Medical support systems, medical support devices, and programs

Abstract

To provide a technology regarding a system that pertains to assisting in medical care, with which it is possible to reduce the burden of diagnosing the seriousness of the disease of a patient that is to be diagnosed by medical personnel.SOLUTION: Provided is a medical examination assistance system comprising: symptom emergence exercise information acquisition means that acquires symptom emergence exercise information that includes the content of an exercise in which a symptom pertaining to the disease of a patient to be diagnosed has emerged; minimum exercise strength calculation means that determines minimum exercise strength, on the basis of the symptom emergence exercise information, that represents the smallest exercise strength of an exercise among exercises in which a symptom pertaining to the disease has emerged; estimated seriousness information calculation means that determines estimated seriousness information, on the basis of the minimum exercise strength, that indicates the seriousness of the disease of the patient; medical examination assistance information set generation means that generates a medical examination assistance information set including the minimum exercise strength and / or estimated seriousness information of the patient in a prescribed period; and output means that outputs a medical examination assistance image.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention belongs to the technical field related to healthcare, and relates to a medical support system, a medical support device, and a program.

Background Art

[0002] In recent years, a system has been proposed that continuously acquires and records a patient's biological information and shows the change over time of these biological information to support a doctor's medical treatment (for example, Patent Document 1).

[0003] Patent Document 1 discloses a medical information processing system that stores a patient's vital data in association with time, displays the vital data in a time series, and calculates and displays statistical information related to the time series-displayed vital data. According to this, an operator such as a doctor can easily grasp the trend of a patient's vital data, and it becomes easy to grasp the patient's condition and determine the type and dosage of medicine to be prescribed to the patient.

[0004] With such a system, the burden on doctors for the medical treatment of patients with chronic diseases in particular can be reduced, and if an appropriate treatment policy can be quickly determined by this, the effect will also extend to the patients.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] Incidentally, in the diagnosis and treatment of heart failure, one of the major chronic diseases, it is common practice to evaluate the severity (progression) of the disease based on subjective symptoms that arise from various daily physical activities, using classifications such as the NYHA classification (New York Heart Association functional classification). Based on the evaluated severity, physicians then decide on the type and dosage of medications to prescribe, as well as other treatment strategies.

[0007] Traditionally, determining which of the above classifications a patient belonged to was determined by the doctor's questioning during the examination, asking the patient about the types of physical activities that caused (or did not cause) significant (distressing) symptoms. This method has the problem that it is difficult to accurately elicit information from the patient and make an accurate classification (evaluation) within the limited consultation time. Furthermore, from the patient's perspective, being forced to answer the same questions at every outpatient visit is stressful and places a significant burden on the patient.

[0008] Conventional medical support systems, such as those described in Patent Document 1, can display information on changes in vital data such as the patient's pulse rate and blood pressure, but they have the problem of not being able to support the classification of severity based on physical activity and subjective symptoms as described above.

[0009] In view of the above-mentioned problems, the present invention aims to provide a system related to medical support that can reduce the burden on medical professionals in diagnosing the severity of diseases that patients are being treated for. [Means for solving the problem]

[0010] To solve the above problems, the present invention adopts the following configuration. That is, A means for acquiring symptom-causing exercise information, which is information including the content of exercises in which symptoms related to the disease being treated by the patient appear, A minimum exercise intensity calculation means that, based on the exercise information in which the symptoms related to the disease appeared, determines the minimum exercise intensity, which is the exercise with the lowest exercise intensity among the exercises in which the symptoms related to the disease appeared. An estimated severity information calculation means that obtains estimated severity information indicating the severity of the patient's disease based on the minimum exercise intensity, A medical support information set generation means for generating a medical support information set that includes the minimum exercise intensity and / or estimated severity information of the patient during a predetermined period of time, Output means for outputting the aforementioned medical support image, It is a medical support system that has [the following features].

[0011] Here, the "specified period" can be any period that allows for a reasonable amount of time to reflect on daily life and / or a period during which it is easy to grasp the progression of symptoms and changes in severity, but for example, it can be one week (7 days). Also, "exercise intensity" can be indicated using an index such as METs. METs is an index of activity intensity that shows how many times more energy various activities consume than resting (sitting quietly) (1 MET). Also, "severity of the disease" and teeth , this This includes the severity classification defined in the treatment guidelines for the disease, as well as the degree of decline in physical function.

[0012] Furthermore, the term "medical support information set" as used here can be, for example, image data, but is not limited to this; it may also be text data, audio data, etc. Also, the "output means" can be a means of visual output (for example, a display device such as an LCD, a printing device such as a printer, etc.) or an auditory output (for example, a speaker, etc.), depending on the format of the medical support information set.

[0013] With this configuration, physicians can refer to the outputted clinical support information set to access information related to the estimated severity of the patient's illness. For example, by acquiring (inputting) the necessary information before the patient's examination and referring to the clinical support information set generated based on this information in advance, the questions asked during the examination to diagnose the severity can be narrowed down, enabling a more efficient and appropriate severity diagnosis. Furthermore, since redundant questions and answers used to narrow down the severity can be reduced, it can also contribute to reducing the burden on the patient. For this reason, it is particularly suitable for physicians who monitor a large number of patients, such as those who are responsible for many patients.

[0014] Furthermore, the medical support system may also have a storage means for storing an exercise intensity table that associates the content of the exercise with the exercise intensity of the exercise, and the minimum exercise intensity calculation means may calculate the minimum exercise intensity by referring to the exercise intensity table. With such a configuration, the minimum exercise intensity calculation means can efficiently calculate the minimum exercise intensity while suppressing the load on the system.

