JP2024052718A - Medical support device, medical support method, and medical support program - Google Patents

Abstract

[Problem] To provide a technology capable of supporting the treatment of a user even when the user has a complex condition involving multiple diseases. [Solution] To provide a medical support device having an acquisition unit that acquires personal data including the user's examination data and interview data, and an output unit that determines the user's disease state for individual diseases that constitute a complex disease based on the personal data, and outputs an improvement goal that the user should achieve in order to improve the complex disease state 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 results in a complex disease state. [Selected Figure] Figure 5

Description

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

Currently, systems aimed at improving a user's health condition are known. For example, Patent Literature 1 discloses a health management device that can suggest measures to maintain or improve a user's health condition based on the nutritional value of the food the user has consumed and the user's health condition.

JP 2021-176053 A

Currently, medical devices and medical programs aimed at supporting the treatment of individual diseases such as diabetes are approved and provided in Europe and elsewhere. However, because these medical devices and medical programs are aimed at individual diseases, it is difficult to support the treatment of patients with multiple diseases, such as metabolic syndrome.

Therefore, the present disclosure aims to provide technology that can assist users in treating their condition even when multiple diseases are present.

A medical support device according to one aspect of the present disclosure includes an acquisition unit that acquires personal data including a user's test data and interview data, and an output unit that determines the user's disease state for individual diseases that constitute a complex disease based on the personal data, and outputs an improvement goal that the user should achieve in order to improve the complex disease state when 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.

This disclosure provides technology that can assist users in treating patients even when they have multiple diseases.

1 is a diagram illustrating an example of a medical support system according to an embodiment of the present invention. 1 is a flowchart showing an overview of a process performed by the medical support system. FIG. 11 is a diagram showing an example of personal data. FIG. 13 is a diagram showing an example of a case where a composite disease state is judged based on judgment method 1. FIG. 13 is a diagram showing an example of a case where a composite disease state is judged based on judgment method 2. FIG. 1 is a schematic diagram showing a flow of medical support using a medical support system. 2 is a diagram illustrating an example of the hardware configuration of a medical support device, a patient terminal, and a doctor terminal. FIG. 2 is a diagram illustrating an example of a functional block configuration of a medical support device. 11A to 11C are diagrams showing examples of patient information, individual disease definition information, complex disease/goal definition information, questionnaire definition information, and score definition information. FIG. 11 is a diagram illustrating an example of advice definition information. FIG. 1 is a diagram illustrating an example of a trained model. FIG. 2 is a diagram illustrating an example of a functional block configuration of a patient terminal. FIG. 2 is a diagram illustrating an example of a functional block configuration of a doctor's terminal. FIG. 11 is a sequence diagram illustrating an example of a processing procedure performed by the medical support system. FIG. 11 is a sequence diagram illustrating an example of a processing procedure performed by the medical support system. FIG. 11 is a diagram showing a specific example of inspection data. FIG. 11 is a diagram showing a specific example of medical interview data. FIG. 13 is a diagram showing a specific example of individual disease definition information. FIG. 13 is a diagram showing a specific example of individual disease definition information. FIG. 13 is a diagram showing a specific example of complex disease/goal definition information. FIG. 11 is a diagram illustrating an example of behavioral goal definition information. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a patient terminal. FIG. 13 is a diagram showing an example of a screen display of a doctor's terminal. FIG. 13 is a diagram showing an example of a screen display of a doctor's terminal. FIG. 13 is a diagram showing an example of a screen display of a doctor's terminal. FIG. 1 shows experimental data.

The following describes an embodiment of the present invention with reference to the attached drawings. In each drawing, the same reference numerals denote the same or similar configurations.

<System Configuration>
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 for supporting a patient's disease treatment, 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. The patient terminal 20 and the doctor terminal 30 may each be one or more.

The medical support system 1 is a system that aims to support patients (who may be referred to as "users") suffering from multiple diseases by helping them understand their disease states and encouraging them to change their own behavior to help them recover from their disease states. The medical support system 1 may have, for example, the following multiple functions.
1. A function for determining a patient's disease state; 2. A function for indicating the patient's disease state to a doctor; 3. A function for proposing improvement goals to be achieved in order to improve the disease state to a doctor, and for accepting the setting of improvement goals to be achieved by the patient; 4. A function for indicating the patient's own disease state to a patient, and for presenting improvement goals to be achieved; 5. A function for accepting the setting of behavioral goals (which may be called "challenges") to be worked on in order to achieve improvement goals from the patient; 6. A function for displaying a score regarding the degree of achievement of behavioral goals to be worked on by the patient, based on the responses to a questionnaire regarding daily behavioral goals received from the patient. The medical support device 10 has the function of determining a patient's disease state, proposing improvement goals, and accepting the setting of daily behavioral goals, as well as 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 the patient, and has a function of displaying information received from the medical support device 10 and a function of accepting various inputs from the patient. The patient terminal 20 may be, for example, a smartphone, a tablet terminal, a personal computer, etc.

The doctor's 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 accepting various inputs from the doctor. The doctor's terminal 30 is assumed to be a personal computer or the like installed in a medical institution, but is not limited to this, and may be, for example, a smartphone or a tablet terminal. The medical support device 10 has a web server function, and a web browser installed on the doctor's terminal 30 may access the medical support device 10 to display information and accept inputs on the doctor's terminal 30. Alternatively, a dedicated application installed on the patient's terminal 20 may access the medical support device 10 to display information and accept inputs on the doctor's terminal 30.

The patient terminal 20 may include a wearable device worn by the patient. The medical support system 1 may acquire and store various data related to the patient (hereinafter referred to as "biometric information") from the wearable device. For example, the patient may wear the wearable device and transmit various biometric information (heart rate, number of steps, amount of exercise, etc.) to the medical support device 10, and may use a smartphone to set behavioral goals and refer to a score related to the degree of achievement of the behavioral goals.

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

Blood test data may also include lipid-related data such as triglycerides, HDL cholesterol, LDL cholesterol, and non-HDL cholesterol; liver and pancreas function-related data such as AST (GOT), ALT (GPT), and γ-GPT; kidney function-related data such as creatinine; anemia-related data such as hematocrit value, hemoglobin content, white blood cell volume, and red blood cell volume; blood pressure-related data such as systolic blood pressure and diastolic blood pressure; blood glucose-related data such as fasting blood glucose (potential difference method) and HbA1c (NGSP value); and general blood data including uric acid levels. Urine test data may also include data such as urinary sugar, urinary protein, and urinary occult blood.

The interview data may include, for example, data on illnesses the patient has suffered from in the past (medical history), data on illnesses that are already known to affect the patient (e.g., disease names), past and current data on illnesses of family members and close relatives (family history), data on medication history (past and present use of medication, names of specific medications taken/being taken, etc.), data on social history (educational background, annual income, family structure, etc.), smoking information (past and present smoking habits, amount smoked, duration of smoking, willingness to improve, etc.), drinking information (whether or not drinking has been done, specific details of drinking habits such as amount, type and duration of alcohol consumption, etc.), diet (number of meals, meal contents, whether or not eating out, willingness to improve diet, etc.), amount of activity (whether or not exercise is done daily, specific amount of exercise, frequency and willingness to improve activity, etc.), information on weight change, sleep information (information on quality and quantity of sleep, willingness to improve, etc.), job content, attendance information, hobbies and preferences, stress, and other lifestyle data. Medical history, disease names, and family history are collectively referred to as "medical history". In this embodiment, the medical history is not limited to including all of the medical history, disease name, and family history. Anything that includes at least one of the medical history, disease name, and family history may be referred to as medical history.

