Information processing device, information provision method, and program

Abstract

To provide a mechanism that allows the confirmation of a change in a distribution state of a measured value on and after a start date of recording through a program executed with a terminal operated by a user who changes his / her action.SOLUTION: An information processing device includes one or a plurality of processors in which the one or the plurality of processors classify a measured value into any of a plurality of sections set according to a standard value defined for each user, generate distribution information of the measured value corresponding to the plurality of sections in a predetermined period unit, and present the distribution information in the predetermined period unit on and after a start date of recording in a list.SELECTED DRAWING: Figure 12

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an information providing method, and a program. [Background technology]

[0002] The doctor's app has a function that displays the average blood pressure values ​​recorded by the patient on their smartphone for the most recent month (4 weeks ago to the previous day) and the average for the month before that (8 weeks ago to 4 weeks ago) on the viewing screen. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] CureApp, Inc., "By being able to see blood pressure trends and behavioral changes, we can provide effective guidance to each patient," [online], [Retrieved April 26, 2024], Internet<URL:https: / / cureapp.co.jp / productsite / ht / > Summary of the Invention [Problem to be solved by the invention]

[0004] Doctors and patients can check changes in blood pressure values ​​over the past two months on the doctor app screen, but they cannot see changes in the distribution of blood pressure values ​​compared to when they first started recording them.

[0005] As one aspect of the present disclosure, a mechanism is provided that enables a user who changes their behavior to check changes in the distribution of measured values ​​after the start date of recording through a program executed on a terminal operated by the user. [Means for solving the problem]

[0006] The invention described in claim 1 is an information processing device having one or more processors, which reads measurement values ​​recorded in the past through a program executed on a terminal operated by a user who is changing their behavior, classifies the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user, generates distribution information of the measurement values ​​corresponding to the plurality of intervals in units of a predetermined period, and presents a list of the distribution information for the predetermined period from the start date of recording. The invention recited in claim 2 is the information processing device recited in claim 1, wherein the one or more processors set a therapeutic target value determined for each user as the reference value. The invention described in claim 3 is an information processing device described in claim 2, wherein the one or more processors, when receiving a change in the therapeutic target value, reset the multiple intervals and regenerate distribution information of the measurement values ​​corresponding to the multiple intervals after resetting in units of the specified period. A fourth aspect of the present invention is the information processing device according to the first aspect, wherein the one or more processors set the measurement value on a start date of recording as the reference value. The invention described in claim 5 is an information processing device described in claim 1, wherein the one or more processors classify a first measurement value recorded through a program requiring a prescription and a second measurement value recorded through another program not requiring a prescription into one of the multiple intervals when the specified period includes the first measurement value and the second measurement value. The invention described in claim 6 is the information processing device described in claim 1, wherein the program is a program that requires a prescription. The invention described in claim 7 is the information processing device described in claim 1, wherein the program is a program that does not require a prescription. The invention described in claim 8 is an information provision method in which a computer executes the following processes: reading out measurement values ​​recorded in the past through a program executed on a terminal operated by a user who changes his or her behavior; classifying the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user; generating distribution information of the measurement values ​​corresponding to the plurality of intervals in units of a predetermined period; and presenting a list of the distribution information in the units of the predetermined period from the start date of recording. The invention described in claim 9 is a program for enabling a computer to perform the following functions: reading out measurement values ​​recorded in the past through a program executed on a terminal operated by a user who changes his or her behavior; classifying the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user; generating distribution information of the measurement values ​​corresponding to the plurality of intervals in units of a predetermined period; and presenting a list of the distribution information for the predetermined period from the start date of recording. [Effects of the Invention]

[0007] According to one embodiment of the present disclosure, it is possible to provide a mechanism that enables a user who changes their behavior to check changes in the distribution of measurement values ​​after the start date of recording through a program executed on a terminal operated by the user. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an overall configuration of an information processing system. [Figure 2] FIG. 1 is a diagram illustrating an example of the hardware configuration of a PDT platform. [Figure 3] FIG. 2 is a diagram illustrating an example of status management data stored in an auxiliary storage device of the PDT platform. [Figure 4] FIG. 2 is a diagram illustrating an example of the hardware configuration of a PDT server. [Figure 5] FIG. 10 is a diagram illustrating an example of patient data stored in an auxiliary storage device of the PDT server. [Figure 6]FIG. 2 is a diagram illustrating an example of the hardware configuration of a doctor terminal and a patient terminal. [Figure 7] FIG. 2 is a diagram illustrating an example of a processing sequence executed in the information processing system. [Figure 8] FIG. 10 is a diagram illustrating an example of an operation screen in a patient application. [Figure 9] FIG. 1 is a diagram illustrating a treatment program. [Figure 10] FIG. 10 is a diagram illustrating an example of a management screen for the usage status of a patient application displayed on an output device of the doctor terminal. [Figure 11] FIG. 10 is a diagram illustrating an example of a patient data viewing screen. [Figure 12] FIG. 10 is a diagram illustrating a display example of a distribution table screen. [Figure 13] FIG. 10 is a diagram illustrating another example of the display of the distribution table screen. [Figure 14] FIG. 10 is a diagram illustrating changes in distribution ratios per period in three blood pressure intervals shown in the distribution table when the blood pressure reduction target value is changed during treatment. [Figure 15] FIG. 10 is a diagram illustrating another example of the display of the distribution table screen. [Figure 16] FIG. 10 illustrates an embodiment in which measurements recorded via a non-patient app and measurements recorded via a patient app are used in combination. [Figure 17] FIG. 10 is a diagram illustrating another embodiment in which measurements recorded through a non-patient app and measurements recorded through a patient app are used in combination. [Figure 18] FIG. 10 is a diagram illustrating another example of a processing sequence executed in the information processing system. [Figure 19] FIG. 10 is a diagram illustrating another example of a processing sequence executed in the information processing system. [Figure 20] FIG. 10 is a diagram illustrating another example of a processing sequence executed in the information processing system. [Figure 21] FIG. 10 is a diagram illustrating an example of a distribution table screen display when the disease is diabetes. DETAILED DESCRIPTION OF THE INVENTION

[0009] <Terminology> First, terms used in the embodiments described below will be explained. A "program that encourages behavioral change" is a program that is provided with the intention of encouraging a change in a person's behavior. However, this program does not guarantee that a person's behavior will change. Whether or not a person's behavior actually changes depends on the user who uses the program. Therefore, a program that encourages behavioral change can also be said to be a program that supports behavioral change. This type of program can be classified as a medical device or a non-medical device. A medical device program is an example of a program that requires a prescription, while a non-medical device program is an example of a program that does not require a prescription.

[0010] "Program objectives" refer to the effects to be achieved by using a program to promote behavioral change. Program objectives vary depending on the disease for which the program promotes behavioral change is targeted. For example, program objectives may include improving lifestyle habits, maintaining improved lifestyle habits, and maintaining improved numerical values. "Program goal" refers to the goal to be achieved through the use of a program to promote behavioral change. Goals are defined from the perspective of achieving the objective. Goals are classified into qualitative indicators and quantitative indicators. Goals are also classified into indicators defined by measurements or other numerical values ​​and indicators defined by the content of actions. For example, goals can include improving or maintaining habits, behaviors, or numerical values. Program goals can also be further defined by one or more subgoals. Subgoals are smaller-scale targets set to achieve the corresponding goal.

[0011] "Therapeutic App" refers to an application program that has been approved under the Pharmaceuticals and Medical Devices Act. Therapeutic Apps are programs that are classified as medical devices. Therapeutic apps are approved for each disease. Diseases for which approval has already been obtained include hypertension, nicotine addiction, and insomnia. Diseases for which therapeutic apps are currently in development include NASH (non-alcoholic steatohepatitis), diabetes, dyslipidemia, kidney disease, and alcoholism.

[0012] "User" refers to a person who changes their behavior through a program that encourages behavioral change. Users include users who have not yet visited a medical institution and users who have visited a medical institution. Users who have visited a medical institution include users who are subject to medical fee calculations and users who are not subject to medical fee calculations. A "patient" refers to a user who is currently receiving treatment at a medical institution. In other words, a patient refers to a user who has started or is currently undergoing treatment at a medical institution.

[0013] Treatment apps include patient apps and doctor apps. A "Patient App" is an application program that runs on a device operated by a patient (hereinafter also referred to as a "Patient Terminal") and is prescribed to the patient by a doctor. In this sense, the Patient App is also called a PDT (Prescription Digital Therapeutic). The patient app can be downloaded from, for example, an app store. In the embodiment described below, a code required for activation (hereinafter referred to as a "prescription code") is issued by a doctor's prescription. The patient app is used to record patient data outside of medical institutions (hereinafter also referred to as "patient app data").

[0014] A validity period is set for a patient app at the time of approval. This validity period is determined based on, for example, the period during which the public medical insurance system applies. The validity period is determined depending on the type of disease that the patient app covers. For example, the validity period for a patient app for hypertension is six months, counting from the month following the month in which the patient app was prescribed. However, six months is just an example, and it could be, for example, nine months or 12 months. The validity period may also be determined in days, such as 60 days or 180 days, or in weeks, such as eight weeks or 24 weeks. Needless to say, these values ​​are just examples.

[0015] A "doctor app" refers to an application program that can be used through a terminal operated by a doctor or other medical professional (hereinafter also referred to as a "doctor terminal"). In the embodiment described below, the doctor app runs on a cloud server that can be operated from the doctor terminal. The doctor app is used to view patient data (including patient app data). Note that medical professionals are also referred to as medical workers.

[0016] "Patient data" includes, for example, patient attributes, measurement values, activity records, mood records, physical condition records, medical examination history, patient app operation history, biological characteristics, psychological characteristics, social characteristics, habits, and goal achievement status. However, the items recorded as patient data vary depending on the disease, and do not necessarily have to be all of the exemplified information, but may be some of it or may include other information. Note that the items recorded as patient data are all examples of health-related data.

[0017] The "patient attributes" include, for example, the patient's name, gender, and date of birth. These pieces of information are examples of basic patient information. "Measurement value" refers to a numerical value measured using a measuring device. The measurement value items recorded as patient app data are specified for each disease. For example, if the disease is hypertension, blood pressure values ​​are recorded as measurement values. Blood pressure values ​​are specified, for example, as systolic blood pressure (i.e., maximum blood pressure) and diastolic blood pressure (i.e., minimum blood pressure). For example, if the disease is nicotine addiction, the measurements recorded would be carbon monoxide (CO) in the breath and nicotine concentration in the saliva.

