WO2019035166A1 - Treatment supporting device and program for supporting treatment - Google Patents

Abstract

The present invention is provided with: a disease severity acquisition unit 25 which acquires data about the disease severity obtained by a user using a system related to an information processing technology for treatment of the disease; a use history acquisition unit 26 which acquires data for indicating a system use history by the user; a treatment continuation probability estimation unit 27 which estimates a treatment continuation probability of the user on the basis of data related to the acquired disease severity and the data for indicating the system use history; and a message notification unit 28 which provides a notification of a message that motivates the user to continue the use of the system, when the estimated treatment continuation probability satisfies a prescribed condition, wherein, before the user actually stops usage of the system, the user is provided with a message that motivates the user to use the system continuously, and is restricted from withdrawing in the middle of treatment.

Description

Treatment support apparatus and program for treatment support

The present invention relates to a treatment support apparatus and a treatment support program, and in particular, a treatment support apparatus and treatment for supporting treatment of a disease based on data obtained by a user sequentially using a system related to information processing technology. It is suitable for use in support programs.

There are many people suffering from insomnia at present. If insomnia continues, it can not sleep well and causes daytime sleepiness, alertness, fatigue, and various physical problems. Usually, cognitive behavioral therapy or drug therapy by a clinical psychologist is used to treat insomnia. Cognitive-behavioral therapy is a method of treating insomnia by acting on the cognition and behavior of the patient. In the long term, it is said to be more effective than drug therapy, but the current situation is that the spread has not progressed due to lack of clinical psychologists.

On the other hand, conventionally, a system for managing the sleep of the user has been devised from the viewpoint of improving the quality of the sleep of the user (for example, see Patent Document 1). The system described in Patent Document 1 monitors one or more objective parameters related to the sleep quality of the user who is in bed, and measures cognitive or psychomotor performance while the user is awake. The objective test data feedback is presented to the user via a portable device such as a mobile phone.

In this patent document 1, as an example of a cognitive test or a psychomotor test, a method of measuring a response time (drowsiness and mood disorder accumulated when sleeping for 1 week lasting for 4 weeks is continued for 1 week And methods of measuring loss of psychomotor performance due to insomnia). In the system described in Patent Document 1, information (warning, guide, advice, message encouraging the user to influence the user's behavior to improve the quality of sleep later, based on the result of the cognitive test etc. Etc.) to the user.

According to the system described in Patent Document 1, information such as a warning, a guide, advice, and a message encouraging the user is presented based on the result of the test such as the measurement of the reaction time of the user. By acting, it is said that the quality of sleep will be improved.

In addition, if a user takes action once according to the presented information according to the result of one test, insomnia will not necessarily be eliminated immediately. Therefore, it is necessary to conduct tests continuously and to take action to improve insomnia continuously.

There are also methods using sleep logs or sleep diaries as a diagnostic method to assess the quality of sleep. However, this diagnostic method has the disadvantage that its accuracy is influenced by the patient's subjective bias. For example, it is often difficult for the patient to remember the nightly sleep and wake periods correctly. In order to solve such problems, there is known a system in which an automatic sleep log is recorded using body vital signs as objective data for evaluating night sleep and wake periods ( See, for example, Patent Document 2).

The system described in this patent can also be used for sleep restriction therapy, which is a non-pharmacologic method for treating insomnia. That is, if the sleep pattern of the patient can be analyzed from the sleep log data, then appropriate treatment can be achieved. Here, continuous recording of the sleep log is essential in order to obtain a correct evaluation result about the quality of sleep and apply it to the sleep restriction therapy.

JP 2011-36649 A JP 2011-517982

However, in order to continuously perform cognitive tests, psychomotor tests, sleep log recording, etc., a certain load is imposed on the user. Therefore, there are patients who can not continue the treatment and withdraw from the treatment halfway. In addition, although cognitive tests, psychomotor tests, and sleep log recording etc. have the convenience of using information processing technology, they are based on treatment because they are dissatisfied with the operability of the system or because they do not know how to use them. There is also a possibility of leaving.

