JP2023158148A - Medical support device, medical support method and medical support program - Google Patents

Abstract

To provide a technology capable of supporting treatment of a user even in a state where a plurality of diseases are complicated.SOLUTION: A medical support device comprises: an acquisition unit that acquires personal data including examination data and interview data of a user; and an output unit that, based on the personal data, determines the user's disease state with respect to individual diseases constituting a complex disease, and when a combination of the disease states of the individual diseases or a combination of the disease states of the individual diseases and the personal data is a complex disease state, outputs an improvement goal to be achieved by the user in order to improve the complex disease state.SELECTED DRAWING: Figure 5

Description

The present disclosure relates to a medical support device, a medical support method, and a medical support program.

Currently, systems aimed at improving the health condition of users are known. For example, Patent Document 1 discloses a health management device that can indicate measures to maintain or improve a user's health condition based on the nutritional value of food ingested by the user and the user's health condition. ing.

JP 2021-176053 Publication

Additionally, medical devices and programs aimed at supporting the treatment of individual diseases such as diabetes are currently being approved and provided in Europe and other countries. However, since these medical devices and medical programs are targeted at individual diseases, it is difficult to support the treatment of patients with multiple diseases, such as metabolic syndrome.

Therefore, an object of the present disclosure is to provide a technology that can support the treatment of a user even in a state where a plurality of diseases are complex.

A medical support device according to one aspect of the present disclosure includes an acquisition unit that acquires personal data including test data and interview data of a user, and a medical support device that acquires personal data including test data and interview data of a user, and a medical support device that determines the user's disease regarding individual diseases constituting a complex disease based on the personal data. If the combination of the disease states of the individual diseases or the combination of the disease states of the individual diseases and the personal data is a complex disease state, what should the user achieve in order to improve the complex disease state? and an output unit that outputs an improvement target.

According to the present disclosure, it is possible to provide a technology that can support the treatment of a user even in a state where a plurality of diseases are complex.

FIG. 1 is a diagram showing an example of a medical support system according to the present embodiment. It is a flowchart showing an outline of processing performed by the medical support system. It is a figure showing an example of personal data. 2 is a diagram illustrating an example of a case where a complex disease state is determined based on determination method 1. FIG. FIG. 6 is a diagram illustrating an example of a case where a complex disease state is determined based on determination method 2. FIG. 2 is a schematic diagram showing the flow of medical support using the medical support system. It is a diagram showing an example of the hardware configuration of a medical support device, a patient terminal, and a doctor terminal. It is a diagram showing an example of a functional block configuration of a medical support device. It is a diagram showing an example of patient information, individual disease definition information, complex disease/goal definition information, questionnaire definition information, and score definition information. It is a figure showing an example of advice definition information. FIG. 3 is a diagram showing an example of a trained model. It is a figure showing an example of functional block composition of a patient terminal. It is a figure showing an example of functional block composition of a terminal for doctors. It is a sequence diagram which shows an example of the processing procedure performed by a medical support system. It is a sequence diagram which shows an example of the processing procedure performed by a medical support system. It is a figure which shows the specific example of test|inspection data. FIG. 3 is a diagram showing a specific example of interview data. FIG. 3 is a diagram showing a specific example of individual disease definition information. FIG. 3 is a diagram showing a specific example of individual disease definition information. FIG. 3 is a diagram showing a specific example of complex disease/goal definition information. It is a figure showing an example of behavioral goal definition information. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a patient terminal. It is a figure which shows the example of a screen display of a terminal for doctors. It is a figure which shows the example of a screen display of a terminal for doctors. It is a figure which shows the example of a screen display of a terminal for doctors. It is a figure showing experimental data.

Embodiments of the present invention will be described with reference to the accompanying drawings. In addition, in each figure, those with the same reference numerals have the same or similar configurations.

<System configuration>
FIG. 1 is a diagram showing an example of a medical support system 1 according to the present embodiment. The medical support system 1 is a system that supports disease treatment of patients, and includes a medical support device 10, a patient terminal 20 (first terminal), and a doctor terminal 30 (second terminal). The medical support device 10, the patient terminal 20, and the doctor terminal 30 are connected via a wireless or wired communication network N, and can communicate with each other. Note that the number of patient terminals 20 and doctor terminals 30 may be one or more.

The medical support system 1 helps patients suffering from multiple diseases (also referred to as "users") recover from their disease states by helping them understand their disease states and encouraging them to change their own behavior. It is a system whose purpose is to support. The medical support system 1 may include, for example, the following multiple functions.
1. Function to determine the patient's disease status 2. Function to indicate the patient's disease status to the doctor 3. Function to propose improvement goals that should be achieved in order to improve the disease state to the doctor, and to accept the setting of improvement goals that the patient should achieve 4. Function to show the patient's own disease status and present improvement goals to be achieved 5. 6. A function to accept from patients the setting of behavioral goals (which may also be referred to as "challenges") that should be addressed in order to achieve improvement goals.6. The medical support device 10 has the function of displaying a score regarding the degree of achievement of the behavioral goals that the patient should work on based on the questionnaire answers regarding the daily behavioral goals received from the patient. It has a function of accepting the setting of behavioral goals, etc., and displaying various information regarding the patient on the screens of the patient terminal 20 and the doctor terminal 30.

The patient terminal 20 is a terminal used by a patient, and has a function of displaying information received from the medical support device 10 and a function of receiving various inputs from the patient. The patient terminal 20 may be, for example, a smartphone, a tablet terminal, a personal computer, or the like.

The doctor terminal 30 is a terminal used by a doctor, and has a function of displaying information received from the medical support device 10 and a function of receiving various inputs from the doctor. The doctor terminal 30 is assumed to be a personal computer installed in a medical institution, but is not limited to this, and may be a smartphone or a tablet terminal, for example. The medical support device 10 is equipped with a web server function, and by accessing the medical support device 10 with a web browser installed on the doctor terminal 30, information can be displayed and input can be accepted on the doctor terminal 30. You may also do so. Alternatively, a dedicated application installed on the patient terminal 20 may access the medical support device 10 to display information and accept input on the doctor terminal 30.

Note that the patient terminal 20 may include a wearable device worn by the patient. The medical support system 1 may acquire and store various data regarding the patient (hereinafter referred to as "biological information") from the wearable device. For example, a patient wears a wearable device and transmits various biological information (heart rate, number of steps, amount of exercise, etc.) to the medical support device 10, and also uses a smartphone to set behavioral goals. It may also be possible to refer to the score regarding the degree of achievement.

FIG. 2 is a flowchart showing an overview of the processing performed by the medical support system 1. First, the medical support device 10 acquires the patient's personal data (S10). Personal data includes either or both of test data obtained by examining a patient's physical condition at a medical institution, etc., and interview data obtained by asking questions of the patient. Test data includes, for example, data obtained by measuring the patient's body such as height, weight, body fat, BMI, and waist circumference (body measurement data), data obtained by conducting a blood test (blood test data), The data may include data obtained by performing a urine test (urinalysis data), data obtained by examining the state of body parts such as organs and blood vessels (organ data), and the like.

In addition, blood test data includes, for example, lipid-related data such as triglycerides, HDL-cholesterol, LDL cholesterol, and non-HDL cholesterol, and liver and pancreatic function data such as AST (GOT), ALT (GPT), and γ-GPT. Related data, renal function-related data such as creatinine, anemia-related data such as hematocrit level, hemoglobin content, white blood cell content, red blood cell content, blood pressure-related data such as systolic blood pressure and diastolic blood pressure, or fasting blood sugar (potentiometric method), HbA1c ( Data such as blood sugar related data such as NGSP value) and general blood data such as uric acid value may also be included. Further, the urine test data may include, for example, data on urine sugar, urine protein, urine occult blood, and the like.

The interview data includes, for example, data regarding diseases that the patient has suffered in the past (anamnestic history), data regarding diseases that the patient is currently known to suffer from (e.g. disease name), and past information regarding diseases of family members and close relatives. and current data (family history), data regarding drug history (presence of past and current drug use, names of specific drugs taken/currently taking, etc.), data regarding social history (educational background, annual income, etc.) , family composition, etc.), smoking information (presence of past and current smoking habits, amount smoked, duration of smoking, presence or absence of desire to improve, etc.), drinking information (drinking habits such as past and current smoking habits, amount, type, and duration of drinking) (specific details, etc.), eating habits (number of meals, meal contents, whether to eat out or not, and whether there is a desire to improve the meal contents, etc.), activity level (whether or not there is a daily exercise habit, the specific amount of exercise, frequency, and activity content) Information on weight changes, sleep information (information on the quality and quantity of sleep, whether there is a desire to improve, etc.), job content, attendance information, hobbies and preferences, stress, etc. You can leave it there. Past medical history, disease name, and family history are also collectively referred to as "medical history." Note that in this embodiment, the medical history is not limited to including all of the medical history, disease name, and family history. What includes at least one of past medical history, disease name, and family history may be referred to as medical history.

