JP2024094291A - Health management system and health management method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a health management system capable of calculating a disease onset risk of a subject.

SOLUTION: A health management system 10 according to the embodiment is connected to a plurality of disease-onset risk primary calculation units 101A, 101B, 101C.... Each of the plurality of disease-onset risk primary calculation units 101A, 101B, 101C... acquires vital data of a subject and calculates a primary calculation value of a disease-onset risk of the subject by using correlations between the vital data and the disease-onset risk. The health management system 10 includes a disease-onset risk secondary calculation part 11 for calculating a secondary calculation value of the disease-onset risk of the subject by using correlations between a plurality of vital data and the disease-onset risk on the basis of the plurality of vital data of the subject acquired by the plurality of disease-onset risk primary calculation parts 101A, 101B, 101C....

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to a health management system and a health management method.

Measuring vital data of humans or animals has been proposed in the past (see, for example, Patent Documents 1 to 7).

Japanese Patent No. 6203765 Patent No. 6217787 Patent No. 6288485 Patent No. 6342095 Patent No. 6566241 Patent No. 6577761 Patent No. 7168270

One of the objectives of the present invention is to provide a health management system and health management method that can calculate a subject's risk of developing a disease.

The health management system according to the embodiment is a health management system connected to a plurality of disease onset risk primary calculation units, each of which acquires vital data of a subject and calculates a primary calculation value of the subject's disease onset risk using the correlation between the vital data and the disease onset risk, and the health management system includes a disease onset risk secondary calculation unit which calculates a secondary calculation value of the subject's disease onset risk using the correlation between the plurality of vital data and the disease onset risk based on the plurality of vital data of the subject acquired by the plurality of disease onset risk primary calculation units.

The health management system according to the embodiment may further include a diagnosis recommendation unit that recommends that the subject undergo a diagnosis at a medical institution when the subject is determined to be at risk of developing a disease based on the calculated secondary calculated value of the disease development risk.

The health management system according to the embodiment may further include a diagnosis result acquisition unit that acquires the diagnosis results when the subject is diagnosed at a medical institution.

The health management system according to the embodiment may further include a correction unit that compares the diagnosis result with the primary calculation value of the disease onset risk calculated by each of the multiple primary disease onset risk calculation units, and corrects the correlation used by each of the multiple primary disease onset risk calculation units so that the primary calculation value of the disease onset risk approaches the diagnosis result.

In the health management system according to the embodiment, each of the multiple disease development risk primary calculation units may calculate a primary calculation value of the disease development risk based on vital data and a threshold value.

In the health management system according to the embodiment, the correction unit may correct the threshold value based on the diagnosis result.

In the health management system according to the embodiment, each of the multiple disease development risk primary calculation units may calculate a primary calculation value of the disease development risk using the correlation between the rate of change of vital data and the disease development risk.

In the health management system according to the embodiment, the correction unit may correct the correlations used by each of the multiple primary disease development risk calculation units based on the diagnosis results.

The health management system according to the embodiment may further include a correction unit that compares the diagnosis result with the secondary calculation value of the disease onset risk calculated by the secondary disease onset risk calculation unit, and corrects the correlation used by the secondary disease onset risk calculation unit so that the secondary calculation value of the disease onset risk approaches the diagnosis result.

In the health management system according to the embodiment, the secondary disease development risk calculation unit may calculate a secondary disease development risk calculation value based on multiple vital data and a threshold value.

In the health management system according to the embodiment, the correction unit may correct the threshold value based on the diagnosis result.

In the health management system according to the embodiment, the secondary disease development risk calculation unit may calculate a secondary calculated value of the disease development risk using the correlation between the rate of change of multiple vital data and the disease development risk.

In the health management system according to the embodiment, the correction unit may correct the correlation used by the secondary disease development risk calculation unit based on the diagnosis result.

In the health management system according to the embodiment, the correlations used by each of the multiple disease onset risk primary calculation units may be associated with a subject.

In the health management system according to the embodiment, the correlation used by the secondary disease onset risk calculation unit may be associated with a subject.

In the health management system according to the embodiment, the secondary disease development risk calculation unit may receive input of subjective symptoms from the subject, and calculate a secondary calculated value of the subject's disease development risk using multiple vital data and correlations between the subjective symptoms and disease development risk.

The health management system according to the embodiment may further include a correlation storage unit that stores correlations between multiple vital data and disease development risk, and the secondary disease development risk calculation unit may access the correlation storage unit to calculate a secondary calculation value of the disease development risk.

In the health management system according to the embodiment, multiple primary disease development risk calculation units may be included in multiple vital data acquisition devices, respectively.

In the health management system according to the embodiment, multiple vital data acquisition devices may be installed in a building in which the subject is present.

In the health management system according to the embodiment, multiple vital data acquisition devices may be attached to the subject.

In the health management system according to the embodiment, the subject may be a human or an animal.

In the health management system according to the embodiment, the type of disease in the first calculation of the disease development risk may be the same as the type of disease in the second calculation of the disease development risk.

In the health management system according to the embodiment, the type of disease in the first calculated value of the disease development risk may be different from the type of disease in the second calculated value of the disease development risk.

The health management system according to the embodiment may further include a vital data correction unit that receives vital data from each of the multiple disease onset risk primary calculation units and corrects missing vital data and/or reduced accuracy of the vital data based on vital data previously acquired by the same disease onset risk primary calculation unit.

The health management system according to the embodiment may further include a vital data correction unit that receives vital data from each of the multiple primary disease onset risk calculation units and corrects missing vital data and/or reduced accuracy in one of the multiple primary disease onset risk calculation units based on vital data simultaneously acquired by another primary disease onset risk calculation unit.

The health management system according to the embodiment may further include an estimation unit that receives vital data from each of the multiple disease onset risk primary calculation units and estimates different types of vital data based on the received vital data.

In the health management system according to the embodiment, the vital data may include at least one of the subject's gender, age, height, and weight.

In the health management system according to the embodiment, the vital data may include at least one of the subject's medical history and family history.

In the health management system according to the embodiment, the vital data may include at least one of the subject's heart rate, breathing, body movement, body temperature, ambient temperature, and ambient humidity.

In the health management system according to the embodiment, the vital data may include at least one of the subject's blood pressure, biochemical test results, and hematology test results.

In the health management system according to the embodiment, the vital data may include the subject's ingested foods.

