For example, in another example shown in FIG. 5, if the medical cost assumed for a disease with a medium risk level is less than “10000” yen, it is unlikely that it will be difficult to pay the medical cost in the future. Under the assumption, the action to be proposed to the user is set as “investment” or “arbitrary”. However, the calculation apparatus 100 may accept a definition for proposing “saving” depending on the situation of the user who generates the proposal information even under the above-described conditions.

  Although illustration in FIG. 5 is omitted, the definition information storage unit 127 may store information regarding more detailed definitions. For example, the definition information storage unit 127 may store information such as a type of insurance to be proposed (insurance corresponding to a disease) and an appropriate investment destination according to an assumed medical cost. In this case, the calculation apparatus 100 appropriately refers to information stored in the definition information storage unit 127 and generates a proposal related to the user's action.

(About the control unit 130)
The control unit 130 is configured such that various programs (corresponding to an example of a calculation program) stored in a storage device inside the calculation apparatus 100 are stored in a work area by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. It is realized by generating as. The control unit 130 is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As illustrated in FIG. 2, the control unit 130 according to the embodiment includes an acquisition unit 131, a calculation unit 132, a generation unit 133, and a notification unit 134, and realizes information processing functions and operations described below. Or generate. The internal configuration of the control unit 130 is not limited to the configuration illustrated in FIG. 2, and may be another configuration as long as the information processing described later is performed. In addition, the connection relationship between the processing units included in the control unit 130 is not limited to the connection relationship illustrated in FIG. 2, and may be another connection relationship.

(About the acquisition unit 131)
The acquisition unit 131 acquires various types of information. For example, the acquisition unit 131 acquires risk information that is information indicating a risk related to the health of the user. Specifically, the acquisition unit 131 acquires the result of the genetic test that the user has previously visited as risk information.

  In addition, the acquisition unit 131 acquires medical cost information corresponding to the risk information. When the risk information is a genetic test result, the acquisition unit 131 acquires medical cost information corresponding to the disease type indicated in the analysis item of the genetic test. For example, the acquisition unit 131 accesses a database of published medical cost information and acquires medical cost information for use in processing.

  In addition, the acquisition unit 131 acquires definition information that is information related to the definition used in the generation process executed by the calculation apparatus 100. For example, the acquisition unit 131 acquires definition information by receiving an input from an administrator of the calculation apparatus 100. Alternatively, the acquisition unit 131 may acquire definition information by accessing a predetermined database.

  The acquisition unit 131 stores the acquired information in each storage unit. For example, the acquisition unit 131 stores the acquired risk information in the risk information storage unit 121. In addition, the acquisition unit 131 stores the acquired medical cost information in the medical cost information storage unit 125. The acquisition unit 131 stores the acquired definition information in the definition information storage unit 127. Note that the acquisition unit 131 does not necessarily store the acquired information in the storage unit 120, and may directly send the acquired information to each processing unit used for processing.

(About the calculation unit 132)
The calculation unit 132 calculates a future medical cost assumed for the user based on the medical cost information indicating the medical cost corresponding to the risk information and the risk level indicated by the risk information acquired by the acquisition unit 131. To do.

  When the acquisition unit 131 acquires risk information indicating the degree of risk for each disease type, the calculation unit 132 uses the medical cost information indicating the medical cost set in advance for each disease type. The medical cost assumed for the user is calculated. In this case, the calculation unit 132 may flexibly calculate a medical cost assumed for the user according to the situation. For example, regarding the predetermined disease type, when the risk level does not exceed the predetermined threshold, the calculation unit 132 corresponds to the predetermined disease type as compared with the case where the risk level exceeds the predetermined threshold. You may make it calculate the future medical expenses low. That is, the calculation unit 132 calculates the assumed medical expenses related to the diseases having a risk level of “high” and “medium” as the same amount as the acquired monthly medical expenses, and assumes the assumed medical expenses related to the diseases whose risk level is “low”. May be adjusted as appropriate, such as calculating as the amount of medical expenses multiplied by a predetermined ratio (for example, half of the acquired monthly medical expenses).

  In addition, the calculation unit 132 adds the medical expenses related to the disease type whose risk degree exceeds a predetermined threshold as a part of the future medical expenses assumed for the user, and the risk degree does not exceed the predetermined threshold. The estimated medical expenses may be calculated without adding the medical expenses related to the disease type as a part of the expected future medical expenses for the user. That is, the calculation unit 132 calculates an assumed medical cost only for diseases with a risk level of “high” and “medium”, and assumes that the medical cost is low for a disease with a risk level of “low”. Adjustments such as not adding up medical expenses may be made.

