Program, health risk prediction device, medical expense prediction device, health estimation age prediction device, complex system, health risk prediction method, medical expense prediction method, health estimation age prediction method, and storage medium

Abstract

To provide a program that enables a future prediction related to health.SOLUTION: A program of the present disclosure includes: an object person information acquisition procedure; health risk calculation procedure; and a health risk output procedure. The object person information acquisition procedure is configured to acquire object person information. Therein the object person information includes health diagnosis information, medical interview information and attribute information on an object person. The health risk calculation procedure is configured to calculate a health risk of the object person from the object person information. Therein the health risk output procedure is configured to output the health risk, in which the health risk is at least one of a probability of the object person contracting a disease, and a probability of an examination value of the object person being an abnormal value. The program is a health risk prediction program for causing a computer to implement each procedure.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a program, a health risk prediction device, a medical expense prediction device, an estimated health age prediction device, a composite system, a health risk prediction method, a medical expense prediction method, an estimated health age prediction method, and a recording medium. [Background technology]

[0002] In the medical field, for example, there is a system that can accumulate medical data of subjects and extract the accumulated medical data (Patent Document 1). Such a system, for example, can improve the efficiency of doctors' diagnoses of patients. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2002-366655 A Summary of the Invention [Problem to be solved by the invention]

[0004] On the other hand, in the system disclosed in Patent Document 1, although it is possible to view medical data, it is not possible to predict future health-related events, such as predicting diseases that a subject may develop in the future. It is very important to predict health risks in advance and prepare for the future.

[0005] Therefore, the present disclosure aims to provide a program capable of making future health-related predictions, a health risk prediction device, a medical expense prediction device, an estimated health age prediction device, a composite system, a health risk prediction method, a medical expense prediction method, an estimated health age prediction method, and a recording medium. [Means for solving the problem]

[0006] In order to achieve the above object, the health risk prediction program disclosed herein comprises: The method includes a subject information acquisition procedure, a health risk calculation procedure, and a health risk output procedure, The subject information acquisition step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A health risk prediction program for causing a computer to execute each of the above procedures.

[0007] The medical cost prediction program disclosed herein is The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs. The step of acquiring predicted medical cost calculation information includes acquiring information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, This is a medical cost prediction program for causing a computer to execute each of the above steps.

[0008] The health estimated age prediction program of the present disclosure is The method includes a procedure for obtaining predicted medical expenses, a procedure for calculating an estimated health age, and a procedure for outputting an estimated health age, The step of obtaining predicted medical expenses includes obtaining predicted medical expenses of a subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age. The present invention relates to a health age prediction program for causing a computer to execute each of the above steps.

[0009] The composite program of the present disclosure comprises: At least one of a health risk prediction program, a medical expense prediction program, and a health estimated age prediction program is included; The health risk prediction program is a health risk prediction program of the present disclosure, The health risk prediction program outputs a health risk; The medical cost prediction program is a medical cost prediction program of the present disclosure, The medical cost prediction program outputs predicted medical costs, The health age prediction program is a health age prediction program of the present disclosure, The estimated health age prediction program outputs an estimated health age. It is a complex program.

[0010] The health risk prediction device of the present disclosure comprises: The present invention includes a subject information acquisition unit, a health risk calculation unit, and a health risk output unit, The subject information acquisition unit acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation unit calculates a health risk of the subject from the subject information, The health risk output unit outputs the health risk, The health risk is at least one of the probability that the subject will contract a disease and the probability that the subject's test value will be abnormal.

[0011] The medical cost prediction device of the present disclosure is The present invention includes a predicted medical cost calculation information acquisition unit, a predicted medical cost calculation unit, and a predicted medical cost output unit, The predicted medical cost calculation information acquisition unit acquires information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation unit calculates predicted medical expenses of the subject from the information, The predicted medical expenses output unit outputs the predicted medical expenses.

[0012] The health age prediction device of the present disclosure includes: The present invention includes a predicted medical expense acquisition unit, a health estimated age calculation unit, and a health estimated age output unit, The predicted medical expenses acquisition unit acquires predicted medical expenses of the subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation unit calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output unit outputs the estimated health age.

[0013] The composite system of the present disclosure comprises: At least one of a health risk prediction device, a medical expense prediction device, and a health age prediction device, The health risk prediction device is a health risk prediction device according to the present disclosure, The health risk prediction device outputs a health risk, The medical cost prediction device is a medical cost prediction device according to the present disclosure, The medical cost prediction device outputs predicted medical costs, The health age prediction device is a health age prediction device according to the present disclosure, The estimated health age prediction device outputs an estimated health age.

[0014] The health risk prediction method of the present disclosure includes: The method includes a subject information acquisition step, a health risk calculation step, and a health risk output step, The subject information acquiring step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will contract a disease and the probability that the subject's test value will be abnormal.

[0015] The medical cost prediction method of the present disclosure includes: The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs, The predicted medical cost calculation information acquisition step acquires information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical expenses output step outputs the predicted medical expenses.

[0016] The health age prediction method of the present disclosure includes: The method includes a step of obtaining a predicted medical expense, a step of calculating an estimated health age, and a step of outputting an estimated health age, The predicted medical expenses acquisition step acquires predicted medical expenses of the subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age.

[0017] The recording medium of the present disclosure is a computer-readable recording medium having the program of the present disclosure recorded therein. Effect of the Invention

[0018] According to the present disclosure, it is possible to provide a program capable of making future health-related predictions, a health risk prediction device, a medical expense prediction device, an estimated health age prediction device, a composite system, a health risk prediction method, a medical expense prediction method, an estimated health age prediction method, and a recording medium. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 is a flowchart showing an example of a procedure in the health risk prediction program of the present disclosure. [Diagram 2] FIG. 2 is a block diagram showing a configuration of an example of a health risk prediction device of the present disclosure. [Diagram 3] FIG. 3 is a block diagram showing an example of a hardware configuration of the health risk prediction device of the present disclosure. [Figure 4] FIG. 4 is a flowchart showing an example of a procedure in the medical expense prediction program of the present disclosure. [Diagram 5] FIG. 5 is a block diagram showing a configuration of an example of a medical cost prediction device according to the present disclosure. [Figure 6] FIG. 6 is a block diagram showing an example of a hardware configuration of the medical expense prediction device of the present disclosure. [Figure 7] FIG. 7 is a flowchart showing an example of a procedure in the estimated health age prediction program of the present disclosure. [Figure 8] FIG. 8 is a block diagram showing a configuration of an example of a health estimated age prediction device of the present disclosure. [Figure 9] FIG. 9 is a block diagram showing an example of a hardware configuration of a health estimated age prediction device according to the present disclosure. [Figure 10] FIG. 10 is a block diagram showing a configuration of an example of a composite system according to the present disclosure. [Figure 11] FIG. 11 is a diagram showing an example of the health risk (probability that a subject will contract a disease) output by the health risk prediction device of the present disclosure. [Figure 12] FIG. 12 is a diagram showing an example of the health risk (probability that a test value of a subject will be an abnormal value) output by the health risk prediction device of the present disclosure. [Figure 13] FIG. 13 is a diagram showing an example of predicted medical expenses output by the medical expense prediction device of the present disclosure. [Figure 14] FIG. 14 is a diagram showing an example of calculation of an estimated healthy age. [Figure 15] FIG. 15 is a diagram showing an example of the estimated health age output by the estimated health age prediction device of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] An embodiment of the present disclosure will be described. Note that the present disclosure is not limited to the following embodiment. Note that in each of the following drawings, the same parts are given the same reference numerals. Furthermore, the explanations of each embodiment can be mutually incorporated unless otherwise specified. Furthermore, the configurations of each embodiment can be combined unless otherwise specified. Furthermore, in each procedure described later in the program of the present disclosure, for example, "procedure" can be read as "processing".