[0015] The means for acquiring symptom-related motor information may include, for example, input means (e.g., keyboard, mouse, touch panel) of an information processing terminal used by a medical professional such as a doctor. That is, a medical professional may input the symptom-related motor information by interviewing the patient at a medical institution, the patient's home, etc. Furthermore, the means for acquiring symptom-related motor information may include means for requesting the patient themselves (or their caregiver) to input the symptom-related motor information.

[0016] That is, the medical support system further includes an automated medical interview terminal that performs an automated medical interview process that requests the patient to input patient information, including information on the movement of symptoms that occurred within the most recent predetermined period, and the symptom movement information acquisition means is ,beforeThe system may also acquire the symptom appearance and movement information entered by the patient through an automated medical interview process performed on the automated medical interview terminal.

[0017] Here, the "automated medical interview terminal" may be a terminal installed in a medical institution, or it may be an information processing terminal (for example, a smartphone) owned by the patient. Furthermore, the symptom appearance exercise information acquisition means may accept input of the patient information through a user interface provided by an application executed on the automated medical interview terminal. The application may also include daily health management functions. This would allow for the management of the patient's health as well.

[0018] Furthermore, the automated medical interview terminal may modify the content of the questions asked to the patient during the automated medical interview process according to the patient's symptoms and / or the patient's past responses. Here, "modifying the content of the questions" includes changing the order of multiple questions.

[0019] For patients, being forced to undergo similar interviews frequently throughout the long course of treatment is stressful. Therefore, for example, for patients with mild symptoms that persist, it is possible to reduce this stress and lessen the burden on patients of inputting information by narrowing down (simplifying) the questions used to obtain the aforementioned symptom-related motor information, or by changing the order of the questions.

[0020] Furthermore, the disease being treated is heart failure, and the estimated severity information may be an estimate of the NYHA classification. In such cases, the present invention is suitable.

[0021] Further, the medical support information set is an image, and the medical support information set generation means generates a medical support image as the medical support information set, and generates the medical support image including a list in which the content of the exercise, the exercise intensity of the exercise, and the estimated NYHA classification when the exercise intensity is the minimum exercise intensity are associated with each other. If a medical support image including such a list can be referred to at the time of diagnosis, a doctor can more efficiently conduct an interview for diagnosing the severity of a patient. Here, the "image" referred to herein means something that visually and easily grasps and aggregates information, and includes not only a still image and a moving image but also something composed only of text data such as a character string.

[0022] Further, the present invention can also be regarded as a medical support device having the symptom appearance exercise information acquisition means, the minimum exercise intensity calculation means, the estimated severity information calculation means, and the medical support information set generation means, and constituting at least a part of the medical support system.

[0023] Further, the present invention can also be regarded as a program for causing a computer to function as such a medical support device and a computer-readable recording medium on which such a program is non-temporarily recorded.

[0024] Note that each of the above configurations and processes can be combined with each other to constitute the present invention as long as no technical contradiction occurs.

Effects of the Invention

[0025] According to the present invention, regarding a system related to medical support, it is possible to provide a technology capable of reducing the burden on medical staff for diagnosing the severity of a disease to be treated in a patient.

Brief Description of the Drawings

[0026] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of a medical support system according to an embodiment. [Figure 2]Figure 2 is a block diagram showing the functional configuration of a server device according to an embodiment. [Figure 3] Figure 3 shows an example of a data table related to the embodiment. [Figure 4] Figure 4 is a block diagram showing the functional configuration of the physician's terminal according to the embodiment. [Figure 5] Figure 5 is the first diagram illustrating an example of a medical support image output on the physician's terminal. [Figure 6] Figure 6A is the second figure illustrating an example of a medical support image output on the physician's terminal. Figure 6B is the third figure illustrating an example of a medical support image output on the physician's terminal. [Figure 7] Figure 7A is the fourth figure illustrating an example of a medical support image output on the physician's terminal. Figure 7B is the fifth figure illustrating an example of a medical support image output on the physician's terminal. [Figure 8] Figure 8A is the sixth figure illustrating an example of a medical support image output on the physician's terminal. Figure 8B is the seventh figure illustrating an example of a medical support image output on the physician's terminal. [Figure 9] Figure 9 is the eighth figure illustrating an example of a medical support image output on the physician's terminal. [Figure 10] Figure 10 is a block diagram showing the functional configuration of the patient-side terminal according to the embodiment. [Figure 11] Figure 11A is the first diagram illustrating an example of a user interface displayed on the patient's terminal. Figure 11B is the second diagram illustrating an example of a user interface displayed on the patient's terminal. [Figure 12] Figure 12 is a diagram showing the flow of information exchange and processing within the medical support system according to the embodiment. [Figure 13] Figure 13 is a schematic diagram of another type of medical support system. [Modes for carrying out the invention]

[0027] <Example 1> Specific embodiments of the present invention will be described below with reference to the drawings. However, unless otherwise specified, the dimensions, shapes, and relative arrangements of the components described in these embodiments are not intended to limit the scope of the present invention to those specific components.

[0028] (System Configuration) Figure 1 is a schematic diagram showing the configuration of the medical support system 1 according to this embodiment. As shown in Figure 1, the medical support system 1 consists of a server device 100, a physician-side terminal 200 used by a physician, a patient-side terminal 300 used by a patient P, and measuring instruments 400, and each of these components can communicate with each other via a communication network N.

[0029] The medical support system 1 according to this embodiment is a medical system that transmits measured biological information such as heart rate, pulse rate, blood pressure, and weight, measured by the patient at home or elsewhere, to a server device 100 via a network N, processes the information, and provides it to medical professionals, thereby supporting doctors in treating patients.