(About the generator 133)
The generation unit 133 generates proposal information including a proposal related to user behavior based on the future medical expenses calculated by the calculation unit 132. For example, the generation unit 133 generates proposal information for the user by comparing the calculated amount of future medical expenses and the degree of risk corresponding to the medical expenses with a predetermined condition.

  The proposal information is a proposal generated based on the amount of future medical expenses assumed for the user, the amount of expected medical expenses, and the degree of risk, and includes a proposal related to the user's behavior. In other words, the generation unit 133 includes information on the future medical expenses calculated by the calculation unit 132 and, as an action to secure the future medical expenses, the risk information indicated by the risk information used for calculating the future medical expenses Proposal information including a proposal regarding an action according to the degree is generated.

  Specifically, the generation unit 133 generates proposal information including a proposal regarding asset management performed by the user or a proposal regarding insurance that the user should join as an action to secure future medical expenses. In other words, the generation unit 133 generates a proposal related to asset management such as whether the user should save, invest or insurance for the necessary medical expenses. At this time, the generation unit 133 uses the asset management performed by the user based on the relationship between the future medical cost calculated by the calculation unit 132 and the degree of risk used in calculating the future medical cost. The contents of the proposal concerning the insurance or the proposal concerning the insurance that the user should join may be determined. In other words, the generation unit 133 may determine to propose saving to prepare for medical expenses even if the degree of risk is medium and the medical expenses for the disease corresponding to the risk are high. Alternatively, the generation unit 133 may determine that, if the degree of risk is moderate, even if the medical cost of the disease corresponding to the risk is high, it is suggested that funds be used for investment instead of saving. Good. As described above, the generation unit 133 can flexibly change and determine the content to be proposed to the user according to the situation.

(About the notification unit 134)
The notification unit 134 notifies various information. For example, the notification unit 134 notifies the user of a proposal included in the proposal information by transmitting the proposal information generated by the generation unit 133 to the user terminal 10.

  Here, FIG. 6 shows an example of a proposal that the notification unit 134 notifies the user terminal 10. FIG. 6 is a diagram illustrating an example of notification processing according to the embodiment. As shown in FIG. 6, the notification unit 134 provides a “suggestion to you” as well as a classification such as “a disease that you are likely to have” and “a disease that you may have” as well as the type of the disease Notification of medical expenses and actions that users should be able to take.

  In the example of FIG. 6, the notification unit 134 notifies the user of a disease corresponding to a risk level of “high” and “medium” as “a disease that you are likely to have”. In addition, the notification unit 134 notifies the user of a disease whose risk level is “low” as “a disease that you may have”. In addition, the notification unit 134 notifies the user of the total medical expenses related to diseases whose risk levels are “high” and “medium”. In addition, the notification unit 134 notifies the user of the total medical expenses related to the disease whose risk level is “low”. In addition, the notification unit 134 presents a disease corresponding to a risk level of “high” and “medium” and an assumed medical cost, and as an action that the user can take, “save of 480,000 yen per year” ”Or“ insurance ”. In addition, the notification unit 134 presents a disease corresponding to a risk level of “low” and an assumed medical cost, and “saves” or “investment” as an action that the user can take. "Proposes to do." The user can know the action guidelines that can be taken by referring to the proposal information via the user terminal 10.

  In the example of FIG. 6, the notification unit 134 notifies the sum of the medical expenses related to the diseases whose risk degrees are “high” and “medium”, but the risk degrees are “high” and “medium”. You may notify separately the amount corresponding to each disease corresponding to "." Moreover, although the notification part 134 has shown 2 types of action to propose, you may notify more proposals. Furthermore, the notification unit 134 may notify the detailed content of the proposed action. For example, when the user selects the item “insurance” shown in FIG. 6, the notification unit 134 may cause the user terminal 10 to display detailed contents of insurance corresponding to the disease.

[3. Processing procedure)
Next, a processing procedure performed by the calculation apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 7 is a flowchart illustrating a processing procedure performed by the calculation apparatus 100 according to the embodiment.