The present invention was made to solve such problems, and it is in the middle of treatment in the treatment of a disease that is performed based on data obtained by a user using a system related to information processing technology one by one. The purpose is to make it possible to minimize the user's withdrawal.

In order to solve the problems described above, the present invention acquires data on disease severity obtained by the user using a system relating to information processing technology to treat a disease, and also uses the system usage history by the user. Data to be represented is acquired, and the treatment continuation probability of the user is estimated based on the acquired data on the disease severity and the data on the system use history. Then, when the estimated treatment continuation probability satisfies a predetermined condition, the user is notified of a message that motivates the user to continue using the system.

According to the present invention configured as described above, when a user uses the system for treatment of a disease, based on data relating to the disease severity obtained through its actual use and data representing the history of use of the system A treatment continuation probability is estimated that indicates the likelihood that the user will continue treatment using the system. Then, if the treatment continuation probability satisfies a predetermined condition, a message is provided to motivate the user to continue using the system. This will provide the user with a message that motivates continued use of the system before the user actually ceases using the system, and may be able to minimize the user's withdrawal during treatment become.

BRIEF DESCRIPTION OF THE DRAWINGS It is a figure which shows the example of whole structure of the insomnia treatment system which mounted the treatment assistance apparatus by this embodiment. It is a block diagram showing an example of functional composition of a server apparatus by this embodiment. It is a figure for demonstrating the conditions which the message alerting | reporting part of this embodiment alert | reports a message. It is a flowchart which shows the operation example of the treatment assistance apparatus by this embodiment.

Hereinafter, an embodiment of the present invention will be described based on the drawings. FIG. 1 is a diagram showing an example of the overall configuration of an insomnia treatment system in which a treatment support apparatus according to the present embodiment is implemented. The insomnia treatment system shown in FIG. 1 is configured to include a portable terminal 100 used by a patient with insomnia (hereinafter referred to as a user), a server device 200, and an external measurement device 300. The mobile terminal 100 and the server device 200 are connected via a communication network 400 such as the Internet or a mobile telephone network.

The insomnia treatment system shown in FIG. 1 corresponds to the “system related to information processing technology” in the claims. The user receives treatment for insomnia by cognitive behavioral therapy by sequentially using this insomnia treatment system.

Specifically, the user uses the insomnia treatment application installed on the mobile terminal 100 to sequentially execute various information processing necessary for the treatment. For example, the user inputs an answer to the inquiry provided from the server device 200 to the insomnia treatment application of the mobile terminal 100. Questionnaire responses are optional. In addition, the user measures biological information such as blood pressure, pulse, and temperature in the external measurement device 300, and inputs the measurement result to the insomnia treatment application. The contents of these answers and the biological information are information that can be used as one of the indicators indicating how much the insomnia has been improved.

In addition, the input method to the insomnia treatment application of the biological information measured by the external measurement apparatus 300 is arbitrary. For example, the portable terminal 100 and the external measuring device 300 are connected by wired or wireless communication means, and the biological information measured by the external measuring device 300 is transmitted to the portable terminal 100, whereby the biological information is insomnia. It is possible to input to the treatment app. Alternatively, a predetermined input screen may be displayed in the insomnia treatment application, and the user may manually input the value of the biological information measured by the external measurement device 300 from the input screen.

Also, the user executes a predetermined measurement test according to the function of the insomnia treatment app. For example, a drowsiness test is performed as a predetermined measurement test. In the sleepiness test, a predetermined sign is repeatedly displayed on the screen of the portable terminal 100, and in each case, an elapsed time until the user taps the sign on the screen and a tap position are detected, and the elapsed time (speed of response) The degree of sleepiness (or the awakening degree) is determined based on the false tap rate. By performing this drowsiness test at the time of getting up, it is possible to use the resulting data as one of the indicators showing how much the insomnia has been improved. In addition, the drowsiness test mentioned here is an example of a measurement test, and is not limited to this.

The insomnia treatment application transmits, to the server apparatus 200, the execution result of the information processing by the user (the answer to the inquiry, the execution result of the drowsiness test, etc.) and the measurement result of the biological information input from the external measurement device 300 Prompting the user for action that is effective for treatment by receiving and displaying notifications regarding various advices from 200. The user treats insomnia by acting in accordance with the contents of this advice.