[0021] In this disclosure, unless otherwise specified, the term "estimated health age" refers to an index that expresses the age at which a subject's health condition is equivalent.

[0022] [Embodiment 1] A health risk prediction program, a health risk prediction device, and a health risk prediction method according to the present disclosure will be described. Note that the health risk prediction program according to the present disclosure is, for example, a program for the health risk prediction device.

[0023] First, an example of a health risk prediction program according to the present disclosure will be described with reference to a flowchart S10 in FIG.

[0024] The subject information acquisition procedure acquires subject information (S11). The subject information includes health check information, interview information, and attribute information of the subject. The health check information includes, for example, general test information measured during a health check. The interview information includes, for example, information about the subject's habits such as smoking and drinking. The attribute information includes, for example, information about the subject's age, gender, etc. The acquisition may be, for example, from a storage device described below, or from an external storage device such as cloud storage.

[0025] The health risk calculation procedure calculates the health risk of the subject from the subject information (S12). The calculation of the health risk may be, for example, a calculation by a health risk prediction model. The health risk prediction model may be, for example, a health risk prediction model that is machine-learned using statistical data of health check information, interview information, and attribute information as learning data, or may be a trained model that calculates and outputs the health risk of the subject when the health check information of the subject is input. In the calculation of the health risk, for example, a prediction score may be calculated, and the health risk may be calculated from the calculated prediction score. In addition, the health risks may be grouped, for example, based on a certain criterion. By the grouping, for example, even when the reliability of the calculated health risk is low, the reliability can be increased. Furthermore, when the health risk is calculated by a numerical value, for example, the numerical value may be simplified based on a certain criterion. The simplification is, for example, simplification of the numerical value by rounding off or the like. By the simplification, for example, the strictness of the predicted health risk can be relaxed, so that the user can easily read the health risk output thereafter.

[0026] The health risk output procedure ends with outputting the health risk (S13). The output may be, for example, an output device included in the health risk prediction device of the present disclosure described below or in another device.

[0027] The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the test value of the subject will be abnormal. The disease is not particularly limited, but examples thereof include lifestyle-related diseases, cancer, and gynecological diseases. Examples of the lifestyle-related diseases include hypertension, diabetes, liver disease, kidney disease, heart disease, cerebrovascular disease, and dyslipidemia. Examples of the cancer include lung cancer, stomach cancer, colon cancer, liver cancer, pancreatic cancer, prostate cancer, breast cancer, and uterine cancer. Examples of the gynecological diseases include premenstrual syndrome (PMS), hypomenorrhea, menstrual irregularity, and menopausal disorders. The test values ​​are not particularly limited, and are test values ​​of general tests usually performed in health checkups, etc., such as BMI, waist circumference, systolic blood pressure, diastolic blood pressure, electrocardiogram, triglycerides, HDL cholesterol, LDL cholesterol, total cholesterol, blood sugar (BS), HbA1c (hemoglobin A1c), urinary sugar, red blood cells (RBC), hematocrit, hemoglobin (hemoglobin), uric acid (UA), creatinine (CRE), GOT (AST), GPT (ALT), γ-GT (γ-GPT), ALP (alkaline phosphatase), urinary protein, urinary occult blood reaction, serum creatinine, blood urea nitrogen (BUN), creatinine clearance (CCr), etc. The probability of developing the disease may be, for example, the incidence rate by gender.

[0028] The health risk may be, for example, the health risk of the subject that may occur within a certain period of time. The certain period of time is not particularly limited, but may be, for example, within a certain time, within a certain number of days, within a certain number of weeks, within a certain number of months, or within a certain number of years. When the certain period of time is within the certain number of years, it is preferably within 5 years.

[0029] Next, an example of a health risk prediction device according to the present disclosure will be described with reference to FIGS.

[0030] Fig. 2 is a block diagram showing an example of the configuration of a health risk prediction device 10 of the present disclosure. As shown in Fig. 2, the health risk prediction device 10 includes a subject information acquisition unit 11, a health risk calculation unit 12, and a health risk output unit 13. Although not shown, the health risk prediction device 10 of the present disclosure is connectable to a medical expense prediction device and an estimated health age prediction device, which will be described later, via a communication network 40.

[0031] The health risk prediction device 10 may be, for example, a single device including each of the above-mentioned units, or a device to which each of the above-mentioned units can be connected via a communication line network. The health risk prediction device 10 may also be connected to an external device described later via the communication line network. The communication line network is not particularly limited, and a known network may be used, for example, wired or wireless. Examples of the communication line network include an Internet line, a World Wide Web (WWW), a telephone line, a Local Area Network (LAN), a Storage Area Network (SAN), a Delay Tolerant Networking (DTN), a Low Power Wide Area (LPWA), and a Local 5G (L5G). Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), a Local 5G, and a LPWA. Examples of the wireless communication may include a form in which each device directly communicates with each other (Ad Hoc communication), an infrastructure (infrastructure communication), and an indirect communication via an access point. The health risk prediction device 10 may be incorporated into a server as a system, for example. Furthermore, the health risk prediction device 10 may be, for example, a personal computer (PC, for example, desktop type or notebook type) on which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. The health risk prediction device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the above-mentioned units is on a server and the other units are on a terminal.

[0032] 3 illustrates an example block diagram of the hardware configuration of health risk prediction device 10. Health risk prediction device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, an output device 106, a communication device 107, etc. Each part of health risk prediction device 10 is connected to each other via bus 103 by its respective interface (I / F).

[0033] The central processing unit 101 cooperates with other components via a controller (system controller, I / O controller, etc.) and is responsible for overall control of the health risk prediction device 10. In the health risk prediction device 10, the central processing unit 101 executes, for example, the program of the present disclosure and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 101 functions as a subject information acquisition unit 11, a health risk calculation unit 12, and a health risk output unit 13. The central processing unit 101 may include, as a calculation device, a CPU, a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these.