In the health management system according to the embodiment, the vital data may include the subject's history of treatment and drug administration.

In the health management system according to the embodiment, the vital data may include genetic information of the subject.

The health management method according to the embodiment includes a health management system acquiring a primary calculation value of the disease development risk of the subject, the primary calculation value being calculated by each of a plurality of primary disease development risk calculation units acquiring vital data of the subject and using the correlation between the vital data and the disease development risk, and the health management system calculating a secondary calculation value of the disease development risk of the subject based on the plurality of vital data of the subject acquired by the plurality of primary disease development risk calculation units, using the correlation between the plurality of vital data and the disease development risk.

The health management method according to the embodiment may further include the health management system recommending that the subject undergo a diagnosis at a medical institution when the health management system determines that the subject is at risk of developing a disease based on the calculated secondary calculated value of the disease development risk.

The health management method according to the embodiment may further include the health management system acquiring a diagnosis result when the subject is diagnosed at a medical institution.

The health management method according to the embodiment may further include a health management system comparing the diagnosis result with the primary calculation value of the disease onset risk calculated by each of the multiple primary disease onset risk calculation units, and correcting the correlation used by each of the multiple primary disease onset risk calculation units so that the primary calculation value of the disease onset risk approaches the diagnosis result.

In the health management method according to the embodiment, each of the multiple disease development risk primary calculation units may calculate a primary calculation value of the disease development risk based on vital data and a threshold value.

In the health management method according to the embodiment, the threshold may be modified based on the diagnosis results when making the correction.

In the health management method according to the embodiment, each of the multiple disease development risk primary calculation units may calculate a primary calculation value of the disease development risk using the correlation between the rate of change in vital data and the disease development risk.

In the health management method according to the embodiment, the correction may involve correcting the correlations used by each of the multiple disease onset risk primary calculation units based on the diagnosis results.

The health management method according to the embodiment may further include a health management system comparing the diagnosis result with the secondary calculated value of the disease development risk, and correcting the correlation used to calculate the secondary calculated value of the disease development risk so that the secondary calculated value of the disease development risk approaches the diagnosis result.

In the health management method according to the embodiment, a secondary calculation value of the disease development risk may be calculated based on multiple vital data and a threshold value.

In the health management method according to the embodiment, the modification may be modification of the threshold value based on the diagnosis result.

In the health management method according to the embodiment, a secondary calculation value of the disease development risk may be calculated using the correlation between the rate of change of multiple vital data and the disease development risk.

In the health management method according to the embodiment, the correction may involve correcting the correlation used to calculate the secondary calculated value of the disease onset risk based on the diagnosis result.

In the health management method according to the embodiment, the correlations used by each of the multiple disease onset risk primary calculation units may be associated with a subject.

In the health management method according to the embodiment, the correlation used to calculate the secondary calculated value of the disease onset risk may be associated with the subject.

In the health management method according to the embodiment, the health management system may receive input of subjective symptoms from a subject, and calculate a secondary calculated value of the subject's disease development risk using multiple vital data and correlations between the subjective symptoms and disease development risk.

In the health management method according to the embodiment, multiple disease onset risk primary calculation units may be included in multiple vital data acquisition devices, respectively.

In the health management method according to the embodiment, multiple vital data acquisition devices may be installed in a building in which the subject is present.

In the health management method according to the embodiment, multiple vital data acquisition devices may be attached to the subject.

In the health management method according to the embodiment, the subject may be a human or an animal.

In the health management method according to the embodiment, the type of disease in the first calculated value of the disease development risk may be the same as the type of disease in the second calculated value of the disease development risk.

In the health management method according to the embodiment, the type of disease in the first calculated value of the disease development risk may be different from the type of disease in the second calculated value of the disease development risk.

The health management method according to the embodiment may further include a health management system receiving vital data from each of the multiple disease onset risk primary calculation units, and correcting missing vital data and/or reduced accuracy of the vital data based on vital data previously acquired by the same disease onset risk primary calculation unit.

The health management method according to the embodiment may further include a health management system receiving vital data from each of the multiple primary disease onset risk calculation units, and correcting missing vital data and/or reduced accuracy in one of the multiple primary disease onset risk calculation units based on vital data simultaneously acquired by another primary disease onset risk calculation unit.

The health management method according to the embodiment may further include the health management system receiving vital data from each of the multiple disease onset risk primary calculation units and estimating different types of vital data based on the received vital data.

In the health management method according to the embodiment, the vital data may include at least one of the subject's gender, age, height, and weight.

In the health management method according to the embodiment, the vital data may include at least one of the subject's medical history and family history.

In the health management method according to the embodiment, the vital data may include at least one of the subject's heart rate, breathing, body movement, body temperature, ambient temperature, and ambient humidity.

In the health management method according to the embodiment, the vital data may include at least one of the subject's blood pressure, biochemical test results, and hematology test results.

In the health management method according to the embodiment, the vital data may include the subject's ingested foods.

In the health management method according to the embodiment, the vital data may include the subject's history of treatment and drug administration.

In the health management method according to the embodiment, the vital data may include genetic information of the subject.

The present invention provides a health management system and a health management method that can calculate a subject's risk of developing a disease.

FIG. 1 is a schematic diagram showing a health management system according to an embodiment. 2 is a flowchart showing a health management system according to an embodiment. 2 is a flowchart showing a health management system according to an embodiment.

As shown in FIG. 1, the health management system 10 according to the embodiment is connected to a plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc. Each of the plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc. acquires vital data of a subject, and calculates a primary calculation value of the subject's disease onset risk using the correlation between the vital data and the disease onset risk. The health management system 10 includes a disease onset risk secondary calculation unit 11 that calculates a secondary calculation value of the subject's disease onset risk using the correlation between the plurality of vital data and the disease onset risk based on the plurality of vital data of the subject acquired by the plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc.

The subject may be a human or an animal. The health management system 10 may be a computer system.

Vital data is any data related to the survival of a person or animal, and is not limited to this. Examples of vital data include the sex, age, height, weight, and pregnancy of a person or animal. Examples of vital data include the medical history and family history of a person or animal. Here, medical history refers to the medical history of a person or animal, and family history refers to the medical history of the family of the person or animal being managed. Family history refers to the medical history of the person or animal's parents, siblings, children, and relatives, for example. When the person or animal being managed is a plurality of people or animals related by blood, the medical history of a certain person may be automatically acquired as the family history of those related by blood to that person. Examples of vital data include the treatment and drug administration history of the person or animal.