Next, the medical support device 10 judges the disease state of the patient based on the acquired personal data of the patient (S11). More specifically, the medical support device 10 judges the presence or absence of an individual disease (hereinafter referred to as "individual disease") suffered by the patient from the personal data of the patient. An individual disease means one disease, and examples thereof include lifestyle-related diseases such as obesity, diabetes, hypertension, dyslipidemia, fatty liver, cardiovascular disease, cerebrovascular disease, osteoporosis, dementia, periodontal disease, alcoholic hepatitis, nonalcoholic fatty liver disease, cirrhosis, hyperuricemia, gastric ulcer, peripheral neuropathy, and allergies. In addition to these, the individual diseases include various diseases such as cancer, renal failure, chronic obstructive pulmonary disease, arthropathy, lower back pain, cataracts, glaucoma, and sleep apnea syndrome. Next, the medical support device 10 judges that the patient is in a "complex disease state" when the patient corresponds to multiple individual diseases defined in advance as a combination pattern, or when the patient corresponds to the conditions of multiple individual diseases and personal data defined in advance as a combination pattern. Furthermore, the medical support device 10 determines that a patient does not have a "complex disease state" if the patient does not fall under a plurality of individual diseases defined in advance as a combination pattern, or if the patient falls under a plurality of individual diseases defined in advance as a combination pattern but does not fall under the conditions of the personal data. In other words, a "complex disease state" means a state in which the patient falls under a plurality of individual diseases defined in advance as a combination pattern, or a state in which the patient falls under a plurality of individual diseases and the conditions of the personal data defined in advance as a combination pattern. Note that a "condition of the personal data" means that a predetermined item of the personal data satisfies a predetermined condition. Examples of the "condition of the personal data" include, for example, that an item indicating sex in the personal data is male, that an item indicating age in the personal data is XX or older, and that an item indicating waist circumference in the personal data is XX cm or more.

A specific example of a complex disease state is metabolic syndrome. In the case of metabolic syndrome, the "multiple individual diseases defined in advance as a combination pattern" corresponds to at least two of diabetes (abnormal blood glucose level), hypertension (abnormal blood pressure), and dyslipidemia (abnormal lipid level), and the "conditions for personal data" may be defined as at least an abdominal circumference of 85 cm or more (for men) or 90 cm or more (for women). The "conditions for personal data" may also be defined as meeting diagnostic criteria for various diseases that can be obtained from personal data in addition to abdominal circumference. According to the definition, if a patient suffers from two or more of diabetes, hypertension, and dyslipidemia, and is male and has an abdominal circumference of 85 cm or more (90 cm or more for women), the medical support device 10 judges that the patient has a complex disease state (metabolic syndrome). The criterion for determining whether or not a patient has metabolic syndrome may be that the patient is obese (more specifically, visceral fat obese), instead of having a waist circumference of 85 cm or more (for men) or 90 cm or more (for women). In this case, the "multiple individual diseases predefined as a combination pattern" in metabolic syndrome may be defined as at least two or more of diabetes, hypertension, and dyslipidemia, in addition to obesity (visceral fat obese).

Other examples of complex disease states include chronic individual diseases, such as diabetes, hypertension, malignant neoplasms (cancer), heart disease (excluding hypertensive diseases), or cerebrovascular disease, as well as anxiety, depression, pain, physical disorders, and neurological disorders, which are not yet named. In such complex disease states, treatment is often performed independently, which tends to increase the number of drugs and complicate the dosage pattern. In addition, since treatment guidelines generally target a single disease, it is easy for treatment to become fragmented and communication between doctors treating each disease to be insufficient. Specifically, it has been reported that diabetes increases the risk of stroke, acute myocardial infarction, heart failure, and depression, and also increases the risk of dementia, so some patients may have both diabetes and depression, or diabetes, depression, and dementia. In the present invention, such a state in which multiple individual diseases occur simultaneously or the risk of developing them is increased may be considered as a complex disease state.

More specifically, the medical support device 10 may determine whether or not the patient is in a complex disease state according to the following method. Furthermore, the medical support device 10 may determine a risk value related to the complex disease state. The risk value related to the complex disease state may indicate the overall severity of the complex diseases from which the patient is suffering, and the higher the risk value, the more severe the condition.

(Determination method 1)
The "plurality of individual diseases predefined as a combination pattern" may be defined as at least a predetermined number of the individual diseases as described above. The predetermined number may be 2, 3 or more. In addition, the medical support device 10 may determine that a patient is in a complex disease state when the patient is afflicted with a predetermined number or more of the individual diseases predefined as a combination pattern or has a high risk of developing the individual diseases. In addition, the medical support device 10 may determine the risk value of the complex disease state based on the number of individual diseases among the plurality of individual diseases predefined as a combination pattern in the complex disease state. For example, when the number of individual diseases is five, the medical support device 10 may determine that the risk is 5. Note that the larger the number, the higher the risk.

Figure 3 is a diagram showing an example of personal data. Figure 3 shows an example of personal data (test data) obtained by testing subjects A to I for 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 fasting blood glucose and HbA1C, which are test items related to blood glucose.

Figure 4 is a diagram showing an example of a case where a complex disease state is judged based on the judgment method 1. In addition, ◯ indicates that it is applicable, and × indicates that it is not applicable. In the example of Figure 4 (the example of Figure 5 is also the same), the medical support device 10 judges whether or not the complex disease state corresponds to metabolic syndrome. For example, a patient whose personal data on visceral fat (waist circumference and BMI) does not meet a predetermined standard corresponds to obesity. A patient whose personal data on lipids (neutral fat, etc.) does not meet a predetermined standard corresponds to dyslipidemia. A patient whose personal data on blood pressure (systolic blood pressure, etc.) does not meet a predetermined standard corresponds to hypertension. A patient whose personal data on blood glucose (fasting blood glucose, etc.) does not meet a predetermined standard corresponds to diabetes. In addition to whether or not the patient corresponds to each individual disease, the medical support device 10 may judge the severity of each individual disease using the individual disease definition information 100b or a learned model described later. "Judgment" indicates whether or not the patient corresponds to a complex disease state (here, metabolic syndrome). "(Reference) Metabolic syndrome assessment" is a reference for the assessment results of metabolic syndrome assessments made by actual doctors according to the academic society's standards. 〇 means that the person has metabolic syndrome, and △ means that the person is at risk of developing metabolic syndrome.

In the example of FIG. 4, if two or more of the multiple individual diseases predefined as combination patterns are present, the condition is determined to be a complex disease state (metabolic syndrome), but this is not limited thereto. For example, if three or more individual diseases are present, the condition may be determined to be a complex disease state (metabolic syndrome).

(Determination method 2)
The medical support device 10 may calculate the risk for each test item using reference values (which may be called cutoff values) of one or more test items related to each of a plurality of individual diseases defined in advance as combination patterns and test data for the test items obtained by testing the patient, and may determine that the patient has a complex disease state if the average value of the calculated risks for each test item is equal to or greater than a predetermined threshold. The medical support device 10 may also determine that the patient does not have a complex disease state if the average value of the risks for each test item is less than a predetermined threshold.

The medical support device 10 may also determine that the average value of the calculated risks for each test item is the risk value for the composite disease state. In this case, 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".