[0030] Patients who have received a confirmed diagnosis of heart failure or other conditions requiring continuous monitoring of their vital signs will begin treatment according to their doctor's diagnosis, continuously measure their vital signs themselves at home, and record their subjective symptoms in their daily lives. The medical support system 1 collects the measured values ​​and information related to subjective symptoms, and based on this, generates medical support images for medical professionals such as doctors to refer to in relation to the patient's treatment, and outputs them via the output means. These medical support images are referred to during the patient's examination and as needed in the course of treatment. In this embodiment, the medical support images correspond to the medical support information set in the present invention.

[0031] Furthermore, if the collected patient measurements meet pre-set alert conditions, the medical support system 1 may display alert information on the medical support image. It may also send alert signals to the physician's information processing terminal, mobile communication terminal, etc. The following describes each component of the system in detail.

[0032] (Server device) Figure 2 is a block diagram showing the functional configuration of the server device 100. The server device 100 is composed of a general server computer and includes a control unit 110, communication means 120, and storage means 130, as shown in Figure 2.

[0033] The control unit 110 is a means for controlling the server device 100 and is composed of a processor such as a CPU (Central Processing Unit) and a DSP (Digital Signal Processor). The control unit 110 also includes the following functional modules related to biological information management: a measurement information acquisition unit 111, a daily measurement value calculation unit 112, a symptom appearance exercise information acquisition unit 113, a minimum exercise intensity calculation unit 114, an estimated severity calculation unit 115, a subjective symptom information acquisition unit 116, a medication-related information acquisition unit 117, and a medical support image generation unit 118. Each of these functional modules will be described in detail later.

[0034] The communication means 120 is a communication means for connecting the server device 100 to the communication network N, and is composed of, for example, a communication interface board and a wireless communication circuit for wireless communication.

[0035] The storage means 130, although not shown in the figures, includes a main memory unit such as a ROM (Read-only memory) or RAM (Random Access Memory), and an auxiliary storage unit such as an EPROM, HDD (Hard Disk Drive) or SSD (Solid State Device), or removable media. The auxiliary storage unit stores the operating system (OS), various programs, etc. The stored programs are loaded into the working area of ​​the main memory unit and executed, and through the execution of the programs, each component is controlled, thereby enabling the realization of each functional unit that fulfills a predetermined purpose.

[0036] The measurement information acquisition unit 111 acquires the measured values ​​of biological information such as heart rate, pulse rate, blood pressure, and weight measured by the patient P with the measuring device 400, as described later, via the communication network N and stores them in the storage means 130. These measured values ​​can be acquired with various known measuring devices. In addition, separate devices corresponding to each type of biological information may be used, or measuring devices that can acquire different measured values ​​with a single device (one measurement) can be used, for example, by using an upper arm oscillometric blood pressure monitor to acquire blood pressure and pulse rate.

[0037] Furthermore, if a specific symptom or suspected symptom, such as atrial fibrillation (AF), is detected during heart rate measurement, the measurement information acquisition unit 111 acquires this information along with the heart rate and stores it in the storage means 130. Also, if a specific symptom or suspected symptom, such as arrhythmia, is measured during pulse rate measurement, the measurement information acquisition unit 111 acquires this information and stores it in the storage means 130. The measurement information acquired by the measurement information acquisition unit 111 includes information about the time the measurement was taken and information about the location where the measurement was taken (for example, whether it was at home or in a doctor's office).

[0038] The daily measurement value calculation unit 112 calculates one heart rate measurement and one pulse rate measurement for patient P on one occasion each day, based on the measurement values ​​stored in the storage means 130 and predetermined calculation rules, and stores them in the storage means 130. One occasion refers to, for example, "morning (within one hour after waking up)" and "evening (before going to bed)" as in the guidelines for the diagnosis and treatment of hypertension. This refers to the timing of measurement of biological information. In this embodiment, a certain time interval is set for such measurement timing, for example, "1 opportunity = 10 minutes (from the start of the first measurement of biological information)," and a series of multiple pieces of biological information (including different types) measured within that time are collectively referred to as "biological information obtained in 1 opportunity." That is, with regard to the measurement of biological information, if multiple measurements are taken within the above-mentioned fixed time, these multiple measurements are collectively referred to as one measurement opportunity, and the multiple measured biological information becomes the biological information obtained in one opportunity. Here, whether the same biological information is measured multiple times, different biological information is measured once each, or different biological information is measured one or more times each, as long as all of these measurements are taken within the fixed time, those multiple measurements are referred to as measurements in 1 opportunity.

[0039] On the other hand, even if two measurements are taken for the same biological information, if those two measurements are not taken within a certain time period (for example, once upon waking in the morning and once before going to bed at night), then the two pieces of biological information will be considered to be taken on separate occasions (related to two separate measurements).

[0040] Here, the calculation of daily measured values ​​by the daily measured value calculation unit 112 will be specifically explained using heart rate as an example. First, if the heart rate is measured only once a day and only that measured value is stored in the storage means 130, the daily measured value calculation unit 112 will use that measured value as the daily heart rate measured value. On the other hand, if multiple measurements are taken in a day and all of those measurements fall within a predetermined time, the daily measured value calculation unit 112 will consider all of those multiple measured values ​​as measurements taken within a single opportunity, and will determine a single value (for example, the average value of the multiple measured values) based on those multiple measured values ​​as the measured value for that single opportunity, and calculate this as the daily heart rate measured value. Furthermore, if multiple measurements are taken in a day and those multiple measurements do not fall within a predetermined time (i.e., measurements for multiple opportunities are taken), the daily measured value calculation unit 112 will use the measured value from one of the multiple opportunities (for example, the measured value from a measurement opportunity at a predetermined timing, such as the measured value when waking up in the morning) to calculate the daily heart rate measured value. In this case, if multiple measurements are taken within a single instance, the method for determining the measurement value for that single instance is as described above. Although heart rate was used as an example here, the daily measurement value calculation unit 112 performs similar calculation processing for other biological information such as pulse rate.