[0018] The "activity record" is, for example, the operation history of the patient app, the medication record, the meal record, the smoking record, the drinking record, and the exercise record. These records are also records of the user's behavior. The activity record is an example of information related to activity. The "mood record" is, for example, a subjective mood. The mood record is an example of information about mood. The "record of physical condition" is, for example, a subjective physical condition or symptom. The record of physical condition is an example of information related to physical condition.

[0019] The "medical examination history" includes, for example, the treatment start date, the consultation date, the content of the treatment, and advice. The medical examination history is an example of information related to medical examinations. The "patient application operation history" is, for example, a history of operations related to the patient application startup operation, and the input operation of measurement values ​​and reviews. "Biological characteristics" include, for example, whether or not the patient has other illnesses, whether or not they have had injuries undergoing treatment, whether or not they have pain in their knees or feet, whether or not they have had treatment for an illness, the number of years since the illness was diagnosed, how strongly seasoned their food is at home, and the amount of food they eat.

[0020] "Psychological characteristics" include, for example, expectations regarding app treatment, willingness to acquire knowledge about disease treatment, whether reducing salt intake is difficult, whether one believes one's sense of taste cannot be changed, and psychological resistance to leaving food on one's plate. "Social characteristics" include, for example, wake-up time, bedtime, type of work (e.g., shift work, day shift, night shift), days of the week worked, start time of work, time home from work, regular days off, and whether or not there is a heater in the changing room.

[0021] "Habits" include, for example, exercise habits, weighing oneself, checking the calorie count on food labels, choosing low-fat foods, not consuming caffeine after 4 p.m., eating and drinking after 10 p.m., skipping breakfast, snacking, taking a bath one hour before bedtime, stretching or massaging before bedtime, and sleeping for six hours or more. The "goal achievement status" is, for example, information indicating the progress status toward a goal set by a doctor for each patient. The "goal achievement status" may be, for example, information indicating the progress status toward a goal set by the patient himself / herself. The "goal achievement status" may be, for example, information indicating the progress status toward a goal presented by a patient app for each patient. The above-mentioned information can be classified into subjective information and objective information. Patient data is recorded, for example, as text, images (moving images, still images), audio, numbers, and codes.

[0022] The "PDT server" is a server that manages patient data entered through a patient app, etc. The PDT server is also an example of a cloud server. A PDT server is basically provided for each patient app. Therefore, in order for a doctor to view patient data, he / she must log in to the PDT server running the doctor app that is paired with the patient app used by the patient.

[0023] For example, if a patient uses a patient app for hypertension provided by service provider A, the doctor needs to log in to the PDT server operated by service provider A for hypertension. Also, if a patient uses a patient app for hypertension provided by service provider B, the doctor needs to log in to the PDT server operated by service provider B for hypertension.

[0024] In addition, if a patient uses a patient app for nicotine addiction provided by service provider A, the doctor needs to log in to the PDT server operated by service provider A for nicotine addiction. It should be noted that multiple patient apps targeting different diseases may share one PDT server. Furthermore, multiple patient apps provided by different service providers may share one PDT server.

[0025] The PDT platform is a server that manages patient app prescriptions and the usage status of patient apps after prescription. The PDT platform is also an example of a cloud server. The PDT platform is also called an APS (Application Prescription Service) server, meaning that it is a server that provides prescription services for patient apps. The usage status may be, for example, "before use begins," "expired," "in use," "scheduled to end," "ended," or "expired."

[0026] "Before use begins" refers to the state in which the prescription for the patient app has been completed but use on the patient's device has not yet begun. For example, this refers to the state in which the patient has not yet entered the prescription code into the device. "Start expired" refers to a state in which the prescription code has not been confirmed as entered within the period in which the prescription code is valid (for example, within four days including the prescription date).

[0027] "In use" refers to the state in which the patient app installed on the patient's device has been activated and is ready for use. Activating the patient app requires the entry of an activation code, such as the prescription code mentioned above. "Scheduled to end" refers to a state in which a medical institution has set the patient to be outside the scope of management within the validity period. For example, this state is set for a patient who will not receive a follow-up examination.

[0028] "Terminated" refers to a state in which the patient app cannot be used due to, for example, the expiration of the validity period. "Expired" is a state that indicates that a predetermined period has passed since the prescription date. The predetermined period is set to be longer than the validity period. For example, if the validity period is 6 months, the predetermined period is set to 8 months. "Selected medical treatment" is displayed when the validity period has expired but the patient is still eligible for selected medical treatment. Selected medical treatment refers to medical services that patients enrolled in social insurance can receive in addition to insurance-covered treatment, but not covered by insurance, by paying an additional fee.

[0029] The PDT platform can support multiple patient apps that target the same disease but are provided by different service providers, as well as multiple patient apps that are provided by the same service provider but target different diseases. In this sense, the PDT platform acts as a platform for multiple patient apps. The app, which runs on the PDT platform, manages the usage status of multiple patient apps for different diseases and service providers on a patient-by-patient basis.

[0030] In the embodiments described below, the "medical institution" is assumed to be a medical institution that is covered by health insurance. More specifically, the medical institution refers to a medical institution that is covered by health insurance and to which a doctor who issues a prescription code required to activate a patient app belongs. However, if deregulation allows pharmacists, public health nurses, nurses, nutritionists, hospital staff, and other medical professionals to issue prescription codes, the term "medical institution" also includes facilities and organizations that employ these medical professionals. In the following, these medical professionals will be collectively referred to as "doctors, etc." The issuance of prescription codes is not limited to medical treatment, but may also be for non-insurance treatment (i.e., private treatment) or mixed treatment. Incidentally, medical treatment is not limited to face-to-face treatment, but also includes online treatment.

[0031] <Overall system> Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. 1 is a diagram illustrating the overall configuration of an information processing system 1. The information processing system 1 shown in FIG. 1 is composed of a PDT platform 10, PDT servers 20 (20A, 20B, 20C, . . . 20F), a doctor terminal 30, and a patient terminal 40.

[0032] 1 depicts only one PDT platform 10, although multiple PDT platforms 10 may exist. The PDT platform 10 may be configured with multiple servers connected via a network. In this case, the multiple servers cooperate to provide the services of the PDT platform. The PDT platform 10 and the PDT server 20 are communicatively connected via a network (not shown). The network may be, for example, a LAN (Local Area Network), the Internet, or a mobile communication system (4G, 5G, etc.).

[0033] 1, six PDT servers 20 are connected to one PDT platform 10. However, the number of PDT servers 20 connected to one PDT platform 10 is arbitrary. The PDT server 20 is a server that performs patient authentication, manages patient application data input through the patient application, provides patient data to the doctor terminal 30, and the like. In the case of FIG. 1, the PDT server 20A is a server that manages patient data of a patient application (hereinafter referred to as "patient application A") provided by company A for patients with hypertension. The PDT server 20B is a server that manages patient data of a patient application (hereinafter referred to as "patient application B") provided by Company B for patients with hypertension.

[0034] The PDT server 20C is a server that manages patient data of a patient application (hereinafter referred to as "patient application C") provided by Company A for diabetes patients. The PDT server 20D is a server that manages patient data of a patient application (hereinafter referred to as "patient application D") provided by Company B for diabetes patients. The PDT server 20E is a server that manages patient data of a patient application (hereinafter referred to as "patient application E") provided by Company C for patients with dyslipidemia. The PDT server 20F is a server that manages patient data of a patient application (hereinafter referred to as "patient application F") provided by Company D for patients with NASH.

[0035] 1, a PDT server 20 is prepared for each combination of a disease targeted by a patient app and a service provider that provides the patient app. Therefore, even if the service provider that provides the patient app is the same, if the targeted diseases are different, a different PDT server 20 is prepared. Furthermore, even if the target disease is the same, if the service provider that provides the patient app is different, a different PDT server 20 will be prepared.

[0036] However, it is also possible to provide one PDT server 20 for a plurality of patient applications with different combinations. The PDT platform 10 and the PDT server 20 may be operated by different operators, not necessarily by the same operator. For example, some of the PDT servers 20 may be operated by the same operator as the PDT platform 10.

[0037] The doctor terminal 30 is a terminal operated by a doctor or the like who uses the services provided by the PDT platform 10 and the PDT server 20. In Figure 1, only one doctor terminal 30 is depicted as a representative. For example, a doctor can view the usage status of the patient app by logging in to the PDT platform 10. Also, a doctor can view patient data by logging in to the PDT server 20. The patient terminal 40 is a terminal operated by a patient. The patient terminal 40 uploads patient application data recorded through the patient application to the corresponding PDT server 20. In Fig. 1, only one patient terminal 40 is depicted as a representative example.

[0038] <Device hardware configuration> <PDTプラットフォーム> 2 is a diagram illustrating an example of the hardware configuration of the PDT platform 10. The PDT platform 10 is a so-called server. The PDT platform 10 shown in FIG. 2 has a processor 11, a semiconductor memory 12, an auxiliary storage device 13, and a communication interface 14. Each device is connected through a bus or other signal lines.

[0039] The processor 11 is a device that realizes various functions through program execution. The semiconductor memory 12 stores UEFI (Unified Extensible Firmware Interface) etc. The semiconductor memory 12 is also used as a program execution area. The processor 11 and the semiconductor memory 12 function as a computer.

[0040] The auxiliary storage device 13 is composed of, for example, a hard disk device or a semiconductor storage. The auxiliary storage device 13 stores an operating system and other programs. Other programs include, for example, an application program that displays a list of usage statuses of patient apps. In addition, the auxiliary storage device 13 also stores data for managing the status management data 130 by prescription code prescribed by a medical institution. The communication interface 14 is an interface for communicating with an external terminal such as a PDT server 20 (see FIG. 1) through a network. The communication interface 14 supports communication standards such as Ethernet (registered trademark), Wi-Fi (registered trademark), and mobile communication systems.