The medical support device 10 may also calculate the risk for each test item using the formula "Risk = (patient's test data - reference value) ÷ reference value" or "Risk = (reference value - patient's test data) ÷ reference value." Specifically, for test items that are considered to be abnormal when they exceed the reference value, the formula "Risk = (patient's test data - reference value) ÷ reference value" may be used, and for test items that are considered to be abnormal when they are below the reference value, such as HDL cholesterol, the formula "Risk = (reference value - patient's test data) ÷ reference value" may be used.

The medical support device 10 may also 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 "weighting value" that indicates the importance that each test item gives to the complex disease state, and may be determined in advance for each test item. The medical support device 10 may also add a number obtained by multiplying "the number of test items whose test data exceeds the reference value" by 0.1 to the average value of the calculated risks for each test item, and if the average value of the risks for each test item after the addition is equal to or greater than a predetermined threshold, determine that the patient has a complex disease state.

Figure 5 is a diagram showing an example of a case where a composite disease state is judged based on judgment method 2. Points that are not particularly mentioned may be the same as those in Figure 4. Each value in Figure 5 indicates a risk calculated based on the measurement data in Figure 3. Also, the risk value of the composite disease state (risk value related to the composite disease state) in Figure 5 is the average value of the risk for each test item plus the number of test items whose test data exceeds the reference value multiplied by 0.1. In judgment method 2, the risk value of the composite disease state is calculated by adding the number of test items whose test data exceeds the reference value multiplied by 0.1 to the risk value of the composite disease state. Therefore, the number of test items whose test data exceeds the reference value affects the risk value. This makes it possible to appropriately express the risk of the composite disease state.

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

Next, if the medical support device 10 determines that the patient has 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's terminal 30 and set (confirmed) upon confirmation (approval) by the doctor. In addition, the medical support device 10 may accept corrections to the output improvement goal from the doctor.

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

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

The improvement target value may be set to a stricter value (e.g., a value closer to a normal value, and so forth) the greater the number of individual diseases included in the combination of individual diseases in the composite disease state. In addition, if the patient's age exceeds a certain threshold (e.g., 45 years or older for men, 55 years or older for women, etc.), the improvement target value may be set to a stricter value than if the threshold is not exceeded. In addition, if the patient is a smoker, the improvement target value may be set to a stricter value than for non-smoking patients. In other words, the greater the number of individual diseases (number of risk factors) that make up the composite disease state, the stricter the improvement target value may be set to.

For example, assume that the improvement target of LDL cholesterol for a patient suffering only from dyslipidemia is set to less than 140 mg/dl. In this case, the medical support device 10 may set the improvement target of LDL cholesterol 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. The medical support device 10 may set the improvement target of LDL cholesterol for a patient 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. The medical support device 10 may set the improvement target of LDL cholesterol for a patient suffering from dyslipidemia, diabetes, and coronary artery disease to less than 70 mg/dl, which is closer to the normal value than less than 100 mg/dl, which is the improvement target of LDL cholesterol for a patient suffering from dyslipidemia and coronary artery disease.
In addition, in the case of a disease that is considered to be a lifestyle-related disease, the improvement goal may be an improvement goal for the patient's lifestyle. For example, improvement goals may include "limit strong-flavored dishes to one dish per meal,""walk after meals," or "go to bed one hour earlier than usual."

Next, the medical support device 10 accepts from the patient the setting of behavioral goals that the patient should work on to achieve the improvement goal (S13). The behavioral goals may be divided into a plurality of categories. The plurality of categories may include, for example, at least one of "stress," "sleep," "activity," "diet," "smoking," and "alcohol." Note that activity includes not only exercise but also general physical movement such as walking. In other words, the behavioral goals that the patient should work on to achieve the improvement goal may include at least one of behavioral goals related to improving the patient's stress, behavioral goals related to improving the patient's sleep time, behavioral goals related to improving the patient's exercise amount, behavioral goals related to improving the patient's diet, behavioral goals related to reducing the amount of smoking of the patient, and behavioral goals related to reducing the amount of alcohol consumed by the patient. For example, these behavioral goals may be specific behavioral goals in accordance with the patient's treatment plan, such as walking for 30 minutes or more, not eating after 9 p.m., always eating breakfast, or not drinking alcohol after 8 p.m., or the behavioral goals of each category related to the patient's lifestyle habits described above may be scored. Note that the categories are merely examples, 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 on to achieve the improvement goal, and may accept the patient's selection of the behavioral goal to work on from among the presented options. The medical support device 10 may determine the options for behavioral goals that the patient should work on 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. For example, if the patient's complex disease state is metabolic syndrome corresponding to hypertension and diabetes, the improvement goal is to reduce blood pressure to less than 130/80 mmHg, the blood glucose control goal is to reduce HbA1c to less than 6.0%, and the patient is 60 years old or older, the medical support device 10 may present options for behavioral goals such as "build stamina by walking fast," "avoid high-carbohydrate meals," and "avoid drinking alcohol."

Next, the medical support device 10 accepts from the patient a response to a questionnaire regarding the behavioral goal that the patient should work on (S14). More specifically, the questionnaire may be a questionnaire that confirms with the patient that the patient is working on the behavioral goal that the patient should work on. The questionnaire may include a questionnaire that directly confirms the results of the work on the behavioral goal selected by the patient in step S13 (the progress status). For example, if the patient selects "avoid high-carbohydrate meals" as the behavioral goal, a questionnaire such as "Did you avoid high-carbohydrate meals today?" may be included to directly confirm the results of the work on the behavioral goal selected by the patient. If the patient selects "walk for 30 minutes or more," a questionnaire such as "How many minutes in total did you exercise enough to make you sweat (including brisk walking and housework)?" may be included. In addition, the medical support device 10 accepts the patient's biological information from a wearable device worn by the patient.

Next, the medical support device 10 outputs a score on the degree of achievement of the behavioral goal that the patient should work on and advice on the degree of achievement of the behavioral goal that the patient should work on based on the answers to the questionnaire and/or the bioinformation received in step S14 (S15). As described above, since the behavioral goal may be divided into multiple categories, the score may also be output in the same category as the behavioral goal. The multiple categories may include, for example, at least one of "stress", "sleep", "exercise", "diet", "smoking" and "alcohol drinking" as with the behavioral goal. In other words, the score may include at least one of a score on stress, a score on sleep, a score on exercise, a score on diet, a score on smoking, and a score on alcohol drinking. In addition, the score may be calculated so that it is a high value when the patient is actively working toward achieving the improvement goal, and a low value when the patient is not actively working toward achieving the improvement goal. For example, the scores are exemplified as 80 for sleep, 59 for exercise, 78 for diet, and 100 for smoking/alcohol drinking. These scores may also be used as behavioral goals. In addition, the advice may be to praise the patient (e.g., "Keep up the good work") if the patient is taking proactive steps toward achieving the improvement goal, or to encourage improvement (e.g., "If you don't cut down on your drinking, your disease will get worse") if the patient is not taking proactive steps toward achieving the improvement goal.

In the processing procedure of step S15, the medical support device 10 may image and display a current or future image of the patient's appearance and/or a current or future image of the organs based on the improvement goal, behavioral goal, questionnaire, or advice.

The images of organs displayed by the medical support device 10 include the brain, liver, eyes, kidneys, heart, blood vessels, lungs, and nerves. This allows the patient to visually recognize and understand their current and future conditions by displaying images of each organ based on the patient's current condition, improvement goals, behavioral goals, questionnaires, or advice.