[0041] The symptom-generating exercise information acquisition unit 113 acquires symptom-generating exercise information, which includes information about the type of exercise in which symptoms related to the disease being treated by patient P (heart failure in this case) appeared, and stores it in the storage means 130. Specifically, an application executed on the patient-side terminal 300, described later, allows patient P to input or select the type of exercise (physical activity) in which they experienced symptoms at predetermined intervals (e.g., one week), thereby acquiring the symptom-generating exercise information via the patient-side terminal 300.

[0042] The minimum exercise intensity calculation unit 114 calculates the minimum exercise intensity, which is the exercise intensity of the exercise with the lowest intensity among the exercises in which symptoms related to heart failure appeared within a predetermined period, based on the symptom appearance exercise information stored in the storage means 130. In this embodiment, exercise intensity is expressed in METs, and below, the exercise intensity of the exercise with the lowest intensity among the exercises in which symptoms related to heart failure appeared within a predetermined period is defined as the minimum METs for symptom appearance. Specifically, the minimum exercise intensity calculation unit 114 may store an exercise intensity table in the storage means 130 that associates the content of the exercise with the exercise intensity of that exercise, and determine the minimum METs for symptom appearance by referring to this exercise intensity table. The minimum METs for symptom appearance calculated here is stored in the storage means 130.

[0043] The estimated severity calculation unit 115 calculates based on the minimum METs for symptom appearance stored in the memory means 130. Next, estimated severity information indicating the severity of heart failure is obtained. In this embodiment, the severity is based on the NYHA classification, and hereafter, the estimated severity is also referred to as the estimated NYHA classification. The estimated severity calculation unit 115 may, for example, obtain the estimated severity by referring to a data table stored in the storage means 130 that associates the minimum METs for symptom appearance with the estimated NYHA classification. Figure 3 shows an example of a data table that associates the content of exercise, the METs (numerical value) of the exercise, and the estimated NYHA classification when the METs of the exercise are the minimum METs for symptom appearance. The content of exercise shown in Figure 3 (and the corresponding METs and estimated NYHA classification) is a selection of representative examples, and in reality, many more types of exercise are defined. The estimated severity calculated here is stored in the storage means 130.

[0044] The subjective symptom information acquisition unit 116 acquires information about the presence (and type) of heart failure symptoms in patient P at predetermined intervals (for example, daily) and stores it in the storage means 130. Specifically, similar to the symptom appearance exercise information, an application executed on the patient terminal 300 can be used to have patient P select the symptoms they experienced on that day at a fixed time each day, thereby acquiring the information via the patient terminal 300. Specifically, for example, a list of symptoms may be presented and the patient may select a symptom from the list, or text information related to subjective symptoms may be accepted as a memo or similar.

[0045] Furthermore, the medication-related information acquisition unit 117 acquires information regarding whether the patient is taking their medication and their medication adherence rate (frequency of medication), and stores it in the storage means 130. It may also acquire information regarding the nature and frequency of side effects during medication. This information can be acquired, for example, via the patient-side terminal 300 by having the patient P select whether or not they are taking their medication at a fixed time each day through an application executed on the patient-side terminal 300, similar to the information regarding the appearance of symptoms. In addition, although not shown, the medication-related information acquisition unit 117 may be configured to cooperate with an external system (e.g., an electronic medical record system) to acquire information about the medications prescribed to patient P (prescription information).

[0046] The medical support image generation unit 118 generates medical support images for medical professionals to refer to, based on data output from the measurement information acquisition unit 111, the daily measurement value calculation unit 112, the symptom appearance exercise information acquisition unit 113, the minimum exercise intensity calculation unit 114, the estimated severity calculation unit 115, the subjective symptom information acquisition unit 116, and the medication-related information acquisition unit 117, and stored in the storage means 130. The generated medical support images are transmitted to the physician's terminal 200 via the communication network N. Details of the medical support images will be described later.

[0047] (Doctor's terminal) Figure 4 is a block diagram showing the functional configuration of the physician's terminal 200. The physician's terminal 200 is a general-purpose computer, such as a fixed-location personal computer, a portable notebook personal computer, or a tablet terminal, and is equipped with a control unit 210, input means 220, output means 230, storage means 240, and communication means 250.

[0048] The control unit 210 is a means for controlling the physician's terminal 200 and is composed of, for example, a CPU. The input means 220 is a means for receiving information input from external sources, such as a keyboard, mouse, touch panel, camera, and microphone. The output means 230 is composed of, for example, a liquid crystal display, speaker, and printer. The storage means 240 is composed of, similar to a server device, a main memory unit, an auxiliary memory unit, etc., and stores the operating system (OS), various programs, and various data acquired via the communication network N. The communication means 250 is composed of, for example, a communication interface board and a wireless communication circuit for wireless communication.

[0049] Although not shown in the diagram, the doctor's terminal is capable of accessing the electronic medical record management system. Alternatively, the system may read the patient's electronic medical record data stored in the electronic medical record management system and send this electronic medical record data to the server device 100, or it may link the information sent from the server device 100 with the electronic medical record data. In such cases, it also becomes possible for physicians to view medical support images via the electronic medical record management system.

[0050] On the physician's terminal 200, medical support images are acquired from the server device 100 via the communication network N, and this information is output to the output means 230. Figures 5 to 9 show examples of screens (medical support images) displayed on the output means 230 of the physician's terminal 200. Figure 5 is an explanatory diagram showing an example of a medical support image for one of the patients P under the care of the physician who is the administrator of the terminal. As shown in Figure 5, the medical support image in this embodiment is composed of multiple areas that each show different information. Specifically, it includes an overview information area OV, a weight information area W, an estimated NYHA classification change area NT, a subjective symptom information area S, a medication information area ME, a blood pressure information area BP, and a heart rate / pulse information area HP. Note that the entire medical support image does not need to be displayed on the output means, and the display area can be selected as appropriate (screen scrolling, zooming in / out, etc.). In addition, the medical support image may be generated in a combination and order of items specified in advance by the physician.