[0041] <Management data of the PDT platform> FIG. 3 is a diagram for explaining an example of the status management data 130 stored in the auxiliary storage device 13 (see FIG. 2) of the PDT platform 10 (see FIG. 1). The status management data 130 shown in FIG. 3 stores a prescription code 130A, a patient ID / patient name 130B, a prescription date / medical treatment date 130C, a medical institution ID / prescriber ID 130D, a patient app name 130E, and a usage status 130F. However, these are just examples, and other information that may be stored include the patient's medical record number, the patient's gender, the patient's date of birth, the patient's age, the type of health insurance card, the insurer number, and the version of the patient app.

[0042] The prescription code 130A is issued from the doctor terminal 30 for each notification of a prescription. The patient ID / patient name 130B is the patient ID and patient name registered when the prescription was made in the patient app. In the case of Figure 3, the patient name of patient ID "12543" is "Mr. A," the patient name of patient ID "12544" is "Mr. B," and the patient name of patient ID "12545" is "Mr. C."

[0043] The prescription date / treatment date 130C is the date on which the doctor examined the patient. In this embodiment, the treatment date on which the doctor prescribed the patient app is referred to as the "prescription date" to distinguish it from other treatment dates. In the case of FIG. 3, only the prescription date is stored. In the case of FIG. 3, the prescription date of the patient app for "Mr. A" and "Mr. B" is "2024 / 5 / 28", and the prescription date of the patient app for "Mr. C" is "2024 / 2 / 24". The medical institution ID / prescriber ID 130D is an ID that identifies the medical institution and prescriber that prescribed the patient app. In the case of Figure 3, the prescription codes "12345" and "23456" were prescribed by the same doctor at the same medical institution.

[0044] The patient app name 130E is the name of the patient app prescribed by a doctor or the like. However, as long as it is possible to identify the patient app, an identification code of the patient app may be stored. In the case of FIG. 3, patient app A has been prescribed to "Mr. A" and "Mr. B." Patient app D has been prescribed to "Mr. C." The usage status 130F is information indicating the usage status of the patient app. The usage status stores one of the following: before use, start deadline expired, in use, scheduled to end, finished, and expired. In the case of FIG. 3, all patient apps are "in use."

[0045] <PDTサーバ> FIG. 4 is a diagram illustrating an example of the hardware configuration of the PDT server 20. As shown in FIG. The PDT server 20 shown in FIG. 4 has a processor 21, a semiconductor memory 22, an auxiliary storage device 23, and a communication interface 24. Each device is connected through a bus or other signal lines. The processor 21 is a device that realizes various functions through program execution. <## The semiconductor memory 22 stores UEFI and the like. The semiconductor memory 22 is also used as a program execution area. The processor 21 and the semiconductor memory 22 function as a computer.

[0046] The auxiliary storage device 23 is composed of, for example, a hard disk device or a semiconductor storage. The auxiliary storage device 23 stores an operating system and other programs. Other programs include, for example, a doctor app. The doctor app is an application program that generates a browsing screen for patient data corresponding to patients diagnosed by doctors and the like.

[0047] Other programs also include an application program that generates a distribution table of measurement values. In addition, the auxiliary storage device 23 also records patient data 230 recorded through the patient app. The communication interface 24 is an interface for communicating with external terminals such as the PDT platform 10 through a network. The communication interface 24 supports Ethernet (registered trademark), Wi-Fi (registered trademark), mobile communication systems, and other communication standards.

[0048] <PDT server management data> FIG. 5 is a diagram for explaining an example of patient data 230 stored in the auxiliary storage device 23 (see FIG. 4) of the PDT server 20. Note that the patient data 230 shown in FIG. 5 assumes data of a hypertensive patient. The patient data 230 shown in FIG. 5 stores measurement values and other information recorded through the patient app.

[0049] 5, patient data 230 stores prescription code 230A, patient ID / patient name 230B, and patient application data 230C. In the present embodiment, patient application data 230C refers to management data of the patient application and data recorded by the patient through the patient application. The prescription code 130A (see FIG. 3) issued by the PDT platform 10 (see FIG. 1) is recorded in the prescription code 230A. The prescription code 130A is registered by the patient when the patient starts using the patient app (i.e., when the patient first registers). The patient ID / patient name 230B is, for example, the patient ID and the patient name of the medical institution that prescribed the patient app. The patient ID and the patient name are acquired from the PDT platform 10, for example, when authenticating the prescription code.

[0050] 5 includes a measurement value / measurement date and time 230C1, a review / input date and time 230C2, a current step of a treatment program 230C3, a treatment program practice history 230C4, a behavioral goal 230C5, a target value 230C6, an outpatient record 230C7, and a medication record 230C8. Note that the illustrated items do not need to be all of the patient application data 230C, and may be only a part of the patient application data 230C, or may include other items. The measured blood pressure value and the date and time when the blood pressure was measured are recorded in the measurement value / measurement date and time 230C1. The blood pressure value is given as a systolic blood pressure value and a diastolic blood pressure value.

[0051] The review / input date and time 230C2 records a review of the day's actions and the input date and time. In the review, for example, the level of physical condition, stress level, length of sleep, weight, and details of the actions taken are recorded. The details of the actions are composed of the category of the actions taken and text input. Other label candidates include, for example, "sleep," "stress," "moderate drinking," and "other." In this embodiment, the category of the actions taken is recorded by checking buttons labeled "reduce salt," "weight loss," "exercise," etc. In the text input, it is possible to freely input details and emotions that cannot be recorded by checking buttons.

[0052] The current step 230C3 of the treatment program records a step indicating the progress of the treatment program provided by the patient app. In this embodiment, the treatment program is composed of three steps. The three steps are, for example, "acquiring knowledge," "practicing behavioral goals," and "making behavior a habit." The treatment program practice history 230C4 records the history of learning and behavior practiced in accordance with the treatment program. For example, in the case of "Step 1," the learning history records whether or not each learning item has been taken. For example, in the case of "Step 2," the behavior history records the practice status of each goal, such as "reducing salt intake," "reducing weight," "exercise," "sleep," "stress," "alcohol," and "quitting smoking." For example, in the case of "Step 3," the practice status of the behavior set by the patient as a goal is recorded.

[0053] The behavioral goal 230C5 records behaviors that the patient has set as goals. The goals here include one or more behavioral goals that the patient has selected from among the goals presented by the patient app according to the progress of the treatment program. For example, the behavioral goal 230C5 records a behavioral goal that the patient has set in step 2 or 3 of the treatment program. A behavioral goal refers to a behavioral goal that should be achieved in order to achieve a target. The behavioral goal is not limited to a behavioral goal selected from the behaviors presented by the patient app, and may include behaviors individually set by the patient.

[0054] In the target value 230C6, a value set by a doctor or the like in the "blood pressure reduction target value field" 313 (see FIG. 11) on the patient data viewing screen 310 (see FIG. 11) is recorded. The blood pressure reduction target value field 313 is an example of a quantitative target in that it is given as a numerical value. The outpatient record 230C7 records appointments with the doctor, the next appointment date, medication timing, etc. The appointments with the doctor record appointments that the patient should make or be aware of before the next medical examination. In this embodiment, appointments with the doctor can only be recorded through the patient app. Note that appointments with the doctor may also be recorded only from the doctor terminal 30 (see FIG. 1). The medication record 230C8 records information about taking prescribed medication.

[0055] <Doctor's terminal / Patient's terminal> Figure 6 is a diagram illustrating an example of the hardware configuration of the doctor terminal 30 and the patient terminal 40. The hardware configuration of the doctor terminal 30 and the hardware configuration of the patient terminal 40 are basically the same. For this reason, in Figure 6, they are expressed in the format of "symbols of elements constituting the doctor terminal 30 / symbols of elements constituting the patient terminal 40". The doctor terminal 30 / patient terminal 40 shown in Figure 6 includes a processor 31 / 41, a semiconductor memory 32 / 42, an auxiliary storage device 33 / 43, an input interface 34 / 44, an input device 35 / 45, an output interface 36 / 46, an output device 37 / 47, and a communication interface 38 / 48. Each device is connected via a bus or other signal lines.

[0056] The processor 31 / 41 is a device that realizes various functions through the execution of a program. The semiconductor memory 32 / 42 stores UEFI and the like. The semiconductor memory 32 / 42 is also used as an execution area for programs. The processor 31 / 41 and the semiconductor memory 32 / 42 function as a computer. The auxiliary storage device 33 / 43 is configured by, for example, a hard disk drive or semiconductor storage, and stores an operating system and other programs.

[0057] In the case of the doctor terminal 30, the auxiliary storage device 33 stores a client certificate for accessing the PDT platform 10 (see FIG. 1) and a client certificate for accessing the PDT server 20 (see FIG. 1). In the case of the patient terminal 40, a client certificate for accessing the PDT server 20 (see FIG. 1) is recorded in the auxiliary storage device 43. In addition, the auxiliary storage device 43 also records patient application data 230C (see FIG. 5). The input interface 34 / 44 uses, for example, USB (=Universal Serial Bus) or Bluetooth (registered trademark) for connection to the input device 35 / 45. The input device 35 / 45 may be, for example, a keyboard, a mouse, or a touch panel.

[0058] The output interfaces 36 / 46 may be, for example, HDMI (=High-Definition Multimedia Interface) (registered trademark) or a LAN interface for connection to the output devices 37 / 47. The output devices 37 / 47 may be, for example, a monitor or a printer. The communication interface 38 / 48 is an interface for communicating with an external terminal via a network, and is compatible with Ethernet (registered trademark), Wi-Fi (registered trademark), mobile communication systems, and other communication standards.

[0059] <Patient data viewing screen output> The output process of the patient data viewing screen in the information processing system 1 (see FIG. 1) will be described below with reference to FIGS. 7 is a diagram illustrating an example of a processing sequence executed by the information processing system 1 (see FIG. 1). The symbol S in FIG. 7 represents a step.

[0060] <Step 101> Patients record measurements and other data from the operation screen of the patient app. Patients are an example of users who change their behavior. Patients record, for example, measurements, reflections, behavioral goals, target values, outpatient records, and medication records. These records are examples of health-related data. 8 is a diagram illustrating an example of an operation screen in the patient application. The operation screen shown in FIG. 8 can be transitioned from the home screen 401. The measurement value input screen 402 is, for example, a screen for inputting blood pressure values. Measurement values ​​can be input manually or through data linkage with a blood pressure monitor. However, data linkage with a blood pressure monitor is limited to cases where the blood pressure monitor can be linked with a patient app.