The medical support device 10 may also provide the patient with specific medical information on diseases and test items related to each organ in the form of "tidbits" in the form of videos and/or text. For example, in the case of the liver as an organ, explanatory videos on diseases such as fatty liver, hepatitis, cirrhosis, and liver cancer may be provided. In the case of dyslipidemia as a disease, a medical explanatory document on the disease such as "dyslipidemia is a disease in which LDL cholesterol (bad cholesterol) and neutral fats (triglycerides) become abnormal, and when cholesterol accumulates on the walls of blood vessels, it forms plaques (lumps), which block the passage of blood and develop into arteriosclerosis" may be displayed.

In this way, by allowing patients to visually grasp the state of their individual diseases and complex diseases, as well as the medical information related to them, patients themselves can understand their own condition, which will encourage them to make behavioral changes, such as to their lifestyle, based on an improvement plan, etc.

The medical support device 10 may also display data that allows the trend and distribution of input values such as the patient's personal data (e.g., personal data such as weight, blood pressure, and blood glucose level measured by the patient) over a period of one week, one month, or one year to be confirmed. Furthermore, the medical support device 10 may be configured to display information that allows the trend of each score, questionnaire responses, and advice, etc., over a period of one day, one week, or one month for each lifestyle category (stress, sleep, activity, diet, smoking, drinking, etc.). As a result, the patient himself/herself can understand his/her own condition and further encourage behavioral changes such as his/her lifestyle based on an improvement plan, etc.

Furthermore, the medical support device 10 may display quizzes aimed at improving literacy regarding health and lifestyle-related diseases. The format of the quiz is not particularly limited, but an example is a format in which one quiz question is displayed per day and the patient is asked to answer the quiz. By adding an innovative system in which five points are awarded for a correct answer and three points are awarded for an incorrect answer, patients can have fun while learning about knowledge and information regarding their health and lifestyle-related diseases, and can immediately put the health knowledge they have learned to use, which can promote improved health literacy and behavioral change.

The processing procedure of steps S10 to S12 described above is executed when the patient is examined by a doctor, and the processing procedure of steps S13 to S15 may be executed repeatedly every day between the end of the examination and the next examination.

Figure 6 is a schematic diagram showing the flow of medical support using the medical support system 1. As shown in Figure 6, the doctor examines the patient and inputs the patient's personal data (various test data, etc.) from the doctor's terminal 30. The patient also inputs the patient's personal data (various interview data) from the patient's terminal 20. The doctor also 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's terminal 30 and his own medical insight, etc.

After completing the consultation, the patient becomes aware of their own disease state and improvement goals by checking the disease state and improvement goals displayed on the patient terminal 20. The patient also sets daily behavioral goals toward achieving the improvement goals on the screen of the patient terminal 20, and answers a questionnaire displayed on the patient terminal 20 every day. When the patient answers the questionnaire, a score and advice regarding the achievement of the behavioral goal are displayed on the patient terminal 20, allowing the patient to reflect on their daily behavior. Furthermore, by repeatedly setting behavioral goals, answering the questionnaire, and checking the score and advice every day, the patient is able to continually review their own behavior, which ultimately enables them to achieve recovery from the disease.

<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 each have a processor 11 such as a CPU (Central Processing Unit) or a GPU (Graphical Processing Unit), a storage device 12 such as a memory, a HDD (Hard Disk Drive) and/or an SSD (Solid State Drive), a communication IF (Interface) 13 for wired or wireless communication, an input device 14 for accepting input operations, and an output device 15 for outputting information. The input device 14 is, for example, a keyboard, a touch panel, a mouse, and/or a microphone. The output device 15 is, for example, a display, a touch panel, and/or a speaker. The medical support device 10 may be composed of one or more physical servers, or may be composed of a virtual server operating on a hypervisor, or may be composed of a cloud server.

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

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

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 described. "Patient ID (Identification)" is an identifier for identifying a patient. "Age" indicates the age of the patient. "Gender" indicates the gender of the patient. "Personal data" stores various examination data and various interview data of the patient. "Disease state", "Disease risk", and "Improvement goal" store the disease state (disease state of each individual disease and complex disease state), disease risk, and improvement goal output from the medical support device 10 based on the personal data, respectively. "Behavioral goal" stores the behavioral goal selected by the patient. "Questionnaire response" stores the contents of the answers to the questionnaire answered by the patient. "Biometric information" stores information such as the amount of daily activity (number of steps, walking distance, calories burned, etc.), sleep information, and heart rate obtained from the wearable device.

Next, the individual disease definition information 100b will be described. The individual disease definition information 100b shown in FIG. 9A is defined for each individual disease. In the "personal data pattern", a pattern of test data and interview data corresponding to an individual disease (i.e., a predetermined standard that corresponds to an individual disease) is stored. The "severity" corresponds to the disease state of the individual disease and indicates the severity of the individual disease corresponding to the personal data pattern. The severity may be expressed in multiple levels (stages), and the higher the level, the more severe the disease. For example, in the individual disease definition information 100b corresponding to hypertension, the personal data pattern may be defined as level 5 hypertension when the systolic blood pressure is 180 mmHg or more and the diastolic blood pressure is 110 mmHg or more, and level 4 hypertension when the systolic blood pressure is 160 to 179 mmHg and the diastolic blood pressure is 100 to 109 mmHg. In addition, it means that an individual data pattern that is not included in the individual disease definition information 100b 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 can determine that a patient whose systolic blood pressure is 130 mmHg or less and whose diastolic blood pressure is 80 mmHg or less does not have hypertension.

Next, the composite disease/goal definition information 100c will be described. The composite disease/goal definition information 100c shown in FIG. 9A is defined for each composite disease state. For example, if the medical support device 10 is capable of judging the composite disease state A and the composite disease state B, the storage unit 100 stores the composite disease/goal definition information 100c corresponding to the composite disease state A and the composite disease/goal definition information 100c corresponding to the composite disease state B. The "disease state of individual diseases" and "personal data conditions" store a combination of the disease states of individual diseases corresponding to the composite disease state, or a combination of the disease states of individual diseases and personal data conditions corresponding to the composite disease state. If the composite disease state corresponds to a combination of the disease states of individual diseases, the "personal data conditions" may be omitted. The "disease risk" stores information indicating the name of another disease that the patient may suffer from, which is not currently affected but is inferred from the combination of the disease states of the patient's individual diseases or the combination of the disease states of the patient's individual diseases and personal data conditions, and the degree of the possibility of suffering from the disease. It is known that patients with metabolic syndrome may suffer from cerebrovascular disease or coronary artery disease in the future, and the more severe the individual diseases that make up metabolic syndrome, the higher the risk of suffering from cerebrovascular disease or coronary artery disease. Therefore, the "disease risk" in the complex disease/goal definition information 100c corresponding to metabolic syndrome may store a numerical value indicating the risk of suffering from cerebrovascular disease or coronary artery disease (for example, the higher the value, the higher the possibility of developing the disease in the future) and information regarding the color indicating the severity (magnitude of risk). The "improvement goal" stores a numerical improvement goal that the patient should achieve in order to improve the complex disease state.