[0051] The following section provides a detailed explanation of the information displayed in each area of ​​the clinical support image. Figure 6A is an enlarged view of the overview information area OV. As shown in Figure 6A, the overview information area OV displays information about patient attributes such as patient name, gender, and age, as well as recently acquired patient information and patient information from the previous consultation. One of the patient information items is the minimum METs information MM, which indicates the minimum METs (and estimated NYHA classification) at which symptoms appear. This display allows physicians to check the most recent minimum METs (and estimated NYHA classification) for patient P, as well as refer to the previous minimum METs (and estimated NYHA classification), enabling them to efficiently conduct interviews to diagnose the severity of patient P's condition during consultations.

[0052] Figure 6B is an enlarged view of the weight information area W. As shown in Figure 6B, the weight information area W displays the changes in patient P's weight over a specified period (for example, from the 1st to the last day of the previous month, the past month, the past week, etc.) in a graph. When cardiac function deteriorates, blood flow worsens, making it easier for fluid to accumulate in the body. Therefore, weight gain (for example, the weekly increase) (derived from this fluid accumulation) becomes an important indicator of the severity of heart failure. For this reason, the weight information area W may display alert information if the weight change over a specified period exceeds a threshold.

[0053] Figure 7A is an enlarged view of the estimated NYHA classification transition region NT. As shown in Figure 7A, the estimated NYHA classification transition region NT displays an estimated severity time-series graph showing estimated severity indicator bars SB, which allow for the identification of class differences by color, representing the estimated NYHA classification for each predetermined period within the displayed period. In addition, the corresponding minimum METs (and estimated NYHA classification) for symptom onset is displayed as text near the estimated severity indicator bars SB. This display allows physicians to easily check the changes in the patient's estimated NYHA classification within the displayed period, enabling them to efficiently conduct interviews to diagnose the severity of patient P during examinations.

[0054] The estimated severity indicator bar SB is generally displayed at predetermined intervals. However, if there is a change in the timing of information acquisition by the symptom appearance exercise information acquisition unit 113, or if the predetermined period includes dates before the first day or after the last day of the display area, the estimated severity indicator bar SB may be displayed for a period shorter than the predetermined period.

[0055] Figure 7B is an enlarged view of the subjective symptom information area S. As shown in Figure 7B, the subjective symptom information area Area S displays information indicating whether or not the patient experienced any subjective symptoms related to heart failure each day, using dots to indicate the type of symptom (the dotted symptom represents the symptom the patient experienced on that day). Additionally, if the patient is keeping daily notes via the patient terminal 300 (described later), this information may also be displayed. By referring to this display, the physician can easily confirm the changes in the type and frequency of symptoms the patient P is experiencing on a daily basis.

[0056] Furthermore, by aligning this subjective symptom information area S with the estimated severity display bar SB on a time axis, physicians can easily confirm the correspondence between the daily changes in subjective symptoms and the changes in estimated severity, thereby efficiently understanding the progression of the patient's condition.

[0057] Figure 8A is an enlarged view of the medication information area ME. As shown in Figure 8A, the medication information area ME displays daily information about the patient's medication adherence (whether or not the prescribed medication was taken correctly) within the displayed period, indicated by the activation or deactivation of capsule marks. If the patient took as-needed medication, this is indicated separately in the column for the date of administration. If the patient is required to take medication multiple times a day (for example, in the morning, at noon, and in the evening), columns indicating whether or not the medication was taken for each time may be provided. Alternatively, the daily medication adherence rate may be displayed (for example, by displaying marks for the number of doses taken, or by displaying it as a fraction), or a pie chart may be used.

[0058] Figure 8B is an enlarged view of the blood pressure information area BP. As shown in Figure 8B, the blood pressure information area BP displays blood pressure values ​​on a daily basis within the display period. Specifically, a bar graph with systolic blood pressure at the top and diastolic blood pressure at the bottom shows the blood pressure value for one measurement. If there are measurements for two or more occasions (for example, upon waking in the morning and before going to bed at night), these can be displayed side by side as shown in Figure 8B. In addition, the measurement occasions (e.g., morning / evening / other) can be distinguished using color coding or other methods.

[0059] Figure 9 is an enlarged view of the heart rate and pulse information area (HP). As shown in Figure 9, the heart rate and pulse information area (HP) displays a graph plotting the daily heart rate and daily pulse rate calculated by the daily measurement calculation unit 112, as well as the heart rate at the time of detection of atrial fibrillation (AF), if AF is detected, on the same graph area (X axis is the time axis, Y axis is the number of beats). In this graph, the daily heart rate and daily pulse rate are represented as a single value per day, but if AF is detected multiple times in a day, all heart rates at the time of detection are plotted. This allows for the distinction between items whose changes should be tracked over time and items for which information should be grasped on a one-off basis, while still allowing for their correlation. Additionally, a separate mark may be displayed on days when AF is detected or when irregular pulse waves (arrhythmias) are detected.

[0060] In the example shown in Figure 9, there was a measurement opportunity to determine the daily heart rate and pulse rate for every day of the display period, and the heart rate and pulse rate from those measurement opportunities are plotted. On the other hand, if there is a day on which there is no measurement opportunity in which both the heart rate and pulse rate are properly measured, the heart rate and pulse rate for that day may not be plotted. Alternatively, one may predetermine which biometric information to prioritize between heart rate and pulse rate, and plot (display) only the values ​​of that biometric information. Alternatively, only the values ​​of biometric information that have been properly measured may be displayed in a manner that makes it clear that they are reference values.