[0034] The bus 103 can also be connected to, for example, an external device. Examples of the external device include an external storage device such as an external database, a printer, an external input device, an external display device, an external imaging device, etc. The health risk prediction device 10 can be connected to an external network (the communication line network) by, for example, a communication device 107 connected to the bus 103, and can also be connected to other devices via the external network.

[0035] The memory 102 is, for example, a main memory (primary storage device). When the central processing unit 101 performs processing, the memory 102 reads various operation programs, such as the program of the present disclosure, stored in the storage device 104 described below, and the central processing unit 101 receives data from the memory 102 and executes the program. The main memory is, for example, a RAM (random access memory). The memory 102 may also be, for example, a ROM (read only memory).

[0036] The storage device 104 is also called an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program including the program of the present disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive that reads and writes from the recording medium. The recording medium is not particularly limited, and may be, for example, an internal or external type, such as a HD (hard disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, memory card, etc. The storage device 104 may be, for example, a hard disk drive (HDD) in which the recording medium and the drive are integrated, and a solid state drive (SSD). The storage device 104 may also include, for example, the subject information.

[0037] In the health risk prediction device 10, the memory 102 and the storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the health risk prediction device 10, and information used when the health risk prediction device 10 executes processing. In this case, the memory 102 and the storage device 104 may store, for example, the above-mentioned information. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and the storage device 104, or may be stored in a distributed manner in multiple terminals using block chain technology or the like.

[0038] The health risk prediction device 10 further includes, for example, an input device 105 and an output device 106. Examples of the input device 105 include pointing devices such as a touch panel, a track pad, and a mouse; a keyboard; imaging means such as a camera and a scanner; a card reader such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the output device 106 include a display device such as an LED display and a liquid crystal display; an audio output device such as a speaker; a printer; and the like. In the present disclosure, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated device, such as a touch panel display.

[0039] Next, the health risk prediction method of the present disclosure will be described.

[0040] The health risk prediction method of the present disclosure may incorporate the descriptions in the program and health risk prediction device of the present disclosure. The health risk prediction method of the present disclosure is a method implemented by replacing each "procedure" in the program of the present disclosure with a "step". Specifically, the health risk prediction method of the present disclosure includes a subject information acquisition step, a health risk calculation step, and a health risk output step. The health risk prediction method of the present disclosure may be implemented, for example, using the health risk prediction device 10 of FIG. 2. Note that the health risk prediction method of the present disclosure is not limited to use of the health risk prediction device 10 of FIG. 2.

[0041] [Embodiment 2] A medical cost prediction program, a medical cost prediction device, and a medical cost prediction method according to the present disclosure will be described. Note that the medical cost prediction program according to the present disclosure is, for example, a program for the medical cost prediction device.

[0042] First, an example of a program according to the present disclosure will be described with reference to a flow chart S20 in FIG.

[0043] The procedure for acquiring predicted medical cost calculation information includes acquiring information including medical cost statistics for each disease and the subject's health risk (S21). The acquisition may be, for example, from a storage device described below, or from an external storage device such as cloud storage.

[0044] The diseases are not particularly limited, and examples thereof include lifestyle-related diseases, cancers, gynecological diseases, etc. Examples of the lifestyle-related diseases include hypertension, diabetes, liver diseases, kidney diseases, heart diseases, cerebrovascular diseases, dyslipidemia, etc. Examples of the cancers include lung cancer, stomach cancer, colon cancer, liver cancer, pancreatic cancer, prostate cancer, breast cancer, uterine cancer, etc. Examples of the gynecological diseases include premenstrual syndrome (PMS), hypomenorrhea, menstrual irregularities, menopausal disorders, etc.

[0045] The medical cost statistics may be calculated by, for example, an individual, a corporation, a government, a country, etc., or may be published by the National Federation of Health Insurance Societies (Kenpo Ren). The medical cost statistics may include, for example, various expenses such as food costs and bed charges.

[0046] The health risk may be, for example, a health risk calculated by at least one of the health risk prediction program, health risk prediction device, and health risk prediction method disclosed herein, or may be a health risk calculated by at least one of other programs, devices, and methods.

[0047] The information may be, for example, information recorded on a recording medium provided in the medical expense prediction device disclosed herein, which will be described later, or in another device.

[0048] The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information (S22). The predicted medical expenses are, for example, predicted medical expenses calculated from the product of the medical expenses statistics and the health risk. In this case, the health risk is preferably the probability that the subject will suffer from a disease. The predicted medical expenses may be, for example, predicted medical expenses calculated taking into account the medical expenses burden ratio. The predicted medical expenses may also be, for example, the sum of predicted medical expenses calculated for each of the diseases.

[0049] The predicted medical cost output procedure ends by outputting the predicted medical cost (S23). When the predicted medical cost includes the predicted medical cost for each disease, for example, the medical cost of the medical cost statistics may be output as the predicted medical cost for each disease. The output may be, for example, an output device provided in the medical cost prediction device of the present disclosure described below or another device.

[0050] The program of the present disclosure may further include a subject information acquisition step, a health risk calculation step, and a health risk output step. The subject information acquisition step, the health risk calculation step, and the health risk output step may be explained using the explanation of the health risk prediction program of the present disclosure.

[0051] Next, an example of a medical cost prediction device according to the present disclosure will be described with reference to FIGS.

[0052] Fig. 5 is a block diagram showing an example of the configuration of the medical expense prediction device 20 of the present disclosure. As shown in Fig. 5, the medical expense prediction device 20 includes a predicted medical expense calculation information acquisition unit 21, a predicted medical expense calculation unit 22, and a predicted medical expense output unit 23. Although not shown, the medical expense prediction device 20 of the present disclosure can be connected to the above-mentioned health risk estimation device and a later-described health estimated age prediction device via a communication line network 40. In addition, when the medical expense prediction device of the present disclosure includes the configuration of the above-mentioned health risk prediction device of the present disclosure, the medical expense prediction device 20 may further include a subject information acquisition unit, a health risk calculation unit, and a health risk output unit.

[0053] The medical cost prediction device 20 may be, for example, a single device including each of the above-mentioned units, or each of the above-mentioned units may be a device that can be connected via a communication line network. The medical cost prediction device 20 may also be connected to an external device described later via the communication line network. The communication line network is not particularly limited, and a known network may be used, for example, wired or wireless. Examples of the communication line network include an Internet line, WWW (World Wide Web), a telephone line, LAN (Local Area Network), SAN (Storage Area Network), DTN (Delay Tolerant Networking), LPWA (Low Power Wide Area), L5G (Local 5G), etc. Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), local 5G, LPWA, etc. Examples of the wireless communication may include a form in which each device directly communicates (Ad Hoc communication), infrastructure (infrastructure communication), indirect communication via an access point, etc. The medical cost prediction device 20 may be incorporated into a server as a system, for example. Furthermore, the medical cost prediction device 20 may be, for example, a personal computer (PC, for example, desktop type or notebook type) on which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. The medical cost prediction device 20 may be in the form of cloud computing or edge computing, for example, in which at least one of the above-mentioned units is on a server and the other units are on a terminal.