Furthermore, examples of vital data include the human or animal's heart rate, respiration, amount of activity, body temperature, ambient temperature, and ambient humidity. An example of the amount of activity is body movement. Examples of body movement include the number of steps, distance traveled, and speed of movement. Body movement may be the movement of a part of the human or animal's body. Further, examples of vital data include the human or animal's blood pressure, biochemical test results, and hematology test results.

Examples of biochemical test results include total protein amount (albumin and globulin), albumin amount, albumin to globulin ratio, total bilirubin amount, direct bilirubin amount, AST amount, ALT amount, LDH amount, alkaline phosphatase amount, γ-GTP amount, cholinesterase amount, CPK amount, amylase amount, glucose amount (blood glucose level), HbA1c amount, sodium amount, potassium amount, chloride amount, CRP amount, triglyceride amount, total cholesterol amount, HDL-C amount, urea nitrogen amount, creatinine amount, uric acid amount, and iron amount.

Examples of hematology test results include white blood cell count, red blood cell count, hemoglobin count, hematocrit count, platelet count, neutrophil count, lymphocyte count, monocyte count, eosinophil count, basophil count, prothrombin time, activated partial thromboplastin time, fibrinogen count, and D-dimer count.

Another example of vital data is the food consumed by a person or animal. Examples of food consumed at breakfast, lunch, dinner, and snacks, as well as beverages including milk drinks, tea, coffee, juice, and alcoholic beverages. Furthermore, vital data may include data such as the amount of sugar, salt, fat, and calories of the food consumed.

Another example of vital data is genetic information of a person or animal.

The multiple disease development risk primary calculation units 101A, 101B, 101C... may be included in multiple vital data acquisition devices 111A, 111B, 111C... respectively. Examples of the multiple vital data acquisition devices 111A, 111B, 111C include a height gauge, a weight scale, a heart rate monitor, a respirometer, a body movement sensor, a pedometer, a moving distance sensor, a moving speed sensor, a blood pressure monitor, a biochemical testing device, a hematology testing device, a genetic testing device, a microphone, a radar sensor, a body temperature sensor, an image sensor, a camera, and a mattress sensor. Each of the multiple vital data acquisition devices 111A, 111B, 111C may be a global positioning system (GPS) receiver that acquires the number of steps, moving distance, and moving speed indoors and outdoors. For example, the multiple vital data acquisition devices 111A, 111B, 111C... may each measure different vital data. For example, each of the multiple vital data acquisition devices 111A, 111B, 111C, etc. may measure vital data in a non-contact manner.

Each of the multiple vital data acquisition devices 111A, 111B, and 111C may be disposed in a building in which a person or an animal exists. Examples of buildings include residences such as detached houses and apartment buildings, as well as commercial and public facilities such as accommodation facilities, dormitories, company housing, stores, concert halls, art galleries, museums, aquariums, nursing homes, hospitals, offices, and factories. Each of the multiple vital data acquisition devices 111A, 111B, and 111C may be disposed in a room in the building, such as a living room, bedroom, washroom, or toilet. Each of the multiple vital data acquisition devices 111A, 111B, and 111C may be disposed along the movement of the person or animal. Each of the multiple vital data acquisition devices 111A, 111B, and 111C may be attached to the person or animal. Each of the multiple vital data acquisition devices 111A, 111B, and 111C may be a wearable terminal.

The diseases for which the risk of onset is calculated by each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc. are not particularly limited. Examples of diseases include heart failure, dementia, depression, hypertension, diabetes, dyslipidemia, sleep apnea syndrome, chronic obstructive pulmonary disease, glaucoma, and heat stroke. For example, the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc. each calculate a primary calculation value of the risk of onset for a different disease. Each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc. calculates a primary calculation value of the risk of onset of a disease for a person or animal based on the measured vital data of the person or animal. For example, there is a negative correlation between the number of steps and chronic diseases such as diabetes and hypertension. Therefore, the primary calculation value of the risk of onset of a chronic disease may be calculated based on the number of steps. For example, there is a negative correlation between the frequency of going out and dementia. Therefore, the primary calculation value of the risk of onset of dementia may be calculated based on the frequency of going out. For example, there is a positive correlation between the repetition of the same behavior and dementia. Therefore, a primary calculation value for the risk of developing dementia may be calculated based on the frequency with which the same behavior is repeated.

For example, by photographing the subject's body surface using an image sensor or camera, it is possible to observe the subject's blood vessels without contact and measure the subject's blood pressure, heart rate, heart rate variability, blood oxygen level, respiratory rate, sympathetic stress, parasympathetic activity, pulse respiratory index, hemoglobin content, hemoglobin A1C value, and total cholesterol. Blood pressure correlates with heart disease, heart attack, and stroke. Blood oxygen level correlates with chronic disease, lung disease, heart failure, sleep apnea, anemia, and exposure to high altitude, and hypoxemia leads to headaches, tachycardia, coughing, shortness of breath, wheezing, confusion, and pale skin and mucous membranes. Respiratory rate correlates with metabolic abnormalities. Tachycardia detected by heart rate measurement correlates with infection, dehydration, stress, anxiety, thyroid disorders, shock, anemia, and heart disease. Abnormalities in heart rate variability correlate with stress and cardiac events. Low hemoglobin correlates with anemia, vitamin deficiencies, bleeding, and chronic disease. Hemoglobin A1C correlates with diabetes. Cholesterol levels correlate with heart disease and stroke.

For example, by using a radar sensor, it is possible to measure the breathing and heart rate of a subject without contact. Based on the measured breathing and heart rate values, it is possible to calculate the risk of developing sleep apnea syndrome. In addition, because depression, Parkinson's disease, bipolar disorder, and dementia affect the voice, it is possible to calculate the risk of developing depression, Parkinson's disease, bipolar disorder, and dementia by recording the subject's voice with a microphone. In addition, it is possible to measure the breathing of a subject while sleeping with a mattress sensor and calculate the risk of developing heart failure, which is correlated with breathing.