[0061] The review input screen 403 allows users to record their physical condition level, stress level, sleep duration, weight, activity details, mood, and physical condition. As mentioned above, the activity details include records of button operations corresponding to the category of activity that was successfully performed. The activity details also include text input. The start program screen 404 is the screen used in "Step 1" of the treatment program.

[0062] Fig. 9 is a diagram for explaining the treatment program. The treatment program shown in Fig. 9 is composed of "Step 1," "Step 2," and "Step 3." "Step 1" is a learning stage aimed at acquiring knowledge about diseases. "Step 1" is made up of multiple chapters. The chapters are sequential, and you cannot move on to the next chapter until you have completed studying one chapter. Once you have completed studying all the chapters, you can move on to "Step 2." In "Step 1," the patient is first asked to enter information about their employment status, preferences, etc. Next, the patient's characteristics are analyzed from the entered information.

[0063] Once the analysis results are obtained, knowledge regarding "reducing salt intake," "weight loss," "exercise," "sleep," "stress," "alcohol," "tobacco," "understanding the disease," and "blood pressure measurement" is presented according to the patient's characteristics. In addition, some of the information presented to patients will be adjusted depending on whether or not kidney dysfunction is indicated, their usual exercise habits, alcohol consumption, etc. The recommended duration for "Step 1" is two weeks.

[0064] "Step 2" is the stage where behavioral goals are put into practice. First, in "Step 2," behavioral goals appropriate for the patient are presented from among "reducing salt," "reducing weight," "exercise," "sleep," "stress," "alcohol," and "tobacco." The patient confirms the presented actions and records the results of the actions. Regarding the behavioral goals in this step, the displayed content of each item is partially adjusted based on the information entered by the patient themselves.

[0065] In "Step 2," specific behavioral goals are presented for multiple behavioral categories that represent lifestyle habits that will improve the disease. Examples of behavioral categories include "reducing salt intake," "weight loss," "exercise," "sleep," "stress," and "alcohol." For example, behavioral goals in the "reducing salt intake" category include "avoiding salty snacks such as snacks and rice crackers," "avoiding drinking the broth of udon or ramen noodles," "avoiding convenience stores or eating out for lunch," "avoiding eating two hours before bed," "walking for 20 minutes," and "getting at least six hours of sleep." Once behavioral goals for all behavioral categories have been achieved, the patient can move on to "Step 3." The target duration for "Step 3" is one month.

[0066] "Step 3" is the stage where behavior becomes a habit. The patient sets the blood pressure target themselves. The blood pressure target is an example of an achievement goal. The patient records the progress of achieving the blood pressure target. In "Step 3," behaviors that the patient himself evaluated as being highly effective in "Step 2" are presented as behavioral goals with priority. The patient sets the presented behavior as a behavioral goal and aims to make the behavior a habit.

[0067] Returning to the explanation of Figure 8. The behavioral goal list screen 405 is a screen that can be displayed after "Step 2". A list of behavioral categories is displayed on the behavioral goal list screen 405. The degree of adherence is displayed for each category. The social support screen 406 is a screen that can be displayed after "Step 2". A list of social supports is displayed on the social support screen 406. The social support screen 406 displays treatment know-how that is useful in real life.

[0068] The My Data screen 407 is a screen used to check the progress of steps, measurement values, salt intake status, knowledge, and behavior. The measurement value screen 408 is a screen on which the measurement values ​​recorded up to now are displayed as a trend graph and numerical values. A distribution chart, which will be described later, is also displayed on the measurement value screen 408. The salt intake screen 409 is a screen that can be displayed after "Step 2". On the salt intake screen 409, it is possible to record salt intake, record dietary details, and view the recorded details. The recorded details can be displayed as a trend graph or numerical values. The outpatient record screen 410 is a screen on which the patient can record appointments made with the doctor at the time of the visit, record the next visit date, record the time of day when prescribed medicines will be taken, and view the recorded contents. The medication record input screen 411 is a screen on which medication records can be recorded and the recorded contents can be viewed.

[0069] <Step 102> Returning to the explanation of Figure 7. The patient terminal 40 uploads patient app data at predetermined times. One of the predetermined times is when new data is recorded or updated. This upload is performed when the patient app remains logged in to the PDT server 20. Another predetermined time is when the patient signs in to the PDT server 20. This upload is performed when the patient app logs out of the PDT server 20 and then logs in to the PDT server 20 again.

[0070] <Step 103> The PDT server 20 stores the uploaded patient application data, which constitutes part of the patient data 230 (see FIG. 5). Steps 101 to 103 shown in FIG. 7 are executed in response to a recording operation by a patient to the patient application.

[0071] <Step 104> When a doctor or the like logs in to the PDT platform 10 via the doctor terminal 30, the PDT platform 10 presents a confirmation screen for the usage status of the patient app to the doctor terminal 30. FIG. 10 is a diagram illustrating an example of a management screen 300 for the use status of patient applications displayed on the output device 37 (see FIG. 6) of the doctor terminal 30 (see FIG. 6).

[0072] The management screen 300 shown in FIG. 10 is an example of a management screen that displays, in a list, the usage status of patient apps prescribed to patients by a doctor or the like who operates the doctor terminal 30. The management screen 300 may display only the usage status of patient apps prescribed by the doctor or the like operating the doctor terminal 30, or may display the usage status of patient apps prescribed by the medical institution to which the doctor or the like operating the doctor terminal 30 belongs. In other words, the management screen 300 may include the usage status of patient apps prescribed by other doctors or the like who belong to the same medical institution.

[0073] In addition, the management screen 300 may be configured to display the usage status of patient apps prescribed by other doctors or other medical institutions. This display function is useful, for example, when a patient requests a second opinion. This display can be realized, for example, by a doctor operating the doctor terminal 30 providing information identifying the patient under treatment (for example, a medical record number or a patient name) to the PDT platform 10. Furthermore, technically, it is also possible to include information on all patients managed by the PDT platform 10 on the management screen 300. In that case, however, it is desirable to be able to narrow down or rearrange the patients displayed on the management screen using the ID of the doctor operating the doctor terminal 30, etc.

[0074] The management screen 300 shown in FIG. 10 is composed of an information field 301 , a current date and time 302 , a “Details” button 303 , a “New prescription” button 304 , and a “Close” button 305 . Management information of the patient app prescribed to each patient is displayed in the information field 301. In the case of Fig. 10, the information field 301 is displayed in a table format. Incidentally, information for each patient is displayed in the rows, and management items of the patient app are displayed in the columns. FIG. 10 shows, as management items, examples of medical record number / patient name 301A, application name 301B, usage status 301C, prescription date 301D, and prescription code expiration date 301E.

[0075] The medical record number / patient name 301A displays the medical record number and the patient name, which are examples of information for identifying a patient to whom the patient application has prescribed a medication. The information for identifying a patient may include a user ID, an address, etc. The application name 301B displays the name of the patient application prescribed to the patient. In this embodiment, four applications are displayed: patient application A, patient application B, patient application C, and patient application D. The application name 301B may include version information.

[0076] Note that if multiple patient apps are approved for a patient, the information will be displayed in different rows. In addition to or in addition to the application name 301B, the name of the disease targeted by the patient application may be displayed. The usage status 301C is used to display the usage status of the patient app. In the case of Fig. 10, the usage status 301C displays three options: "Before starting usage," "In use," and "Ended." However, as mentioned above, the usage status 301C also displays "Start deadline expired," "Scheduled to end," "Expired," etc.

[0077] The prescription date 301D displays the date on which the patient app was prescribed by a doctor or the like. The last date on which the prescription code is valid is displayed in prescription code expiration date 301E. In this embodiment, the date three days after prescription date 301D is displayed in prescription code expiration date 301E. The current date and time 302 is the date and time when the patient application usage status management screen 300 is viewed.

[0078] The "Details" button 303 is a button used to display a patient data viewing screen. The "Details" button 303 is arranged on each row corresponding to a patient. When the "Details" button 303 is operated, the patient data viewing screen for the patient corresponding to the "Details" button 303 is displayed. The "New Prescription" button 304 is used when prescribing a patient app to a patient. When the "New Prescription" button 304 is operated, a screen for inputting the app name, patient name, gender, date of birth, etc. is displayed. The name of the prescribing doctor is also registered at the same time. The "close" button 305 is a button for closing the management screen 300 shown in FIG.

[0079] <Step 105> Returning to the explanation of Figure 7. The doctor terminal 30 accepts the selection of a patient on the management screen 300 (see FIG. 10) described above. Specifically, the doctor terminal 30 accepts the operation of the "Details" button 303 (see FIG. 10). For example, the doctor terminal 30 accepts the operation of the "Details" button 303 corresponding to Mr. H, for whom more than five months have passed since the prescription date. The doctor terminal 30 that has accepted the operation of the "Details" button 303 accesses the PDT server 20 of the patient app prescribed to the patient corresponding to the operated "Details" button 303.

[0080] It is assumed that the doctor or the like has already logged in to the PDT server 20 to be accessed via the doctor terminal 30. In this access, the prescription code of the patient app prescribed to the patient corresponding to the operated “Details” button 303 is notified. The doctor terminal 30 may request the PDT platform 10 to issue a one-time token required to access the corresponding PDT server 20. In this case, the doctor terminal 30 accesses the PDT server 20 using the one-time token returned from the PDT platform 10. When this method is adopted, doctors and other personnel can access patient app data of PDT servers 20 to which they are not logged in.

[0081] <Step 106> The PDT server 20, which is accessed by the doctor terminal 30, generates a patient data viewing screen for the selected patient. FIG. 11 is a diagram illustrating an example of a patient data viewing screen 310. The viewing screen 310 shown in FIG. 11 is composed of a “patient information field” 311, a “measurement result display field” 312, a “blood pressure reduction target value field” 313, a “review information display field” 314, an “activity record display field” 315, a “Go to examination date registration screen” button 316, and an “Exit” button 317.

[0082] The "patient information column" 311 shown in FIG. 11 indicates that the medical record number is "13002," the patient name is "Mr. H," the age is "60 years old," and the sex is "male." The average blood pressure measured at home is displayed numerically and graphically in the "measurement result display column" 312 shown in Figure 11. Daily measurement values ​​can be entered on the measurement value input screen 402 (see Figure 8).