[0054] 6 illustrates a block diagram of a hardware configuration of the medical expense prediction device 20. The medical expense prediction device 20 includes, for example, a central processing unit (CPU, GPU, etc.) 201, a memory 202, a bus 203, a storage device 204, an input device 205, an output device 206, a communication device 207, etc. Each unit of the medical expense prediction device 20 is connected to each other via the bus 203 by each interface (I / F).

[0055] The central processing unit 201 cooperates with other components through a controller (system controller, I / O controller, etc.) and controls the entire medical expense prediction device 20. In the medical expense prediction device 20, the central processing unit 201 executes, for example, the program of the present disclosure and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 201 functions as a predicted medical expense calculation information acquisition unit 21, a predicted medical expense calculation unit 22, and a predicted medical expense output unit 23. The central processing unit 201 may further function as a subject information acquisition unit, a health risk calculation unit, and a health risk output unit (not shown). The central processing unit 201 may include, as a calculation unit, a CPU, a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these.

[0056] The bus 203 can also be connected to, for example, an external device. Examples of the external device include an external storage device such as an external database, a printer, an external input device, an external display device, an external imaging device, etc. The medical cost prediction device 20 can be connected to an external network (the communication line network) by, for example, a communication device 207 connected to the bus 203, and can also be connected to other devices via the external network.

[0057] The memory 202 is, for example, a main memory (primary storage device). When the central processing unit 201 performs processing, the memory 202 reads various operation programs, such as the program of the present disclosure, stored in the storage device 204 described below, and the central processing unit 201 receives data from the memory 202 and executes the program. The main memory is, for example, a RAM (random access memory). The memory 202 may also be, for example, a ROM (read only memory).

[0058] The storage device 204 is also called an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 204 stores an operating program including the program of the present disclosure. The storage device 204 may be, for example, a combination of a recording medium and a drive for reading and writing from and to the recording medium. The recording medium is not particularly limited, and may be, for example, an internal or external type, such as a HD (hard disk), a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, a memory card, and the like. The storage device 204 may be, for example, a hard disk drive (HDD) in which a recording medium and a drive are integrated, and a solid state drive (SSD). The storage device 204 may also include, for example, information such as the subject information, medical cost statistics for each disease, and health risks of the subject.

[0059] In the medical expense prediction device 20, the memory 202 and the storage device 204 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the medical expense prediction device 20, and information used when the medical expense prediction device 20 executes processing. In this case, the memory 202 and the storage device 204 may store, for example, the above-mentioned information. Note that at least a part of the information may be stored, for example, in an external server other than the memory 202 and the storage device 204, or may be stored in a distributed manner in multiple terminals using block chain technology or the like.

[0060] The medical cost prediction device 20 further includes, for example, an input device 205 and an output device 206. Examples of the input device 205 include pointing devices such as a touch panel, a track pad, and a mouse; a keyboard; an imaging means such as a camera and a scanner; a card reader such as an IC card reader and a magnetic card reader; and an audio input means such as a microphone. Examples of the output device 206 include a display device such as an LED display and a liquid crystal display; an audio output device such as a speaker; a printer; and the like. In the present disclosure, the input device 205 and the output device 206 are configured separately, but the input device 205 and the output device 206 may be configured as an integrated device, such as a touch panel display.

[0061] Next, the medical cost prediction method of the present disclosure will be described.

[0062] The medical cost prediction method of the present disclosure may use the descriptions in the program and medical cost prediction device of the present disclosure. The medical cost prediction method of the present disclosure is a method implemented by replacing each "procedure" in the program of the present disclosure with a "step". Specifically, the medical cost prediction method of the present disclosure includes a predicted medical cost calculation information acquisition step, a predicted medical cost calculation step, and a predicted medical cost output step. The medical cost prediction method of the present disclosure may further include a subject information acquisition step, a health risk calculation step, and a health risk output step. The medical cost prediction method of the present disclosure may be implemented, for example, using the medical cost prediction device 20 of FIG. 5. Note that the medical cost prediction method of the present disclosure is not limited to the use of the medical cost prediction device 20 of FIG. 5.

[0063] [Embodiment 3] The present disclosure relates to a health age prediction program, a health age prediction device, and a health age prediction method. The health age prediction program of the present disclosure is, for example, a program for the health age prediction device.

[0064] First, an example of a program according to the present disclosure will be described with reference to a flow chart S30 in FIG.

[0065] The predicted medical expenses acquisition procedure acquires predicted medical expenses of a subject (S31). The acquisition may be, for example, from a storage device described below, or from an external storage device such as cloud storage. The predicted medical expenses are medical expenses calculated from information including medical expense statistics for each disease and the subject's health risk. The predicted medical expenses may be, for example, predicted medical expenses calculated by at least one of the medical expense prediction program, medical expense prediction device, and medical expense prediction method disclosed herein, or may be health risks calculated by at least one of other programs, devices, and methods.

[0066] The estimated health age calculation step calculates the estimated health age of the subject from the predicted medical expenses (S32). The estimated health age may be, for example, the estimated health age for the age of the subject after a certain period of time has passed. The estimated health age may be, for example, an estimated health age calculated based on a regression line or a regression curve consisting of age and the expected medical expenses for each age. The estimated health age may be, for example, an estimated health age calculated based on a regression line or a regression curve for each gender. The estimated health age may be, for example, an estimated health age calculated based on a trained model (hereinafter, sometimes referred to as a "estimated health age prediction model") including the regression line or the regression curve. The estimated health age prediction model may be, for example, an estimated health age prediction model trained by machine learning using age and the medical expenses required for each age as training data, or may be a trained model that outputs the estimated health age of the subject when the predicted medical expenses of the subject are input.

[0067] The estimated health age output procedure ends by outputting the estimated health age (S33). The output may be output by an output device included in the estimated health age prediction device of the present disclosure described below or another device.

[0068] The program of the present disclosure may further include a subject information acquisition procedure, a health risk calculation procedure, a health risk output procedure, a predicted medical expense calculation information acquisition procedure, a predicted medical expense calculation procedure, and a predicted medical expense output procedure. The subject information acquisition procedure, the health risk calculation procedure, the health risk output procedure, the predicted medical expense calculation information acquisition procedure, the predicted medical expense calculation procedure, and the predicted medical expense output procedure may be described with reference to the description of the health risk prediction program of the present disclosure and the medical expense prediction program of the present disclosure described above.