For example, each of the multiple disease onset risk primary calculation units 101A, 101B, 101C... calculates how many times the disease onset risk of the managed person or animal is compared to a person or animal whose vital data value is within the threshold of the standard range. Alternatively, each of the multiple disease onset risk primary calculation units 101A, 101B, 101C... calculates how many times the disease onset risk of the managed person or animal is compared to a person or animal whose rate of change in vital data over time is within the threshold of the standard range. For example, each of the multiple disease onset risk primary calculation units 101A, 101B, 101C... calculates the disease onset risk according to the vital data of the managed person or animal. For example, if the managed person or animal has a high sugar intake or a high blood sugar level, at least one of the multiple disease onset risk primary calculation units 101A, 101B, 101C... calculates the risk of diabetes onset according to the vital data.

The vital data acquisition devices 111A, 111B, 111C... may each further include a correlation storage unit 102A, 102B, 102C... that stores the correlation between vital data and disease development risk. The primary disease development risk calculation units 101A, 101B, 101C... may each access the correlation storage units 102A, 102B, 102C... to calculate a primary calculation value of disease development risk based on the measured vital data of a person or animal and the correlation between the vital data and disease development risk. The correlation may be associated with an individual subject.

The correlation between the vital data and the disease development risk is not particularly limited. The correlation storage units 102A, 102B, 102C, etc. each store, for example, an algorithm that defines the correlation between the vital data and the disease development risk. The correlation between the vital data and the disease development risk is given, for example, by the following formula (1).
y = f(x) (1)

In equation (1), x represents an independent variable of vital data, and y represents a dependent variable of the risk of developing a certain disease. Correlation storage units 102A, 102B, 102C, etc. each store a correlation between vital data and disease development risk for each disease. The correlation between vital data and disease development risk is acquired in advance. For example, the vital data of a large number of subjects and the disease development records of the subjects can be statistically analyzed to acquire the correlation between vital data and disease development risk in advance, and the correlation can be stored in each of correlation storage units 102A, 102B, 102C, etc. For example, when the vital data is blood pressure, the correlation between vital data and disease development risk is set so that the higher the blood pressure, the higher the risk of developing diabetes.

The vital data acquisition devices 111A, 111B, 111C, etc. may further include primary calculation value storage units 103A, 103B, 103C, etc. that store the primary calculation values of the disease onset risk calculated by the disease onset risk primary calculation units 101A, 101B, 101C, etc., respectively.

The vital data acquisition devices 111A, 111B, 111C, etc. may be connected to an output device 122. The output device 122 may output the primary calculation value of the disease onset risk calculated by the disease onset risk primary calculation units 101A, 101B, 101C, etc. Examples of the output device 122 include a display and a speaker. The display may be built into a mirror display or a tablet. The speaker may be a smart speaker.

The disease onset risk secondary calculation unit 11 of the health management system 10 acquires multiple vital data from multiple vital data acquisition devices 111A, 111B, 111C, etc. The health management system 10 may be connected to the multiple vital data acquisition devices 111A, 111B, 111C, etc. by wire or wirelessly. The health management system 10 may be connected to the multiple vital data acquisition devices 111A, 111B, 111C, etc. via a network. The health management system 10 may be located close to the multiple vital data acquisition devices 111A, 111B, 111C, etc., or may be located remotely.

The disease onset risk secondary calculation unit 11 calculates a secondary calculation value of the subject's disease onset risk based on the multiple vital data of the subject acquired by the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., using the correlation between the multiple vital data and the disease onset risk. Since the disease onset risk secondary calculation unit 11 calculates the disease onset risk based on the multiple vital data, it calculates the disease onset risk with higher accuracy than each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc.

The disease whose risk of onset is calculated by the disease onset secondary calculation unit 11 is not particularly limited. Examples of diseases include cancer, diabetes, ischemic heart disease, dementia, high blood pressure, arrhythmia, stroke, and heart failure. For example, the disease onset secondary calculation unit 11 may calculate the risk of onset for the same disease as at least one of the multiple disease onset primary calculation units 101A, 101B, 101C, etc. The disease onset secondary calculation unit 11 may also calculate the risk of onset for a disease different from the diseases whose risk of onset is calculated by the multiple disease onset primary calculation units 101A, 101B, 101C.

For example, the disease onset risk secondary calculation unit 11 calculates how many times the risk of disease onset of the managed person or animal is compared to a person or animal whose respective values of multiple vital data are within the threshold of the standard range. Alternatively, the disease onset risk secondary calculation unit 11 calculates how many times the risk of disease onset of the managed person or animal is compared to a person or animal whose respective rate of change of multiple vital data over time is within the threshold of the standard range. For example, the disease onset risk secondary calculation unit 11 calculates the disease onset risk according to the vital data of the managed person or animal. For example, if the managed person or animal has a high sugar intake or a high blood sugar level, the disease onset risk secondary calculation unit 11 calculates the risk of diabetes onset according to the vital data.

The health management system 10 may further include a correlation storage unit 12 that stores correlations between multiple vital data and disease development risk. The secondary disease development risk calculation unit 11 may access the correlation storage unit 12 and calculate a secondary calculation value of disease development risk based on multiple vital data acquired from multiple vital data acquisition devices 111A, 111B, 111C, etc. and the correlations between the multiple vital data and disease development risk. The correlations may be associated with individual subjects.

The correlation between the plurality of vital data and the disease development risk is not particularly limited. The correlation storage unit 12 stores, for example, an algorithm that defines the correlation between the plurality of vital data and the disease development risk. The correlation between the plurality of vital data and the disease development risk is given, for example, by the following formula (2).
z = f ( _v1 , _v2 , _v3 , ..., _vn ) (2)

In formula (2), n represents a natural number, v _n represents n independent variables of vital data, and z represents a dependent variable of the risk of developing a certain disease. The correlation storage unit 12 stores the correlation between a plurality of vital data and the disease development risk for each disease. The correlation between the plurality of vital data and the disease development risk is acquired in advance. For example, the correlation between the plurality of vital data and the disease development risk is acquired in advance by statistically analyzing a plurality of vital data of a large number of subjects and the disease development record of the subject, and is stored in the correlation storage unit 12. For example, when the vital data is blood pressure, the correlation between the vital data and the disease development risk is set so that the higher the blood pressure, the higher the risk of developing diabetes.