[0083] In the case of FIG. 11, the average values ​​for two intervals, "8 weeks to 4 weeks ago" and "4 weeks ago to the day before," are shown. Here, the day before means the day before the current date and time when the viewing screen 310 is opened. Doctors and other medical professionals can check the progress of treatment by viewing the numerical values ​​and other information displayed in the "measurement result display column" 312. A "distribution table" button 312A is arranged in the "measurement result display column" 312 shown in Fig. 11. The processing operations executed when the "distribution table" button 312A is operated and the corresponding screens will be described later.

[0084] 11 indicates that the target value for home systolic blood pressure (maximum blood pressure) is less than 125 mmHg, and the target value for diastolic blood pressure (minimum blood pressure) is less than 75 mmHg. Note that blood pressure targets may differ depending on gender, the presence of other diseases, age, and other factors. 11, a "change" button for the target value is provided in the "blood pressure reduction target value field" 313. Only a doctor or the like can change the target time. Records of mood and physical condition are displayed in the "retrospective information display field" 314 shown in Fig. 11. The retrospective information can be input from the above-mentioned retrospective input screen 403 (see Fig. 8).

[0085] The activity record display field 315 shown in Figure 11 displays activity records such as the number of days the patient app was used, the number of days a reduction in salt intake was recorded, and the number of days a weight loss was recorded. The "Go to consultation date registration screen" button 316 shown in FIG. 11 is a button for opening a consultation date registration screen (not shown). The "Exit" button 317 shown in FIG. 11 is a button for closing the patient data viewing screen 310.

[0086] <Step 107> Returning to the explanation of Figure 7. The doctor terminal 30 accepts the display of a distribution table of measurement values. Specifically, it accepts the operation of the "Distribution Table" button 312A (see FIG. 11). Note that the processing operations from step 107 onwards are executed only when the "Distribution Table" button 312A is operated. The doctor terminal 30 notifies the PDT server 20 of the acceptance of the operation of the "distribution table" button 312A.

[0087] <Step 108> The PDT server 20 reads out the blood pressure reduction target value for the patient. Specifically, the PDT server 20 reads out the blood pressure reduction target value from the target value 230C6 (see FIG. 5). The blood pressure reduction target value is an example of a reference value determined for each user. In other words, the blood pressure reduction target value is an example of a therapeutic target value determined for each user.

[0088] <Step 109> Next, the PDT server 20 sets a plurality of blood pressure intervals for classifying blood pressure values ​​according to blood pressure reduction target values. For example, if the systolic blood pressure (maximum blood pressure) is 125 mmHg, the following three blood pressure zones are set for the systolic blood pressure. The three blood pressure zones are, for example, a first blood pressure zone of 125 mmHg or less, a second blood pressure zone of 126 mmHg to 144 mmHg, and a third blood pressure zone of 145 mmHg or more. In this embodiment, the boundary value between the second and third blood pressure zones is a value obtained by adding 20 mmHg to the blood pressure reduction target value. Therefore, the first, second, and third blood pressure zones are examples of zones set according to reference values ​​determined for each user.

[0089] On the other hand, if the diastolic blood pressure (lowest blood pressure) is 75 mmHg, the following three blood pressure zones are set for the diastolic blood pressure. The three blood pressure zones are, for example, a fourth zone of 75 mmHg or less, a fifth zone of 76 mmHg to 89 mmHg, and a sixth zone of 90 mmHg or more. In this embodiment, the boundary value between the fifth and sixth blood pressure zones is the target blood pressure reduction value plus 15 mmHg. Therefore, the fourth, fifth, and sixth blood pressure zones are examples of zones set according to reference values ​​determined for each user.

[0090] <Step 110> The PDT server 20 classifies the measured values ​​from the start date of recording into one of a number of blood pressure intervals. In this embodiment, the start date of recording is the prescription date. However, even if a patient app is prescribed, it may take several days for the patient app to be activated. Also, the patient may start recording blood pressure values ​​in the patient app several days after activation. In such cases, the date on which blood pressure values ​​are first recorded may be the start date of recording.

[0091] In this embodiment, there are three blood pressure sections for each of the systolic blood pressure and the diastolic blood pressure. That is, the PDT server 20 classifies the measured value of the systolic blood pressure into one of the first to third blood pressure sections. The PDT server 20 also classifies the measured value of the diastolic blood pressure into one of the fourth to sixth blood pressure sections. In this embodiment, the systolic blood pressure measurement value and the diastolic blood pressure measurement value are each the average value for one day. For example, if blood pressure is measured twice in the morning and twice in the evening, the systolic blood pressure measurement value and the diastolic blood pressure measurement value are each the average value of the four measurements.

[0092] It is also possible to distinguish between two morning systolic blood pressure measurements and two evening systolic blood pressure measurements, in which case two measurements per day are classified into one of the categories. When distinguishing between the frequency distribution table of morning measurement values ​​and the frequency distribution table of evening measurement values, the morning measurement values ​​and the evening measurement values ​​are distinguished. In this case, the morning classification results and the evening classification results are distinguished.

[0093] <Step 111> The PDT server 20 counts the frequency of blood pressure values ​​belonging to a plurality of blood pressure intervals for each predetermined period. In this embodiment, the predetermined period is set in a retroactive direction starting from the current day. In this embodiment, the predetermined period is one month. Therefore, for systolic blood pressure, the frequency of the first, second, and third blood pressure sections is tallied for each month. Similarly, for each long-term blood pressure, the frequency of the fourth, fifth, and sixth blood pressure sections is tallied for each month. It is also possible to use 28 days for the specified period.

[0094] <Step 112> The PDT server 20 generates a distribution table screen 320 (see FIG. 12) showing the frequency ratio of each blood pressure interval for each predetermined period. Fig. 12 is a diagram for explaining a display example of the distribution table screen 320. In Fig. 12, parts corresponding to those in Fig. 11 are assigned the same reference numerals. 12 is composed of a patient information field 311, a systolic distribution table 321, a diastolic distribution table 322, and a "Return to previous screen" button 323. The distribution tables 321 and 322 are a form of a frequency distribution table. The distribution tables 321 and 322 are also an example of distribution information.

[0095] In the case of FIG. 12, the common title for the systolic distribution table 321 and the diastolic distribution table 322 is "Changes in Measured Blood Pressure." 12, the vertical axis of each of the systolic distribution table 321 and the diastolic distribution table 322 represents time going back from the present to the past. The vertical axes of the distribution tables 321 and 322 shown in FIG. 12 are divided into six rows.

[0096] The top row is the period "one month ago." Specifically, the top row is the period from the present to one month ago. The second row from the top is the period "2 months ago." Specifically, the second row from the top is the period from one month ago to two months ago. The third row from the top is the period "3 months ago." Specifically, the third row from the top is the period from 2 months ago to 3 months ago.

[0097] The fourth row from the top is the period "four months ago." Specifically, the fourth row from the top is the period from three months ago to four months ago. The fifth row from the top is the period "five months ago." Specifically, the fifth row from the top is the period from four months ago to five months ago. The sixth row from the top is the "six months ago" period. Specifically, the sixth row from the top is the period from five months ago to six months ago. The oldest measurement value included in the "six months ago" period is the measurement value on the start date of recording.

[0098] In the case of Fig. 12, the left end of the horizontal axis of each of systolic distribution table 321 and diastolic distribution table 322 is 0% and the right end is 100%. As a guide, 25%, 50%, and 75% are also displayed on the horizontal axis of distribution tables 321 and 322 shown in Fig. 12. In the case of FIG. 12, in the systolic distribution table 321 and the diastolic distribution table 322, the frequency ratio of the measured values ​​classified into three blood pressure intervals corresponding to each row is represented by the length of the bar graph.

[0099] In the case of Figure 12, the first blood pressure period in the systolic distribution table 321 is "125 or less," the second blood pressure period is "126-144," and the third blood pressure period is "145 or more." In addition, the fourth blood pressure period in the diastolic distribution table 322 is "75 or less," the fifth blood pressure period is "76-89," and the sixth blood pressure period is "90 or more." For example, in the case of the systolic distribution table 321, it can be seen that the first blood pressure zone was 0% six months ago, approximately 5% five months ago, approximately 11% four months ago, approximately 13% three months ago, approximately 12% two months ago, and approximately 30% one month ago. On the other hand, in the case of the diastolic distribution table 322, it can be seen that the fourth blood pressure zone was approximately 13% six months ago, approximately 30% five months ago, approximately 35% four months ago, approximately 38% three months ago, approximately 70% two months ago, and approximately 87% one month ago. In this way, by using the distribution tables 321 and 322, it becomes easy to understand the changes in the distribution of blood pressure values ​​over a long period of time.

[0100] In the actual distribution table screen 320, each blood pressure zone is displayed in a different color. For example, the first and fourth blood pressure zones are displayed in green, the second and fifth blood pressure zones are displayed in orange, and the third and sixth blood pressure zones are displayed in red. The length of the green bar graph represents the distribution percentage of normal measurement values. The length of the orange bar graph represents the distribution percentage of measurement values ​​requiring caution. The length of the red bar graph represents the distribution percentage of measurement values ​​requiring even greater caution. These distribution percentages are an example of distribution information by period.

[0101] Incidentally, consultation dates are not necessarily one month apart from the prescription date. Therefore, the number of days in the oldest period may be less than 30 days. Also, the number of days in a month varies, and it is possible that measurements may be forgotten. In other words, the number of days for which measurements are recorded each month is expected to vary. However, in this embodiment, the distribution ratio of the frequency in three blood pressure intervals is displayed, and therefore the variation in the number of measurement days corresponding to each period is ignored.

[0102] 12, the systolic distribution table 321 and the diastolic distribution table 322 show, in a list format, the changes in the frequency distribution ratio of measured values ​​classified into each blood pressure interval over a six-month period. In other words, the systolic distribution table 321 and the diastolic distribution table 322 show the changes in the frequency distribution of measured values ​​in each blood pressure interval after the start date of recording. In this embodiment, the display of distribution tables 321 and 322 starts six months ago, but the display period of distribution tables 321 and 322 varies depending on the prescription date of the patient app. For example, if the prescription date of the patient app is three months ago, the frequency distribution for three periods is displayed in three rows.