When judging a composite disease state according to judgment method 1, it is possible to use the individual disease definition information 100b and the composite disease/goal definition information 100c shown in FIG. 9A. On the other hand, when judging a composite disease state according to judgment method 2, the composite disease/goal definition information 100c described above may store, instead of the items shown in FIG. 9A, data indicating the processing logic and reference values of each test item required to execute judgment method 2 as data common to each composite disease state, and data corresponding to "disease risk" and "improvement goal" as data for each composite disease state. In addition, the individual disease definition information 100b may store, instead of the items shown in FIG. 9A, data for each individual disease, a "predetermined value" used when judging whether or not a patient corresponds to an individual disease, and data indicating the correspondence between the risk value calculated for each test item related to an individual disease and the severity.

Next, the survey definition information 100d will be described. "Category" indicates the category of behavioral goals that the user is working on. In the example of FIG. 9A, examples of categories include stress, sleep, exercise, diet, smoking, and drinking, but are not limited to these. "Survey ID" indicates an identifier that identifies the survey. "Survey content" stores the content of the survey.

Next, the score definition information 100e will be described. "Questionnaire ID" indicates an identifier for identifying a questionnaire. The questionnaire ID corresponds to the questionnaire ID of the questionnaire definition information 100d. "Answer" indicates an answer to the questionnaire. "Score" indicates a value to be added to the score. In the example of FIG. 9A, it is shown that if "Yes" is answered to the questionnaire for stress 1, 1 is added to the score of the stress category. Similarly, it is shown that if "No" is answered to the questionnaire for stress 1, nothing is added to the score of the stress category. Note that the score definition information 100e shown in FIG. 9A is an example and 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 answers. For example, when the answer to questionnaire 1 belonging to stress is "Yes", the answer to questionnaire 5 belonging to stress is "Yes", and the answer to questionnaire 1 belonging to sleep is "No", logic may be stored such that 3 is added to the score of the stress category. In addition, the score definition information 100e may further define information related to bioinformation and the score to be added in association with each other. For example, information may be defined 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 sleep time is equal to or greater than a predetermined time.

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

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

The output unit 102 judges the disease state of the patient for the individual diseases that constitute the complex disease based on the patient's personal data, and when 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, outputs an improvement goal that the patient should achieve in order to improve the complex disease state. The improvement goal may include an improvement target value for the test value included in the patient's personal data. The patient's personal data may also include data on the patient's lifestyle, and the improvement goal may include an improvement goal for the patient's lifestyle. The lifestyle may include at least one of the patient's stress, the patient's sleep time, the patient's amount of exercise, the patient's diet, the patient's amount of smoking, and the patient's amount of alcohol consumption.

The output unit 102 may also 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.

The output unit 102 may also be configured to determine the disease state of the patient by referring to the individual disease definition information 100b, and to obtain an improvement goal when the combination of disease states of individual diseases or the combination of disease states of individual diseases and personal data is a composite disease state by referring to the composite disease/goal definition information 100c, and output the obtained improvement goal as an improvement goal to be achieved by the patient. For example, when the patient's personal data corresponds to any of the records of the "personal data pattern" defined in the individual disease definition information 100b corresponding to the individual disease A, the output unit 102 may determine that the patient corresponds to the individual disease A, and may also determine the disease state (severity) of the individual disease A that the patient suffers from by referring to the "severity" field of the corresponding record. The output unit 102 may also be configured to repeat the same process for each individual disease to determine which individual disease the patient corresponds to and the disease state (severity) of the corresponding individual disease. Next, the output unit 102 may refer to the composite disease/goal definition information 100c corresponding to the composite disease state A, and if the disease state of each individual disease of the patient and the patient's personal data correspond to any of the records of "individual disease state" and "personal data condition" defined in the composite disease/goal definition information 100c, determine that the patient is in the composite disease state A, and may acquire the improvement goal of the patient by referring to the "improvement goal" field of the corresponding record. The output unit 102 may also repeat the same process for each composite disease state to determine which of the composite disease states the patient corresponds to and acquire the improvement goal if the patient corresponds to the composite disease state.

The output unit 102 may also calculate the risk for each test item for each individual disease constituting a complex disease using reference values for one or more test items related to the individual disease and test data for the test items obtained by testing the patient, and determine that the patient has a complex disease state if the calculated risk for each test item satisfies a predetermined condition. The output unit may also output an improvement goal that the patient should achieve in order to improve the complex disease state if it is determined that the patient has a complex disease state.

In addition, 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 equal to or greater than a predetermined threshold. In this case, the output unit 102 may output the average value of the calculated risks for each test item as a value indicating the risk related to a composite disease state.

The output unit 102 may also be configured to output the patient's improvement goal obtained by inputting the patient's personal data to a trained model capable of outputting an improvement goal for improving a complex disease state as the improvement goal to be achieved by the patient.

FIG. 10 is a diagram showing an example of a trained model. The trained model shown in FIG. 10 shows a model trained to output, when personal data is input, a flag indicating whether or not the combination corresponds to a composite disease state, an identifier indicating the name of the corresponding composite disease state, the state of each individual disease constituting the composite disease state (e.g., a flag indicating the presence or absence of an individual disease, a value indicating the severity of each individual disease, etc.), an improvement target, and a disease risk. The trained model may operate to identify, from the input personal data, whether or not the combination of personal data corresponds to each individual disease constituting the composite disease, and to output an improvement target, etc., when the combination corresponds to each individual disease constituting the composite disease (when the patient has a composite disease state). The trained model may further be trained to output a risk value related to the composite disease state.

Such a trained model can be generated by generating a large amount of training data from a large amount of past clinical data, using personal data as input data, and having the model trained, with a flag indicating whether or not the patient corresponds to a composite disease state, an identifier indicating the name of the corresponding composite disease state, a flag indicating whether or not each individual disease constituting the composite disease state corresponds, a value indicating the severity of each individual disease, an improvement target value, and a disease risk as correct answer data. In addition, when a risk value for a composite disease state is output from the trained model, this can be achieved by including a risk value for the composite disease state in the correct answer data of the training data. The model may be any algorithm, and for example, a neural network, a decision tree, a random forest, a gradient boosting decision tree, etc. can be used. In addition, the trained model may be prepared as a different model for each composite disease state. Returning to FIG. 8, the explanation will be continued.

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 the first output unit. The output unit 102 that outputs data to the doctor terminal 30 may be called the second output unit.

The output unit 102 (first output unit) may also be configured to output the improvement goal or the improvement goal corrected 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 the first reception unit. The reception unit that receives various inputs from the doctor terminal 30 (or from the doctor) may be called the second reception unit. The reception unit 103 (first reception unit) receives from the patient a behavioral goal that the patient should work on in order to achieve the improvement goal. The reception unit 103 that receives the behavioral goal from the patient may be called the first reception unit. The reception unit 103 (first reception unit) may also receive from the patient a behavioral goal that the patient should work on from among multiple options regarding behavioral goals for achieving the patient's improvement goal. The reception unit 103 (first reception unit) may also determine multiple options to be presented to the patient by referring to the behavioral goal definition information 100f and extracting options corresponding to the patient's personal data, improvement goal, or the patient's complex disease state. The output unit 102 may output the behavioral goal that the patient is working on, which is received by the reception unit 103 (first reception unit), to a patient terminal 20 used by the patient and/or a doctor terminal 30 used by the doctor who examines the patient.