The disease onset risk secondary calculation unit 11 may calculate the onset risk of another disease related to the disease based on the calculated onset risk of the disease. For example, the correlation storage unit 12 stores the correlation between the onset risk of a disease and the onset risk of another disease. The disease onset risk secondary calculation unit 11 may access the correlation storage unit 12 and calculate the onset risk of another disease based on the calculated onset risk of the disease and the correlation between the onset risk of the disease and the onset risk of the other disease. The correlation may be associated with an individual subject.

The correlation between the risk of developing a certain disease and the risk of developing another disease is not particularly limited. The correlation storage unit 12 stores, for example, an algorithm that defines the correlation between the risk of developing a certain disease and the risk of developing another disease. The correlation between the risk of developing a certain disease and the risk of developing another disease is given, for example, by the following formula (3).
d = f(z) (3)

In formula (3), z represents an independent variable of the risk of developing a certain disease, and z represents a dependent variable of the risk of developing another disease. The correlation storage unit 12 stores the correlation between the risk of developing a certain disease and the risk of developing another disease for each risk of developing a certain disease. The correlation between the risk of developing a certain disease and the risk of developing another disease is acquired in advance. For example, the history of developing a certain disease in a large number of subjects and the history of developing another disease in the subjects are statistically analyzed to acquire the risk of developing a certain disease and the risk of developing another disease in advance, and are stored in the correlation storage unit 12. For example, when a certain disease is diabetes, the correlation between the risk of developing a certain disease and the risk of developing another disease is set so that the higher the risk of developing diabetes, the higher the risk of developing heart failure.

The disease onset risk secondary calculation unit 11 may receive input of subjective symptoms from the subject, and may calculate a secondary calculation value of the subject's disease onset risk using multiple vital data and correlations between subjective symptoms and disease onset risk. The disease onset risk secondary calculation unit 11 of the health management system 10 acquires subjective symptoms, for example, via a subjective symptom input device 121. The health management system 10 may be connected to the subjective symptom input device 121 by wire or wirelessly. The health management system 10 may be connected to the subjective symptom input device 121 via a network. The health management system 10 may be located close to the subjective symptom input device 121, or may be located remotely.

The correlation between the multiple vital data, the subjective symptoms, and the disease development risk is not particularly limited. The correlation storage unit 12 stores, for example, an algorithm that defines the correlation between the multiple vital data, the subjective symptoms, and the disease development risk. The correlation between the multiple vital data, the subjective symptoms, and the disease development risk is given, for example, by the following formula (4).
z = f ( _v1 , _v2 , _v3 , ..., _vn , w) (4)

In formula (4), n represents a natural number, _vn represents n independent variables of vital data, w represents an independent variable of subjective symptoms, and z represents a dependent variable of the risk of developing a certain disease. The correlation storage unit 12 stores the correlation between multiple vital data, subjective symptoms, and disease development risk for each disease. The correlation between multiple vital data, subjective symptoms, and disease development risk is acquired in advance. For example, multiple vital data and subjective symptoms of multiple subjects and the disease development records of the subjects are statistically analyzed to acquire the correlation between multiple vital data, subjective symptoms, and disease development risk in advance, and store it in the correlation storage unit 12.

The health management system 10 may further include a secondary calculation value storage unit 13 that stores the secondary calculation value of the disease onset risk calculated by the disease onset risk secondary calculation unit 11. The output device 122 may output the secondary calculation value of the disease onset risk calculated by the disease onset risk secondary calculation unit 11.

The health management system 10 may further include a diagnosis recommendation unit 14 that recommends the subject to receive a diagnosis at a medical institution when the subject is determined to have a disease development risk based on the secondary calculation value of the disease development risk calculated by the disease development risk secondary calculation unit 11. For example, when the secondary calculation value of the disease development risk is equal to or greater than a threshold, the subject is determined to have a disease development risk. The diagnosis recommendation unit 14 may be the one that makes the judgment, or the diagnosis recommendation unit 14. The diagnosis recommendation unit 14 recommends the subject to receive a diagnosis at a medical institution via the output device 122. The diagnosis recommendation unit 14 may transmit the recommendation that the subject receive a diagnosis at a medical institution to a person who manages the health of the subject, such as an industrial physician of an organization such as a company to which the subject belongs. In this case, each of the multiple vital data acquisition devices 111A, 111B, and 111C may be located in a company house. The output device 122 may be connected to the health management system 10 by wire or wirelessly. The output device 122 may be connected to the health management system 10 via a network. The output device 122 may be located near the health management system 10 or may be located remotely.

The health management system 10 may further include a diagnostic result acquisition unit 15 that acquires diagnostic results when the subject is diagnosed at a medical institution. The diagnostic result includes, for example, the presence or absence of a disease in the subject, the degree of the disease in the subject, and the possibility of the disease in the subject. The diagnostic result acquisition unit 15 of the health management system 10 acquires the diagnostic result via, for example, a diagnostic result input device 123. The health management system 10 may be connected to the diagnostic result input device 123 by wire or wirelessly. The health management system 10 may be connected to the diagnostic result input device 123 via a network. The health management system 10 may be located close to the diagnostic result input device 123 or may be located in a remote location. The transmission of the diagnostic result to the diagnostic result acquisition unit 15 or the input of the diagnostic result to the diagnostic result input device 123 may be performed by the subject or by the medical institution. The diagnostic result obtained by the online diagnosis may be input to the diagnostic result input device 123.

The health management system 10 may further include a correction unit 16 that compares the diagnosis result acquired by the diagnosis result acquisition unit 15 with the primary calculation value of the disease onset risk calculated by each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., and corrects the threshold value and/or correlation used by each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc. so that the primary calculation value of the disease onset risk approaches the diagnosis result.

The correction unit 16, for example, compares the primary calculation value of the disease development risk stored in at least one of the multiple primary calculation value storage units 103A, 103B, 103C, etc. with the diagnosis result acquired by the diagnosis result acquisition unit 15. If the primary calculation value of the disease development risk is low compared to the diagnosis result, the correction unit 16 corrects the threshold and/or correlation used in calculating the primary calculation value of the disease development risk so that the primary calculation value of the disease development risk becomes high. If the primary calculation value of the disease development risk is high compared to the diagnosis result, the correction unit 16 corrects the threshold and/or correlation used in calculating the primary calculation value of the disease development risk so that the primary calculation value of the disease development risk becomes low.