[0103] Incidentally, in the chart shown in the upper part of the "measurement result display column" 312 (see FIG. 11), only the average blood pressure values ​​for two periods can be confirmed, and the frequency distribution for the three blood pressure intervals cannot be seen. In addition, the line graph shown in the lower part of the "Measurement result display column" 312 allows you to check the changes in measured blood pressure on a daily basis from the previous day to five weeks ago, but it also does not show the frequency percentages for the three blood pressure ranges. The "return to previous screen" button 323 is a button for returning to the patient data viewing screen 310 (see FIG. 11).

[0104] <Summary> In this embodiment, a doctor or the like can open a distribution table screen 320 (see FIG. 12) from a patient data viewing screen 310 (see FIG. 11). A distribution table 321 for the systolic period and a distribution table 322 for the diastolic period are displayed on a distribution table screen 320 (see FIG. 12). In distribution tables 321 and 322, blood pressure values ​​recorded through the patient app after the prescription date are classified into one of three blood pressure ranges in monthly increments going back from the most recent consultation date, and the distribution percentage of the three blood pressure ranges for each period is displayed. In other words, distribution tables 321 and 322 display changes in the three distribution percentages of blood pressure values ​​recorded after the prescription date. These distribution tables 321 and 322 can provide doctors and others with new indicators for understanding the progress of treatment effects.

[0105] In this embodiment, the blood pressure intervals in the distribution tables 321 and 322 are set according to the blood pressure reduction target for each patient. For example, for a patient whose blood pressure reduction target is 125 mmHg / 75 mmHg, three blood pressure intervals are set with 125 mmHg and 75 mmHg as the reference values. For example, for a patient whose blood pressure reduction target is 135 mmHg / 85 mmHg, three blood pressure intervals are set with 135 mmHg and 85 mmHg as the reference values. In this way, the blood pressure intervals of the distribution tables 321 and 322 in this embodiment are customized for each patient. This makes it easy to check changes in the distribution of the patient's blood pressure values ​​in relation to the blood pressure reduction target. This effect is an advantage that cannot be obtained when a single blood pressure interval is applied to any patient.

[0106] <Other embodiments> (1) Although the embodiments of the present disclosure have been described above, the technical scope of the present disclosure is not limited to the scope of the above-described embodiments. It is clear from the claims that various modifications or improvements to the above-described embodiments are also included in the technical scope of the present disclosure.

[0107] (2) The processor in the above-described embodiments refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPUs (=Central Processing Units)) as well as dedicated processors (e.g., GPUs (=Graphical Processing Units), ASICs (=Application Specific Integrated Circuits), FPGAs (=Field Programmable Gate Arrays), programmable logic devices, etc.). Furthermore, the operations of the processors in each of the above-described embodiments may be performed by multiple processors working together, rather than by a single processor. The order in which the operations of the processors are performed is not limited to the above-described order, and may be changed individually.

[0108] (3) In the above-described embodiment, the calculation requirements for medical fees under the public medical insurance system are assumed, but information regarding the applicability of medical fees under the private medical insurance system may also be displayed on the work screen of the doctor terminal 30 (see FIG. 1). For example, if the requirements for approval of calculation of medical fees under the private medical insurance system require the use of a specific app or medical treatment that refers to patient data entered through a specific app, the explanation of the above-described embodiment can be applied.

[0109] (4) In the above-described embodiment, the numerical value set in the "blood pressure reduction target value field" 313 (see FIG. 11) on the patient data viewing screen 310 (see FIG. 11) is recorded in the target value 230C6 (see FIG. 5), but the target value set by the patient himself / herself in step 3 of the treatment program may also be recorded in the target value 230C6. In this case, distribution tables 321 and 322 (see FIG. 12) in which three blood pressure ranges are set according to the target value set by the patient himself / herself are displayed on the distribution table screen 320 (see FIG. 12).

[0110] The patient application data 230C (see FIG. 5) may record both the value set in the “blood pressure reduction target value column” 313 and the target value set by the patient himself / herself. In this case, the doctor or the like may be able to select which value to use as the reference value of the distribution tables 321 and 322. Fig. 13 is a diagram for explaining another display example of the distribution table screen 320. In Fig. 13, parts corresponding to those in Fig. 12 are assigned the same reference numerals.

[0111] A reference value selection field 324 has been added to the distribution table screen 320 shown in Fig. 13. The reference value selection field 324 shown in Fig. 13 shows two options: "blood pressure reduction target" and "step 3 target value." "Step 3 target value" refers to the target value set by the patient in step 3 of the treatment program. The number of options may be three or more. For example, options may be provided that allow a doctor or other such person to input an arbitrary value. By changing the reference value, it becomes easier to confirm changes in the distribution ratio that reflect the distribution of blood pressure values ​​near the boundary value.

[0112] (5) In the above-described embodiment, it is assumed that the "blood pressure reduction target value field" 313 (see FIG. 11) on the patient data viewing screen 310 (see FIG. 11) remains the same throughout the treatment period. However, there is a possibility that the blood pressure reduction target may change during treatment. For example, there may be cases where a patient develops another disease during treatment, making it necessary to change the blood pressure reduction target, or where the patient is classified as elderly during treatment, making it necessary to change the blood pressure reduction target. Fig. 14 is a diagram illustrating changes in the distribution ratio per period in the three blood pressure ranges shown in distribution tables 321 and 322 when the blood pressure control target value is changed during treatment. In Fig. 14, parts corresponding to those in Fig. 12 are assigned the same reference numerals.

[0113] Incidentally, the distribution table screen 320A corresponds to a case where the blood pressure reduction target is 125 mmHg / 75 mmHg, and the distribution table screen 320B corresponds to a case where the blood pressure reduction target is 135 mmHg / 85 mmHg. As described above, when the blood pressure reduction target is changed during treatment, multiple blood pressure intervals are reset according to the changed blood pressure reduction target, and the blood pressure values ​​are reclassified into each blood pressure interval, as shown in Fig. 14. Then, the frequency of blood pressure values ​​belonging to the reclassified blood pressure intervals is recounted, and distribution tables 321 and 322 are regenerated. That is, steps 109 to 112 (see Fig. 7) are re-executed.

[0114] In this way, when a doctor or the like changes the blood pressure reduction target, the distribution table screen 320A is changed to the distribution table screen 320B. That is, it becomes possible to check the change in the distribution of past blood pressure values ​​from the perspective of the changed blood pressure reduction target. If the blood pressure reduction target used to generate the distribution table is fixed to the blood pressure reduction target at the start of treatment, consistency with the current effect target will be lost, and the utility value of the distribution tables 321 and 322 will decrease.

[0115] Furthermore, when both the distribution table before the change of the blood pressure target and the distribution table after the change of the blood pressure target are displayed, the target period of the distribution table is divided into two or more periods, which reduces the usefulness of the distribution tables 321 and 322, which allow an overview of changes in the distribution of past blood pressure values ​​from a single reference value. However, different distribution tables may be displayed before and after the change of the blood pressure target. The distribution table screens 320A and 320B shown in FIG. 14 are also display examples when the reference value is changed using the reference value selection field 324 (see FIG. 13).

[0116] (6) In the above embodiment, an example was described in which three blood pressure zones were set using the blood pressure reduction target as the reference value. However, multiple blood pressure zones may also be set using the blood pressure value on the start date of recording, i.e., the initial value, as the reference value. Fig. 15 is a diagram for explaining another display example of the distribution table screen 320C. In Fig. 15, parts corresponding to those in Fig. 12 are assigned the same reference numerals.

[0117] In the distribution table screen 320C shown in FIG. 15, the reference value is set to the weight on the start date of the record. In the distribution table screen 320C shown in Fig. 15, four weight loss zones are set according to the reference values. The first weight zone is "3% weight loss or less," the second weight loss zone is "3% to 5% weight loss," the third weight loss zone is "5% to 7% weight loss," and the fourth weight loss zone is "7% or more weight loss." In Fig. 15, the second weight loss zone is labeled "5% weight loss," the third weight loss zone is labeled "7% weight loss," and the fourth weight loss zone is labeled "10% weight loss."

[0118] The vertical axis of the distribution table screen 320C shown in Figure 15 is the number of days. Therefore, in the case of Figure 15, the maximum value on the vertical axis is 30 days. Note that since there are months with less than 30 days and months with more than 30 days, the maximum number of days in the relevant month is normalized to 30 days and the frequency of each weight loss interval is tallied. Note that since normalization is performed, the maximum value on the vertical axis may be displayed as 100% and the minimum value as 0%.

[0119] In the actual distribution table screen 320C, each weight loss section is displayed in a different color. For example, the first weight loss section is displayed in red. The second weight loss section is displayed in orange. The third weight loss section is displayed in light green. The fourth weight loss section is displayed in dark green. Therefore, the length of the red bar represents the frequency of weights classified into the first weight loss section. Similarly, the length of the orange bar represents the frequency of weights classified into the second weight loss section, the length of the light green bar represents the frequency of weights classified into the third weight loss section, and the length of the dark green bar represents the frequency of weights classified into the fourth weight loss section.

[0120] The left end of the horizontal axis of the distribution table screen 320C shown in Figure 15 is "1 month ago" and the right end is "6 months ago." In the case of Figure 15 as well, the weight measurement values ​​are classified into one of four weight loss zones in monthly increments. In the case of the distribution table screen 320C shown in FIG. 15, in the period six months ago, "less than 3% weight loss" occurred for 30 days, that is, 100%.

[0121] However, the proportion of "5% weight loss" gradually increased from five months ago to four months ago, and three months ago there were several days when the weight was classified as "7% weight loss." Two months ago, no weight measurements were taken that were classified as "less than 3% weight loss," and weight measurements that were classified as "10% weight loss" appeared on several days.

[0122] One month ago, there were 5 days (about 16%) where the weight was classified as "10% weight loss," 10 days (about 33%) where the weight was classified as "7% weight loss," and 15 days (about 50%) where the weight was classified as "5% weight loss." By viewing this distribution table screen 320C, it is possible to confirm the magnitude of weight loss after the prescription date as a percentage change in the four weight loss intervals.

[0123] (7) In the above-described embodiment, the viewing screen for blood pressure values ​​recorded through a patient app prescribed for the treatment of hypertension is assumed, but for other diseases, different target values ​​and initial values ​​(see FIG. 15) are set as reference values. For example, in the case of nicotine addiction, the measured values ​​of the amount of nicotine intake, the number of times a nicotine-containing medium is ingested, the number of times a nicotine-containing medium is ingested, and the CO concentration in the exhaled breath may be classified into multiple intervals according to the reference values ​​set for each patient, and a frequency distribution table of the frequencies classified into each interval may be displayed.