The treatment support apparatus of this embodiment is mounted in the server apparatus 200. The treatment support device is a device for cognitive behavior therapy performed based on data obtained by the user sequentially using the insomnia treatment application (various data transmitted from the portable terminal 100 to the server device 200 as described above). It is for supporting the treatment. The support for the treatment of cognitive behavior therapy here is not to notify the above-described various advices to the mobile terminal 100, but to support the user to continue using the insomnia treatment application. . This is because the treatment of insomnia by cognitive behavioral therapy is effective only when the user continuously uses the insomnia treatment app.

FIG. 2 is a block diagram showing an example of the functional configuration of the server apparatus 200. As shown in FIG. The block diagram shown in FIG. 2 includes both functional blocks for performing treatment of cognitive behavior therapy and functional blocks of the treatment support apparatus according to the present embodiment.

As shown in FIG. 2, the server apparatus 200 has a data acquisition unit 21, a data recording unit 22, a data processing unit 23, a data provision unit 24, a disease severity acquisition unit 25, a usage history acquisition unit 26 as its functional configuration. A treatment continuation probability estimation unit 27 and a message notification unit 28 are provided. The server device 200 also includes a storage unit 20 as a storage medium.

Each of the functional blocks 21 to 28 can be configured by any of hardware, DSP (Digital Signal Processor), and software. For example, when configured by software, each of the functional blocks 21 to 28 actually comprises a CPU, a RAM, a ROM and the like of a computer, and a program stored in a recording medium such as a RAM, a ROM, a hard disk or a semiconductor memory Is realized by operating.

Among the functional blocks 21 to 28, the data acquiring unit 21, the data recording unit 22, the data processing unit 23, and the data providing unit 24 are functional blocks for treating the cognitive behavioral therapy. The disease severity acquisition unit 25, the usage history acquisition unit 26, the treatment continuation probability estimation unit 27, and the message notification unit 28 are functional blocks of the treatment support apparatus according to the present embodiment. Thus, the disease severity acquisition unit 25, the usage history acquisition unit 26, the treatment continuation probability estimation unit 27, and the message notification unit 28 are implemented as a part of the insomnia treatment system function.

The data acquisition unit 21 acquires various data obtained by the user sequentially using the insomnia treatment application from the portable terminal 100. Specifically, the data acquisition unit 21 includes data on a response to a medical inquiry provided from the server device 200 to the insomnia treatment application of the portable terminal 100, data on an execution result of a sleepiness test provided through the insomnia treatment application, and The measurement data of the biological information input from the external measurement device 300 to the insomnia treatment application is acquired.

In addition, user ID which identifies the user who is using the insomnia treatment application is added to the data which the data acquisition part 21 acquires. This user ID is set, for example, when installing the insomnia treatment application on the portable terminal 100.

The data recording unit 22 divides the data acquired by the data acquisition unit 21 for each user ID together with date and time information and records the data in the storage unit 20. Each time the data acquisition unit 21 acquires data from the portable terminal 100, the data recording unit 22 sequentially records the data together with date and time information in the storage unit 20 for each user ID. Thereby, in the storage unit 20, various data obtained by sequentially using the insomnia treatment application are accumulated for each user who is using the insomnia treatment application.

The data processing unit 23 executes predetermined data processing using the data stored in the storage unit 20 to analyze the degree of improvement of the user's insomnia and to provide information on advice effective for the improvement of the insomnia. Generate For example, based on the data stored in the storage unit 20, the data processing unit 23 analyzes what is preventing sleep and generates advice information on a countermeasure for eliminating it.

For example, the data processing unit 23 generates advice information that recommends that a user who is anxious to feel uneasy to go to bed when he or she enters the bed has a delay in entering the bed. A user who is anxious about not being able to sleep is likely to try to enter the bed at an early time even though he is not so sleepy, because of the anxiety that he or she can not sleep immediately. The opposite effect is that the time from bedtime to sleep time (time to stay in sleep state) becomes longer and sleep efficiency decreases. On the other hand, by forcibly delaying the bedtime, it is possible to give the user a sense of security that the user does not have to enter the bed early. In addition, it is expected that the time from bedtime to the sleeping time will be shortened because the patient will get sleepy before entering the bed.