[0069] As described above, in the present disclosure, the estimated health age is predicted from the predicted medical expenses. By predicting the estimated health age from the predicted medical expenses, the reliability of the predicted estimated health age is improved compared to the case where the estimated health age is predicted from the subject's health information obtained from a medical checkup or the like.

[0070] Next, an example of a health estimated age prediction device of the present disclosure will be described with reference to FIG. 8. Note that in the present disclosure, the health risk prediction device of the present disclosure, the medical expense prediction device of the present disclosure, and the health estimated age prediction device are described as separate devices, but this is not limited to this. For example, the health risk prediction device of the present disclosure, the medical expense prediction device of the present disclosure, and the health estimated age prediction device of the present disclosure may be integrated into one device. Also, for example, the health estimated age prediction device of the present disclosure may be a health estimated age prediction device including the configuration of the health risk prediction device of the present disclosure and the medical expense prediction device of the present disclosure.

[0071] FIG. 8 is a block diagram showing an example of the configuration of the health estimated age prediction device 30 of the present disclosure. As shown in FIG. 8, the device 30 includes a predicted medical cost acquisition unit 31, a health estimated age calculation unit 32, and a health estimated age output unit 33. Although not shown, the device 30 of the present disclosure can be connected to the health risk prediction device of the present disclosure and the medical cost prediction device of the present disclosure via a communication line network 40. In addition, when the health estimated age prediction device of the present disclosure includes the configuration of the health risk prediction device of the present disclosure and the medical cost prediction device of the present disclosure, the health estimated age prediction device 30 may further include a subject information acquisition unit, a health risk calculation unit, a health risk output unit, a predicted medical cost calculation information acquisition unit, a predicted medical cost calculation unit, and a predicted medical cost output unit.

[0072] The device 30 may be, for example, a single device including each of the above-mentioned units, or a device to which each of the above-mentioned units can be connected via the communication line network. The device 30 may be connected to an external device described later via the communication line network. The device 30 may be incorporated in a server as a system. The device 30 may be, for example, a personal computer (PC, for example, desktop type or notebook type) in which the program of the present disclosure is installed, a smartphone, a tablet terminal, or the like. The device 30 may be in the form of cloud computing or edge computing, for example, in which at least one of the above-mentioned units is on a server and the other units are on a terminal.

[0073] 9 illustrates a block diagram of a hardware configuration of the present device 30. The present device 30 includes, for example, a central processing unit (CPU, GPU, etc.) 301, a memory 302, a bus 303, a storage device 304, an input device 305, an output device 306, a communication device 307, etc. Each part of the present device 30 is connected to each other via the bus 303 by each interface (I / F).

[0074] The central processing unit 301 cooperates with other components through a controller (system controller, I / O controller, etc.) and controls the entire device 30. In the device 30, the central processing unit 301 executes, for example, the program of the present disclosure and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 301 functions as a predicted medical cost acquisition unit 31, a health estimated age calculation unit 32, and a health estimated age output unit 33. The central processing unit 301 may further function as a subject information acquisition unit, a health risk calculation unit, a health risk output unit, a predicted medical cost calculation information acquisition unit, a predicted medical cost calculation unit, and a predicted medical cost output unit (not shown). The central processing unit 301 may include a CPU, a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these as a computing device.

[0075] The bus 303 can also be connected to, for example, an external device. Examples of the external device include an external storage device such as an external database, a printer, an external input device, an external display device, an external imaging device, etc. The present device 30 can be connected to an external network (the above-mentioned communication line network) by, for example, a communication device 307 connected to the bus 303, and can also be connected to other devices via the external network.

[0076] The memory 302 may be, for example, a main memory (primary storage device). When the central processing unit 301 performs processing, the memory 302 reads various operation programs, such as the program of the present disclosure, stored in the storage device 304 described below, and the central processing unit 301 receives data from the memory 302 and executes the program. The main memory may be, for example, a RAM (random access memory). The memory 302 may also be, for example, a ROM (read only memory).

[0077] The storage device 304 is also called an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 304 stores an operating program including the program of the present disclosure. The storage device 304 may be, for example, a combination of a recording medium and a drive for reading and writing from and to the recording medium. The recording medium is not particularly limited, and may be, for example, an internal or external type, such as a HD (hard disk), a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, a memory card, and the like. The storage device 304 may be, for example, a hard disk drive (HDD) in which a recording medium and a drive are integrated, and a solid state drive (SSD). The storage device 304 may also include, for example, information such as the subject information, medical cost statistics for each disease, the subject's health risk, and the subject's predicted medical cost.

[0078] In the present device 30, the memory 302 and the storage device 304 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 30, and information used when the present device 30 executes processing. In this case, the memory 302 and the storage device 304 may store, for example, the above-mentioned information. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 302 and the storage device 304, or may be stored in a distributed manner in multiple terminals using block chain technology or the like.

[0079] The device 30 further includes, for example, an input device 305 and an output device 306. The input device 305 may be, for example, a pointing device such as a touch panel, a track pad, or a mouse; a keyboard; an imaging means such as a camera or a scanner; a card reader such as an IC card reader or a magnetic card reader; or an audio input means such as a microphone. The output device 306 may be, for example, a display device such as an LED display or a liquid crystal display; an audio output device such as a speaker; a printer; or the like. In the present disclosure, the input device 305 and the output device 306 are configured separately, but the input device 305 and the output device 306 may be configured as an integrated device, such as a touch panel display.

[0080] Next, the estimated health age prediction method of the present disclosure will be described.

[0081] The health age prediction method of the present disclosure can be implemented by using the descriptions in the program and the health age prediction device of the present disclosure. The health age prediction method of the present disclosure is implemented by replacing each "procedure" in the program of the present disclosure with "step". Specifically, the health age prediction method of the present disclosure includes a predicted medical cost acquisition step, a health estimated age calculation step, and a health estimated age output step. The health estimated age prediction method of the present disclosure may further include a subject information acquisition step, a health risk calculation step, a health risk output step, a predicted medical cost calculation information acquisition step, a predicted medical cost calculation step, and a predicted medical cost output step. The health estimated age prediction method of the present disclosure can be implemented, for example, using the device 30 of FIG. 9. Note that the health estimated age prediction method of the present disclosure is not limited to the use of the device 30 of FIG. 9.

[0082] [Embodiment 4] The composite program of the present disclosure will now be described.

[0083] The composite program of the present disclosure includes at least one of a health risk prediction program, a medical expense prediction program, and a health estimated age prediction program. The health risk prediction program is the health risk prediction program of the present disclosure. The health risk prediction program outputs a health risk. The medical expense prediction program is the medical expense prediction program of the present disclosure. The medical expense prediction program outputs predicted medical expenses. The health estimated age prediction program is the health estimated age prediction program of the present disclosure. The health estimated age prediction program outputs an estimated health age.