  As illustrated in FIG. 7, the acquisition unit 131 according to the calculation apparatus 100 determines whether a genetic test result has been received from the user as risk information (step S101). The acquisition part 131 waits until it receives, when the genetic test result is not received (step S101; No).

  On the other hand, when the acquisition unit 131 receives the genetic test result (step S101; Yes), the calculation unit 132 specifies medical cost information corresponding to the genetic test (step S102). Subsequently, the calculation unit 132 calculates a future medical cost assumed for the user based on the medical cost information corresponding to the genetic test (step S103).

  Subsequently, the generation unit 133 generates proposal information for the user based on the calculated medical expenses (step S104). And the notification part 134 notifies a user of a proposal by transmitting the proposal information produced | generated by the production | generation part 133 to a user (step S105).

[4. (Modification)
The calculation device 100 according to the above-described embodiment may be implemented in various different forms other than the above-described embodiment. Therefore, in the following, another embodiment of the calculation device 100 will be described.

[4-1. Lifestyle habit〕
In the said embodiment, the example which the calculation apparatus 100 produces | generates proposal information based on the genetic test result acquired from the user was shown. Here, the calculation apparatus 100 may further acquire detailed user information and generate proposal information. This point will be described with reference to FIG.

  FIG. 8 is a diagram illustrating an example of calculation processing according to the modification. In the example illustrated in FIG. 8, the user U01 who uses the user terminal 10 provides the calculation apparatus 100 with information on his / her daily behavior along with the genetic test result. And the calculation apparatus 100 produces | generates proposal information based on the information provided from the user U01.

  As illustrated in FIG. 8, the user terminal 10 transmits information related to the daily behavior of the user U01 to the calculation device 100 (step S21). Note that the user terminal 10 may transmit information to the calculation device 100 by an operation of the user U01, or may periodically transmit information to the calculation device 100 at a predetermined timing. For example, the user terminal 10 acquires a log related to the operation of the user terminal 10 and installs an application that accumulates the acquired log. Then, the user terminal 10 may transmit the accumulated log to the calculation device 100 according to the operation by the installed application. The accumulated log includes, for example, the number of walks of the user U01 measured by the physical sensor of the user terminal 10, and the life log recorded in the user terminal 10 by the user U01 (in the example of FIG. ).

  The calculation device 100 acquires information related to daily activities related to the user U01. The calculation device 100 stores the acquired information regarding daily behavior in the user behavior table 123. Then, the calculation device 100 calculates an assumed medical cost based on the daily behavior of the user U01, in other words, based on the lifestyle of the user U01 (step S22). In this case, it is assumed that the calculation device 100 has already calculated the medical cost assumed for the user U01 based on the genetic test result as shown in FIG. And the calculation apparatus 100 calculates the medical expenses assumed based on a lifestyle by adjusting the medical expenses calculated based on the genetic test result based on the lifestyle provided from the user U01. In addition, although mentioned later in detail, the calculation apparatus 100 calculates the total amount which considered the medical expenses regarding those diseases, when there exists a disease assumed that the user U01 has a risk of developing based on a lifestyle. You may make it do.

  Prior to the calculation process, the calculation apparatus 100 acquires information on lifestyle habits that cause the risk of disease to fluctuate. The calculation apparatus 100 stores the acquired information related to lifestyle in the lifestyle table 128. Specifically, the information on generation habits means that if the number of walks per day is 10,000 or more, the risk of diabetes decreases, and if the number of eating outs per month is 10 or less, the risk of hypertension decreases. This is statistical data indicating that

  Then, the calculation device 100 collates the information regarding the daily behavior acquired from the user U01 with the information stored in the lifestyle table 128. Then, when the user U01 changes the daily behavior, the calculation device 100 calculates the amount of the expected medical cost in consideration of the changing medical cost. For example, if the number of daily walks of the user U01 is 10,000 steps or more and the risk level of diabetes is determined to be low, the calculation device 100 takes into account that the expected medical costs will be reduced accordingly. Perform the calculation. In addition, if the number of eating-outs per month of the user U01 becomes 10 or less and the risk level of hypertension is determined to be low, the calculation device 100 may indicate that the expected medical cost will be reduced accordingly. Perform a calculation that takes into account.