The correction unit 16 may compare the diagnosis result acquired by the diagnosis result acquisition unit 15 with the secondary calculation value of the disease onset risk calculated by the secondary disease onset risk calculation unit 11, and correct the threshold value and/or correlation used by the secondary disease onset risk calculation unit 11 so that the secondary calculation value of the disease onset risk approaches the diagnosis result.

The correction unit 16, for example, compares the secondary calculated value of the disease development risk stored in the secondary calculated value storage unit 13 with the diagnosis result acquired by the diagnosis result acquisition unit 15. If the secondary calculated value of the disease development risk is low compared to the diagnosis result, the correction unit 16 corrects the threshold and/or correlation used in calculating the secondary calculated value of the disease development risk so that the secondary calculated value of the disease development risk becomes high. If the secondary calculated value of the disease development risk is high compared to the diagnosis result, the correction unit 16 corrects the threshold and/or correlation used in calculating the secondary calculated value of the disease development risk so that the secondary calculated value of the disease development risk becomes low.

When the correction unit 16 corrects the threshold and/or correlation used in calculating the secondary calculated value of the disease development risk so that the secondary calculated value of the disease development risk becomes higher, the correction unit 16 may correct the insurance premium for the disease to be higher. Also, when the correction unit 16 corrects the threshold and/or correlation used in calculating the secondary calculated value of the disease development risk so that the secondary calculated value of the disease development risk becomes lower, the correction unit 16 may correct the insurance premium for the disease to be lower.

The health management system 10 may further include a control unit 17 that controls each of the multiple vital data acquisition devices 111A, 111B, and 111C. For example, the control unit 17 instructs the vital data acquisition device to increase the frequency with which the vital data acquisition device used to calculate the risk of developing a disease determined to be present or possible based on the diagnosis result acquired by the diagnosis result acquisition unit 15 acquires vital data. The control unit 17 also instructs the vital data acquisition device to decrease the frequency with which the vital data acquisition device used to calculate the risk of developing a disease other than the disease determined to be present or possible acquires vital data. The control unit 17 also instructs the vital data acquisition device to decrease the frequency with which the vital data acquisition device used to calculate the risk of developing a disease determined to be absent or possible acquires vital data.

The control unit 17 may, for example, instruct the vital data acquisition device to improve the environment in which the vital data acquisition device measures vital data used to calculate the risk of developing a disease that is determined to be present or possible based on the diagnosis result acquired by the diagnosis result acquisition unit 15.

The control unit 17 may instruct the vital data acquisition device to delete or compress a primary calculation value of disease development risk stored in a primary calculation value storage unit of the vital data acquisition device used to calculate the risk of development of a disease other than a disease determined to be present or possible in the diagnosis result. The control unit 17 may also instruct the vital data acquisition device to delete or compress a primary calculation value of disease development risk stored in a primary calculation value storage unit of the vital data acquisition device used to calculate the risk of development of a disease determined to be absent or possible.

The health management system 10 may further include a vital data correction unit 18 that receives vital data from each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., and corrects missing and/or reduced accuracy of the vital data based on vital data previously acquired by the same disease onset risk primary calculation unit. The vital data correction unit 18 may receive vital data from each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., and correct missing and/or reduced accuracy of the vital data in one of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., based on vital data simultaneously acquired by another disease onset risk primary calculation unit.

The control unit 17 may output to the output device 122 information about a vital data acquisition device that is experiencing a loss of vital data and/or a decrease in accuracy, and may recommend repair, replacement, or relocation of the vital data acquisition device.

The health management system 10 may further include an estimation unit 19 that receives vital data from each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., and estimates different types of vital data based on the received vital data. For example, the estimation unit 19 may estimate blood pressure vital data based on heart rate vital data. The disease onset risk secondary calculation unit 11 may calculate a secondary calculation value of the target's disease onset risk using the correlation between the multiple vital data and the disease onset risk based on the vital data estimated by the estimation unit 19 and the multiple vital data of the target acquired by the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc.

Next, a health management method according to an embodiment will be described with reference to FIG. 2. In step S101, a plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc. included in a plurality of vital data acquisition devices 111A, 111B, 111C, etc. acquire vital data. In step S102, the plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc. read out correlations from correlation storage units 102A, 102B, 102C, etc. In step S103, the plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc. calculate a primary calculation value of disease onset risk using correlations based on vital data. The plurality of disease onset risk primary calculation units 101A, 101B, 101C, etc. store the calculated primary calculation value of disease onset risk in primary calculation value storage units 103A, 103B, 103C, etc.

In step S104, optionally, the vital data correction unit 18 receives vital data from each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., and corrects missing vital data and/or reduced accuracy of the vital data based on vital data previously acquired by the same disease onset risk primary calculation unit. Alternatively, the vital data correction unit 18 corrects missing vital data and/or reduced accuracy of the vital data in one of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., based on vital data simultaneously acquired by another disease onset risk primary calculation unit. In step S105, optionally, the estimation unit 19 estimates different types of vital data based on the vital data received from each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc.

In step S106, the disease onset risk secondary calculation unit 11 reads out the correlation from the correlation storage unit 12. In step S107, the disease onset risk secondary calculation unit 11 accepts input of subjective symptoms from the subject. In step S108, the disease onset risk secondary calculation unit 11 calculates a secondary calculation value of the disease onset risk using the correlation based on the multiple vital data and subjective symptoms received from the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc. The multiple vital data may be vital data corrected by the vital data correction unit 18. The multiple vital data may include vital data estimated by the estimation unit 19. The disease onset risk secondary calculation unit 11 stores the calculated secondary calculation value of the disease onset risk in the secondary calculation value storage unit 13. In step S109, if it is determined that the subject is at risk of developing a disease based on the secondary calculated value of the disease development risk calculated by the disease development risk secondary calculation unit 11, the diagnosis recommendation unit 14 recommends that the subject receive a diagnosis at a medical institution. In step S110, the diagnosis result acquisition unit 15 acquires the diagnosis result when the subject is diagnosed at a medical institution.

In step S111, the correction unit 16 compares the diagnosis result acquired by the diagnosis result acquisition unit 15 with the primary calculation value of the disease onset risk calculated by each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc., and corrects the threshold value and/or correlation used by each of the multiple disease onset risk primary calculation units 101A, 101B, 101C, etc. so that the primary calculation value of the disease onset risk approaches the diagnosis result. In addition, the correction unit 16 compares the diagnosis result acquired by the diagnosis result acquisition unit 15 with the secondary calculation value of the disease onset risk calculated by the disease onset risk secondary calculation unit 11, and corrects the threshold value and/or correlation used by the disease onset risk secondary calculation unit 11 so that the secondary calculation value of the disease onset risk approaches the diagnosis result.