[0124] In the case of alcoholism, for example, the measured amount of alcohol intake can be classified into multiple intervals according to the reference values ​​set for each patient, and a frequency distribution table showing the frequency of each interval can be displayed. In the case of NASH or obesity, for example, the measured weight may be classified into multiple intervals according to the reference values ​​set for each patient, and a frequency distribution table showing the frequency of classification into each interval may be displayed.

[0125] In the case of insomnia, for example, records of the amount of sleeping pills taken and the total score of the Pittsburgh Sleep Quality Index (PSQI), which consists of 24 items, can be classified into multiple intervals according to the standard values ​​set for each patient, and a frequency distribution table of the frequency of classification into each interval can be displayed. Other diseases contemplated include, for example, kidney disease, cancer, chronic heart failure, attention deficit hyperactivity disorder, depression, tinnitus, delayed grief disorder, opioid-induced constipation, post-mastectomy pain syndrome, bronchial asthma, and nephrotic syndrome.

[0126] (8) In the above-described embodiment, a distribution table with the same measurement items for one disease is displayed, but multiple distribution tables with different measurement items for one disease may be displayed. For example, a distribution table for blood pressure and a distribution table for weight may be displayed simultaneously or selectively.

[0127] (9) In the above-described embodiment, it is assumed that all measurement values ​​after the start date of recording are recorded through the patient app, i.e., measurement values ​​are recorded by a program located in the medical device. However, in addition to the measurement values ​​recorded through a program located in a medical device, the measurement values ​​may also include measurement values ​​recorded through a program located in a non-medical device, which is a program whose main purpose is to record measurement values ​​such as blood pressure.

[0128] Incidentally, a measurement value recorded through a program located in a medical device is an example of a first measurement value, and a measurement value recorded through a program located in a non-medical device is an example of a second measurement value. In the following, programs that are classified as non-medical devices will be referred to as "non-patient apps." FIG. 16 is a diagram illustrating an embodiment in which measurement values ​​recorded through a non-patient app and measurement values ​​recorded through a patient app are used in combination.

[0129] The horizontal axis in Figure 16 is the time axis. The right end of the time axis is the consultation date, and the left end is the past tense. Figure 16 shows up to 7 months ago. In the case of FIG. 16, the prescription date for the patient app is between three months and four months ago. Before being prescribed the patient app, the patient (i.e., the user) records measurement values ​​via the non-patient app. Note that the measurement values ​​may be recorded only on the patient terminal 40, only on the management server 50, or on both the patient terminal 40 and the management server 50. The management server 50 is, for example, a server operated by a business operator that provides the non-patient app.

[0130] Non-patient apps in this context are sometimes called healthcare apps. Healthcare apps are programs whose primary purpose is to record health information and are not medical devices. In the case of Fig. 16, the measurement values ​​recorded through the non-patient app before the patient app is prescribed are imported from the patient terminal 40 or the management server 50 to the PDT server 20. Of course, when importing, the identity of the user is confirmed using a user account or the like.

[0131] Therefore, on the day of the consultation, not only are the measurement values ​​for about four months after the patient app is prescribed, but also the measurement values ​​for about three months before the patient app is prescribed are stored in the PDT server 20. In other words, the PDT server 20 stores the patient's measurement values ​​for about seven months. In this case, for each period from the consultation date up to three months prior, the measurement values ​​recorded through the patient app (i.e., the first measurement values) are classified into one of several intervals, and the frequency distribution rate for each interval is calculated.

[0132] For the period four months prior to the consultation date, both the measurements recorded through the patient app (i.e., the first measurement) and the measurements recorded through the non-patient app (i.e., the second measurement) are classified into one of several intervals, and the frequency distribution percentage for each interval is calculated. For each period of at least five months prior to the consultation date, the measurements recorded through the non-patient app (i.e., the second measurements) are classified into one of several intervals, and the frequency distribution percentage for each interval is calculated.

[0133] Then, the PDT server 20 displays a distribution table in which these distribution ratios are arranged on the time axis on the doctor terminal 30 (see FIG. 1). In the case of the embodiment described using Figures 1 to 12, the distribution table displayed on the doctor terminal 30 covers a maximum of four months from the prescription date. Also, the distribution ratio for each interval four months prior is normalized by the frequency. Of course, even with this display format, it is possible to check the change in the distribution ratio of the measurement value. However, in the embodiment described with reference to Fig. 16, it is also possible to check the distribution ratio of the measurement values ​​before starting treatment using the patient app. As a result, it becomes possible to diagnose the progress of the patient's treatment from a longer-term perspective.

[0134] (10) In the above-described embodiment, it is assumed that the examination date falls within the insured medical treatment period. However, a distribution table may also be generated without distinguishing between measurements recorded through a program that is classified as a non-medical device even after the insured medical treatment period. FIG. 17 is a diagram illustrating another embodiment in which measurement values ​​recorded through a non-patient app and measurement values ​​recorded through a patient app are used in combination.

[0135] The horizontal axis in Figure 17 is the time axis. The right end of the time axis is the consultation date, and the left end is the past tense. Figure 17 shows up to 7 months ago. In the case of Figure 17, the prescription date in the patient app is 7 months ago, and the insured medical treatment period expired within the period 2 months before the consultation date. In the case of Figure 17, after the expiration of the insured medical treatment period, a medical treatment period not covered by insurance (i.e., outside the health insurance medical treatment period) begins.

[0136] 17, it is assumed that a patient app continues to be used after the validity period has expired to record measurement values ​​outside of the health insurance medical treatment period. In other words, it is assumed that a patient app continues to be used as a non-patient app after the validity period has expired. For this reason, not only measurement values ​​during the health insurance medical treatment period but also measurement values ​​outside of the health insurance medical treatment period are recorded in the PDT server 20.

[0137] However, measurement values ​​may be recorded on the patient terminal 40 (see FIG. 16) or management server 50 (see FIG. 16) using a non-patient app that is different from the patient app used during the insured medical treatment period. If the measurement values ​​recorded through the non-patient app are not stored in the PDT server 20, the measurement values ​​are imported from the patient terminal 40 or management server 50 to the PDT server 20, and then the distribution table generation process described above is started.

[0138] In the case of Figure 17, for each period three months or more prior to the consultation date, the measurement values ​​recorded through the patient app (i.e., the first measurement values) are classified into one of several intervals. Then, the frequency distribution rate for each interval is calculated. Additionally, for the period two months prior to the consultation date, both the measurements recorded through the patient app (i.e., the first measurements) and the measurements recorded through, for example, the non-patient app (i.e., the second measurements) are classified into one of several intervals, and the frequency distribution rate for each interval is calculated.

[0139] For the period one month prior to the consultation date, the measurements recorded through the non-patient app (i.e., the second measurements) are classified into one of several intervals, and the frequency distribution percentage for each interval is calculated. Then, the PDT server 20 displays a distribution table in which these distribution ratios are arranged on the time axis on the doctor terminal 30 (see FIG. 1). In the embodiment described with reference to Figure 17, it is possible to check changes in the distribution ratio of measurement values, including those measured during treatment by the patient app, even after the expiration of the insured medical treatment period. As a result, it becomes possible to diagnose the progress of a patient's treatment from a longer-term perspective.

[0140] (11) In the above embodiment, the distribution table of measurement values ​​is generated by the PDT server 20 (see FIG. 1), but it may also be generated by the doctor terminal 30 (see FIG. 1). Fig. 18 is a diagram illustrating another example of a processing sequence executed by the information processing system 1 (see Fig. 1). In Fig. 18, parts corresponding to those in Fig. 7 are assigned the same reference numerals. In the case of FIG. 18, the processing contents up to step 107 are the same as those in FIG.

[0141] One difference is that in step 121, the PDT server 20, having received a notification from the doctor terminal 30 in step 107 that it has received a request to display a distribution table of measured values, notifies the doctor terminal 30 of the blood pressure reduction target values ​​and measured values ​​of the selected patient. Note that in Fig. 18, only the data necessary for generating the distribution table is notified to the doctor terminal 30, but it is also possible to notify the doctor terminal 30 of all the patient data of the patient being treated.

[0142] Another difference is that the processes of steps 108 to 112 are executed on the side of the doctor terminal 30. After executing step 112, the doctor terminal 30 also executes a process of displaying the generated distribution table on the display. In the embodiment described with reference to FIG. 18, the processing load on the PDT server 20 can be reduced.

[0143] (12) In the above-described embodiment, the PDT server 20 (see FIG. 1) starts the process of generating a distribution table of measurement values ​​based on a notification that the doctor terminal 30 (see FIG. 1) has accepted the display of the distribution table. However, the process of generating the distribution table may be started as a function of the PDT server 20 alone or in response to an instruction from the patient terminal 40 (see FIG. 1). Fig. 19 is a diagram illustrating another example of a processing sequence executed by the information processing system 1 (see Fig. 1). In Fig. 19, parts corresponding to those in Fig. 7 are assigned the same reference numerals.

[0144] One difference is that the timing of providing a distribution table or receiving an instruction to display the distribution table from the patient terminal 40 (step 131) by the PDT server 20 triggers the start of the processing operations from step 108 onwards. The timing of providing the distribution table here is assumed to be, for example, the timing of notifying a regular report. The notification timing is assumed to be, for example, once every four weeks. Another difference is that the PDT server 20, which has executed steps 108 to 112, executes step 132 of providing the generated distribution table to the patient terminal 40. In the embodiment described with reference to Fig. 19, the distribution table is output to the patient terminal 40. As a result, it is possible to assist the patient in checking changes in the distribution of their own measurement values.

[0145] (13) In the above-described embodiment, the PDT server 20 (see Figure 1) starts the process of generating a distribution table of measurement values ​​based on a notification that the doctor terminal 30 (see Figure 1) has accepted the display of the distribution table. However, the process of generating the distribution table may also be executed as a function of the patient app. Fig. 20 is a diagram illustrating another example of a processing sequence executed by the information processing system 1 (see Fig. 1). In Fig. 20, parts corresponding to those in Fig. 7 are assigned the same reference numerals.