In addition, the data processing unit 23 generates message information for prompting the user who has analyzed that the work is stressed to review the amount of work per day. In addition, the data processing unit 23 advises that it is recommended to refrain from actions that are likely to lead to sleep disorders, such as alcohol drinking just before going to bed and operations on a smartphone, and advice information that recommends creating a check sheet and looking back on actions before going to bed Generate various kinds of advice information effective for treating insomnia by cognitive behavioral therapy.

The processing content of the data processing unit 23 described here is merely an example. The data processing unit 23 is not a functional configuration of the treatment support apparatus according to the present embodiment, and is not the main object of the present invention, and thus the detailed description thereof will be omitted.

The data providing unit 24 provides the advice information generated by the data processing unit 23 to the insomnia treatment application of the mobile terminal 100. The user causes the insomnia treatment application to display the advice information provided by the data providing unit 24, and treats the insomnia by acting in accordance with the contents of the advice.

The disease severity acquisition unit 25 acquires, from the storage unit 20, data on the disease severity obtained by the user using the insomnia treatment system (insomnia treatment application). The data to be acquired is history data stored in the storage unit 20 for a past fixed period.

Here, the disease severity acquisition unit 25 receives data on subjective disease severity obtained by the user inputting an answer to the inquiry provided from the server device 200 to the insomnia treatment application (one for each inquiry Answer) and data on objective disease severity obtained through the execution of predetermined measurements for the user. Data on objective disease severity includes the first measurement data (reaction time and false tap rate) obtained by the user performing a measurement test (eg, a sleepiness test) provided by the insomnia treatment app; And second measurement data (blood pressure, pulse, body temperature) measured by the external measurement device 300.

The use history acquisition unit 26 acquires, from the storage unit 20, data representing the use history of the insomnia treatment system (insomnia treatment application) by the user. As described above, each time various data obtained by the user using the insomnia treatment application are transmitted from the portable terminal 100 to the server device 200, they are sequentially recorded in the storage unit 20 together with date and time information. Therefore, it can be said that this date and time information is data representing the use history of the insomnia treatment application. Therefore, the usage history acquisition unit 26 acquires date and time information from the storage unit 20 as data representing the usage history of the insomnia treatment application by the user. Also regarding data representing the usage history, what is acquired is history data for the past fixed period stored in the storage unit 20.

The treatment continuation probability estimation unit 27 determines the user based on the data on the disease severity acquired by the disease severity acquisition unit 25 and the data representing the use history of the insomnia treatment system acquired by the use history acquisition unit 26. Estimate the treatment continuation probability of As a specific functional configuration for estimating the treatment continuation probability, the treatment continuation probability estimation unit 27 includes a prediction model storage unit 27A and an estimation processing unit 27B. The treatment continuation probability estimation unit 27 estimates the treatment continuation probability by machine learning by the prediction model storage unit 27A and the estimation processing unit 27B. The random forest method is used as an example of machine learning.

That is, the prediction model storage unit 27A stores a prediction model including a plurality of decision trees corresponding to various combination contents of data on disease severity and data representing use history of the insomnia treatment system. Further, the estimation processing unit 27B applies the data relating to the disease severity acquired by the disease severity acquiring unit 25 and the data representing the use history acquired by the use history acquisition unit 26 to a prediction model, and a plurality of decision trees Based on the percentage of the decision tree that has become active or inactive, the treatment continuation probability of the user is estimated.

Each decision tree of the prediction model searches for a boundary line that divides into a group continuing treatment and a group not continuing treatment based on various data input to the prediction model. This boundary is expressed as a branched structure in the form of a binary tree. Further, the boundary is determined in accordance with the contents of various data to be input. Each decision tree configured in this way indicates either active (treatment continuation) or non-activation (treatment non-continuation) bordering on the boundary determined according to the contents of the input various data. . The estimation processing unit 27B estimates the treatment continuation probability of the user based on the ratio of the decision tree which is in either the active or inactive state.