[0061] By referring to this display, physicians can easily confirm the changes in patient P's cardiac contractility. Furthermore, by plotting heart rate and pulse rate in the same graph area, even if there is a measurement error in either the heart rate or pulse rate measurement, patient P's cardiac contractility can be diagnosed based on the other value. If discrepancies exist, it is possible to consider and determine, based on other information, whether significant events such as measurement errors or changes in the patient's symptoms have occurred.

[0062] By referring to the clinical support images that display the information described above, physicians can efficiently obtain information about patient P, significantly reducing the burden on physicians who must keep track of information on many patients. Furthermore, by referring to the clinical support images, physicians can streamline the content of their medical interviews during consultations, thereby reducing the burden on patient P during their examinations.

[0063] (Patient-side terminal) Figure 10 is a block diagram showing the functional configuration of the patient-side terminal 300. The patient-side terminal 300 is a portable information processing terminal such as a smartphone, tablet, or smartwatch-type wearable device, and includes a control unit 310, input means 320, output means 330, storage means 340, and communication means 350. In this embodiment, the patient-side terminal 300 corresponds to the automated medical interview terminal according to the present invention.

[0064] The control unit 310 is a means for controlling the patient terminal 300 and is composed of, for example, a CPU. The input means 320 can be a touch panel display integrated with the output means 330. The storage means 340, like other terminals, is composed of a main memory unit, an auxiliary memory unit, etc., and stores the operating system (OS), various programs, and various data acquired via the communication network N. The communication means 250 is composed of, for example, a wireless communication circuit for wireless communication.

[0065] The control unit 310 includes an automated medical interview execution unit 311 as a functional module related to patient information management, including symptom appearance and movement information. The automated medical interview execution unit 311 is implemented, for example, as a function provided by an application program, and accepts patient information input through a user interface (hereinafter referred to as UI) that prompts the user to input information as if conducting a medical interview. The automated medical interview execution unit 311 may display a UI that, for example, displays multiple icons related to predetermined items and prompts the user to make a selection, or it may adopt a format such as a so-called chatbot. Furthermore, the application program may be stored in the storage means 340 of the patient terminal 300, or it may be provided in the form of SaaS (Software as a Service) on the server device 100.

[0066] Figures 11A and 11B show examples of a state where the UI provided by the automated medical interview execution unit 311 is displayed on the screen of a smartphone, which is an example of a patient-side terminal 300. Figure 11A shows a UI that accepts input of daily medication information and information about the presence or absence of subjective symptoms (subjective symptom information). As shown in Figure 11A, the UI for medication information is used to input by selecting medication icons for each time slot (morning, noon, and evening), and the selected icons are displayed and activated. Similarly, for subjective symptom information, icons representing each symptom are displayed, and the UI for input is used to select the icon of the symptom the user has experienced. Here again, the selected icons are displayed and activated. The automated medical interview execution unit 311 performs an automated medical interview process that requests the patient to input medication information and subjective symptom information at a scheduled time each day (for example, 21:00). Note that the screen shown in Figure 11A is an example of a UI related to medication information and subjective symptom input, and other UIs may be used to request the user to input subjective symptoms. Specifically, for example, a list of symptoms may be presented, and the patient may be asked to select a symptom from that list, or text information related to the subjective symptoms may be accepted as a memo or similar.

[0067] Figure 11B shows a U that accepts input of symptom appearance and motor information at predetermined intervals (e.g., one week). An example of I is shown. As shown in Figure 11B, a list of items indicating the content of multiple exercises (physical activities) with different exercise intensities is displayed, and the UI is designed to input by selecting the physical activity in which the subjective symptoms appeared. A check mark is displayed next to the selected physical activity to clearly indicate the selected item. Note that the screen shown in Figure 11B is just one example of a UI for inputting information on exercises in which symptoms appear, and other UIs may be used.

[0068] For example, the physical activity items shown in Figure 11B are representative selections from a database (e.g., a data table stored in the memory means 130) that shows a larger range of physical activities. Therefore, instead of such an excerpted display, it may be possible to show all physical activities stored in the database. Alternatively, instead of a list display, the UI may display physical activities from the database in order of increasing intensity, allowing the user to select the physical activity in which they felt symptoms. Furthermore, the automated medical questionnaire execution unit 311 may appropriately change the content and display order of the questions presented to the patient according to the severity of the patient's symptoms and past response history. For example, when displaying a list of physical activities, the displayed physical activities may be narrowed down based on the previous answers. Also, when presenting physical activities in order from mildest to most severe, the first physical activity presented may be one with a corresponding moderate severity of symptoms, based on the previous answers.

[0069] The automated medical interview execution unit 311 performs an automated medical interview process that prompts the patient to input information about the onset of symptoms at a predetermined time (for example, 21:00 every Saturday) through a screen illustrated in Figure 11B. The timing at which the automated medical interview execution unit 311 performs the automated medical interview process (the timing of the notification prompting information input) is not limited to "specific days of the week (and time)" as described above, i.e., a predetermined period applied to the calendar. It may also be a timing calculated relatively using the previous response date and a predetermined period, such as "7 days after the previous automated medical interview execution date (response date)."

[0070] Furthermore, if the automated medical interview execution unit 311 has issued a notification prompting the patient to enter information but the patient has not entered the information, it may issue another notification (reminder) prompting the patient to enter the information at a predetermined time without waiting for the next predetermined period to arrive. Here, the predetermined time may be, for example, a pre-scheduled time such as the same time the following day. Alternatively, the reminder may be issued when the patient next uses the patient terminal 300. Specifically, for example, when measuring biological information with the measuring device 400 described later, the measurement results may be displayed along with the reminder message.