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

In addition, 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 a functional block configuration of the patient terminal 20. The patient terminal 20 includes a storage unit 200, a reception unit 201, and a display control unit 202. The storage unit 100 can be realized by using the storage unit 12 included in the medical support device 10. 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 unit 12. The program can be stored in a storage medium. The storage medium storing the program may be a computer-readable non-transient storage medium. The non-transient storage medium is not particularly limited, and may be, for example, a storage medium such as a USB memory or a CD-ROM.

The memory 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 provided in the patient terminal 20. For example, the reception unit 201 receives various inputs detected by a touch panel provided in the patient terminal 20.

The display control unit 202 displays the data etc. acquired from the medical support device 10 on the display of the patient terminal 20.

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

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

The memory 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 provided in the doctor's terminal 30. For example, the reception unit 301 receives various inputs detected by a keyboard or mouse provided in the doctor's terminal 30. The reception unit 301 also transmits the received various input data to the medical support device 10.

The display control unit 202 acquires various data from the medical support device 10 and displays the acquired data on the display of the doctor's terminal 30.

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

<Processing Procedure>
Next, a detailed description will be given of the processing procedure performed by the medical support system 1. In the following description, the composite disease state will be described as metabolic syndrome. Also, the medical support device 10 will be described as determining the composite disease state according to the determination method 1 described above.

Figure 13 is a sequence diagram showing an example of the processing procedure performed by the medical support system 1. The processing procedure shown in Figure 13 is assumed to be repeatedly executed each time a doctor examines a patient, but from the second examination onwards, some of the interviews (such as interviews whose content does not change from examination to examination) may be omitted.

The doctor terminal 30 accepts input of the patient's examination data from the doctor and transmits it to the medical support device 10 (S100, S101). The patient terminal 20 also accepts input of interview data from the patient and transmits it to the medical support device 10 (S102, S103). For example, when the doctor examines the patient, the doctor may prompt the patient to input the interview data from the patient terminal 20. The interview data may also be input to the doctor terminal 30 and transmitted to the medical support device 10. Next, 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 Fig. 15 includes data obtained by measuring the patient's body, such as height, weight, and waist circumference (physical measurement data), data on blood pressure, data on anemia, data on liver and gallbladder function, data on blood lipids, data on blood glucose levels, data on uric acid, data on kidney function, data obtained by performing a urine test, etc.

FIG. 16 is a diagram showing a specific example of medical interview data. The medical interview data shown in FIG. 16 includes a medical interview regarding smoking, a medical interview regarding diet, a medical interview regarding alcohol consumption, a medical interview regarding medications currently being taken, a medical interview regarding medical history, a medical interview regarding lifestyle history, and the like. The medical interview data may further include a medical interview necessary for calculating a score regarding the patient's lifestyle habits. The score regarding the lifestyle habits may be divided into a plurality of categories. The plurality of categories may be, for example, stress, sleep, exercise, diet, smoking, and drinking.

Then, 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 output the patient's disease state, improvement goal, and disease risk, and stores them in the patient information 100a (S105, S106, S107). More specifically, the patient's disease state may be a flag indicating whether or not the patient corresponds to a complex disease state (or the name of the complex disease state), or, if the patient is in a complex disease state, the state of each individual disease constituting 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.). In addition, the improvement goal output by the output unit 102 of the medical support device 10 may include an improvement goal value of the lifestyle habit score. In addition, the output unit 102 of the medical support device 10 may be configured to output a risk value related to the complex disease state when the patient corresponds to a complex disease state.

Figure 14 is a diagram showing a specific example of the individual disease definition information 100b. Figure 17A shows an example of 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. Figure 17B shows an example of individual disease definition information 100b-4 corresponding to obesity. Also, Figure 18 is a diagram showing a specific example of the complex disease/goal definition information 100c. First, the output unit 102 detects a record corresponding to the patient's examination data and interview data by comparing the "personal data pattern" of the individual disease definition information 100b corresponding to hypertension with the patient's examination data and interview data. For example, if the patient's examination data is systolic blood pressure = 190 mmHG and diastolic blood pressure = 120 mmHG, the output unit 102 detects that the patient's examination data and interview data correspond to the record in the second row. Next, the output unit 102 acquires the severity of hypertension by referring to the "severity" of the record in the second row. This allows the output unit 102 to determine that the patient has hypertension and that the severity is level 5. Next, the output unit 102 refers to the individual disease definition information 100b-2 corresponding to dyslipidemia, the individual disease definition information 100b-3 corresponding to diabetes, and the individual disease definition information 100b-4 corresponding to obesity to determine whether the patient has hypertension, dyslipidemia, diabetes, or obesity, and, if so, the severity. Here, it is assumed that the patient has been determined to have hypertension (level 5), dyslipidemia (level 3), diabetes (level 3), and obesity (level 3).

Next, the output unit 102 detects a record corresponding to the disease state and personal data of the patient's individual disease by comparing 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. As described above, since the disease states of the patient's individual diseases are hypertension (level 5), dyslipidemia (level 3), diabetes (level 3), and obesity (level 3), the output unit 102 detects that the record corresponding to the disease state and personal data of the patient's individual disease corresponds to the record in the third column. Next, the output unit 102 acquires the patient's disease risk and improvement goal by referring to the "disease risk" and "improvement goal" of the record in the third column.

Next, the output unit 102 outputs, as the disease state of the patient, a flag indicating that the patient corresponds to a complex disease state (metabolic syndrome), a flag indicating that the patient corresponds to hypertension, a flag indicating that the patient corresponds to dyslipidemia, a flag indicating that the patient corresponds to diabetes, a flag indicating that the patient 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. In addition, the output unit 102 outputs, as improvement goals, a waist circumference of 80 cm or less, a systolic blood pressure of 160 mmHg or less, a diastolic blood pressure of 100 mmHg or less, a lifestyle habit score related to stress that is improved by 20% or more, and a lifestyle habit score related to sleep that is improved by 20% or more. In addition, the output unit 102 outputs, as the disease risk, a high risk of cerebrovascular disease, a high risk of coronary artery disease, and the like. The disease risk may be expressed as a numerical value. In addition, when outputting the improvement goal, the output unit 102 may output a specific numerical value as the lifestyle habit score. For example, the output unit 102 may calculate the lifestyle habit score based on the interview data, and multiply the calculated lifestyle habit score (e.g., sleep = 50) by the target value indicated in the improvement goal (e.g., lifestyle habit score for sleep is improved by 20% or more) to output a specific target value (e.g., score 50 x 120% = score 60). In addition, the output unit 102 may output the number of individual diseases corresponding to the patient as a risk value for a complex disease state (metabolic syndrome) as the disease state of the patient. Here, the output unit 102 may output "4" as the risk for the complex disease state. Returning to FIG. 13, the explanation will be continued.

Next, the output unit 102 transmits the disease state and disease risk output in steps S105 and 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).

The output unit 102 also 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 a screen (S113). If the doctor wishes to modify the improvement goal, the doctor terminal 30 may accept the modification of the improvement goal (S114). This makes it possible for the doctor to present the improvement goal output from the medical support device 10 to the patient when examining the patient, and modify the improvement goal in consultation with the patient.

When the doctor's terminal 30 receives a correction to the improvement goal from the doctor, it transmits the corrected 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 corrected improvement goal (S116). Next, 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 goal received from the medical support device 10 on the screen (S118).

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

The output unit 102 of the medical support device 10 determines options for behavioral goals that the patient should work on 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 may compare the patient's personal data, the patient's improvement goal, and/or the patient's complex disease state with selection criteria defined in the behavioral goal definition information 100f, and determine options for behavioral goals that satisfy the selection criteria as the options for behavioral goals to be presented to the patient.