Subsequently, the medical support device 10 determines the disease state of the patient based on the acquired personal data of the patient (S11). More specifically, the medical support device 10 determines whether the patient has an individual disease (hereinafter referred to as "individual disease") from the patient's personal data. Individual disease refers to one disease, such as obesity, diabetes, hypertension, dyslipidemia, fatty liver, cardiovascular disease, cerebrovascular disease, osteoporosis, dementia, periodontal disease, and alcoholism. Patients have lifestyle-related diseases such as hepatitis, nonalcoholic fatty liver disease, cirrhosis, hyperuricemia, gastric ulcer, peripheral neuropathy, and allergies. In addition to these, individual diseases include various diseases such as cancer, renal failure, chronic obstructive pulmonary disease, arthropathy, low back pain, cataracts, glaucoma, and sleep apnea syndrome. Next, when the patient falls under a plurality of individual diseases defined in advance as a combination pattern, or when the patient falls under conditions of a plurality of individual diseases and personal data defined in advance as a combination pattern, the medical support device 10 , the patient is determined to have a "complex disease state." In addition, the medical support device 10 may be configured to handle cases where the patient does not fall under a plurality of individual diseases defined in advance as a combination pattern, or falls under a plurality of individual diseases defined in advance as a combination pattern, but does not meet the conditions of the personal data. If not applicable, the patient is considered not to have a “complex disease state.” In other words, a "complex disease state" is a condition that corresponds to multiple individual diseases defined in advance as a combination pattern, or a condition that corresponds to conditions of multiple individual diseases and personal data defined in advance as a combination pattern. It means that. Note that "conditions for personal data" means that a predetermined item of personal data satisfies a predetermined condition. Examples of "conditions for personal data" include, for example, the item indicating gender in personal data is male, the item indicating age in personal data is XX years or older, and the item indicating waist circumference in personal data. is XX cm or more.

A specific example of a complex disease state is, for example, metabolic syndrome. In the case of metabolic syndrome, "multiple individual diseases defined in advance as a combination pattern" is at least two of diabetes (abnormal blood sugar level), hypertension (abnormal blood pressure), and dyslipidemia (abnormal lipid value). The "conditions for personal data" may be defined as having a waist circumference of at least 85 cm (for men) or 90 cm (for women). In addition to the waist circumference, the "personal data conditions" may be defined as satisfying diagnostic reference values for various diseases that can be obtained from personal data. According to the definition, the medical support device 10 is used when the patient is suffering from two or more of diabetes, hypertension, and dyslipidemia, is male, and has an abdominal circumference of 85 cm or more (90 cm or more for women). , it is determined that the patient has a complex disease state (metabolic syndrome). In addition to having an abdominal circumference of 85 cm or more (for men) or 90 cm or more (for women), metabolic syndrome also means that the patient has obesity (more specifically, visceral fat obesity). It may also be a criterion. In this case, "multiple individual diseases defined in advance as a combination pattern" in metabolic syndrome corresponds to at least two of diabetes, hypertension, and dyslipidemia, in addition to obesity (visceral fat obese state). It may be defined as.

Other examples of complex disease states include chronic individual diseases, such as diabetes, hypertension, malignant neoplasms (cancer), and heart disease (hypertensive This includes conditions such as cerebrovascular disease, anxiety, depression, pain, physical disorders, and neurological disorders, as well as multiple co-occurring individual diseases. In such complex disease states, treatments are often performed independently, which tends to increase the number of drugs and complicate dosing patterns, and treatment guidelines generally target a single disease. Fragmentation of treatment and insufficient communication between doctors treating each disease were likely to occur. Specifically, it has been reported that having diabetes increases the risk of stroke, acute myocardial infarction, heart failure, and depression, as well as increases the risk of developing dementia. Possible conditions include diabetes and depression, or diabetes, depression, and dementia. In the present invention, such a state in which a plurality of individual diseases co-occur or the risk of developing the disease is increased may be regarded as a complex disease state.

More specifically, the medical support device 10 may determine whether or not the patient falls under a complex disease state according to the following method. Furthermore, the medical support device 10 may determine a risk value regarding a complex disease state. The risk value regarding a complex disease state means the severity of the complex disease that the patient is suffering from as a whole, and it may be assumed that the larger the risk value is, the more severe the disease is.

(Judgment method 1)
"A plurality of individual diseases defined in advance as a combination pattern" may be defined as at least a predetermined number or more of the above-mentioned individual diseases. The predetermined number may be 2 or 3 or more. Furthermore, if the patient is suffering from a predetermined number or more of the individual diseases defined in advance as a combination pattern or has a high risk of developing the individual diseases, the medical support device 10 determines that the patient has a complex disease state. You may decide. Furthermore, the medical support device 10 may determine the risk value of a complex disease state based on the number of applicable individual diseases among a plurality of individual diseases defined in advance as a combination pattern. . For example, if the number of applicable individual diseases is five, the medical support device 10 may determine that the risk is five. Note that the higher the number, the greater the risk.

FIG. 3 is a diagram showing an example of personal data. Figure 3 shows abdominal circumference and BMI, which are test items related to visceral fat, triglycerides, HDL cholesterol, and LDL cholesterol, which are test items related to lipids, systolic blood pressure and diastolic blood pressure, which are test items related to blood pressure, and blood sugar. An example of personal data (test data) obtained by testing subjects A to I for fasting blood sugar and HbA1C, which are test items related to the above, is shown below.

FIG. 4 is a diagram illustrating an example of a case where a complex disease state is determined based on determination method 1. Note that 〇 indicates that the item is applicable, and × indicates that it is not applicable. In the example of FIG. 4 (the example of FIG. 5 is similar), it is assumed that the medical support device 10 determines whether the complex disease condition corresponds to metabolic syndrome. For example, a patient whose personal data regarding visceral fat (abdominal circumference and BMI) does not meet a predetermined standard is considered obese. Patients whose personal data regarding lipids (such as triglycerides) do not meet predetermined standards fall under dyslipidemia. A patient whose personal data regarding blood pressure (systolic blood pressure, etc.) does not meet a predetermined standard falls under hypertension. A patient whose personal data regarding blood sugar (fasting blood sugar, etc.) does not meet a predetermined standard is considered to have diabetes. The medical support device 10 determines whether or not a patient falls under each individual disease, as well as the severity of each corresponding individual disease, using individual disease definition information 100b or a learned model, which will be described later. You can also do this. “Determination” indicates whether the condition corresponds to a complex disease state (metabolic syndrome in this case). "(Reference) Metabolic syndrome determination" is a reference to the determination result of metabolic syndrome determined by an actual doctor according to the standards of the academic society. ○ means metabolic syndrome, and △ means metabolic syndrome premonitory group.

In the example of FIG. 4, a complex disease state (metabolic syndrome) is determined when two or more individual diseases among a plurality of individual diseases defined in advance as a combination pattern apply, but the present invention is not limited to this. For example, if the condition corresponds to three or more individual diseases, it may be determined that the condition is a complex disease state (metabolic syndrome).

(Judgment method 2)
The medical support device 10 uses standard values (also called cut-off values) of one or more test items related to each of a plurality of individual diseases defined in advance as a combination pattern, and the results obtained by testing the patient. The risk for each test item is calculated using the test data for the test item, and if the average value of the calculated risks for each test item is greater than or equal to a predetermined threshold, the patient is considered to have a complex disease state. You may decide. Furthermore, the medical support device 10 may determine that the patient is not in a complex disease state if the average value of risks for each test item is less than a predetermined threshold.

Furthermore, the medical support device 10 may determine that the average value of the calculated risks for each test item is the risk value related to the complex disease state. At this time, the medical support device 10 may calculate the average value of the risks for each test item using the formula "average value=total value of risks for each test item÷number of test items".

In addition, the medical support device 10 calculates the risk for each test item using the formula: "Risk = (Patient test data - Reference value) / Standard value" or "Risk = (Reference value - Patient test data) / Standard value" It may be calculated using the formula "value". Specifically, for test items that are considered abnormal if they exceed the standard value, we use the formula ``Risk = (patient test data - standard value) ÷ standard value'', and test items that are below the standard value, such as HDL cholesterol. For test items that are considered to be abnormal values, the formula "risk = (reference value - patient test data) / reference value" may be used.

Furthermore, the medical support device 10 may calculate the risk for each test item using the formula "risk = (patient's test data - reference value) / reference value x adjustment coefficient." The adjustment coefficient is a "weight value" indicating the importance that each test item gives to the complex disease state, and may be predetermined for each test item. In addition, the medical support device 10 adds a number obtained by multiplying "the number of items whose test data exceeds the reference value among test items" by 0.1 to the calculated average risk for each test item, If the average value of the risks for each test item after addition is greater than or equal to a predetermined threshold, it may be determined that the patient has a complex disease state.

FIG. 5 is a diagram showing an example of a case where a complex disease state is determined based on determination method 2. Points not particularly mentioned may be the same as those in FIG. 4. Each numerical value in FIG. 5 indicates a risk calculated based on the measurement data in FIG. 3. In addition, the risk value of a complex disease state in Figure 5 (risk value related to a complex disease state) is determined by the average value of the risk for each test item and the "number of test items for which the test data exceeds the standard value". It is the sum of the numbers multiplied by 0.1. In determination method 2, the risk value of a complex disease state is calculated by multiplying the number of test items whose test data exceeds the standard value by 0.1, so that the risk value of the complex disease state is calculated by multiplying the number of test items whose test data exceeds the standard value by 0.1. The size of the number of items will affect the risk value. This makes it possible to adequately represent the risk of complex disease states.

When using determination method 2, the medical support device 10 determines that the patient has an individual disease in which there is one or more items for which the risk is greater than or equal to a predetermined value (for example, 0) among one or more test items corresponding to the individual disease. You may decide to do so. For example, in the example of FIG. 5, subject F has risks of chest circumference, BMI, LDL cholesterol, systolic blood pressure, and diastolic blood pressure that are greater than or equal to predetermined values. Therefore, the medical support device 10 may determine that the subject F falls under the individual diseases of obesity, dyslipidemia, and hypertension.