[0084] The composite system of the present disclosure will now be described.

[0085] An example of the composite system of the present disclosure will be described with reference to the block diagram of Fig. 10. Fig. 10 is a block diagram showing the configuration of an example of the composite system of the present disclosure.

[0086] [Embodiment 5] The composite system of the present disclosure includes at least one of a health risk prediction device, a medical expense prediction device, and a health estimated age prediction device. The health risk prediction device is the health risk prediction device of the present disclosure. A health risk is output by the health risk prediction device. The medical expense prediction device is the medical expense prediction device of the present disclosure. A predicted medical expense is output by the medical expense prediction device. The health estimated age prediction device is the health estimated age prediction device of the present disclosure. The health estimated age prediction device outputs an estimated health age.

[0087] In the composite system of the present disclosure, at least one of the health risk prediction device, the medical expense prediction device, and the health estimated age prediction device can communicate with each other. For example, as shown in FIG. 10, the health risk prediction device 10 of the present disclosure, the medical expense prediction device 20 of the present disclosure, and the health estimated age prediction device 30 of the present disclosure are connected via a communication line network 40. Note that FIG. 10 is merely an example, and for example, only the health risk prediction device 10 of the present disclosure and the medical expense prediction device 20 of the present disclosure may be connected via the communication line network 40, only the health risk prediction device 10 of the present disclosure and the health estimated age prediction device 30 of the present disclosure may be connected via the communication line network 40, or only the medical expense prediction device 20 of the present disclosure and the health estimated age prediction device 30 of the present disclosure may be connected via the communication line network 40.

[0088] [Embodiment 6] A procedure for predicting a health risk using the health risk prediction device of the present disclosure will be described with specific examples using Fig. 11 and Fig. 12. Fig. 11 is a diagram showing an example of a health risk (probability that a subject will contract a disease) output by the health risk prediction device of the present disclosure. Fig. 12 is a diagram showing an example of a health risk (probability that a subject's test value will be abnormal) output by the health risk prediction device of the present disclosure.

[0089] First, subject information is acquired in the health risk prediction device of the present disclosure. Next, the health risk prediction device of the present disclosure calculates the health risk of the subject from the subject information. When the health risk is, for example, the "probability that the subject will contract a disease," a prediction score may be calculated as in Table 1 below, and the health risk may be calculated from a correspondence table between the prediction score and the incidence rate that has been calculated in advance. The above-mentioned process is also the same when the health risk is, for example, the "probability that the subject's test value will be abnormal," as in Table 2 below.

[0090] [Table 1]

[0091] [Table 2]

[0092] Thereafter, the health risk prediction device of the present disclosure outputs, as the health risk, at least one of the probability that the subject will suffer from a disease and the probability that the test value of the subject will be an abnormal value (FIGS. 11 and 12). Note that FIG. 11 and FIG. 12 are merely examples and are not limited thereto.

[0093] [Embodiment 7] A procedure for predicting medical expenses using the medical expense prediction device of the present disclosure will be described with a specific example with reference to Fig. 13. Fig. 13 is a diagram showing an example of predicted medical expenses output by the medical expense prediction device of the present disclosure.

[0094] First, in the medical cost prediction device of the present disclosure, information including medical cost statistics and health risks for each disease is acquired. The medical cost statistics are, for example, as shown in Table 3 below. The health risks are, for example, health risks output by the above-mentioned health risk prediction device.

[0095] [Table 3]

[0096] Next, the medical cost prediction device of the present disclosure calculates the predicted medical cost of the subject from the information. At this time, the predicted medical cost is calculated from the product of the medical cost statistics and the health risk, for example, as shown in Table 4 below.

[0097] [Table 4]

[0098] Thereafter, the medical expense prediction device of the present disclosure outputs the predicted medical expenses (FIG. 13). As shown in FIG. 13, the calculation conditions and the like may be written together with the predicted medical expenses to be output. Furthermore, when the predicted medical expenses include predicted medical expenses for each disease, the medical expenses in the medical expense statistics are output as the predicted medical expenses for each disease. Note that FIG. 13 is merely an example and is not limited thereto.

[0099] [Embodiment 8] A procedure for predicting medical expenses using the estimated health age prediction device of the present disclosure will be described with specific examples using Fig. 14 and Fig. 15. Fig. 14 is a diagram showing an example of calculation of an estimated health age. Fig. 15 is a diagram showing an example of an estimated health age output by the estimated health age prediction device of the present disclosure.

[0100] First, the estimated health age prediction device of the present disclosure obtains the estimated medical expenses of the subject. Next, the estimated health age prediction device of the present disclosure calculates the estimated health age of the subject from the estimated medical expenses. At this time, the estimated health age is, for example, an estimated health age calculated based on a regression line or a regression curve consisting of ages and expected medical expenses for each age. The regression line or the regression curve may be, for example, a regression line or a regression curve as shown in FIG. 14. As shown in FIG. 14, for example, an estimated health age Y can be calculated based on the estimated medical expenses X.

[0101] Thereafter, the estimated health age prediction device of the present disclosure outputs the estimated health age (FIG. 15). As shown in FIG. 15, the estimated health age to be output may be accompanied by calculation conditions and the like.

[0102] [Embodiment 9] The program of the present disclosure may be recorded, for example, in a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable recording medium. The recording medium is not particularly limited, and may be, for example, a random access memory (RAM), a read-only memory (ROM), a hard disk (HD), a flash memory (for example, a USB flash memory, an SD / SDHC card, etc.), an optical disk (for example, a CD-R / CD-RW, a DVD-R / DVD-RW, a BD-R / BD-RE, etc.), a magneto-optical disk (MO), a floppy (registered trademark) disk (FD), etc. In addition, the program of the present disclosure (for example, also referred to as a programming product or a program product) may be, for example, in a form distributed from an external computer. The "distribution" may be, for example, distribution via a communication line network or distribution via a device connected by wire. The program of the present disclosure may be installed and executed in the device to which it is distributed, or may be executed without being installed.

[0103] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. The configuration and conditions of the present disclosure may be modified in various ways that can be understood by a person skilled in the art within the scope of the present disclosure.