[0146] One difference is that the timing of providing a distribution table or the reception of an instruction to display a distribution table by the patient terminal 40 (specifically, the patient application) (step 141) serves as a trigger to start the processing operations from step 108 onwards. The timing of providing the distribution table here is also assumed to be, for example, the timing of notification of a regular report. Another difference is that the patient terminal 40 that has executed steps 108 to 112 executes step 142 of displaying the generated distribution table. In the embodiment described with reference to Fig. 20, the distribution table can be displayed as a standalone function of the patient app that runs on the patient terminal 40. As a result, it is possible to assist the patient in checking changes in the distribution of their own measurement values.

[0147] (14) In the above-described embodiment, the patient app is assumed to be a program located in a medical device, but it may be a program located in a non-medical device. In other words, it may be assumed that all measurement values ​​are recorded through a program located in a non-medical device. In this case, as described above, the server that manages the measurement values ​​may generate the distribution table, or the patient terminal 40 may generate the distribution table.

[0148] (15) In the above embodiment, the case where blood pressure values ​​as measurement values ​​are classified into three blood pressure zones has been described, but the number of classified zones is not limited to three. For example, it may be two, or four or more. The display example shown in FIG. 15 above is an example of four zones. Of course, it may be five or more zones. The number of sections into which the data are classified may vary depending on the type of disease and the magnitude of the change in the measured values.

[0149] For example, if the number of intervals is too small compared to the amount of change in the measured values, it becomes difficult to grasp the change in the distribution of the measured values. Therefore, a reference value for increasing the number of intervals can be set, and the number of intervals can be increased if the maximum amount of change in the measured values ​​within a period exceeds this reference value. On the other hand, if the number of intervals is too large compared to the amount of change in the measured values, it becomes difficult to grasp the change in the distribution of the measured values. Therefore, a reference value for reducing the number of intervals can be set, and the number of intervals can be reduced if the maximum amount of change in the measured values ​​within a period exceeds this reference value.

[0150] (16) In the above-described embodiment, the distribution table is generated using measurement values ​​after the prescription date of the patient app or the start date of recording measurement values ​​by the non-patient app. However, the doctor, patient, etc. may be able to specify any date as the start date of the recording used to generate the distribution table. For example, it may be possible to specify six months or 12 months from the present. In other words, the distribution table may be generated for a range specified by the doctor, patient, etc. after the start date of the recording. By allowing this type of specification, it is possible to avoid a decrease in visibility due to an excessive increase in the number of periods that make up the distribution table.

[0151] However, if the target period is longer than the reference value, the unit of the specified period may be changed from one month to two months, etc., to suppress the increase in the number of periods displayed. In this case, for measurements taken more than six months ago, the frequency of each interval may be tallied in two-month increments, but for measurements taken within six months, the frequency of each interval may be tallied in one-month increments. In other words, the unit length of the specified period may be changed based on the results of comparing the number of days going back in time from the present with the reference value.

[0152] (17) In the above-described embodiment, a distribution table is generated that shows the distribution of measurement values ​​in units of a period going back in time, starting from the day when the instruction to display the distribution table was received. However, the starting date of the distribution table may be arbitrarily specified by a doctor, patient, etc. For example, the starting date may be set to the previous day or one week ago. For example, if it is clear that measurement values ​​are missing due to travel or other reasons just before a medical examination, a distribution table may be generated that avoids those periods.

[0153] (18) In the above-described embodiment, a patient app for hypertension is exemplified as a patient app used to record measurement values ​​at home, but as mentioned above, the above-described technology can also be applied to patient apps developed for various diseases. Of course, the content of the measurement values ​​shown in the distribution table will change depending on the disease. 21 is a diagram for explaining a display example of a distribution table screen 320D when the disease is diabetes. In Fig. 21, parts corresponding to those in Fig. 12 are assigned the same reference numerals. A distribution table 325 of fasting blood glucose and a distribution table 326 of blood glucose two hours after a meal are arranged on the distribution table screen 320D shown in FIG.

[0154] The vertical axes of the two distribution tables shown in Fig. 21 also represent time going back from the present to the past. Similarly, the horizontal axes of the two distribution tables shown in Fig. 21 have 0% at the left end and 100% at the right end. The blood glucose level intervals in the fasting blood glucose distribution table 325 shown in FIG. 21 are divided into three ranges: "110 or less," "111-125 or less," and "126 or more." On the other hand, the blood glucose level ranges in the distribution table 326 of blood glucose levels two hours after a meal shown in FIG. 21 are divided into three ranges: "140 or less," "141-199 or less," and "200 or more."

[0155] The two distribution tables shown in Figure 21 also display each interval in a different color. For example, the intervals "110 or less" and "140 or less" are displayed in blue, "111-125 or less" and "141-199 or less" are displayed in yellow, and "126 or more" and "200 or more" are displayed in red. In the case of the distribution table screen 320D shown in FIG. 21, it can also be seen that the rate of normal values ​​increases as the current date and time approaches compared to the time at the start of treatment.

[0156] <Summary> The disclosed examples described in the above-mentioned embodiments are shown below. (((1))) An information processing device having one or more processors, which reads measurement values ​​recorded in the past through a program executed on a terminal operated by a user who changes his or her behavior, classifies the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user, generates distribution information of the measurement values ​​corresponding to the plurality of intervals in units of a predetermined period, and presents a list of the distribution information in units of a predetermined period from the start date of recording. This information processing device can provide a mechanism that enables a user who changes his or her behavior to check changes in the distribution of measured values ​​after the start date of recording through a program executed on a terminal operated by the user.

[0157] (((2))) The information processing device according to (((1))), wherein the one or more processors set a therapeutic target value determined for each user as the reference value. This information processing device makes it possible to check changes in the distribution of measurement values ​​in relation to therapeutic target values ​​determined for each user.

[0158] (((3))) The information processing device described in (((2))), wherein when one or more processors receive a change in a therapeutic target value, they reset multiple intervals and regenerate distribution information of measurement values ​​corresponding to the reset multiple intervals in predetermined period units. According to this information processing device, even when a therapeutic target value is changed, it is possible to check the change in the distribution of the measured values ​​in relation to the changed target value.

[0159] (((4))) The information processing device according to (((1))), wherein the one or more processors set the measurement value on the start date of recording as the reference value. According to this information processing device, it is possible to present changes in the distribution of measurement values ​​in relation to the measurement values ​​on the start date of recording.

[0160] (((5))) The information processing device described in (((1))), wherein one or more processors classify a first measurement value recorded through a program requiring a prescription and a second measurement value recorded through another program not requiring a prescription into one of a plurality of intervals when the first measurement value and the second measurement value are included in a predetermined period. According to this information processing device, it is possible to effectively utilize both measurement values ​​recorded by a program that requires a prescription and measurement values ​​recorded by a program that does not require a prescription.

[0161] (((6))) The information processing device according to (((1))), wherein the program is a program requiring a prescription. This information processing device makes it possible to check changes in the distribution of measurement values ​​recorded by a program requiring a prescription since the start date of recording.

[0162] (((7))) The information processing device according to (((1))), wherein the program is a program that does not require a prescription. This information processing device makes it possible to check changes in the distribution of measurement values ​​recorded using a program that does not require a prescription, since the start date of recording.

[0163] (((8))) An information provision method in which a computer performs the following processes: reading out measurement values ​​recorded in the past through a program executed on a terminal operated by a user whose behavior is changing; classifying the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user; generating distribution information of the measurement values ​​corresponding to the plurality of intervals in units of a specified period; and presenting a list of distribution information in units of a specified period from the start date of recording. This information providing method can provide a mechanism that enables a user who changes his / her behavior to check changes in the distribution of measured values ​​after the start date of recording through a program executed on a terminal operated by the user.

[0164] (((9))) A program for enabling a computer to perform the following functions: read out measurement values ​​recorded in the past through a program executed on a terminal operated by a user who changes their behavior; classify the measurement values ​​into one of multiple intervals set according to a reference value determined for each user; generate distribution information of the measurement values ​​corresponding to the multiple intervals in specified time periods; and present a list of distribution information in specified time periods from the start date of recording. This program can provide a mechanism that enables a user who changes his or her behavior to check changes in the distribution of measured values ​​after the start date of recording through a program executed on a terminal operated by the user. [Explanation of symbols]

[0165] 10...PDT platform, 20, 20A, 20B, 20C, 20D, 20E, 20F...PDT server, 30...doctor's terminal, 40...patient's terminal, 50...management server

Claims

1. having one or more processors, the one or more processors: The program runs on the device operated by the user who is changing their behavior, and the recorded measurements are read back in time. classifying the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user; generating distribution information of the measurement values ​​corresponding to the plurality of sections in units of a predetermined period; presenting a list of the distribution information for the predetermined period from the start date of recording onward; Information processing device.

2. the one or more processors: a therapeutic target value determined for each user is set as the reference value; The information processing device according to claim 1 .

3. the one or more processors: When a change in the therapeutic target value is received, the plurality of intervals are reset, and distribution information of the measurement values ​​corresponding to the plurality of intervals after the reset is regenerated in units of the predetermined period. The information processing device according to claim 2 .

4. the one or more processors: The measurement value on the start date of recording is set as the reference value. The information processing device according to claim 1 .

5. the one or more processors: If a first measurement value recorded through a program requiring a prescription and a second measurement value recorded through another program not requiring a prescription are included in the predetermined period, the first measurement value and the second measurement value are classified into the plurality of intervals. The information processing device according to claim 1 .

6. The program is a prescription-based program. The information processing device according to claim 1 .

7. The program is a non-prescription program. The information processing device according to claim 1 .

8. The computer A process of retroactively reading out the measurements recorded through a program executed on a terminal operated by a user who changes his / her behavior; A process of classifying the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user; generating distribution information of the measurement values ​​corresponding to the plurality of sections in units of a predetermined period; a process of presenting a list of the distribution information for the predetermined period from the start date of recording onward; Information provision method to carry out.

9. On the computer, The ability to retroactively retrieve measurements recorded through a program run on a device operated by a behavior-changing user; a function of classifying the measurement values ​​into one of a plurality of intervals set according to a reference value determined for each user; a function of generating distribution information of the measurement values ​​corresponding to the plurality of sections in units of a predetermined period; a function of presenting a list of the distribution information for the predetermined period from the start date of recording onward; A program to achieve this.

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