Subsequently, when the medical support device 10 determines that the patient is in a complex disease state, it outputs an improvement goal that the patient should achieve in order to improve the complex disease state (S12). The improvement goal may be displayed on the doctor terminal 30 and set (confirmed) by the doctor's confirmation (approval). Further, corrections to the output improvement goals may be accepted from the doctor.

The improvement target may be an improvement target value for a test value included in the patient's personal data. Further, the improvement goal may be the patient's own self-improvement goal, or may be an improvement goal discussed by the doctor and the patient. For example, when the complex disease condition is metabolic syndrome, improvement goals include, for example, reducing blood pressure to less than 135/85 mmHg, reducing LDL cholesterol to less than 140 mg/dl, and reducing waist circumference to 85 cm or less.

The medical support device 10 sets improvement target values for test values included in a patient's personal data based on a combination of individual diseases or a combination of individual diseases and personal data in the patient's complex disease state. Good too. A specific improvement target value may be determined in advance according to a combination of individual diseases in a complex disease state, or a combination of individual diseases and personal data in a complex disease state.

Further, the improvement target value may be set to a more severe value (for example, a value close to a normal value, and the same applies below) as the number of individual diseases included in the combination of individual diseases in a complex disease state increases. . In addition, if the patient's age exceeds a certain threshold (for example, men over 45 years old, women over 55 years old, etc.), the improvement target value will be set to a stricter value than when the patient does not exceed the threshold. You can also do this. Furthermore, if the patient is a smoker, the improvement target value may be set to a stricter value than for a patient who is not a smoker. That is, the larger the number of individual diseases (number of risk factors) constituting the complex disease state, the more severe the improvement target value may be set.

For example, assume that the LDL cholesterol improvement goal for a patient suffering only from dyslipidemia is set at less than 140 mg/dl. In this case, the medical support device 10 may set the LDL cholesterol improvement target for a patient suffering from dyslipidemia and diabetes to less than 120 mg/dl, which is closer to the normal value than less than 140 mg/dl. Furthermore, the medical support device 10 may set the LDL cholesterol improvement target for patients suffering from dyslipidemia and coronary artery disease to less than 100 mg/dl, which is closer to the normal value than less than 140 mg/dl. In addition, the medical support device 10 sets the LDL cholesterol improvement target for patients suffering from dyslipidemia, diabetes, and coronary artery disease to 100 mg/mL, which is the LDL cholesterol improvement target for patients suffering from dyslipidemia and coronary artery disease. It may be set to less than 70 mg/dl, which is closer to the normal value than less than dl.
Further, in the case of a disease considered to be a lifestyle-related disease, the improvement goal may be an improvement goal for the patient's lifestyle. For example, goals for improving your diet include ``limiting to one strong-tasting dish per meal,'' changing your activity to ``going for a walk after eating,'' or changing your sleep to ``going to bed an hour earlier than usual.''

Subsequently, the medical support device 10 receives from the patient the setting of a behavioral goal that the patient should work toward in order to achieve the improvement goal (S13). The behavioral goals may be divided into multiple categories. The plurality of categories may include, for example, at least one of "stress", "sleep", "activity", "meal", "smoking", and "drinking". Note that activity includes not only exercise but also general body movements such as walking. In other words, the behavioral goals that patients should work on to achieve their improvement goals include behavioral goals related to improving stress, behavioral goals related to improving sleep time, behavioral goals related to improving physical activity, and behavioral goals related to improving eating habits. At least one of a goal, a behavioral goal related to reducing the patient's smoking amount, and a behavioral goal related to reducing the patient's drinking amount may be included. For example, these behavioral goals may be based on the patient's treatment plan, such as walking for at least 30 minutes, not eating after 9 pm, always eating breakfast, or not drinking after 8 pm. It may be a specific behavioral goal, or the behavioral goals of each category related to the patient's lifestyle described above may be scored. Note that this category is only an example, and the present embodiment is not limited thereto.

The medical support device 10 may present the patient with options for behavioral goals that the patient should work toward in order to achieve the improvement goal, and may accept selection of a behavioral goal that the patient should work on from among the presented options. The medical support device 10 may determine options for behavioral goals that the patient should work toward in order to achieve the improvement goal based on the patient's personal data, the patient's improvement goal, and/or the patient's complex disease state. good. For example, the patient's complex disease condition is metabolic syndrome that corresponds to hypertension and diabetes, the improvement goal is to reduce blood pressure to less than 130/80 mmHg, the blood sugar control goal is to reduce HbA1c to less than 6.0%, and, If the patient is 60 years of age or older, the medical support device 10 provides behavioral goal options such as "Build up stamina by walking briskly," "Do not eat high-carbohydrate meals," and "Do not drink alcohol." Action goals may also be presented.

Subsequently, the medical support device 10 receives answers from the patient to a questionnaire regarding behavioral goals that the patient should pursue (S14). More specifically, the questionnaire may be a questionnaire that confirms with the patient that he/she is carrying out the behavioral goals to which the patient should work. Note that the questionnaire may include a questionnaire in which the patient directly confirms the execution result (initiative status) of the behavioral goal selected by the patient in step S13. For example, if a patient selects ``avoid eating high-carbohydrate meals'' as a behavioral goal, a questionnaire such as ``Did you try not to eat high-carbohydrate meals today?'' or a patient who selects ``30 minutes If the patient chooses to walk more than 30 minutes, the results of the behavioral goal selected by the patient will be directly displayed, such as a questionnaire asking, ``How many minutes in total did you do exercise that made you sweat (including brisk walking and housework)?'' It may also include a questionnaire to confirm. The medical support device 10 also receives biometric information of a patient from a wearable device worn by the patient.

Subsequently, the medical support device 10 calculates a score related to the degree of achievement of the behavioral goal that the patient should work on, and a score related to the degree of achievement of the behavioral goal that the patient should work on, based on the answers to the questionnaire and/or the biological information received in step S14. Advice is output (S15). As described above, since the behavioral goal may be divided into a plurality of categories, the score may also be output after being divided into the same category as the behavioral goal. The plurality of categories may include, for example, at least one of "stress," "sleep," "exercise," "meal," "smoking," and "drinking," similar to the behavioral goal. That is, the score may include at least one of a score related to stress, a score related to sleep, a score related to exercise, a score related to eating, a score related to smoking, and a score related to drinking. In addition, the score will be high if the patient is actively working toward achieving the improvement goal, and low if the patient is not actively working toward achieving the improvement goal. It may be calculated so that it becomes a value. For example, the score may be 80 for sleep, 59 for exercise, 78 for eating, and 100 for smoking/drinking. Furthermore, these scores may be used as behavioral goals. In addition, if the patient is actively working towards achieving their improvement goals, the advice should be to praise the patient (e.g., "Let's keep up the good work") and help the patient achieve their improvement goals. If the person is not actively working towards achieving the goal, the content may encourage improvement (for example, ``If you don't reduce your drinking, your disease will get worse'').

In the processing procedure of step S15, the medical support device 10 images a current or future image of the patient's appearance and/or a current or future image of the organ based on the improvement goal, behavioral goal, questionnaire, or advice. May be displayed.

Examples of images of organs displayed by the medical support device 10 include the brain, liver, eyes, kidneys, heart, blood vessels, lungs, and nerves. This allows patients to visually recognize and understand their current and future conditions by displaying an image of the patient's current condition, improvement goals, behavioral goals, questionnaires, advice, etc. for each organ. can do.

Furthermore, the medical support device 10 may provide the patient with specific medical information on diseases and test items related to each organ in the form of "trivia" in the form of videos and/or texts. For example, in the case of the liver as an organ, explanatory videos regarding diseases such as fatty liver, hepatitis, liver cirrhosis, and liver cancer may be provided. In addition, in the case of dyslipidemia as a disease, "dyslipidemia is a disease in which LDL cholesterol (bad cholesterol) and triglyceride (triglyceride) levels are abnormal, and when cholesterol accumulates on the walls of blood vessels, it causes plaque (bumps). A medical explanatory document regarding the disease may be displayed, such as, "The blood passage becomes blocked, leading to arteriosclerosis."

In this way, by allowing patients to visually understand the status of each disease and complex disease, as well as related medical information, patients can understand their own condition, and as a result, improvement can be achieved. Based on the plan, etc., it will encourage behavioral changes such as one's own lifestyle habits.

The medical support device 10 also records input values such as patient's personal data (for example, personal data measured by the patient such as weight, blood pressure, and blood sugar level) for a period of one week, one month, or one year. You may display data that allows you to check trends and distribution. Furthermore, the medical support device 10 analyzes changes in scores and questionnaires for each lifestyle category (stress, sleep, activity, diet, smoking, drinking, etc.) over a period of one day, one week, or one month. It may also be possible to display information that allows the user to confirm the content of the answer and advice. As a result, patients themselves can understand their own conditions and further encourage behavioral changes such as their own lifestyle habits based on improvement plans.

Furthermore, the medical support device 10 may display quizzes and the like aimed at improving literacy regarding health and lifestyle-related diseases. The format of the quiz is not particularly limited, but for example, one quiz question per day may be displayed and the user must answer the quiz. By adding ideas such as giving 5 points for a correct answer and 3 points for a wrong answer, students can have fun learning knowledge and information about patient health and lifestyle-related diseases, and can immediately put the health knowledge they have learned to use. This can improve health literacy and encourage behavior change.