[0104] <Additional Notes> Some or all of the above embodiments may be described as follows, but are not limited to the following: (Appendix 1) The method includes a subject information acquisition procedure, a health risk calculation procedure, and a health risk output procedure, The subject information acquisition step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A health risk prediction program for causing a computer to execute each of the above steps. (Appendix 2) The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs. The step of acquiring predicted medical cost calculation information includes acquiring information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, A medical cost prediction program for causing a computer to execute each of the above steps. (Appendix 3) The program described in Appendix 2, wherein the health risk is a health risk calculated by the health risk prediction program described in Appendix 1. (Appendix 4) The program according to claim 2 or 3, wherein the predicted medical expenses are calculated from the product of the medical expense statistics and the health risk. (Appendix 5) The program of any one of claims 2 to 4, wherein the health risk is the probability that the subject will suffer from a disease. (Appendix 6) The program of claim 5, wherein the predicted medical expenses are the sum of the predicted medical expenses calculated for each of the diseases. (Appendix 7) The method includes a procedure for obtaining predicted medical expenses, a procedure for calculating an estimated health age, and a procedure for outputting an estimated health age, The step of obtaining predicted medical expenses includes obtaining predicted medical expenses of a subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age. A health estimation age prediction program for causing a computer to execute each of the above steps. (Appendix 8) The program described in Appendix 7, wherein the predicted medical expenses are predicted medical expenses calculated by a medical expense prediction program described in any one of Appendixes 2 to 6. (Appendix 9) The program according to claim 7 or 8, wherein the estimated healthy age is calculated based on a regression line or regression curve consisting of age and expected medical expenses for each age. (Appendix 10) At least one of a health risk prediction program, a medical expense prediction program, and a health estimated age prediction program is included; The health risk prediction program is a program described in Appendix 1, The health risk prediction program outputs a health risk; The medical cost prediction program is a program described in any one of Supplementary Notes 2 to 6, The medical cost prediction program outputs predicted medical costs, The health estimated age prediction program is a program according to any one of appendices 7 to 9, The estimated health age prediction program outputs an estimated health age. Combined program. (Appendix 11) The present invention includes a subject information acquisition unit, a health risk calculation unit, and a health risk output unit, The subject information acquisition unit acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation unit calculates a health risk of the subject from the subject information, The health risk output unit outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be abnormal; Health risk prediction device. (Appendix 12) The present invention includes a predicted medical cost calculation information acquisition unit, a predicted medical cost calculation unit, and a predicted medical cost output unit, The predicted medical cost calculation information acquisition unit acquires information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation unit calculates predicted medical expenses of the subject from the information, The predicted medical cost output unit outputs the predicted medical cost. Medical cost prediction device. (Appendix 13) The device described in Appendix 12, wherein the health risk is a health risk calculated by the health risk prediction device described in Appendix 11. (Appendix 14) The device of claim 12 or 13, wherein the predicted medical expenses are predicted medical expenses calculated from the product of the medical expense statistics and the health risk. (Appendix 15) 15. The apparatus of any of claims 12 to 14, wherein the health risk is the probability that the subject will suffer from a disease. (Appendix 16) The device of claim 15, wherein the predicted medical expenses are a sum of predicted medical expenses calculated for each of the diseases. (Appendix 17) The present invention includes a predicted medical expense acquisition unit, a health estimated age calculation unit, and a health estimated age output unit, The predicted medical expenses acquisition unit acquires predicted medical expenses of the subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation unit calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output unit outputs the estimated health age. Health estimation and age prediction device. (Appendix 18) The device described in Appendix 17, wherein the predicted medical expenses are predicted medical expenses calculated by a medical expense prediction device described in any one of Appendixes 12 to 16. (Appendix 19) The device described in Appendix 17 or 18, wherein the estimated health age is a calculated estimated health age based on a regression line or regression curve consisting of age and expected medical expenses for each age. (Appendix 20) At least one of a health risk prediction device, a medical expense prediction device, and a health age prediction device, The health risk prediction device is the device described in Supplementary Note 11, The health risk prediction device outputs a health risk, The medical cost prediction device is a device according to any one of appendices 12 to 16, The medical cost prediction device outputs predicted medical costs, The health age prediction device is a device according to any one of Supplementary Notes 17 to 19, The estimated health age prediction device outputs an estimated health age. Complex system. (Appendix 21) The method includes a subject information acquisition step, a health risk calculation step, and a health risk output step, The subject information acquiring step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A health risk prediction method, wherein each of the steps is carried out by a computer. (Appendix 22) The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs, The predicted medical cost calculation information acquisition step acquires information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, A medical cost prediction method, wherein each of the steps is executed by a computer. (Appendix 23) The method of claim 23, wherein the health risk is a health risk calculated by the health risk prediction method of claim 22. (Appendix 24) The method of claim 22 or 23, wherein the predicted medical expenses are predicted medical expenses calculated from the product of the medical expense statistics and the health risk. (Appendix 25) 25. The method of any one of claims 22 to 24, wherein the health risk is the probability that the subject will suffer from a disease. (Appendix 26) The method of claim 25, wherein the predicted medical expenses are the sum of the predicted medical expenses calculated for each of the diseases. (Appendix 27) The method includes a step of obtaining a predicted medical expense, a step of calculating an estimated health age, and a step of outputting an estimated health age, The predicted medical expenses acquisition step acquires predicted medical expenses of the subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age, A health age prediction method, wherein each of the steps is executed by a computer. (Appendix 28) The method of claim 27, wherein the predicted medical expenses are predicted medical expenses calculated by a medical expense prediction method described in any one of claims 22 to 26. (Appendix 29) The method according to claim 27 or 28, wherein the estimated healthy age is calculated based on a regression line or regression curve consisting of age and expected medical expenses for each age. (Appendix 30) The method includes a subject information acquisition procedure, a health risk calculation procedure, and a health risk output procedure, The subject information acquisition step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A computer-readable recording medium having recorded thereon a health risk prediction program for causing a computer to execute each of the above procedures. (Appendix 31) The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs. The step of acquiring predicted medical cost calculation information includes acquiring information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, A computer-readable recording medium having recorded thereon a medical expense prediction program for causing a computer to execute each of the above procedures. (Appendix 32) The recording medium of claim 31, wherein the health risk is a health risk calculated by a program recorded in the recording medium of claim 30. (Appendix 33) The recording medium according to claim 31 or 32, wherein the predicted medical expenses are predicted medical expenses calculated from the product of the medical expense statistics and the health risk. (Appendix 34) 34. The recording medium of any one of appendices 31 to 33, wherein the health risk is the probability that the subject will suffer from a disease. (Appendix 35) The recording medium described in Appendix 34, wherein the predicted medical expenses are a sum of predicted medical expenses calculated for each of the diseases. (Appendix 36) The method includes a procedure for obtaining predicted medical expenses, a procedure for calculating an estimated health age, and a procedure for outputting an estimated health age, The step of obtaining predicted medical expenses includes obtaining predicted medical expenses of a subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age. A computer-readable recording medium having recorded thereon a health estimation age prediction program for causing a computer to execute each of the above procedures. (Appendix 37) The recording medium described in Appendix 36, wherein the predicted medical expenses are predicted medical expenses calculated by a program recorded in the recording medium described in any one of Appendixes 31 to 35. (Appendix 38) 38. The recording medium according to claim 36 or 37, wherein the estimated healthy age is calculated based on a regression line or regression curve consisting of age and expected medical expenses for each age. [Industrial Applicability]