  Subsequently, the calculation apparatus 100 generates proposal information for the user based on the calculated medical expenses (step S23). In this case, the calculation apparatus 100 includes the amount of medical expenses such as how much medical expenses are expected to be reduced if lifestyle improvement is seen, for example, along with future medical expenses based on the genetic test results. Generate proposal information. In addition, the calculation device 100 generates a proposal related to an action to be taken by the user U01 in order to reduce medical costs. Specifically, the calculation device 100 indicates how much medical expenses the user U01 can reduce by increasing the number of walks per day, and then increases the number of days that the user U01 should increase. Proposes that suggest the number of walks.

  Then, the calculation device 100 transmits the generated proposal information to the user terminal 10. That is, the calculation device 100 notifies the user U01 of the generated proposal (step S24). As shown in FIG. 8, the calculation apparatus 100 displays, on the user terminal 10, a content such as “If you walk“ 4500 more steps ”, you can reduce the medical cost of XXX yen in the future”. In addition, the calculation apparatus 100 displays, on the user terminal 10, a content such as “If you reduce eating out“ 20 more times ”, the medical cost of YYY yen can be reduced in the future”.

  In this way, the calculation device 100 acquires information regarding daily activities from the user U01. Then, when there is an action to reduce the amount of the calculated future medical expenses as compared with the acquired action of the user U01, the calculation apparatus 100 determines the future medical expenses as an action to secure the future medical expenses. Proposal information including an action proposal for reducing the amount of medical expenses can be generated. The action to reduce the amount of calculated future medical expenses specifically refers to lifestyle habits such as the number of daily walks of the user U01 and the number of eating outs per month. Thereby, the user U01 can receive not only direct actions related to assets such as investment and savings but also proposals related to indirect actions related to assets such as reducing medical expenses by daily habits of daily activities. As described above, according to the calculation device 100 according to the modification, it is possible to provide the user U01 with more appropriate information regarding the future design.

  Below, the structure of the calculation apparatus 100 which concerns on a modification is demonstrated. FIG. 9 is a diagram illustrating a configuration example of the calculation apparatus 100 according to the modification. As illustrated in FIG. 9, the calculation device 100 according to the modification further includes a user behavior table 123 and a lifestyle table 128 as compared with the calculation device 100 according to the embodiment.

(About the user action table 123)
The user behavior table 123 is one of data tables included in the risk information storage unit 121. The user behavior table 123 stores information related to user behavior. Here, FIG. 10 shows an example of the user behavior table 123 according to the modification. As shown in FIG. 10, the user behavior table 123 includes items such as “user ID”, “lifestyle”, “content”, “occurrence risk”, “risk value”, and “risk degree”.

  “User ID” corresponds to the same item shown in FIG. “Lifestyle” indicates an item of lifestyle that is indicated by daily behavior acquired from the user. “Content” indicates the detailed contents of the items listed in the lifestyle habits.

  “Occurrence risk” indicates the type of risk that is assumed to occur to the user based on lifestyle habits. The items included in the occurrence risk are not limited to diseases, and may include, for example, accident information such as traffic accidents. “Risk value” is a numerical value of the risk that the items listed in the occurrence risk actually occur.

  “Risk degree” indicates a result of determining a degree that an item listed as an occurrence risk is assumed to actually occur based on a risk value. For example, the risk level is indicated by a three-level evaluation such as “high”, “medium”, and “low”.

  That is, in FIG. 10, as an example of risk information related to the lifestyle of the user U01, regarding the lifestyle item “commuting”, when the content is “car” commuting, “traffic accident” is cited as an occurrence risk. The risk value is “1.2”, and the risk level is “low”. In addition, the item “Number of walking” of the lifestyle habit of the user U01 is “5500 steps / day”, the occurrence risk is “diabetes”, the risk value is “1.9”, and the risk degree is “ It shows that it is "medium".

(Regarding the medical cost information storage unit 125 according to the modification)
Next, FIG. 11 shows an example of the medical cost information storage unit 125 according to the modification. As illustrated in FIG. 11, the medical cost information storage unit 125 includes items such as “type of disease (risk)” and “medical cost”.

  “Type of disease (risk)” indicates the type of disease or risk corresponding to the medical cost. “Medical expenses” indicates the amount of medical expenses required for one month and the medical expenses required when an accident or injury occurs once.

  For example, in FIG. 11, as an example of information on medical expenses, if the type of disease (risk) is “traffic accident (car)”, the average medical expenses for one time should be “18000” yen. Show. In addition, when the type of the disease (risk) is “fracture”, it indicates that the average medical cost for one time is “8000” yen. The medical cost information storage unit 125 may store an average medical cost for a month until the accident or injury is completely cured as a medical cost when an accident or injury occurs once. In this case, the calculating unit 132 adds the monthly medical expenses required for illness, etc., and the average monthly medical expenses until the accident or injury is completely cured, and the user is required for one month in the future. An assumed medical cost may be calculated.