The processing procedures from step S10 to step S12 explained above are executed when the patient receives a medical examination by a doctor, and the processing procedures from step S13 to step S15 are repeatedly executed every day from the end of the medical examination until the next medical examination. It is also possible to do so.

FIG. 6 is a schematic diagram showing the flow of medical support using the medical support system 1. As shown in FIG. 6, the doctor examines the patient and inputs the patient's personal data (various test data, etc.) from the doctor terminal 30. Furthermore, the patient inputs his or her personal data (various types of interview data) from the patient terminal 20. Further, the doctor sets improvement goals that the patient should achieve based on the improvement goals output from the medical support device 10 and displayed on the doctor terminal 30 and his own medical insight.

After completing the examination, the patient recognizes his or her own disease state and improvement goals by checking the disease state and improvement goals displayed on the patient terminal 20. In addition, the patient daily sets behavioral goals for achieving improvement goals on the screen of the patient terminal 20, and answers daily to a questionnaire displayed on the patient terminal 20. When the patient responds to the questionnaire, the patient terminal 20 displays a score and advice regarding the degree of achievement of the behavioral goal, allowing the patient to review his or her daily actions. In addition, by repeatedly setting behavioral goals, answering questionnaires, and checking scores and advice on a daily basis, patients are able to continuously review their own behavior, and as a result, it is possible to achieve recovery from the disease. become.

<Hardware configuration>
FIG. 7 is a diagram showing an example of the hardware configuration of the medical support device 10, the patient terminal 20, and the doctor terminal 30. The medical support device 10, the patient terminal 20, and the doctor terminal 30 include a processor 11 such as a CPU (Central Processing Unit) and a GPU (Graphical Processing Unit), a memory, an HDD (Hard Disk Drive), and/or an SSD (Solid State Drive). ), a communication IF (Interface) 13 that performs wired or wireless communication, an input device 14 that accepts input operations, and an output device 15 that outputs information. The input device 14 is, for example, a keyboard, touch panel, mouse, and/or microphone. The output device 15 is, for example, a display, a touch panel, and/or a speaker. The medical support device 10 may be configured using one or more physical servers, etc., may be configured using a virtual server running on a hypervisor, or may be configured using a cloud server. It may be configured using

<Functional block configuration>
(Medical support equipment)
FIG. 8 is a diagram showing an example of the functional block configuration of the medical support device 10. The medical support device 10 includes a storage section 100, an acquisition section 101, an output section 102, a reception section 103, and a calculation section 104. The storage unit 100 can be realized using the storage device 12 included in the medical support device 10. Further, the acquisition unit 101, the output unit 102, the reception unit 103, and the calculation unit 104 can be realized by the processor 11 of the medical support device 10 executing a program stored in the storage device 12. . Further, the program can be stored in a storage medium. The storage medium storing the program may be a non-transitory computer readable medium. The non-temporary storage medium is not particularly limited, but may be a storage medium such as a USB memory or a CD-ROM.

The storage unit 100 stores patient information 100a that stores various information about patients, individual disease definition information 100b that defines correspondence between personal data and disease states of individual diseases, and combinations of disease states of individual diseases or disease states of individual diseases. Complex disease/goal definition information 100c that defines an improvement goal when the combination of disease state and personal data condition is a complex disease state, questionnaire definition information 100d that defines the content of a questionnaire regarding behavioral goals that the user is working on, and Score definition information 100e that defines a method of calculating a score from answers, behavioral goal definition information 100f that defines behavioral goals to be presented to patients as options, and advice definition information 100g that defines the content of advice to be presented to patients. Remember. The complex disease/goal definition information 100c may be called "goal definition information."

FIG. 9A is a diagram showing an example of patient information 100a, individual disease definition information 100b, complex disease/goal definition information 100c, questionnaire definition information 100d, and score definition information 100e. First, the patient information 100a will be explained. “Patient ID (Identification)” is an identifier that identifies a patient. "Age" indicates the age of the patient. "Gender" indicates the gender of the patient. "Personal data" stores various test data and various interview data of the patient. "Disease status", "Disease risk" and "Improvement target" include the disease status (disease status of each individual disease and complex disease status), disease risk and Improvement goals are stored. The "behavioral goal" field stores the behavioral goal selected by the patient. "Questionnaire response" stores the contents of the questionnaire answered by the patient. "Biological information" stores information such as daily activity amount (step count, walking distance, calories burned, etc.), sleep information, heart rate, etc. obtained from wearable devices.

Next, the individual disease definition information 100b will be explained. Individual disease definition information 100b shown in FIG. 9A is defined for each individual disease. The "personal data pattern" stores patterns of test data and interview data that correspond to individual diseases (that is, predetermined criteria that are considered to correspond to individual diseases). "Severity" corresponds to the disease state of the individual disease and indicates the severity of the individual disease corresponding to the personal data pattern. Severity may be expressed in a plurality of levels (stages), with higher levels indicating greater severity. For example, in the individual disease definition information 100b corresponding to hypertension, if the personal data pattern is that the systolic blood pressure is 180 mmHg or more and the diastolic blood pressure is 110 mmHg or more, it is level 5 hypertension, and the systolic blood pressure is 160 to 179 mmHg and Diastolic blood pressure of 100 to 109 mmHg may be defined as level 4 hypertension. Further, an individual data pattern not included in the individual disease definition information 100b means that it does not correspond to an individual disease. For example, if a personal data pattern in which the systolic blood pressure is 130 mmHg or less and the diastolic blood pressure is 80 mmHg or less is not defined in the individual disease definition information 100b corresponding to hypertension, the medical support device 10 determines that the systolic blood pressure is 80 mmHg or less. Patients whose blood pressure is 130 mmHg or less and whose diastolic blood pressure is 80 mmHg or less can be judged not to have hypertension.

Next, the complex disease/goal definition information 100c will be explained. Complex disease/goal definition information 100c shown in FIG. 9A is defined for each complex disease state. For example, if the medical support device 10 supports judgment of complex disease state A and complex disease state B, the storage unit 100 stores complex disease/goal definition information 100c corresponding to complex disease state A and complex disease state B. Complex disease/goal definition information 100c corresponding to disease state B is stored. "Disease status of individual disease" and "conditions of personal data" include combinations of disease states of individual diseases that fall under complex disease states, or combinations of disease states of individual diseases that fall under complex disease states and conditions of personal data. The combination is stored. If the complex disease state corresponds to a combination of disease states of individual diseases, the "personal data conditions" may be omitted. “Disease risk” is defined as a disease risk for a patient who is not currently suffering from the disease but who may be affected by the disease, which is inferred from the combination of the disease status of the patient's individual disease or the combination of the patient's disease status of the patient's individual disease and personal data conditions. A disease name and information indicating the degree of possibility of contracting the disease are stored. Here, patients with metabolic syndrome are likely to suffer from cerebrocardiovascular disease or coronary artery disease in the future, and the more severe the individual diseases that make up metabolic syndrome are, the more likely they are to suffer from cerebrocardiovascular disease or coronary artery disease. It is also known to be high risk. Therefore, the "disease risk" of the complex disease/goal definition information 100c corresponding to metabolic syndrome is a numerical value indicating the risk of suffering from cerebrocardiovascular disease or coronary artery disease (for example, the larger the value, the higher the possibility of developing the disease in the future). ) and the color indicating its severity (size of risk) may also be stored. The "improvement goal" stores numerical improvement goals that the patient should achieve in order to improve the complex disease state.

Note that when determining a complex disease state according to determination method 1, it can be handled by using the individual disease definition information 100b and the complex disease/goal definition information 100c shown in FIG. 9A. On the other hand, when determining a complex disease state according to judgment method 2, the above-mentioned complex disease/goal definition information 100c includes data common to each complex disease state and the judgment method 2 is executed as data common to each complex disease state, instead of the items shown in FIG. 9A. Data indicating the processing logic necessary for this purpose and reference values of each test item, and data associating "disease risk" and "improvement target" as data for each complex disease state may be stored. In addition, in place of the items shown in FIG. 9A, the individual disease definition information 100b includes, as data for each individual disease, a "predetermined value" used when determining whether or not a patient corresponds to an individual disease; Data indicating the correspondence between the risk value and severity calculated for each test item related to an individual disease may be stored.

Next, the questionnaire definition information 100d will be explained. “Category” indicates the category of the behavioral goal that the user is working on. In the example of FIG. 9A, examples of categories include stress, sleep, exercise, eating, smoking, and drinking, but are not limited thereto. “Questionnaire ID” indicates an identifier that identifies the questionnaire. "Questionnaire content" stores the content of the questionnaire.

Next, the score definition information 100e will be explained. “Questionnaire ID” indicates an identifier that identifies the questionnaire. The questionnaire ID corresponds to the questionnaire ID of the questionnaire definition information 100d. "Answer" indicates the answer to the questionnaire. "Score" indicates a value added to the score. The example in FIG. 9A shows that when the user answers "yes" to the stress 1 questionnaire, 1 is added to the stress category score. Similarly, if you answer "No" to the Stress 1 questionnaire, it is shown that nothing is added to the stress category score. Note that the score definition information 100e shown in FIG. 9A is an example, and the score definition information 100e is not limited to this. For example, the score definition information 100e may store logic for calculating a score by combining one or more questionnaire responses. For example, if the answer to Questionnaire 1, which belongs to stress, is "Yes," the answer to Questionnaire 5, which belongs to stress, is "Yes," and the answer to Questionnaire 1, which belongs to sleep, is "No," then Logic such as adding 3 to the score may be stored. Further, the score definition information 100e may further define biometric information in association with information regarding the score to be added. For example, information such as adding 1 to the activity score if the walking distance is equal to or greater than a predetermined threshold, or adding 1 to the sleep score if the sleeping time is equal to or greater than a predetermined time may be defined. .