The message notification unit 28 is a message that motivates the user to continue using the insomnia treatment system (insomnia treatment application) when the treatment continuation probability estimated by the treatment continuation probability estimation unit 27 satisfies a predetermined condition. Is notified to the portable terminal 100. That is, the message notification unit 28 transmits the message to the insomnia treatment application of the portable terminal 100, and the insomnia treatment application notifies the user of the message through the display of the message on the screen of the portable terminal 100.

For example, as shown in FIG. 3A, the message notification unit 28 has all the treatment continuation probabilities estimated over a plurality of times by the treatment continuation probability estimating unit 27 equal to or more than a predetermined threshold value, and the most recently. If it is descending, a message of the first content is notified. In addition, as shown in FIG. 3B, the message notification unit 28 notifies a message of the second content when the treatment continuation probability estimated by the treatment continuation probability estimation unit 27 is less than a predetermined threshold. .

That is, when the treatment continuation probability is equal to or more than the predetermined threshold, when the treatment continuation probability estimated over a plurality of times is decreasing, small dissatisfaction with the insomnia treatment application has accumulated due to poor operability and the like As a result, the frequency of use may have fallen. Therefore, as the first content message, for example, “Do you have any problems with the operation of the insomnia treatment application, etc.” The message notification unit 28 is listed in the consultation, so please contact us from the inquiry window. Broadcast a message with the content of

Here, the treatment continuation probability estimated over a plurality of times means, for example, the treatment continuation probability estimated this time and the previous treatment continuation probability estimated immediately before. The time interval for estimating the treatment continuation probability is an interval shorter than the non-use period which the user defines as not using the insomnia treatment application (dropout). For example, it is defined as dropped out when the user has not logged in to the insomnia treatment app for 2 days. In this case, the treatment continuation probability estimation unit 27 repeatedly estimates the treatment continuation probability at a time interval shorter than 2 days. Then, the message notification unit 28 determines that the currently estimated treatment continuation probability and the previously estimated treatment continuation probability are both equal to or greater than the threshold value, and the currently estimated treatment continuation probability is smaller than the previously estimated treatment continuation probability. If it has, the message of the first content described above is broadcasted.

On the other hand, if the treatment continuation probability is less than a predetermined threshold, the frequency of use may have fallen due to the familiarity with the use of the insomnia treatment app. Therefore, the message notification unit 28 reports, for example, a message of “The insomnia treatment application exerts a therapeutic effect by daily use” as the message of the second content. At this time, use may be continued to introduce an example of an effect along with a message.

The content of the message shown here is an example, and it is not limited to this. Moreover, the conditions which alert | report a message are also an example, It is not limited to this.

For example, the first content message may be increased to two or more types according to the degree of the gradient in which the treatment continuation probability estimated over a plurality of times is decreasing. Further, by providing a plurality of threshold values, the message of the second content may be increased to two or more types.

In addition, when not only the treatment continuation probability estimated this time and the previous two times but also the treatment continuation probability estimated over three or more times continues to fall, the message of the first content is reported You may

In addition, whenever the condition for reporting the message of the first content or the message of the second content is continuously satisfied each time the treatment continuation probability is estimated before the user drops out, the second and subsequent times are different from the previous one. You may make it alert | report the message of the content.

Further, a message linked to a reason other than the operability of the insomnia treatment application may be notified. For example, the use of the insomnia treatment app is not enough to feel that treatment is effective, that is, the reason that "the dissatisfaction with the effect is" is analyzed from the content of data applied to the prediction model and the transition of treatment continuation probability etc. In such cases, for example, a message such as "There are individual differences in the period until the effect of this application comes out. Even if there is no immediate effect, it will be effective by continuing to use it." You may make it alert | report.

In addition, even when the treatment continuation probability estimated by the treatment continuation probability estimation unit 27 is less than a predetermined threshold, the same contents are obtained even when all the treatment continuation probabilities estimated over a plurality of times are lower than the threshold. A message may be broadcasted. In addition, regardless of whether all the treatment continuation probabilities estimated over a plurality of times are equal to or more than the threshold value, the message may be notified in the case where it is decreasing toward the latest.