(About lifestyle table 128)
The lifestyle table 128 is one of the data tables that the definition information storage unit 127 has. The lifestyle table 128 stores information related to lifestyle. Here, FIG. 12 shows an example of the lifestyle table 128 according to the modification. As shown in FIG. 12, the lifestyle table 128 includes items such as “type of disease (risk)”, “lifestyle”, “content”, and “risk degree”.

  “Type of disease (risk)” indicates the type of disease (risk) that may develop due to lifestyle habits. “Lifestyle” indicates items listed as lifestyle habits. “Contents” indicates detailed contents of lifestyle habits. “Risk degree” indicates the degree of risk that a disease (risk) occurs according to lifestyle.

  For example, in FIG. 12, when the type of disease (risk) is “diabetes” as a definition related to lifestyle, “number of walking / day” of lifestyle is related to the risk. When the number of walks is “0-4999” steps, the risk degree is determined as “high”, and when the number of walks is “5000-9999” steps, the risk degree is determined as “medium”. When the number of walks is “10000” steps or more, the risk degree is determined to be “low”.

  In the modified example, the calculation device 100 publishes, for example, a medical expense data stored in the medical expense information storage unit 125, data related to a lifestyle stored in the lifestyle table 128, and the like from a public institution. Acquire from data or external database. Alternatively, the calculation device 100 may perform processing using medical cost information or lifestyle data that has been independently statistics or learned.

(About processing using lifestyle habits)
As shown in FIGS. 8 to 12, in the modification, the calculation device 100 determines that the risk of developing “diabetes” and “hypertension” is relatively high for the user U01 based on the genetic test result. And the calculation apparatus 100 specifies the lifestyle related to diabetes and hypertension among the action data acquired from the user U01. Subsequently, the calculation device 100 collates the data stored in the user behavior table 123 with the data stored in the lifestyle table 128. Thereby, the calculation apparatus 100 produces | generates the proposal information regarding the said item, when there exists an item determined that the user U01 can reduce the risk of developing by improving a lifestyle habit.

  Moreover, the calculation apparatus 100 may calculate the medical cost regarding the risk which could not be calculated by the genetic test result by handling the information regarding the behavior provided from the user U01 as the risk information. Specifically, the calculation device 100 may calculate a medical cost assumed for the user U01 based on the commuting mode of the user U01 or the hobby preference of the user U01 among the lifestyle habits of the user U01.

  For example, the calculation device 100 calculates the type of risk that occurs and the medical cost corresponding to the risk when the user U01's lifestyle is car commuting or the hobby is snowboarding. In the examples of FIGS. 10 and 11, the calculation device 100 has a risk of “traffic accident” with respect to the lifestyle of the user U01, such as car commuting, but there is a risk of “traffic accident”, and the medical cost is one time of the accident. Is calculated to be “18,000 yen”. Further, regarding the lifestyle that the user U01's snowboard is a hobby, the calculation device 100 has a risk of “fracture” whose risk level is “medium”, and the medical cost is “8000 yen” per occurrence of injury. Is calculated.

  The calculation apparatus 100 can include information related to medical expenses that can be incurred with respect to lifestyle as described above as proposal information for the user U01. And the calculation apparatus 100 can produce | generate the proposal which recommends saving and insurance as a proposal with respect to the medical expenses which may generate | occur | produce about a lifestyle according to definition information.

[4-2. Risk information)
In the said embodiment, the calculation apparatus 100 showed the example which acquires the information regarding a genetic test result and a lifestyle as risk information. However, the risk information acquired by the calculation device 100 is not limited to these. For example, the calculation device 100 may handle any information as risk information as long as it is information that can be acquired and the medical cost corresponding to the risk that occurs. For example, the calculation apparatus 100 may handle the result of a health check received by the user U01 as risk information.

[4-3. (Risk display)
In the above-described embodiment, the calculation device 100 indicates the risk of the user developing for a predetermined disease as a risk value, or indicates the risk level by three-level evaluation such as “high”, “medium”, and “low”. . However, the calculation apparatus 100 does not have to use the display as described above when determining or evaluating the risk. For example, the calculation apparatus 100 may indicate the level of possibility that the user U01 will develop as a percentage or a ratio for a predetermined disease as compared to other general users.