Figure 19 is a diagram showing an example of behavioral goal definition information 100f. "Category" indicates the category of the behavioral goal. "Behavioral goal" indicates the specific content of the behavioral goal. "Selection criteria" indicates the criteria for patients for which the behavioral goal is selected. For example, according to Figure 19, the behavioral goal "Start with vegetables" is extracted as an option when the fasting blood glucose of the test data is 110 mg/dl or more and the triglyceride level is 150 mg/dl. Although not shown in Figure 19, it is also possible to set selection criteria such as "patients whose complex disease state is metabolic syndrome." Let's return to Figure 14 and continue the explanation.

Then, 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 a screen and receives from the patient a selection of the behavioral goal to be undertaken (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).

Then, 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 the screen and accepts input of the questionnaire response from the patient (S206). The patient terminal 20 transmits the questionnaire response received from the patient to the medical support device 10. The patient terminal 20 also transmits bioinformation acquired from a wearable device worn by the patient (S207). The reception unit 103 of the medical support device 10 receives the questionnaire response and the bioinformation and stores them in the patient information 100a (S208). The calculation unit 104 of the medical support device 10 then calculates a score related to the achievement degree of the behavioral goal from the questionnaire response and/or the bioinformation (S209).

The output unit 102 may also select advice to be output to the patient by comparing the questionnaire answers, score and/or biological information with the output conditions by referring to the advice definition information 100g (S209). The output unit 102 may select short-term advice (e.g., daily review) by comparing the questionnaire answers, score and/or biological information of the previous day with the "output conditions" of the advice (daily) definition information 100g-1. The output unit 102 may also select medium-term advice (e.g., one-week review) by comparing the questionnaire answers, score and/or biological information of the past week with the "output conditions" of the advice (weekly summary) definition information 100g-2 for each predetermined day of the week (e.g., Friday, etc.). When selecting medium-term advice, the output unit 102 may also compare the progress or average score of the past week with the "output conditions". Furthermore, the output unit 102 may select long-term advice (e.g., a one-month review) by comparing the questionnaire responses, scores, and/or biometric information from the past month with the "output conditions" of the advice (monthly summary) definition information 100g-3 on a predetermined day of the month (e.g., the end of the month, etc.). When selecting long-term advice, the output unit 102 may compare the progress or average score over the past month with the "output conditions."

The output unit 102 then transmits the calculated score and the selected advice to the patient terminal 20 (S210). The patient terminal 20 displays the score and the advice on the screen (S211). The patient terminal 20 may further display a current or future image of the patient's appearance, a current or future image of an organ, trivia about medical information, an image showing the progress of the patient's personal data, an image showing the progress of the score, various quizzes, and the like (S212). Data required to display 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's terminal 30 requests the medical support device 10 to refer to the patient's behavioral goals, questionnaire responses, score regarding the degree of achievement of the behavioral goals, and advice (S220). The output unit 102 of the medical support device 10 transmits the behavioral goals selected by the patient, the questionnaire responses, score regarding the degree of achievement of the behavioral goals, and advice to the doctor's terminal 30 (S221). The doctor's terminal 30 displays the received behavioral goals, questionnaire responses, score, and advice on the screen (S222). This allows the doctor to check the patient's daily behavior 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 current disease state of the patient himself/herself. When button B10 is pressed, a transition is made to screen A100 that displays the disease name of the composite disease state. When button B11 is pressed, a transition is made to screen A100 that displays the disease name of each disease and the state (severity) of each disease. When button B12 is pressed, a transition is made to screen A100 that displays the name of a disease that may be contracted and the disease risk. Screens A100 to A120 correspond to, for example, the screens displayed in the processing procedure of step S111 in FIG. 13.

Screens A200 and A210 in FIG. 21 show examples of screens that display improvement targets. Screen A200 is a display example in which all improvement targets are displayed, and screen A210 is a display example in which only a limited number of items are displayed to make it easier for the patient to understand. Screens A200 and A210 correspond to the screens displayed in the processing procedure of step S118 in FIG. 13, for example.

Screens A300 and A310 in FIG. 22 show examples of screens that accept the setting of behavioral goals. In screen A300, up to three behavioral goals can be set, and when buttons B30 to B32 are pressed, the screen transitions to screen A310, which displays options for behavioral goals. Screen A310 includes an area B33 that displays a button for selecting a category of behavioral goals, and an area B34 that displays a list of options for behavioral goals corresponding to the selected category. When button B30 is pressed, the screen transitions to screen A310, and the behavioral goal selected in area B34 of screen A310 is reflected in button B30 of screen A300. Similarly, when button B31 is pressed, the screen transitions to screen A310, and the behavioral goal selected in area B34 of screen A310 is reflected in button B31 of screen A300. Screens A300 and 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 a response to a questionnaire. Screen A400 corresponds to, for example, a screen displayed in the processing procedure of step S206 in FIG. 13. Screen A401 in FIG. 23 shows an example of a screen for displaying a score related to the achievement level of a behavioral goal. In area P40, the score related to the achievement level of a behavioral goal is displayed for each category. As shown in area P41 of screen A410, the output unit 102 of the medical support device 10 may display advice for the score on the screen of the patient terminal 20. The advice to be displayed may be advice related to the category with the lowest score. In addition to daily advice, advice as a summary of the week may be displayed on a predetermined day of the week (e.g., Friday, etc.), and advice as a summary of the month may be displayed on a predetermined day of the month (e.g., the end of the month, etc.). Screen A401 corresponds to, for example, a screen displayed in the processing procedure of step S211 in FIG. 13.

Figure 24 is an example of a screen that graphically displays the patient's risk of disease. In this embodiment, the medical support device 10 may calculate the risk of future disease in each of the patient's organs based on the patient's personal data, and display the calculation results on the patient terminal 20. Screen A450 displays an area P45 that displays test data, and an overall body view P46. Organs that may develop disease in the future are highlighted in the overall body view P46. In the example of screen A450, it is shown that there is a possibility of disease developing in both eyes in the future. Screen A460 shows an enlarged view of a portion of the overall body view.

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

Figure 26 shows an example of a screen showing the progress of a patient's personal data. Screen A480 shows the progress of blood pressure, and screen A481 shows the progress of dietary scores. Screen A482 shows a one-week summary generated based on the answers entered by the patient to a questionnaire about diet.

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

(Doctor's terminal)
28 to 30 are diagrams showing examples of screen displays of the doctor's terminal 30. Screen A500 in FIG. 28 is an example of a screen displaying a list of information related to a patient. Area P50 displays the patient's test data. Area P51 displays improvement targets (improvement targets for test values and improvement targets for lifestyle-related scores). Area P52 displays daily changes in scores related to the achievement of behavioral targets. Area P53 displays a monthly summary of questionnaire responses and a monthly summary of data acquired from the patient's wearable device. Area P54 displays the patient's medical history.

Screen A600 in FIG. 29 is an example of a screen that displays detailed medical history and test data. Area P60 displays the patient's medical history. Area P61 displays a list of the patient's test data.

Screen A700 in FIG. 30 is an example of a screen that displays improvement goals in detail. In area P70, the patient's improvement goals are displayed, divided into improvement goal values for test values and improvement goal values for lifestyle-related scores. The doctor can also modify the improvement goals displayed in area P70. Area P71 is a screen for recording the instructions given to the patient. The doctor can record the information he or she has communicated to the patient during the examination in area P71.