In step S112, the control unit 17 instructs the vital data acquisition device, for example, to increase the frequency with which the vital data acquisition device used to calculate the risk of developing a disease determined to be present or possible based on the diagnosis result acquired by the diagnosis result acquisition unit 15 acquires vital data. The control unit 17 also instructs the vital data acquisition device, for example, to decrease the frequency with which the vital data acquisition device used to calculate the risk of developing a disease other than the disease determined to be present or possible, acquires vital data. The control unit 17 also instructs the vital data acquisition device, for example, to decrease the frequency with which the vital data acquisition device used to calculate the risk of developing a disease determined to be absent or possible, acquires vital data.

In step S113, the control unit 17 instructs the vital data acquisition device to delete or compress the primary calculation value of the disease development risk stored in the primary calculation value storage unit of the vital data acquisition device used to calculate the development risk of a disease other than the disease determined to be present or possible. The control unit 17 also instructs the vital data acquisition device to delete or compress the primary calculation value of the disease development risk stored in the primary calculation value storage unit of the vital data acquisition device used to calculate the development risk of a disease determined to be absent or possible.

Although the present invention has been described above by way of an embodiment, the description and drawings forming part of this disclosure should not be understood as limiting this invention. From this disclosure, various alternative embodiments, examples and operating techniques should become apparent to those skilled in the art. It should be understood that the present invention encompasses various embodiments and the like that are not described here.

10: Health management system, 11: Disease onset risk secondary calculation unit, 12: Correlation storage unit, 13: Secondary calculation value storage unit, 14: Diagnosis recommendation unit, 15: Diagnosis result acquisition unit, 16: Correction unit, 17: Control unit, 18: Vital data correction unit, 19: Estimation unit, 101: Disease onset risk primary calculation unit, 102: Correlation storage unit, 103: Primary calculation value storage unit, 111: Vital data acquisition device, 121: Subjective symptom input device, 122: Output device, 123: Diagnosis result input device

Claims (65)