[4-4. User information)
In the embodiment described above, the calculation apparatus 100 has shown an example in which information related to genetic test results and daily behavior is acquired from the user. However, the information acquired by the calculation device 100 is not limited to these.

  For example, the calculation apparatus 100 may acquire user attribute information such as the user's annual income, business type, residential area, and family composition. The calculation apparatus 100 may store each definition information that matches the user attribute information in the definition information storage unit 127. And the calculation apparatus 100 produces | generates the proposal information which considered the user's attribute information, when producing | generating proposal information. For example, the calculation device 100 is flexible according to the user, such as adjusting the suggested savings amount according to the user's annual income, or recommending savings preferentially over investment according to the user's family structure. Proposals may be generated.

[5. Others]
In addition, among the processes described in the above embodiment, all or part of the processes described as being automatically performed can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method. In addition, the processing procedures, specific names, and information including various data and parameters shown in the document and drawings can be arbitrarily changed unless otherwise specified.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  For example, the risk information storage unit 121, the medical cost information storage unit 125, and the definition information storage unit 127 illustrated in FIG. 2 may be stored in an external storage server or the like without being stored in the calculation device 100. In this case, the calculation apparatus 100 acquires medical cost information and the like by accessing the storage server.

  Further, for example, the calculation device 100 described above performs internal processing such as generating proposal information and a front-end server side that executes processing centering on communication with an external device such as accepting risk information from the user terminal 10. You may distribute to the back-end server side to perform.

[6. Hardware configuration)
Further, the calculation apparatus 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 13, for example. FIG. 13 is a hardware configuration diagram illustrating an example of a computer 1000 that implements the functions of the calculation apparatus 100. The computer 1000 includes a CPU 1100, RAM 1200, ROM 1300, HDD 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores a program executed by the CPU 1100, data used by the program, and the like. The communication interface 1500 receives data from other devices via the communication network 500 and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the communication network 500.

  The CPU 1100 controls an output device such as a display and a printer and an input device such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the data generated via the input / output interface 1600 to the output device.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

  For example, when the computer 1000 functions as the calculation device 100, the CPU 1100 of the computer 1000 implements the function of the control unit 130 by executing a calculation program loaded on the RAM 1200. In addition, each data in the storage unit 120 is stored in the HDD 1400. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from other devices via the communication network 500.

[7. effect〕
As described above, the calculation device 100 according to the embodiment includes the acquisition unit 131, the calculation unit 132, and the generation unit 133. The acquisition unit 131 acquires risk information that is information indicating a risk related to the health of the user. The calculation unit 132 calculates a future medical cost assumed for the user based on the medical cost information indicating the medical cost corresponding to the risk information and the degree of risk indicated by the risk information acquired by the acquisition unit 131. calculate.

  As described above, the calculation apparatus 100 according to the embodiment can calculate a medical cost predicted with high accuracy by calculating a medical cost assumed in the future according to the risk information indicated to the user. . In other words, the calculation device 100 calculates a certain amount of reliability with respect to expenditures with many uncertain factors such as medical expenses. And the calculation apparatus 100 produces | generates the proposal information with respect to a user based on the amount of the calculated medical expenses. Thereby, the calculation apparatus 100 can give a guideline of an action to be taken to the user. As a result, the calculation apparatus 100 can provide appropriate information regarding the future design to the user.

  The acquisition unit 131 acquires risk information indicating the degree of risk for each type of disease. The calculation unit 132 calculates a future medical cost assumed for the user, using medical cost information indicating a medical cost preset for each disease type.

  Thereby, the calculation apparatus 100 which concerns on embodiment can calculate the medical expenses assumed with respect to a user in detail. For this reason, the calculation apparatus 100 can generate proposal information more suitable for the user.

  In addition, when the degree of risk does not exceed the predetermined threshold with respect to the predetermined disease type, the calculation unit 132 sets the predetermined disease type as compared with the case where the degree of risk exceeds the predetermined threshold. The corresponding future medical expenses may be calculated low.

  As described above, since the calculation device 100 according to the embodiment calculates the medical cost taking into account the risk of the user, it can calculate the medical cost expected to be actually required by the user with higher accuracy. For this reason, the calculation apparatus 100 can generate proposal information more suitable for the user.