[0071] Furthermore, the automated medical interview execution unit 311 may be configured not to accept further information input after receiving patient input through the automated medical interview process until it notifies the patient of the next automated medical interview process. This prevents the interval between patient responses from becoming shorter than a predetermined period.

[0072] As described above, the information entered by patient P via the application is transmitted from the communication means 350 to the server device 100 via the network N. Similarly, as will be described later, measurement data acquired from the measuring instrument 400 and other necessary information entered by patient P are also transmitted to the server device 100.

[0073] (Measuring instruments) The measuring device 400 is used by patient P to measure their daily biological information. Here, the term "measuring device 400" is used not only to refer to a single device, but also to a concept that includes multiple measuring devices such as a blood pressure monitor, electrocardiograph, and weighing scale (body composition analyzer). Furthermore, each measuring device may take any form. For example, it may be a device that combines an electrocardiograph and a blood pressure monitor, or a body composition analyzer capable of measuring an electrocardiogram. It may also be a stationary device or a portable device. It may be a device capable of handling such devices. It may also include wearable devices that are worn by the patient at all times. It may also be integrated with the patient terminal 300.

[0074] Various measurement data, such as heart rate, pulse rate, blood pressure, and weight, measured using the measuring device 400, are transmitted to the patient terminal 300 via wired or wireless communication, along with information regarding the measurement time. In the case of wireless communication, short-range wireless data communication standards such as Bluetooth® or infrared communication can be used as the communication interface between the measuring device 400 and the patient terminal 300.

[0075] The measuring device 400 does not necessarily have a means of communication. In that case, the patient P may manually input the measurement data (and measurement date and time information) into the patient terminal 300, and this information may be sent to the server device 100.

[0076] Furthermore, the patient-side terminal 300 may also incorporate the functions of the measuring instrument 400. For example, if the patient-side terminal 300 is a wearable device attached to patient P, it can also function as the measuring instrument 400 if it has a measurement function. Alternatively, for example, a stationary measuring instrument 400 may also function as an information processing terminal and thus serve as the patient-side terminal 300.

[0077] (Information processing flow within the system) Next, the flow of information processing performed in the medical support system 1 according to this embodiment, which has the configuration described above, will be explained. Figure 12 is a diagram showing the flow of information exchange and processing performed within the medical support system 1. As shown in Figure 12, first, measurement data obtained by patient P using the measuring device 400, symptom appearance movement information, subjective symptom information, medication information, etc., are input into the patient terminal 300 (S101). This information is sent from the patient terminal 300 to the server device 100 each time, or in batches for a predetermined period (for example, one week) (S102).

[0078] In the server device 100, various types of received information are stored in the storage means 130, and a medical support image is generated based on that information (S103).

[0079] Subsequently, the physician sends a request for a medical support image to the server device 100 via the physician's terminal 200 (S104). The server device 100 then provides the medical support image to the physician's terminal 200 (S105), and the medical support image is displayed on the output means 230 of the physician's terminal 200 (S106). Here, the medical support image may be provided as data that is sent to the physician's terminal 200 and stored in the storage means 240 of the physician's terminal 200, or it may be provided in a SaaS manner and the storage of image data may not be possible. The content of the medical support image is as described above.

[0080] As described above, the medical support system 1 according to this embodiment allows physicians to refer to medical support images that show information on the subjective symptoms of heart failure patients and the changes in estimated severity on a common time axis with measurement data of biological information. Such a screen makes it easy to efficiently grasp the changes in the patient's condition and their current state, which helps to prevent inefficient questioning at each consultation and enables efficient diagnosis of the patient.

[0081] <Variation> In the above embodiment, when multiple measurements are taken on a single day and the measurement values ​​of multiple measurements are stored in the storage means 130, the daily measurement value calculation unit 112 describes an example in which the measurement value of a measurement taken at a preset timing is used as a method for determining one measurement taken on a single day for calculating the daily heart rate and pulse rate. However, the method for determining one measurement taken on a single day from multiple measurement opportunities is not limited to this. Specifically, one measurement taken on a single day can be calculated by other methods as shown below. You can do that.

[0082] (Variation 1) For example, the daily measurement calculation unit 112 may determine a measurement opportunity from among multiple measurement opportunities where the discrepancy between the measured heart rate and pulse rate within that single opportunity is large as the one opportunity for calculating the daily heart rate and pulse rate. This makes it possible to clearly show the difference between the heart rate and pulse rate plotted in the heart rate and pulse rate information area HP, making it easier to draw the attention of physicians.

[0083] (Modification 2) Furthermore, the daily measurement value calculation unit 112 may determine the measurement opportunity with the smallest time difference between the heart rate and pulse rate measurements taken within one of multiple measurement opportunities as the one opportunity for calculating the daily heart rate and pulse rate. Since it is assumed that when a healthy person measures their heart rate and pulse rate simultaneously (and accurately), these values ​​will be equal, the discrepancy between the heart rate and pulse rate within the same measurement opportunity can be used to infer the deterioration of the patient's symptoms or condition. Therefore, the smaller the time difference between the heart rate and pulse rate measurements (i.e., the closer they are to simultaneous), the more desirable.

[0084] (Variation 3) Furthermore, if there are multiple measurement opportunities per day, and the heart rate or pulse rate is measured multiple times at each opportunity, the daily measurement value calculation means 113 may determine the measurement opportunity with the smallest difference between the multiple heart rates or pulse rates acquired at each opportunity as the one opportunity for calculating the daily heart rate / pulse rate. This is because such a measurement opportunity is more likely to measure biological information in a more appropriate (less harmful) state.