<Experimental Results>
The left graph in Fig. 31 shows the change in risk value for a composite disease state, calculated according to the above-mentioned judgment method 2 from the patient's test data at the start and after 12 weeks for a patient with a composite disease state who has attempted to improve his/her lifestyle using the medical support system 1 according to this embodiment. The right graph in Fig. 31 shows the change in risk value for a composite disease state, calculated according to the above-mentioned judgment method 2 from the patient's test data at the start and after 12 weeks for a patient with a composite disease state who has attempted to improve his/her lifestyle without using the medical support system 1 according to this embodiment. The experimental results show that the risk value has improved more in patients with a composite disease state who have attempted to improve their lifestyle using the medical support system 1 according to this embodiment.

<Summary>
According to the embodiment described above, the disease state of the patient is judged for the individual diseases constituting the complex disease based on the patient's personal data, and a risk assessment of related diseases is performed. When the combination of the disease states of the individual diseases is a complex disease state, the improvement goal to be achieved by the patient is output in the form of a long-term goal or a short-term goal in order to improve the complex disease state. In addition, the input questionnaire and biological information are used to score daily life, and short-term (daily) evaluation and advice can be made. As a result, even in a state in which multiple diseases are combined, it is possible to provide a technology that can support appropriate therapeutic intervention for patients by proposing target values and goal settings that must be strengthened compared to when there is a single disease. In addition, in the past, in actual clinical practice, even if a patient has multiple diseases at the same time or is likely to have multiple diseases at the same time, it was normal to treat each individual disease, and composite treatment was not performed for the complex disease. However, in this embodiment, the medical support device 10 presents appropriate improvement goals according to the complex disease state based on the patient's personal data, and efficient treatment is possible by obtaining information on continuous daily life.

In addition, this embodiment outputs improvement targets that are based on the assumption that the condition is a composite disease state. This makes it possible to output improvement targets that can efficiently treat a composite disease state, taking into account the weight (severity) of each individual disease that constitutes the composite disease state, rather than simply combining improvement targets for each individual disease.

In addition, by setting behavioral goals to achieve improvement targets and displaying a daily score based on the responses to a questionnaire regarding the set behavioral goals, patients can reflect on their own behavior on a daily basis and maintain their motivation to achieve their goals.

In addition, the patient's personal data, improvement goals, behavioral goals, questionnaire responses, etc. will be shared with the doctor treating the patient, allowing the doctor to understand the progress of the patient's efforts toward their improvement goals and use this information in the next consultation.

The above-described embodiments are intended to facilitate understanding of the present invention, and are not intended to limit the present invention. The flow charts, sequences, elements included in the embodiments, and their arrangements, materials, conditions, shapes, sizes, etc., described in the embodiments are not limited to those exemplified, and may be modified as appropriate. In addition, configurations shown in different embodiments may be partially substituted or combined.

In the above-described embodiment, 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 may be referred to as the second terminal, the second output unit, and the second reception unit, respectively. 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 may be referred to as the first terminal, the first output unit, and the first reception unit, respectively. In the above-described embodiment, the output unit 102 outputs the magnitude of the risk, score, and severity level using numerical values, but this is not limited to this. For example, instead of the magnitude of the numerical values, the output may be output using colors (for example, red (high severity) to blue (low severity)) or symbols (for example, "A" (maximum score) to "Z" (minimum score)). In this case, the display control unit 202 of the patient terminal 20 may display a yellow icon instead of the display of "Risk is "4"" on the screen A100 of FIG. 20. Additionally, the display control unit 202 of the patient terminal 20 may display alphabets instead of scores on screen A410 in FIG. 23.

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... action 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 examination data and interview data of a user;
an output unit that determines the disease state of the user for each of the individual diseases constituting a composite disease based on the personal data, and outputs an improvement goal that the user should achieve in order to improve the composite disease state when a combination of the disease states of the individual diseases or a combination of the disease states of the individual diseases and personal data is a composite disease state;
A medical support device comprising: The improvement target includes an improvement target value for a test value included in the personal data.
The medical support device according to claim 1 . The output unit sets an improvement target for the test value included in the personal data based on a combination of disease states of the individual diseases or a combination of the disease states of the individual diseases and personal data.
The medical support device according to claim 2. The personal data includes data on the user's lifestyle habits,
The improvement goal includes an improvement goal 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 sleep time, the user's amount of exercise, the user's diet, the user's amount of smoking, and the user's amount of alcohol consumption.
The medical support device according to claim 4. The output unit outputs the improvement goal obtained by inputting the personal data to a trained model having the ability to output an improvement goal for improving the composite disease state as the improvement goal to be achieved by the user.
The medical support device according to any one of claims 1 to 5. a storage unit that stores individual disease definition information that defines a correspondence relationship between the personal data and the disease states of the individual diseases, and goal definition information that defines an improvement goal when a combination of the disease states of the individual diseases or a combination of the disease states of the individual diseases and personal data is a complex disease state,
The output unit determines the disease state of the user by referring to the individual disease definition information, and acquires the improvement goal when a combination of disease states of the individual diseases or a combination of the disease states of the individual diseases and personal data is a composite disease state by referring to the goal definition information, and outputs the acquired 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 will work on from among a plurality of options related to behavioral goals for achieving the improvement goal;
The output unit outputs the behavioral goal to be undertaken by the user, which has been accepted by the first acceptance 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 composite disease state of the user.
The medical support device according to claim 8. The first reception unit receives an input of a response to a questionnaire regarding a behavioral goal to be undertaken by the user;
a calculation unit that calculates a score related to an achievement level 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 goal includes at least one of a behavioral goal related to improving the user's stress, a behavioral goal related to improving the user's sleep time, a behavioral goal related to improving the user's amount of exercise, a behavioral goal related to improving the user's diet, a behavioral goal related to reducing the user's amount of smoking, and a behavioral goal related to reducing the user's amount of alcohol consumption.
The medical support device according to any one of claims 8 to 10. The output unit is
Calculating a risk for each test item for each individual disease constituting the composite disease using reference values for one or more test items related to the individual disease and test data for the test items obtained by testing the user;
If the calculated risk for each test item satisfies a predetermined condition, the user is determined to be in the composite disease state, and an improvement goal to be achieved by the user in order to improve the composite disease state is output.
The medical support device according to any one of claims 1 to 11. When the calculated risk for each test item satisfies a predetermined condition, an average value of the calculated risks for each test item is equal to or greater than a predetermined threshold value,
The output unit outputs an average value of the calculated risks for each test item as a value indicating the risk related to the composite disease state.
The medical support device according to claim 12. A medical support method executed by a medical support device, comprising:
acquiring personal data including at least one of examination data and interview data of a user;
determining the disease state of the user for each of the individual diseases constituting a composite disease based on the personal data, and outputting an improvement goal to be achieved by the user in order to improve the composite disease state when a combination of the disease states of the individual diseases or a combination of the disease states of the individual diseases and personal data is a composite disease state;
A medical support method, comprising: On the computer,
acquiring personal data including at least one of examination data and interview data of a user;
determining the disease state of the user for each of the individual diseases constituting a composite disease based on the personal data, and outputting an improvement goal to be achieved by the user in order to improve the composite disease state when a combination of the disease states of the individual diseases or a combination of the disease states of the individual diseases and personal data is a composite disease state;
A medical support program to implement the above.

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