A health management system connected to a plurality of disease onset risk primary calculation units,
Each of the plurality of disease development risk primary calculation units acquires vital data of a subject, and calculates a primary calculation value of the disease development risk of the subject using a correlation between the vital data and the disease development risk;
The health management system includes a disease onset risk secondary calculation unit that calculates a secondary calculation value of the subject's disease onset risk based on the multiple vital data of the subject acquired by the multiple disease onset risk primary calculation units, using the correlation between the multiple vital data and the disease onset risk. The health management system according to claim 1, further comprising a diagnosis recommendation unit that recommends the subject to receive a diagnosis at a medical institution when the subject is determined to be at risk of developing a disease based on the calculated secondary calculated value of the disease development risk. The health management system according to claim 1, further comprising a diagnostic result acquisition unit that acquires the diagnostic results when the subject is diagnosed at a medical institution. The health management system according to claim 3, further comprising a correction unit that compares the diagnosis result with the primary calculation value of the disease onset risk calculated by each of the plurality of primary disease onset risk calculation units, and corrects the correlation used by each of the plurality of primary disease onset risk calculation units so that the primary calculation value of the disease onset risk approaches the diagnosis result. The health management system according to claim 4, wherein each of the plurality of disease development risk primary calculation units calculates the primary calculation value of the disease development risk based on the vital data and a threshold value. The health management system according to claim 5, wherein the correction unit corrects the threshold value based on the diagnosis result. The health management system according to claim 4, wherein each of the plurality of disease development risk primary calculation units calculates the primary calculation value of the disease development risk using the correlation between the rate of change of the vital data and the disease development risk. The health management system according to claim 7, wherein the correction unit corrects the correlations used by each of the multiple disease onset risk primary calculation units based on the diagnosis results. The health management system according to claim 3, further comprising a correction unit that compares the diagnosis result with the secondary calculation value of the disease onset risk calculated by the secondary disease onset risk calculation unit, and corrects the correlation used by the secondary disease onset risk calculation unit so that the secondary calculation value of the disease onset risk approaches the diagnosis result. The health management system according to claim 9, wherein the disease development risk secondary calculation unit calculates the secondary calculated value of the disease development risk based on the plurality of vital data and a threshold value. The health management system according to claim 10, wherein the correction unit corrects the threshold value based on the diagnosis result. The health management system according to claim 9, wherein the disease development risk secondary calculation unit calculates the secondary calculation value of the disease development risk using the correlation between the rate of change of the plurality of vital data and the disease development risk. The health management system according to claim 12, wherein the correction unit corrects the correlation used by the disease onset risk secondary calculation unit based on the diagnosis result. The health management system of claim 1, wherein the correlation used by each of the multiple disease onset risk primary calculation units is associated with the subject. The health management system of claim 1, wherein the correlation used by the disease onset risk secondary calculation unit is associated with the subject. The health management system according to claim 1, wherein the disease development risk secondary calculation unit receives input of subjective symptoms from the subject, and calculates a secondary calculation value of the disease development risk of the subject using the plurality of vital data, the subjective symptoms, and the correlation between the disease development risk. The health management system according to claim 1, further comprising a correlation storage unit that stores the correlation between the plurality of vital data and the disease development risk, and the disease development risk secondary calculation unit accesses the correlation storage unit to calculate the secondary calculation value of the disease development risk. The health management system of claim 1, wherein a plurality of disease onset risk primary calculation units are included in a plurality of vital data acquisition devices, respectively. The health management system according to claim 18, wherein the plurality of vital data acquisition devices are arranged in a building in which the subject is present. The health management system according to claim 18, wherein the plurality of vital data acquisition devices are attached to the subject. The health management system of claim 1, wherein the subject is a human or an animal. The health management system according to claim 1, wherein the type of disease in the first calculated value of the disease development risk is the same as the type of disease in the second calculated value of the disease development risk. The health management system according to claim 1, wherein the type of disease in the first calculated value of the disease development risk is different from the type of disease in the second calculated value of the disease development risk. The health management system according to claim 1, further comprising a vital data correction unit that receives the vital data from each of the plurality of disease onset risk primary calculation units and corrects missing vital data and/or reduced accuracy of the vital data based on vital data previously acquired by the same disease onset risk primary calculation unit. The health management system according to claim 1, further comprising a vital data correction unit that receives the vital data from each of the plurality of primary disease onset risk calculation units, and corrects the loss of vital data and/or the decrease in accuracy of the vital data in one of the plurality of primary disease onset risk calculation units based on vital data simultaneously acquired by another primary disease onset risk calculation unit. The health management system according to claim 1, further comprising an estimation unit that receives the vital data from each of the plurality of disease onset risk primary calculation units and estimates different types of vital data based on the received vital data. The health management system of claim 1, wherein the vital data includes at least one of the subject's gender, age, height, and weight. The health management system of claim 1, wherein the vital data includes at least one of the subject's medical history and family history. The health management system of claim 1, wherein the vital data includes at least one of the subject's heart rate, respiration, body movement, body temperature, ambient temperature, and ambient humidity. The health management system of claim 1, wherein the vital data includes at least one of the subject's blood pressure, biochemistry test results, and hematology test results. The health management system of claim 1, wherein the vital data includes the subject's intake. The health management system of claim 1, wherein the vital data includes a history of treatments and drug administrations received by the subject. The health management system of claim 1, wherein the vital data includes genetic information of the subject. A health management system acquires a primary calculation value of a disease onset risk of the subject, the primary calculation value being calculated by each of a plurality of disease onset risk primary calculation units acquiring vital data of the subject and using a correlation between the vital data and the disease onset risk;
The health management system calculates a secondary calculation value of the disease development risk of the subject based on the plurality of vital data of the subject acquired by the plurality of disease development risk primary calculation units, using a correlation between the plurality of vital data and the disease development risk;
A health management method comprising: The health management method according to claim 34, further comprising the step of: recommending to the subject that the subject be diagnosed at a medical institution when the health management system determines that the subject is at risk of developing a disease based on the calculated secondary calculated value of the disease development risk. The health management method according to claim 34, further comprising the step of: obtaining a diagnosis result when the subject is diagnosed at a medical institution, the health management system. The health management method according to claim 36, further comprising: the health management system comparing the diagnosis result with the primary calculation value of the disease onset risk calculated by each of the plurality of primary disease onset risk calculation units, and correcting the correlation used by each of the plurality of primary disease onset risk calculation units so that the primary calculation value of the disease onset risk approaches the diagnosis result. The health management method according to claim 37, wherein each of the plurality of disease development risk primary calculation units calculates the primary calculation value of the disease development risk based on the vital data and a threshold value. The health management method according to claim 38, wherein the threshold is modified based on the diagnosis result in the modification. The health management method according to claim 37, wherein each of the plurality of disease development risk primary calculation units calculates the primary calculation value of the disease development risk using the correlation between the rate of change of the vital data and the disease development risk. The health management method according to claim 40, wherein, in the correction, the correlations used by each of the multiple disease onset risk primary calculation units are corrected based on the diagnosis results. The health management method according to claim 36, further comprising the health management system comparing the diagnosis result with the secondary calculated value of the disease development risk, and correcting the correlation used in calculating the secondary calculated value of the disease development risk so that the secondary calculated value of the disease development risk approaches the diagnosis result. The health management method according to claim 42, wherein the secondary calculation value of the disease development risk is calculated based on the plurality of vital data and a threshold value. The health management method according to claim 43, wherein the modifying modifies the threshold value based on the diagnosis result. The health management method according to claim 42, wherein the secondary calculated value of the disease development risk is calculated using a correlation between the rate of change of the plurality of vital data and the disease development risk. The health management method according to claim 45, wherein the correlation used to calculate the secondary calculated value of the disease development risk is corrected based on the diagnosis result in the correction. The health management method according to claim 34, wherein the correlation used by each of the multiple disease onset risk primary calculation units is associated with the subject. The health management method according to claim 34, wherein the correlation used to calculate the secondary calculated value of the disease development risk is associated with the subject. The health management method according to claim 34, wherein the health management system receives input of subjective symptoms from the subject, and calculates a secondary calculated value of the subject's disease development risk using the plurality of vital data, the subjective symptoms, and the correlation between the disease development risk. The health management method according to claim 34, wherein the multiple disease onset risk primary calculation units are included in multiple vital data acquisition devices, respectively. The health management method according to claim 50, wherein the plurality of vital data acquisition devices are arranged in a building in which the subject is present. The health management method according to claim 50, wherein the plurality of vital data acquisition devices are attached to the subject. The health management method according to claim 34, wherein the subject is a human or an animal. The health management method according to claim 34, wherein the type of disease in the first calculated value of the disease development risk is the same as the type of disease in the second calculated value of the disease development risk. The health management method according to claim 34, wherein the type of disease in the first calculated value of the disease development risk is different from the type of disease in the second calculated value of the disease development risk. The health management method according to claim 34, further comprising: the health management system receiving the vital data from each of the plurality of disease onset risk primary calculation units, and correcting missing vital data and/or reduced accuracy of the vital data based on vital data previously acquired by the same disease onset risk primary calculation unit. The health management method according to claim 34, further comprising: the health management system receiving the vital data from each of the plurality of primary disease onset risk calculation units, and correcting a loss and/or a decrease in accuracy of the vital data in one of the plurality of primary disease onset risk calculation units based on vital data simultaneously acquired by another primary disease onset risk calculation unit. The health management method according to claim 34, further comprising the health management system receiving the vital data from each of the plurality of disease onset risk primary calculation units and estimating different types of vital data based on the received vital data. The health management method according to claim 34, wherein the vital data includes at least one of the subject's sex, age, height, and weight. The health management method according to claim 34, wherein the vital data includes at least one of the subject's medical history and family history. The health management method according to claim 34, wherein the vital data includes at least one of the subject's heart rate, respiration, body movement, body temperature, ambient temperature, and ambient humidity. The health management method according to claim 34, wherein the vital data includes at least one of the subject's blood pressure, biochemistry test results, and hematology test results. The health management method of claim 34, wherein the vital data includes the subject's intake. The health management method of claim 34, wherein the vital data includes a history of treatments and medications received by the subject. The health management method according to claim 34, wherein the vital data includes genetic information of the subject.

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