FIG. 9B is a diagram showing an example of advice definition information 100g. As shown in FIG. 9B, the advice definition information 100g includes advice (daily) definition information 100g-1 that defines the content of short-term advice (for example, daily review) for the action content that the patient engages in, and the action content that the patient engages in. Advice (weekly summary) definition information 100g-2 that defines the content of medium-term advice (e.g., a one-week review) and long-term advice (e.g., a one-month review) regarding the actions the patient takes. The advice to be defined (monthly summary) may be divided into definition information 100g-3. “Category” indicates the category of advice. The category stored may be the same as the category of the behavioral goal. "Advice content" stores the wording of the advice to be output. One piece of advice content may be stored for each category, or a plurality of pieces of advice may be stored. "Output conditions" stores conditions for determining which advice to output or not. Note that the output conditions may be defined for each category or for each advice content. Returning to FIG. 8, the explanation will be continued.

The acquisition unit 101 acquires personal data including patient test data and interview data from the patient terminal 20 or the medical support device 10 . Note that the acquisition unit 101 may acquire personal data acquired by a wearable device worn by the patient.

The output unit 102 determines the disease state of the patient with respect to the individual diseases constituting the complex disease based on the patient's personal data, and determines whether the combination of the disease states of the individual diseases or the combination of the disease states of the individual diseases and the personal data is the complex disease. If the condition is the same, output the improvement goals that the patient should achieve in order to improve the complex disease condition. Note that the improvement goals may include improvement target values for test values included in the patient's personal data. Further, the patient's personal data includes data regarding the patient's lifestyle, and the improvement goals may include improvement targets for the patient's lifestyle. The lifestyle may include at least one of the patient's stress, the patient's sleeping hours, the patient's amount of exercise, the patient's eating habits, the patient's smoking amount, and the patient's alcohol consumption.

Further, the output unit 102 may set improvement targets for test values included in the patient's personal data based on a combination of disease states of individual diseases or a combination of disease states of individual diseases and personal data.

Further, the output unit 102 determines the disease state of the patient by referring to the individual disease definition information 100b, and determines the combination of disease states of the individual diseases or the disease state of the individual diseases by referring to the complex disease/goal definition information 100c. An improvement goal may be obtained when the combination of disease state and personal data is a complex disease state, and the obtained improvement goal may be output as an improvement goal that the patient should achieve. For example, if the patient's personal data corresponds to any of the "personal data pattern" records defined in the individual disease definition information 100b corresponding to the individual disease A, the output unit 102 outputs that the patient has the individual disease A. The disease state (severity) of the individual disease A that the patient is suffering from may be determined by determining that the disease is applicable and by referring to the "severity" field of the corresponding record. Furthermore, by repeating the same process for each individual disease, the output unit 102 allows the patient to determine which of the individual diseases the patient falls under and the disease state (severity) of the corresponding individual disease. You can also do this. Next, the output unit 102 refers to the complex disease/goal definition information 100c corresponding to the complex disease state A, and determines whether the disease state of each individual disease of the patient and the patient's personal data are defined in the complex disease/goal definition information 100c. If any of the "individual disease state" and "personal data conditions" records apply, the patient is judged to have complex disease state A, and refer to the "improvement goal" field of the corresponding record. By doing so, the patient's improvement goals may be obtained. In addition, the output unit 102 repeats the same process for each complex disease state to determine which complex disease state the patient falls under, and to obtain improvement goals if the patient falls under the complex disease state. You can do it like this.

In addition, the output unit 102 uses reference values of one or more test items related to the individual disease and test data for the test item obtained by testing the patient for the individual diseases that make up the complex disease. Alternatively, the risk for each test item may be calculated, and if the calculated risk for each test item satisfies a predetermined condition, it may be determined that the patient is in a complex disease state. Further, when the output unit determines that the patient has a complex disease state, the output unit may output an improvement goal that the patient should achieve in order to improve the complex disease state.

Furthermore, if the calculated risk for each test item satisfies a predetermined condition, the average value of the calculated risks for each test item may be greater than or equal to a predetermined threshold. In this case, the output unit 102 may output an average value of the calculated risks for each test item as a value indicating the risk related to the complex disease state.

The output unit 102 also outputs the patient's improvement goal, which is obtained by inputting the patient's personal data, to a trained model that has the ability to output an improvement goal for improving the complex disease state. It may also be output as an improvement target.

FIG. 10 is a diagram illustrating an example of a learned model. When inputting personal data, the trained model shown in Figure 10 generates a flag indicating whether it corresponds to a complex disease state, an identifier indicating the disease name of the complex disease state, and the state of each individual disease that makes up the complex disease state. (For example, a flag indicating the presence or absence of an individual disease, a value indicating the severity of an individual disease, etc.), an improvement target, and a disease risk are shown. The trained model identifies whether or not a combination of personal data corresponds to each individual disease that makes up a complex disease from the input personal data, and if the combination of personal data falls under each individual disease that makes up the complex disease (patient The device may operate so as to output an improvement target, etc. when the patient is in a complex disease state). The trained model may also be trained to output a risk value for a complex disease state.

In addition, such a trained model uses personal data as input data from a large amount of past clinical data, a flag indicating whether or not it corresponds to a complex disease state, an identifier indicating the disease name of the corresponding complex disease state, and a complex Generates a large amount of training data with flags indicating whether each individual disease that makes up the disease state is applicable, values indicating the severity of the individual disease, improvement target values, and disease risk as correct data and training the model. be able to. Furthermore, when outputting a risk value related to a complex disease state from a trained model, this can be handled by including the risk value related to the complex disease state in the correct answer data of the teacher data. The model may be any algorithm, and for example, a neural network, decision tree, random forest, gradient boosting decision tree, etc. can be used. Further, the trained model may be prepared as a different model for each complex disease state. Returning to FIG. 8, the explanation will be continued.

Further, the output unit 102 outputs various data to the patient terminal 20 and the doctor terminal 30. The output unit 102 that outputs data to the patient terminal 20 may be called a first output unit. Further, the output unit 102 that outputs data to the doctor terminal 30 may be called a second output unit.

Further, the output unit 102 (first output unit) may output the improvement target or the improvement target modified by the doctor to the patient terminal 20.

The reception unit 103 receives various inputs from the patient terminal 20 or the doctor terminal 30. The reception unit that receives various inputs from the patient terminal 20 (or from the patient) may be called a first reception unit. Further, the reception unit that receives various inputs from the doctor terminal 30 (or from the doctor) may be called a second reception unit. The reception unit 103 (first reception unit) receives from the patient behavioral goals that the patient should work toward in order to achieve the improvement goal. The reception unit 103 that receives behavioral goals from patients may be referred to as a first reception unit. Further, the reception unit 103 (first reception unit) may receive from the patient a behavioral goal that the patient is working on from among a plurality of options regarding behavioral goals for achieving the patient's improvement goal. In addition, the reception unit 103 (first reception unit) refers to the behavioral goal definition information 100f and extracts options corresponding to the patient's personal data, improvement goals, or patient's complex disease state, thereby presenting multiple options to the patient. Alternatively, the options may be determined. Note that the output unit 102 outputs the behavioral goals that the patient is working on, received by the reception unit 103 (first reception unit), to the patient terminal 20 used by the patient and/or the doctor terminal used by the doctor who examines the patient. 30 may be output.

Further, the reception unit 103 (first reception unit) receives input of answers to a questionnaire regarding behavioral goals that the patient should work on.

Further, when the doctor modifies the improvement goal, the reception unit 103 (second reception unit) may receive the modified improvement goal from the doctor terminal 30.

The calculation unit 104 calculates a score related to the degree of achievement of the behavioral goal that the patient is working on, based on the answers to the questionnaire received by the reception unit 103 (first reception unit). The calculation unit 104 refers to the score definition information 100e and calculates the score according to the score calculation method defined in the score definition information 100e.

(Patient terminal)
FIG. 11 is a diagram showing an example of the functional block configuration of the patient terminal 20. As shown in FIG. The patient terminal 20 includes a storage section 200, a reception section 201, and a display control section 202. The storage unit 100 can be realized using the storage device 12 included in the medical support device 10. Further, the acquisition unit 101, the output unit 102, the reception unit 103, and the calculation unit 104 can be realized by the processor 11 of the medical support device 10 executing a program stored in the storage device 12. . Further, the program can be stored in a storage medium. The storage medium storing the program may be a computer-readable non-transitory storage medium. The non-temporary storage medium is not particularly limited, but may be a storage medium such as a USB memory or a CD-ROM.

The storage unit 200 stores various data acquired from the medical support device 10.

The reception unit 201 receives various inputs detected by the input device 14 included in the patient terminal 20. For example, the reception unit 201 receives various inputs detected by a touch panel included in the patient terminal 20.

The display control unit 202 displays data and the like acquired from the medical support device 10 on a display included in the patient terminal 20.

Note that a web browser installed on the patient terminal 20 may be configured to display information and accept input on the patient terminal 20. In this case, the storage section 200, reception section 201, and display control section 202 may be realized by a Web browser installed in the patient terminal 20. Alternatively, a dedicated application installed on the patient terminal 20 for realizing the functions according to this embodiment may display information and accept input on the patient terminal 20. In this case, the storage unit 200, reception unit 201, and display control unit 202 may be realized by a dedicated application installed on the patient terminal 20.