  In addition, the calculation unit 132 adds the medical expenses related to the disease type for which the degree of risk exceeds a predetermined threshold as a part of the future medical expenses assumed for the user, and the degree of risk sets the predetermined threshold. The medical expenses related to the types of diseases not exceeding may be calculated as the future medical expenses assumed for the user without being added together as a part of the future medical expenses expected for the user.

  As described above, the calculation device 100 according to the embodiment can appropriately adjust items to be calculated as medical expenses according to the risk of the user. Thereby, the calculation apparatus 100 can calculate the medical expenses estimated to be actually required by the user with higher accuracy.

  In addition, the calculation apparatus 100 according to the embodiment further includes a generation unit 133 that generates proposal information including a proposal related to the user's behavior based on the future medical expenses calculated by the calculation unit 132. The generation unit 133 includes information on the future medical expenses calculated by the calculation unit 132, and as an action for securing the future medical expenses, the generation unit 133 sets the degree of risk indicated by the risk information used for calculating the future medical expenses. Proposal information including a proposal regarding the corresponding action is generated.

  As described above, the calculation device 100 according to the embodiment can generate an action proposal according to the risk of the user. That is, the calculation device 100 can generate an appropriate proposal by selecting an action that the user can take according to a risk assumed for the user in the future.

  The generation unit 133 generates proposal information including a proposal related to asset management performed by the user or a proposal related to insurance to be purchased by the user as an action to secure future medical expenses. For example, the generation unit 133 relates to the asset management performed by the user based on the relationship between the future medical cost calculated by the calculation unit 132 and the degree of risk used when calculating the future medical cost. You may make it determine the content of the proposal regarding the proposal or the insurance which a user should join.

  As described above, the calculation apparatus 100 according to the embodiment generates a proposal for an action related to the user's asset management. Thereby, the calculation apparatus 100 can give an appropriate guideline to a user about preparation for the future with a high uncertain element called medical expenses. Further, the calculation device 100 can flexibly determine a proposal to the user according to the situation.

  The acquisition unit 131 acquires information related to user behavior. The generation unit 133 secures the future medical expenses when there is an action to reduce the amount of the future medical expenses calculated by the calculation unit 132 as compared with the user behavior acquired by the acquisition unit 131. Proposal information including an action proposal for reducing the amount of future medical expenses is generated as an action.

  As described above, the calculation apparatus 100 according to the embodiment can make suggestions regarding not only direct actions related to user asset management but also daily actions of the user. As described above, the calculation device 100 can support the user in various aspects with respect to the user's future design.

  When the generation unit 133 has a lifestyle that reduces the amount of future medical expenses calculated by the calculation unit 132 as compared to the user's lifestyle at the time when the acquisition unit 131 acquires information related to the user's behavior Generates proposal information including a lifestyle proposal that reduces the amount of future medical expenses as an action to secure future medical expenses.

  Thus, the calculation apparatus 100 according to the embodiment can generate a proposal related to the user's lifestyle. Thereby, the calculation apparatus 100 can propose a more specific improvement means to the user.

  The acquisition part 131 acquires the genetic test result regarding a user as risk information. The calculation unit 132 calculates a medical cost assumed for the user based on the genetic test result regarding the user.

  Thus, the calculation apparatus 100 according to the embodiment acquires a genetic test result as a specific example of risk information. Thereby, since the calculation apparatus 100 can acquire extremely accurate risk information, as a result, a more useful proposal for the user can be generated.

  Moreover, the acquisition part 131 acquires the information regarding a user's lifestyle as risk information. The calculation part 132 calculates the medical expenses assumed with respect to a user based on a user's commuting form or a user's hobby preference among a user's lifestyle.

  As described above, the calculation device 100 according to the embodiment can also calculate a future medical cost based on the lifestyle of the user. Thereby, the calculation apparatus 100 can calculate medical expenses even for diseases, accidents, injuries, and the like for which risks cannot be measured by genetic test results. That is, since the calculation apparatus 100 can calculate the medical cost assumed for the user using various risk information regardless of the specific test result, the calculation apparatus 100 generates an appropriate proposal that is more in line with the user's situation. can do.

  As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to implement the present invention in other forms with improvements.

  The above-described calculation device 100 may be realized by a plurality of server computers, and depending on the function, the configuration may be realized by calling an external platform or the like with an API (Application Programming Interface) or network computing. Can be changed flexibly.