[0085] (Modification 4) Furthermore, the daily measurement value calculation unit 112 may determine a measurement opportunity in which no measurement conditions that could adversely affect the measurement were detected during the measurement of heart rate and pulse rate (i.e., a measurement opportunity in which there is no additional information indicating such a condition in the measurement value) as one opportunity for calculating the daily heart rate and pulse rate.

[0086] <Other> The above examples are merely illustrative illustrations of the present invention, and the present invention is not limited to the specific forms described above. The present invention can be modified and combined in various ways within the scope of its technical concept. For example, in the above embodiments, the doctor-side terminal 200 and the patient-side terminal 300 were described as a single configuration each, but as shown in Figure 13, the present invention can of course also be applied as a medical support system 2 equipped with multiple doctor-side terminals 200a to 200n and / or multiple patient-side terminals 300a to 300n.

[0087] Furthermore, the medical support image generation means 118 may generate a medical support image that includes a list representing the contents of the data table shown in Figure 3. If a medical support image including such a list can be referred to during a medical examination, the doctor can conduct the interview to diagnose the severity of the patient's condition more efficiently.

[0088] Furthermore, in the above embodiment, the automated medical interview terminal according to the present invention was described as a patient-side terminal 300 (a smartphone owned by the patient), but the automated medical interview terminal is not necessarily limited to this. For example, it may be an information processing terminal installed in a medical institution, or it may be a portable information processing terminal brought by a visiting nurse or the like for the patient to input information into.

[0089] Furthermore, the medical support system according to the present invention may not be configured to include an automated medical interview terminal. That is, information obtained from patients through interviews during consultations or telephone interviews may be input into the system by operating a mouse or keyboard.

[0090] Furthermore, in the above embodiment, the measuring device 400 was configured to transmit measurement data to the patient terminal 300, but it may also be configured to transmit the measurement data (and related information) directly to the server device 100. With such a configuration, even if there is no patient terminal 300 acting as an automated medical interview terminal, the server device 100 can acquire the patient P's daily measurement data.

[0091] Furthermore, while the NYHA classification was used as an example of information indicating the severity of heart failure in the above embodiment, it is not necessarily limited to this. For example, the ACC / AHA (American Heart Association / American College of Cardiology) staging classification may be used as information indicating severity. Moreover, it is not limited to such classifications; it may also indicate the degree of decline in physical function. In addition, while the disease targeted in the above embodiment was heart failure, the diseases treated are not limited to this. For example, the present invention can be applied to the treatment of hypertensive patients. [Explanation of Symbols]

[0092] 1, 2... Medical support system 100... Server device 110, 210, 310... Control Unit 120, 240, 340...Storage means 130, 250, 350... Communication methods 200... Doctor's terminal 220, 320... Input methods 230, 330... Output means 300...Patient terminal 400... Measuring Instruments P...patient N... Communications Network OV...Overview information area MM... Minimum METs information W...Weight information area NT... Estimated NYHA classification transition region SB... Estimated Severity Display Bar S... Subjective Symptom Information Area ME...Medication Information Area BP... Blood pressure information area HP... Heart rate and pulse information area

Claims

1. A means for acquiring symptom-causing exercise information, which is information including the content of exercises in which symptoms related to the disease being treated by the patient appear, A storage means for storing the acquired symptom appearance motor information each time, A minimum exercise intensity calculation means that, based on the stored information on exercises in which symptoms related to the disease appeared during a predetermined period, determines the minimum exercise intensity, which is the exercise with the lowest exercise intensity among the exercises in which symptoms related to the disease appeared during that period. Estimated severity information calculation means for determining estimated severity information indicating the severity of the patient's illness during a predetermined period based on the minimum exercise intensity, A medical support information set generation means for generating a medical support information set that shows the minimum exercise intensity and / or estimated severity information of the patient for each predetermined period, Output means for outputting the aforementioned medical support information set, It has, The storage means further stores the minimum exercise intensity calculated by the minimum exercise intensity calculation means and the estimated severity information calculated by the estimated severity information calculation means each time, The medical support information set generation means generates the medical support information set using the minimum exercise intensity and estimated severity information stored in the storage means. Medical support system.

2. The storage means further stores an exercise intensity table that associates the content of the exercise with the exercise intensity of the exercise, The minimum exercise intensity calculation means calculates the minimum exercise intensity by referring to the exercise intensity table. A medical support system according to claim 1, characterized in that

3. The system further includes an automated medical interview terminal that performs an automated medical interview process that requests the patient to input patient information, including at least the symptom appearance and movement information for the patient within the most recent predetermined period. The means for acquiring information on the movement of symptoms is an automated medical interview process performed in the automated medical interview terminal. The motor information regarding the appearance of symptoms is obtained from the patient via the above method. A medical support system according to claim 1 or 2, characterized in that

4. The automated medical interview terminal modifies the content of the questions asked to the patient during the automated medical interview process according to the patient's symptoms and / or the patient's past responses. The medical support system according to claim 3, characterized in that

5. The disease being treated is heart failure, and the estimated severity information is based on the NYHA classification. A medical support system according to any one of claims 1 to 4, characterized in that

6. The aforementioned medical support information set is an image, The medical support information set generation means generates a medical support image as the medical support information set, and generates the medical support image including a list that associates the content of the exercise, the exercise intensity of the exercise, and the estimated NYHA classification when the exercise intensity is the minimum exercise intensity. The medical support system according to claim 5, characterized in that

7. A medical support device comprising the means for acquiring symptom appearance exercise information, the means for calculating minimum exercise intensity, the means for calculating estimated severity information, the means for generating a medical support information set, and the means for storing information, which constitutes at least a part of the medical support system described in any one of claims 1 to 5.

8. A program for causing a computer to function as a medical support device according to claim 7.

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