(Doctor terminal)
FIG. 12 is a diagram showing an example of the functional block configuration of the doctor terminal 30. The doctor terminal 30 includes a storage section 200, a reception section 201, and a display control section 202. The storage unit 200 can be realized using the storage device 12 included in the doctor terminal 30. Further, the reception unit 201 and the display control unit 202 can be realized by the processor 11 of the doctor terminal 30 executing a program stored in the storage device 12. Further, the program can be stored in a storage medium. The storage medium storing the program may be a computer-readable non-transitory storage medium. The non-temporary storage medium is not particularly limited, but may be a storage medium such as a USB memory or a CD-ROM.

The storage unit 300 stores various data acquired from the medical support device 10.

The reception unit 301 receives various inputs detected by the input device 14 included in the doctor terminal 30. For example, the reception unit 301 accepts various inputs detected by a keyboard or a mouse included in the doctor terminal 30. Further, the reception unit 301 transmits various types of input data received to the medical support device 10.

The display control unit 202 acquires various data from the medical support device 10 and causes the acquired data to be displayed on a display included in the doctor terminal 30.

Note that a web browser installed on the doctor's terminal 30 may be configured to display information and accept input on the doctor's terminal 30. In this case, the storage unit 300, reception unit 301, and display control unit 302 may be realized by a web browser installed in the doctor terminal 30. Alternatively, a dedicated application installed on the doctor's terminal 30 for realizing the functions according to the present embodiment may display information and accept input on the doctor's terminal 30. In this case, the storage unit 300, reception unit 301, and display control unit 302 may be realized by a dedicated application installed on the doctor terminal 30.

<Processing procedure>
Next, the processing procedure performed by the medical support system 1 will be specifically explained. In the following discussion, the complex disease state will be described as metabolic syndrome. Furthermore, the medical support device 10 will be described as one that determines a complex disease state according to the determination method 1 described above.

FIG. 13 is a sequence diagram showing an example of a processing procedure performed by the medical support system 1. The processing procedure shown in Figure 13 is assumed to be executed repeatedly each time the doctor examines the patient, but in the second and subsequent examinations, some parts of the interview (such as interviews with contents that do not change with each consultation) may be omitted.

The doctor terminal 30 receives input of patient test data from the doctor and transmits it to the medical support device 10 (S100, S101). Furthermore, the patient terminal 20 receives input of interview data from the patient and transmits it to the medical support device 10 (S102, S103). For example, when a doctor examines a patient, the doctor may prompt the patient to input interview data from the patient terminal 20. Further, the interview data may be input into the doctor terminal 30 and transmitted to the medical support device 10. Subsequently, the medical support device 10 stores the examination data and interview data received from the patient terminal 20 and the doctor terminal 30 in the patient information 100a (S104).

FIG. 15 is a diagram showing a specific example of test data. The test data shown in Figure 15 includes data obtained by measuring the patient's body such as height, weight, and abdominal circumference (anthropometry data), data related to blood pressure, data related to anemia, data related to liver and gallbladder function, and data related to blood pressure. It includes data on lipids, blood sugar levels, uric acid, kidney function, and data obtained from urine tests.

FIG. 16 is a diagram showing a specific example of interview data. The interview data shown in FIG. 16 includes an interview regarding smoking, an interview regarding eating habits, an interview regarding drinking, an interview regarding the medicines currently being taken, an interview regarding past medical history, an interview regarding lifestyle history, and the like. Note that the interview data may further include an interview necessary to calculate a score related to the patient's lifestyle habits. The lifestyle-related scores may be divided into multiple categories. The plurality of categories may be, for example, stress, sleep, exercise, diet, smoking, and drinking categories.

Subsequently, the output unit 102 of the medical support device 10 refers to the individual disease definition information 100b and the complex disease/goal definition information 100c, or uses the learned model described in FIG. 10 to determine the patient's disease state, The improvement target and disease risk are output and stored in the patient information 100a (S105, S106, S107). More specifically, the patient's disease state includes a flag (or name of the complex disease state) indicating whether or not the patient falls under a complex disease state, and, if the patient has a complex disease state, constitutes the complex disease state. It may be the state of each individual disease (for example, a flag indicating the presence or absence of the individual disease, a value indicating the severity of the individual disease, etc.). Further, the improvement target output by the output unit 102 of the medical support device 10 may include an improvement target value of a score related to lifestyle habits. Further, the output unit 102 of the medical support device 10 may output a risk value related to the complex disease state when the patient falls under the complex disease state.

FIG. 14 is a diagram showing a specific example of the individual disease definition information 100b. FIG. 17A illustrates individual disease definition information 100b-1 corresponding to hypertension, individual disease definition information 100b-2 corresponding to dyslipidemia, and individual disease definition information 100b-3 corresponding to diabetes. . FIG. 17B shows an example of individual disease definition information 100b-4 corresponding to obesity. Further, FIG. 18 is a diagram showing a specific example of the complex disease/goal definition information 100c. First, the output unit 102 compares the "personal data pattern" of the individual disease definition information 100b corresponding to hypertension with the patient's test data and interview data, thereby generating records corresponding to the patient's test data and interview data. To detect. For example, if the patient's test data is systolic blood pressure = 190 mmHG and diastolic blood pressure = 120 mmHG, the output unit 102 detects that the patient's test data and interview data correspond to the record on the second line. . Subsequently, the output unit 102 obtains the severity of hypertension by referring to the "severity" of the record on the second line. Thereby, the output unit 102 can determine that the patient has hypertension and the severity level is level 5. Next, the output unit 102 refers to individual disease definition information 100b-2 corresponding to dyslipidemia, individual disease definition information 100b-3 corresponding to diabetes, and individual disease definition information 100b-4 corresponding to obesity. By doing so, it is determined whether the patient has hypertension, dyslipidemia, diabetes, or obesity, and if so, the severity. Here, it is assumed that the patient is determined to have hypertension (level 5), dyslipidemia (level 3), diabetes (level 3), and obesity (level 3).

Next, the output unit 102 compares the "disease state of individual disease" and "personal data conditions" of the complex disease/goal definition information 100c corresponding to metabolic syndrome with the patient's individual disease state and personal data. , detecting records corresponding to the disease status and personal data of the patient's individual disease. As mentioned above, the individual disease states of the patient are hypertension (level 5), dyslipidemia (level 3), diabetes (level 3), and obesity (level 3), so the output unit 102 It is detected that the record corresponding to the patient's individual disease state and personal data corresponds to the record in the third column. Subsequently, the output unit 102 obtains the patient's disease risk and improvement goal by referring to the "disease risk" and "improvement goal" in the third column record.

Subsequently, the output unit 102 outputs, as the patient's disease state, a flag indicating that the patient falls under a complex disease state (metabolic syndrome), a flag indicating that the patient falls under hypertension, a flag indicating that the patient falls under dyslipidemia, A flag indicating that the condition corresponds to diabetes, a flag indicating that the condition corresponds to obesity, data indicating that the severity of hypertension is level 3, data indicating that the severity of dyslipidemia is level 3, Data indicating that the severity of diabetes is level 3 and data indicating that the severity of obesity is level 3 are output. In addition, the output unit 102 sets the improvement goals to be such that the waist circumference is 80 cm or less, the systolic blood pressure is 160 mmHg or less, the diastolic blood pressure is 100 mmHg or less, and the stress-related lifestyle score is improved by 20% or more. It also outputs information such as improving your sleep-related lifestyle score by 20% or more. Furthermore, the output unit 102 outputs, as disease risks, information such as a high risk of developing cerebrovascular disease and a high risk of developing coronary artery disease. Note that the disease risk may be expressed numerically. Note that when outputting the improvement goal, the output unit 102 may output a specific numerical value as the lifestyle score. For example, the output unit 102 calculates a lifestyle score based on the interview data, and combines the calculated lifestyle score (for example, sleep = 50) with the target value indicated by the improvement goal (for example, the lifestyle score regarding sleep improves by 20% or more. ), a specific target value (for example, score 50×120%=score 60) may be output. Further, the output unit 102 may further output the number of individual diseases applicable to the patient as the disease state of the patient as a risk value regarding the complex disease state (metabolic syndrome). Here, the output unit 102 may output "4" as the risk related to the complex disease state. Returning to FIG. 13, the explanation will be continued.

Subsequently, the output unit 102 transmits the disease state and disease risk output in step S105 and step S107 to the patient terminal 20 (S110). The patient terminal 20 displays the disease state and disease risk received from the medical support device 10 on the screen (S111).

Further, the output unit 102 transmits the disease state, improvement goal, and disease risk output in steps S105 to S107 to the doctor terminal 30 (S112). The medical support device 10 displays the disease state, improvement goal, and disease risk received from the medical support device 10 on the screen (S113). The doctor terminal 30 may accept corrections to the improvement goals if the doctor desires to make corrections to the improvement goals (S114). Thereby, when examining a patient, the doctor can present the improvement target output from the medical support device 10 to the patient and modify the improvement target after consulting with the patient.

When the doctor terminal 30 receives a modification of the improvement goal from the doctor, it transmits the modified improvement goal to the medical support device 10 (S115). The medical support device 10 updates the "improvement goal" of the patient information 100a with the revised improvement goal (S116). Subsequently, the output unit 102 of the medical support device 10 transmits the improvement goal data stored in the "improvement goal" of the patient information 100a to the patient terminal 20 (S117). The patient terminal 20 displays the improvement target received from the medical support device 10 on the screen (S118).