FIG. 4 is a flowchart showing an operation example of the treatment support apparatus according to the present embodiment configured as described above. The flowchart shown in FIG. 4 is always executed while the server device 200 is in operation.

First, the disease severity acquiring unit 25 determines whether or not a predetermined time set as a time interval for estimating the treatment continuation probability has passed from the previous treatment continuation probability estimation (step S1).

Here, when the predetermined time has passed, the disease severity acquisition unit 25 obtains data on the disease severity obtained by the user using the insomnia treatment app (answer data to the inquiry, obtained by executing the drowsiness test) First measurement data, and second measurement data measured by the external measurement device 300 are acquired from the storage unit 20 (step S2). In addition, the use history acquisition unit 26 acquires data representing the use history of the insomnia treatment application by the user from the storage unit 20 (step S3).

Next, the treatment continuation probability estimation unit 27 is based on the data related to the disease severity acquired by the disease severity acquisition unit 25 in step S2 and the data representing the use history acquired by the use history acquisition unit 26 in step S3. Then, the treatment continuation probability of the user is estimated (step S4).

Then, the message notification unit 28 determines whether the treatment continuation probability estimated by the treatment continuation probability estimation unit 27 is less than a predetermined threshold (step S5). If the treatment continuation probability is less than the predetermined threshold, the message notification unit 28 notifies the portable terminal 100 of a message of the second content (step S6).

On the other hand, when the treatment continuation probability is not less than the predetermined threshold, the message notification unit 28 determines whether the treatment continuation probability estimated this time is smaller than the treatment continuation probability estimated last time, that is, the treatment continuation probability Is determined to be lowered (step S7). When the treatment continuation probability is decreasing, the message notification unit 28 notifies the mobile terminal 100 of a message of the first content (step S8).

If the treatment continuation probability does not decrease, the message notification unit 28 does not notify the message. Thus, the process of the flowchart illustrated in FIG. 4 ends.

As described above in detail, in the present embodiment, the data on the disease severity obtained by the user using the insomnia treatment app is acquired, and the data representing the use history of the insomnia treatment app by the user is acquired Based on the acquired data on the disease severity and the data representing the use history, the treatment continuation probability of the user is estimated. And when the presumed treatment continuation probability satisfy | fills predetermined conditions, he is trying to alert | report the message which becomes a motivation which a user continues using the insomnia treatment application.

According to this embodiment configured as described above, when the user uses the insomnia treatment app for treatment by cognitive behavior therapy, data on the disease severity obtained through its actual use and use of the insomnia treatment app Based on the data representing the history, a treatment continuation probability indicating the possibility of the user continuing the treatment using the insomnia treatment app is estimated. Then, when the treatment continuation probability satisfies a predetermined condition, a message is provided to motivate the user to continue using the insomnia treatment application. This will provide the user with a message motivating the continued use of the insomnia treatment app before the user actually ceases using the insomnia treatment app, allowing the user to leave during treatment as much as possible. It will be possible to suppress.

In the above embodiment, an example in which the treatment continuation probability is estimated by machine learning using the random forest method has been described, but the present invention is not limited to this. For example, another learning algorithm such as a neural network, a support vector machine (SVM), or a logistic regression may be used to estimate the treatment continuation probability. Also, instead of machine learning, the treatment continuation probability may be estimated by a predetermined calculation formula.

Further, in the above embodiment, the function of the treatment support apparatus (the functions of the disease severity acquisition unit 25, the use history acquisition unit 26, the treatment continuation probability estimation unit 27 and the message notification unit 28) is a part of the insomnia treatment system Although the example implemented as is described above, the present invention is not limited thereto. For example, the treatment support apparatus may be provided separately from the server apparatus 200. More specifically, the insomnia treatment application may have the function of the treatment support apparatus.

In the above embodiment, as an example of a system related to information processing technology, a system (insomnia treatment application) for treating insomnia by cognitive behavioral therapy has been described as an example, but the present invention is not limited to this. That is, if the treatment of the cognitive behavioral therapy is effective, it is possible to apply the treatment support apparatus of the present embodiment to a system for treating a disease other than insomnia.