  Further, “section (module, unit)” described in the claims can be read as “means”, “circuit”, and the like. For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 Calculation system 10 User terminal 100 Calculation apparatus 110 Communication part 120 Storage part 121 Risk information storage part 122 Genetic test result table 123 User action table 125 Medical expense information storage part 127 Definition information storage part 128 Lifestyle table 130 Control part 131 Acquisition part 132 calculation unit 133 generation unit 134 notification unit

Claims (14)

An acquisition unit for acquiring risk information, which is information indicating a risk related to a user's health;
Calculation for calculating a future medical cost assumed for the user based on medical cost information indicating the medical cost corresponding to the risk information and the degree of risk indicated by the risk information acquired by the acquisition unit And
A calculation device comprising: The acquisition unit
Get risk information that shows the degree of risk for each type of disease,
The calculation unit includes:
Using the medical cost information indicating the medical cost set in advance for each type of disease, calculating the future medical cost assumed for the user,
The calculation apparatus according to claim 1. The calculation unit includes:
When the degree of risk does not exceed a predetermined threshold with respect to a predetermined disease type, a future corresponding to the predetermined disease type is compared with a case where the degree of risk exceeds a predetermined threshold. Calculate medical costs low,
The calculation apparatus according to claim 2, wherein: The calculation unit includes:
Medical expenses related to the type of disease for which the degree of risk exceeds a predetermined threshold are added as part of future medical expenses assumed for the user, and the degree of risk for which the degree of risk does not exceed the predetermined threshold. The medical cost related to the type does not add up as a part of the expected future medical cost for the user, but calculates the expected future medical cost for the user.
The calculation apparatus according to claim 2 or 3, wherein Based on the future medical expenses calculated by the calculation unit, a generation unit that generates proposal information including a proposal related to the user's behavior,
The calculation device according to claim 1, further comprising: The generator is
An action according to the degree of risk indicated by the risk information used for calculating the future medical expenses as an action for securing the future medical expenses as well as including information on the future medical expenses calculated by the calculation unit Generate proposal information including suggestions for
The calculation device according to claim 5, wherein: The generator is
As the action to secure the future medical expenses, generate proposal information including a proposal related to asset management performed by the user or a proposal related to insurance that the user should join,
The calculation apparatus according to claim 6. The generator is
Based on the relationship between the future medical expenses calculated by the calculation unit and the degree of risk used when calculating the future medical expenses, the proposal regarding asset management performed by the user, or the user Determine the content of the insurance proposals
The calculation apparatus according to claim 7. The acquisition unit
Obtaining information about the user's behavior,
The generator is
When there is an action to reduce the amount of the future medical expenses calculated by the calculation part as compared with the user's action acquired by the acquisition part, as an action to secure the future medical expenses, Generate proposal information that includes suggestions for actions that will reduce the amount of future medical expenses;
The calculation device according to any one of claims 6 to 8. The generator is
If there is a lifestyle that reduces the amount of future medical expenses calculated by the calculation unit compared to the user's lifestyle at the time when the information related to the user's behavior is acquired by the acquisition unit, Generate proposal information including lifestyle proposals that reduce the amount of future medical expenses as an action to secure future medical expenses,
The calculation device according to claim 9. The acquisition unit
As the risk information, obtain a genetic test result for the user,
The calculation unit includes:
Based on the genetic test results for the user, calculate the expected medical expenses for the user,
The calculation device according to claim 1, wherein: The acquisition unit
As the risk information, obtain information about the user's lifestyle,
The calculation unit includes:
Of the lifestyle habits of the user, based on the user's commuting mode or the user's hobbies preference, calculate the expected medical expenses for the user,
The calculation device according to claim 1, wherein: A calculation method executed by a computer,
An acquisition step of acquiring risk information, which is information indicating a risk related to a user's health;
Calculation for calculating a future medical cost assumed for the user based on medical cost information indicating the medical cost corresponding to the risk information and the degree of risk indicated by the risk information acquired by the acquisition step Process,
The calculation method characterized by including. An acquisition procedure for acquiring risk information, which is information indicating a risk related to a user's health;
Calculation for calculating a future medical cost assumed for the user based on the medical cost information indicating the medical cost corresponding to the risk information and the degree of risk indicated by the risk information acquired by the acquisition procedure Procedure and
A calculation program for causing a computer to execute.

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