FIG. 14 is a sequence diagram showing an example of a processing procedure performed by the medical support system 1. Although the processing procedure shown in FIG. 14 is assumed to be repeatedly executed every day until the next medical examination, it is not necessarily limited to this. For example, it may be repeatedly executed every other day or every week.

The output unit 102 of the medical support device 10 determines options for behavioral goals that the patient should work toward in order to achieve the improvement goal, based on the patient's personal data, the patient's improvement goal, and/or the patient's complex disease state. S200). The output unit 102 compares the patient's personal data, the patient's improvement goals, and/or the patient's complex disease state with the selection criteria defined in the behavioral goal definition information 100f, and selects behavioral goal options that satisfy the selection criteria. , may be determined as an option for the behavioral goal to be presented to the patient.

FIG. 19 is a diagram showing an example of behavioral goal definition information 100f. “Category” indicates the category of the behavioral goal. "Action goal" indicates the specific content of the action goal. "Selection criteria" indicates the patient criteria for which the behavioral goal is selected. For example, according to Figure 19, the behavioral goal "Eat your meals with vegetables" is an option when the fasting blood sugar level in the test data is 110 mg/dl or higher and the triglyceride level is 150 mg/dl. It means to be extracted. Although not shown in FIG. 19, selection criteria such as "patient whose complex disease state is metabolic syndrome" can also be set. Returning to FIG. 14, the explanation will be continued.

Subsequently, the output unit 102 of the medical support device 10 transmits the behavioral goal options determined in step S200 to the patient terminal 20 (S201). The patient terminal 20 displays the behavioral goal options received from the medical support device 10 on the screen, and accepts the patient's selection of the behavioral goal to be addressed (S202). The patient terminal 20 transmits the selected behavioral goal to the medical support device 10 (S203). The reception unit 103 of the medical support device 10 receives the selected behavioral goal and stores it in the patient information 100a (S204).

Subsequently, the output unit 102 of the medical support device 10 refers to the questionnaire definition information 100d and transmits the questionnaire data stored in the questionnaire definition information 100d to the patient terminal 20 (S205). The patient terminal 20 displays the questionnaire received from the medical support device 10 on its screen, and receives input of questionnaire responses from the patient (S206). The patient terminal 20 transmits the answers to the questionnaire received from the patient to the medical support device 10. Furthermore, the patient terminal 20 transmits biometric information acquired from a wearable device worn by the patient (S207). The reception unit 103 of the medical support device 10 receives the answers to the questionnaire and the biological information, and stores them in the patient information 100a (S208). Subsequently, the calculation unit 104 of the medical support device 10 calculates a score regarding the degree of achievement of the behavioral goal from the answers to the questionnaire and/or the biological information (S209).

Further, the output unit 102 selects advice to be output to the patient by referring to the advice definition information 100g and comparing the questionnaire answers, scores, and/or biological information with the output conditions (S209). The output unit 102 generates short-term advice (for example, daily review) by comparing the answers, scores, and/or biometric information of the previous day's questionnaire with the "output conditions" of the advice (daily) definition information 100g-1. may be selected. In addition, the output unit 102 outputs the answers, scores, and/or biometric information of the past week's questionnaire and the "output conditions" of the advice (weekly summary) definition information 100g-2 for each predetermined day of the week (for example, Friday). You may select medium-term advice (for example, a one-week review) by comparing the following. When selecting medium-term advice, the output unit 102 may compare the trend or average value of scores over the past week with "output conditions." In addition, the output unit 102 outputs the past month's questionnaire responses, scores, and/or biometric information, and advice (monthly summary) definition information 100g- Long-term advice (for example, one month's review) may be selected by comparing with the "output conditions" in step 3. When selecting long-term advice, the output unit 102 may compare the trend or average value of scores over the past month with "output conditions."

Subsequently, the output unit 102 transmits the calculated score and the selected advice to the patient terminal 20 (S210). The patient terminal 20 displays the score and advice on the screen (S211). In addition, the patient terminal 20 further includes current or future images of the patient's appearance, current or future images of organs, trivia regarding medical information, images showing changes in the patient's personal data, and images showing changes in score. , various quizzes, etc. may be displayed (S212). Data necessary for displaying these images may be transmitted from the medical support device 10 to the patient terminal 20 in the processing procedure of step S210.

Upon receiving instructions from the doctor, the doctor terminal 30 requests the medical support device 10 to refer to the patient's behavioral goals, answers to the questionnaire, scores and advice regarding the degree of achievement of the behavioral goals (S220). The output unit 102 of the medical support device 10 transmits the behavioral goal selected by the patient, the answer to the questionnaire, the score and advice regarding the degree of achievement of the behavioral goal to the doctor terminal 30 (S221). The doctor terminal 30 displays the received behavioral goals, questionnaire answers, scores, and advice on the screen (S222). This allows the doctor to check the patient's daily activities at any time.

<Screen display example>
(Patient terminal)
20 to 24 are diagrams showing examples of screen displays of the patient terminal 20. Screens A100 to A120 in FIG. 20 are examples of screens that display the patient's current disease status and the like. When the button B10 is pressed, the screen changes to a screen A100 that displays the disease name of the complex disease state. When the button B11 is pressed, the screen changes to a screen A100 that displays the name of the individual disease and the state (severity) of the individual disease. When the button B12 is pressed, the screen changes to a screen A100 that displays the names of diseases that the user may be affected by and the disease risks. Screens A100 to A120 correspond to, for example, the screens displayed in the processing procedure of step S111 in FIG. 13.

Screen A200 and screen A210 in FIG. 21 show examples of screens that display improvement targets. Screen A200 is a display example in which all items of the improvement goals are displayed, and screen A210 is a display example in which only some items are displayed so that the improvement goals can be easily understood. Screen A200 and screen A210 correspond to, for example, the screens displayed in the processing procedure of step S118 in FIG. 13.

Screen A300 and screen A310 in FIG. 22 show examples of screens that accept setting of behavioral goals. On screen A300, a maximum of three behavioral goals can be set, and when buttons B30 to B32 are pressed, the screen changes to screen A310 that displays behavioral goal options. Screen A310 includes an area B33 that displays buttons for selecting a behavioral goal category, and an area B34 that displays a list of behavioral goal options that correspond to the selected category. When button B30 is pressed, the screen changes to screen A310, and the action goal selected in area B34 of screen A310 is reflected on button B30 of screen A300. Similarly, when button B31 is pressed, the screen changes to screen A310, and the action goal selected in area B34 of screen A310 is reflected on button B31 of screen A300. Screen A300 and screen A310 correspond to, for example, the screens displayed in the processing procedure of step S202 in FIG. 13.

Screen A400 in FIG. 23 shows an example of a screen for inputting answers to the questionnaire. Screen A400 corresponds to, for example, the screen displayed in the processing procedure of step S206 in FIG. 13. Screen A401 in FIG. 23 shows an example of a screen that displays scores regarding the degree of achievement of behavioral goals. In the area P40, scores related to the degree of achievement of behavioral goals are displayed for each category. Note that, as shown in area P41 of screen A410, output unit 102 of medical support device 10 may display advice regarding the score on the screen of patient terminal 20. The displayed advice may be advice related to the category with the lowest score. In addition to daily advice, on predetermined days of the week (for example, Fridays), advice as a summary of the week is displayed, and on predetermined days of the month (for example, at the end of the month), a summary of the month is displayed. Advice may also be displayed. Screen A401 corresponds to, for example, the screen displayed in the processing procedure of step S211 in FIG. 13.

FIG. 24 is an example of a screen that graphically displays a patient's disease risk. In this embodiment, the medical support device 10 may calculate the risk of future diseases occurring in each organ of the patient based on the patient's personal data, and display the calculated results on the patient terminal 20. . On the screen A450, an area P45 for displaying test data and an overall body diagram P46 are displayed. In the overall body diagram P46, organs that are likely to cause disease in the future are highlighted. In the example of screen A450, it is shown that there is a possibility of developing a disease in both eyes in the future. Screen A460 shows a state in which a part of the overall body view is displayed in an enlarged manner.

FIG. 25 shows an example of a screen that displays "trivia" that is specific medical information about diseases and test items related to each organ. Trivia regarding the organ selected on the organ list screen A470 is displayed as trivia screens A471 and A472.

FIG. 26 shows an example of a screen showing changes in patient's personal data. Screen A480 shows changes in blood pressure, and screen A481 shows changes in scores related to meals. Screen A482 shows a one-week summary generated based on the answers to the questionnaire entered by the patient regarding meals.

FIG. 27 shows an example of a screen related to quizzes. Screen A490 is a screen for inputting quiz answers. If the patient answers the quiz correctly, points are awarded to the patient as shown in screen A491. Screen A492 displays an explanation regarding the quiz.

(Doctor terminal)
28 to 30 are diagrams showing examples of screen displays of the doctor terminal 30. Screen A500 in FIG. 28 is an example of a screen that displays a list of information regarding patients. The patient's test data is displayed in the area P50. In the area P51, improvement goals (improvement target values for test values and improvement target values for lifestyle-related scores) are displayed. In the area P52, daily changes in the score regarding the degree of achievement of the behavioral goal are displayed. In the area P53, a monthly summary of the questionnaire response results and a monthly summary of data acquired from the patient's wearable device are displayed. The patient's drug history is displayed in area P54.

Screen A600 in FIG. 29 is an example of a screen that displays medical history and examination data in detail. The patient's medical history is displayed in area P60. In the area P61, a list of patient test data is displayed.