Moreover, if it is a disease that can be treated by the use of a system related to information processing technology as well as cognitive behavioral therapy, it is possible to apply the treatment support device of the present invention to support treatment. For example, as another example of a system related to information processing technology, there is a treatment application in which a diabetic patient exerts a treatment effect in compliance with "lifestyle improvement instruction" prescribed as a treatment from a doctor.

In addition, any of the above-described embodiments is merely an example of embodying the present invention, and the technical scope of the present invention should not be interpreted in a limited manner. That is, the present invention can be implemented in various forms without departing from the scope or main features of the present invention.

25 disease severity acquisition unit 26 use history acquisition unit 27 treatment continuation probability estimation unit 27A prediction model storage unit 27B estimation processing unit 28 message notification unit

Claims (9)

A treatment support apparatus for supporting treatment of a disease, which is performed based on data obtained by a user sequentially using a system related to information processing technology,
A disease severity acquisition unit for acquiring data on disease severity obtained by the user using the system;
A usage history acquisition unit for acquiring data representing a usage history of the system by the user;
The treatment continuation probability of estimating the treatment continuation probability of the user based on the data on the disease severity acquired by the disease severity acquiring unit and the data representing the use history of the system acquired by the use history acquiring unit An estimation unit,
Providing a message notification unit notifying a message serving as a motivation for the user to continue using the system when the treatment continuation probability estimated by the treatment continuation probability estimating unit satisfies a predetermined condition Treatment support device characterized by The above treatment continuation probability estimation unit
A prediction model storage unit storing a prediction model including a plurality of decision trees according to various combination contents of data relating to the disease severity and data representing the use history of the system;
The data on the disease severity acquired by the disease severity acquiring unit and the data representing the use history of the system acquired by the use history acquiring unit are applied to the prediction model, and the activity of the plurality of decision trees is activated. The treatment support apparatus according to claim 1, further comprising: an estimation processing unit configured to estimate the treatment continuation probability of the user based on a ratio of a decision tree that has become inactive or inactive. The said message alerting | reporting part alert | reports the said message, when the said treatment continuation probability estimated over multiple times by the said treatment continuation probability estimation part falls, The treatment of Claim 1 or 2 characterized by the above-mentioned. Support device. The said message alerting | reporting part alert | reports the said message, when the said treatment continuation probability estimated by the said treatment continuation probability estimation part is less than a predetermined | prescribed threshold value, The treatment assistance of Claim 1 or 2 characterized by the above-mentioned. apparatus. The message notification unit is configured to receive the message of the first content when the treatment continuation probability estimated for a plurality of times by the treatment continuation probability estimation unit is equal to or more than the predetermined threshold and is falling. The message according to claim 1 or 2, wherein a message of the second content is notified when the notification is made and the treatment continuation probability estimated by the treatment continuation probability estimation unit is less than a predetermined threshold. Treatment support device. The disease severity acquiring unit is configured to obtain data on subjective disease severity obtained by the user inputting an answer to an inquiry provided by the system, and objectively obtained through execution of a predetermined measurement on the user. The treatment support apparatus according to claim 1 or 2, wherein data on the severity of the disease is acquired. The disease severity acquisition unit includes, as data relating to the objective disease severity, the first measurement data obtained by the user performing the measurement test provided by the system, and a predetermined external measurement device. The treatment support apparatus according to claim 6, wherein the second measurement data measured is acquired. The treatment support according to claim 1, wherein the disease severity acquisition unit, the use history acquisition unit, the treatment continuation probability estimation unit, and the message notification unit are implemented as a part of functions of the system. apparatus. A treatment support program for supporting the treatment of a disease, which is performed based on data obtained by a user sequentially using a system related to information processing technology,
Disease severity acquisition means for acquiring data on disease severity obtained by the user using the system,
Usage history acquisition means for acquiring data representing usage history of the system by the user,
The treatment continuation probability of estimating the treatment continuation probability of the user based on the data on the disease severity acquired by the disease severity acquiring means and the data representing the use history of the system acquired by the use history acquiring means Estimating means, and computer as message notifying means for notifying a message that motivates the user to continue using the system when the treatment continuation probability estimated by the treatment continuation probability estimating means satisfies a predetermined condition Computer readable treatment support program to make it work.

Images