[0105] According to the present disclosure, it is possible to provide a program capable of predicting future health-related predictions, a health risk prediction device, a medical expense prediction device, a health estimated age prediction device, a composite system, a health risk prediction method, a medical expense prediction method, a health estimated age prediction method, and a recording medium. The fields to which the present disclosure can be applied are not limited, and the program of the present disclosure is useful in various fields. [Explanation of symbols]

[0106] 10. Health risk prediction device 11. Target information acquisition department 12 Health Risk Calculation Department 13 Health Risk Output Unit 20 Medical Cost Prediction Device 21. Medical Cost Estimation Information Acquisition Department 22 Medical Cost Estimation Department 23 Predicted medical expenses output section 30 Health Estimation and Age Prediction Device 31 Medical Cost Estimation Department 32 Health Estimated Age Calculation Section 33 Health estimated age output section 101, 201, 301 CPU 102, 202, 302 Memory 103, 203, 303 Buses 104, 204, 304 storage device 105, 205, 305 Input Devices 106, 206, 306 Output Device 107, 207, 307 Communication devices

Claims

1. The method includes a subject information acquisition procedure, a health risk calculation procedure, and a health risk output procedure, The subject information acquisition step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A health risk prediction program for causing a computer to execute each of the above steps.

2. The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs. The step of acquiring predicted medical cost calculation information includes acquiring information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, A medical cost prediction program for causing a computer to execute each of the above steps.

3. The program according to claim 2, wherein the health risk is a health risk calculated by the health risk prediction program according to claim 1.

4. The program according to claim 2 , wherein the predicted medical expenses are calculated from a product of the medical expense statistics and the health risk.

5. The method includes a procedure for obtaining predicted medical expenses, a procedure for calculating an estimated health age, and a procedure for outputting an estimated health age, The step of obtaining predicted medical expenses includes obtaining predicted medical expenses of a subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age. A health estimation age prediction program for causing a computer to execute each of the above steps.

6. The program according to claim 5 , wherein the predicted medical expenses are predicted medical expenses calculated by the medical expense prediction program according to claim 2 .

7. At least one of a health risk prediction program, a medical expense prediction program, and a health estimated age prediction program is included; The health risk prediction program is a program according to claim 1 , The health risk prediction program outputs a health risk; The medical cost prediction program is a program according to any one of claims 2 to 4, The medical cost prediction program outputs predicted medical costs, The health age prediction program is a program according to claim 5 or 6, The estimated health age prediction program outputs an estimated health age. Combined program.

8. The present invention includes a subject information acquisition unit, a health risk calculation unit, and a health risk output unit, The subject information acquisition unit acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation unit calculates a health risk of the subject from the subject information, The health risk output unit outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be abnormal; Health risk prediction device.

9. The present invention includes a predicted medical cost calculation information acquisition unit, a predicted medical cost calculation unit, and a predicted medical cost output unit, The predicted medical cost calculation information acquisition unit acquires information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation unit calculates predicted medical expenses of the subject from the information, The predicted medical cost output unit outputs the predicted medical cost. Medical cost prediction device.

10. The apparatus according to claim 9 , wherein the health risk is a health risk calculated by a health risk prediction apparatus according to claim 8 .

11. The present invention includes a predicted medical expense acquisition unit, a health estimated age calculation unit, and a health estimated age output unit, The predicted medical expenses acquisition unit acquires predicted medical expenses of the subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation unit calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output unit outputs the estimated health age. Health estimation and age prediction device.

12. The device according to claim 11 , wherein the predicted medical expenses are predicted medical expenses calculated by a medical expense prediction device according to claim 9 .

13. At least one of a health risk prediction device, a medical expense prediction device, and a health age prediction device, The health risk prediction device is an apparatus according to claim 8 , The health risk prediction device outputs a health risk, The medical cost prediction device is an apparatus according to claim 9 or 10, The medical cost prediction device outputs predicted medical costs, The health age prediction device is an apparatus according to claim 11 or 12, The estimated health age prediction device outputs an estimated health age. Complex system.

14. The method includes a subject information acquisition step, a health risk calculation step, and a health risk output step, The subject information acquiring step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A health risk prediction method, wherein each of the steps is carried out by a computer.

15. The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs, The predicted medical cost calculation information acquisition step acquires information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, A medical cost prediction method, wherein each of the steps is executed by a computer.

16. The method according to claim 15, wherein the health risk is a health risk calculated by the health risk prediction method according to claim 14.

17. The method includes a step of obtaining a predicted medical expense, a step of calculating an estimated health age, and a step of outputting an estimated health age, The predicted medical expenses acquisition step acquires predicted medical expenses of the subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age, A health age prediction method, wherein each of the steps is executed by a computer.

18. The method according to claim 17, wherein the predicted medical expenses are predicted medical expenses calculated by the medical expense prediction method according to claim 15.

19. The method includes a subject information acquisition procedure, a health risk calculation procedure, and a health risk output procedure, The subject information acquisition step acquires subject information, The subject information includes health check information, medical interview information, and attribute information of the subject, The health risk calculation step calculates a health risk of the subject from the subject information, The health risk output step outputs the health risk, The health risk is at least one of the probability that the subject will suffer from a disease and the probability that the subject's test value will be an abnormal value; A computer-readable recording medium having recorded thereon a health risk prediction program for causing a computer to execute each of the above procedures.

20. The method includes a step of acquiring predicted medical cost calculation information, a step of calculating predicted medical costs, and a step of outputting predicted medical costs. The step of acquiring predicted medical cost calculation information includes acquiring information including medical cost statistics for each disease and a health risk of the subject, The predicted medical expenses calculation step calculates predicted medical expenses of the subject from the information, The predicted medical cost output step outputs the predicted medical cost, A computer-readable recording medium having recorded thereon a medical expense prediction program for causing a computer to execute each of the above procedures.

21. The recording medium according to claim 20, wherein the health risk is a health risk calculated by a program recorded on the recording medium according to claim 19.

22. The method includes a procedure for obtaining predicted medical expenses, a procedure for calculating an estimated health age, and a procedure for outputting an estimated health age, The step of obtaining predicted medical expenses includes obtaining predicted medical expenses of a subject, The predicted medical expenses are calculated from information including medical expense statistics for each disease and the health risk of the subject, The estimated health age calculation step calculates an estimated health age of the subject from the predicted medical expenses, The estimated health age output step outputs the estimated health age. A computer-readable recording medium having recorded thereon a health estimation age prediction program for causing a computer to execute each of the above procedures.

23. 23. The recording medium according to claim 22, wherein the predicted medical expenses are predicted medical expenses calculated by a program recorded on the recording medium according to claim 20.

Images