Screen A700 in FIG. 30 is an example of a screen that displays improvement targets in detail. In area P70, the patient's improvement goals are displayed divided into improvement target values for test values and improvement target values for scores related to lifestyle habits. Note that the doctor can also modify the improvement target displayed in the area P70. Area P71 is a screen for recording the contents of instruction for the patient. The doctor can record the contents conveyed to the patient during the medical examination in the area P71.

<Experiment results>
The left graph in FIG. 31 shows the above-mentioned judgment method 2 based on the patient's test data at the start and after 12 weeks for a patient with a complex disease state whose life was improved using the medical support system 1 according to the present embodiment. Figure 2 shows changes in risk values for complex disease states calculated according to the following. Furthermore, the right graph in FIG. 31 shows the above-mentioned results based on the patient's test data at the start and after 12 weeks for a patient with a complex disease who tried to improve his life without using the medical support system 1 according to the present embodiment. Figure 3 shows changes in risk values regarding complex disease states calculated according to determination method 2. According to the experimental results, it can be seen that patients with complex disease states who tried to improve their lives using the medical support system 1 according to the present embodiment had improved risk values.

<Summary>
According to the embodiment described above, based on the patient's personal data, the disease state of the patient is determined for the individual diseases that make up the complex disease, the risk assessment of related diseases is performed, and the combination of the disease states of the individual diseases is In the case of a disease state, the improvement goals that the patient should achieve in order to improve the complex disease state are output in the form of both long-term goals and short-term goals. In addition, the system aims to create a score for daily life using the input questionnaires and biometric information, making it possible to provide short-term (daily) evaluation and advice. As a result, even when multiple diseases are present, it is possible to recommend target values and goal settings that should be strengthened compared to when a single disease is present, thereby providing technology that can support appropriate therapeutic intervention for patients. becomes possible. In addition, in the past, in actual clinical practice, it has been usual to treat each individual disease, even though the disease is co-occurring or is likely to occur soon. Comprehensive treatment has not been performed. However, in the present embodiment, the medical support device 10 presents appropriate improvement goals according to the complex disease state based on the patient's personal data, so it is possible to efficiently obtain continuous daily life information. treatment becomes possible.

Furthermore, in this embodiment, improvement targets are output on the assumption that the patient is in a complex disease state. As a result, it is possible to output improvement goals that can efficiently treat complex disease states, taking into account the weight (severity) of each individual disease that makes up the complex disease state, rather than simply a combination of improvement goals for each individual disease. becomes possible.

In addition, by setting behavioral goals to achieve improvement goals and displaying daily scores based on the responses to questionnaires regarding the behavioral goals that have been set, patients can reflect on their own behavior on a daily basis and are encouraged to achieve their goals. It will be possible to maintain your motivation.

In addition, patients' personal data, improvement goals, behavioral goals, survey responses, etc. are also shared with the doctor treating the patient, so the doctor can grasp the status of the patient's efforts toward improvement goals and prepare for the next consultation. It becomes possible to make use of it.

The embodiments described above are intended to facilitate understanding of the present invention, and are not intended to be interpreted as limiting the present invention. The flowcharts, sequences, and elements included in the embodiments, as well as their arrangement, materials, conditions, shapes, sizes, etc., described in the embodiments are not limited to those illustrated and can be changed as appropriate. Further, it is possible to partially replace or combine the structures shown in different embodiments.

Further, in the embodiment described above, the patient terminal 20, the output unit 102 that outputs data to the patient terminal 20, and the reception unit that receives various inputs from the patient terminal 20 are replaced with the second terminal and the second output, respectively. It may also be referred to as a department and a second reception department. In addition, the doctor terminal 30, the output unit 102 that outputs data to the doctor terminal 30, and the reception unit that receives various inputs from the doctor terminal 30 are respectively referred to as a first terminal, a first output unit, and a first reception unit. may be called. Further, in the embodiment described above, the output unit 102 outputs the magnitude of the risk, score, and severity level using numerical values, but the output unit 102 is not limited to this. For example, instead of numerical values, colors (for example, red (high severity) to blue (low severity)) or symbols (for example, "A" (maximum score) to "Z" (minimum score)) etc.) may be used for output. In this case, the display control unit 202 of the patient terminal 20 may display a yellow icon on the screen A100 of FIG. 20 instead of displaying "Risk is 4". Further, the display control unit 202 of the patient terminal 20 may display the alphabet instead of the score on the screen A410 of FIG. 23.

DESCRIPTION OF SYMBOLS 1...Medical support system, 10...Medical support device, 11...Processor, 12...Storage device, 13...Communication IF, 14...Input device, 15...Output device, 20...Patient terminal, 30...Doctor terminal, 100... Storage unit, 100a...Patient information, 100b...Individual disease definition information, 100c...Complex disease/goal definition information, 100d...Questionnaire definition information, 100e...Score definition information, 100f...Behavior goal definition information, 101...Acquisition unit, 102... Output unit, 103...Reception unit, 104...Calculation unit, 200...Storage unit, 201...Reception unit, 202...Display control unit, 300...Storage unit, 301...Reception unit, 302...Display control unit

Claims (15)

an acquisition unit that acquires personal data including at least one of the user's examination data and interview data;
Based on the personal data, the disease state of the user is determined for individual diseases constituting a complex disease, and the combination of the disease states of the individual diseases or the combination of the disease states of the individual diseases and the personal data is a complex disease state. an output unit that outputs an improvement goal that the user should achieve in order to improve the complex disease condition;
A medical support device with The improvement goal includes an improvement target value for the test value included in the personal data,
The medical support device according to claim 1. The output unit sets improvement targets for test values included in the personal data based on a combination of disease states of the individual diseases or a combination of disease states of the individual diseases and personal data.
The medical support device according to claim 2. The personal data includes data regarding the user's lifestyle habits,
The improvement goals include improvement goals for the user's lifestyle habits,
The medical support device according to claim 1. The lifestyle habits include at least one of the user's stress, the user's sleeping time, the user's amount of exercise, the user's eating habits, the user's smoking amount, and the user's drinking amount.
The medical support device according to claim 4. The output unit is configured to input the improvement goal obtained by inputting the personal data to a learned model that has the ability to output an improvement goal for improving the complex disease state, and the output unit determines the improvement goal that the user should achieve. output as improvement goals,
The medical support device according to any one of claims 1 to 5. A combination of the individual disease definition information that defines the correspondence between the personal data and the disease state of the individual disease, and the disease state of the individual disease, or a combination of the disease state of the individual disease and the personal data is a complex disease state. and a storage unit that stores goal definition information that defines an improvement goal for a case,
The output unit determines the disease state of the user by referring to the individual disease definition information, and determines a combination of disease states of the individual diseases or a disease state of the individual diseases by referring to the target definition information. and obtaining the improvement goal when the combination of personal data is a complex disease state, and outputting the obtained improvement goal as the improvement goal to be achieved by the user.
The medical support device according to any one of claims 1 to 5. a first reception unit that receives from the user a behavioral goal that the user is working on from among a plurality of options regarding behavioral goals for achieving the improvement goal;
The output unit outputs the action goal that the user is working on, which was received by the first reception unit, to a terminal used by a doctor who examines the user.
The medical support device according to any one of claims 1 to 7. The first reception unit determines the plurality of options based on the personal data, the improvement goal, or the complex disease state of the user.
The medical support device according to claim 8. The first reception unit receives input of answers to a questionnaire regarding behavioral goals that the user is working on,
a calculation unit that calculates a score regarding the degree of achievement of the behavioral goal that the user is working on based on the answers to the questionnaire received by the first reception unit;
The output unit outputs the score calculated by the calculation unit,
The medical support device according to claim 8 or 9. The behavioral goals include a behavioral goal related to improving stress of the user, a behavioral goal related to improving sleep time of the user, a behavioral goal related to improving the amount of exercise of the user, a behavioral goal related to improving the eating habits of the user, and a behavioral goal related to reducing the amount of smoking of the user. including at least one of a behavioral goal and a behavioral goal related to reducing alcohol consumption of the user;
The medical support device according to any one of claims 8 to 10. The output section is
Regarding the individual diseases that make up the complex disease, each test item is determined using the reference value of one or more test items related to the individual disease and the test data for the test item obtained by testing the user. Calculate the risk,
If the calculated risk for each test item satisfies a predetermined condition, determining that the user is in the complex disease state, and outputting an improvement goal that the user should achieve in order to improve the complex disease state;
The medical support device according to any one of claims 1 to 11. If the calculated risk for each test item satisfies a predetermined condition, the average value of the calculated risks for each test item is greater than or equal to a predetermined threshold;
The output unit outputs the average value of the calculated risks for each test item as a value indicating the risk related to the complex disease state.
The medical support device according to claim 12. A medical support method performed by a medical support device, comprising:
acquiring personal data including at least one of test data and interview data of the user;
Based on the personal data, the disease state of the user is determined for individual diseases constituting a complex disease, and the combination of the disease states of the individual diseases or the combination of the disease states of the individual diseases and the personal data is a complex disease state. outputting an improvement goal that the user should achieve in order to improve the complex disease condition;
Medical assistance methods, including: to the computer,
acquiring personal data including at least one of test data and interview data of the user;
Based on the personal data, the disease state of the user is determined for individual diseases constituting a complex disease, and the combination of the disease states of the individual diseases or the combination of the disease states of the individual diseases and the personal data is a complex disease state. outputting an improvement goal that the user should achieve in order to improve the complex disease condition;
Medical support program to carry out.

Images