JPWO2020230257A1 - Clinical trial eligibility determination system, clinical trial eligibility determination method, clinical trial eligibility determination device and clinical trial eligibility determination program - Google Patents

Abstract

The execution result acquisition unit 21 that instructs the user to execute a predetermined process using the medical software and acquires the execution result information indicating the result of the process executed by the user in response to the instruction, and the acquired execution result. Eligibility as a subject to participate in clinical trials of medical software in terms of at least one aspect of informed, reliability of incentives and proficiency in operating information processing equipment. It is equipped with a qualification determination unit 23 for determining sex, and is acquired as a result of the user actually using the medical software and executing a process in response to a given instruction in conducting a clinical test of the medical software. By determining eligibility as a subject from the viewpoint of reliability and proficiency based on the execution result information, it is possible to appropriately determine whether or not the user of the medical software is eligible as a subject. To do.

Description

The present invention relates to a clinical trial eligibility determination system, a clinical trial eligibility determination method, a clinical trial eligibility determination device, and a clinical trial eligibility determination program, and in particular, eligibility as a subject participating in a clinical trial of medical software. It is suitable for use in a system for determining.

Generally, in the process of developing new drugs, medical devices, treatment methods, etc., clinical trials (clinical trials) are conducted on a plurality of subjects in order to confirm their safety and efficacy. Clinical trials are conducted with patients and the like having a specific disease as subjects according to the purpose. Conventionally, a system for executing a process of extracting a patient suffering from a disease subject to a clinical trial as a subject has been proposed (see, for example, Patent Documents 1 and 2).

Patent Document 1 discloses that a patient who is being treated for a disease targeted by a designated investigational drug and whose number of changes in the administered drug is equal to or greater than a threshold value is output as a candidate for the investigational drug. There is. Further, in Patent Document 2, patients who are associated with an identifier of a disease related to a clinical trial and whose treatment period exceeds the reference number of days for the disease related to the clinical trial are output as candidates for the clinical trial. Is disclosed.

The systems described in Patent Documents 1 and 2 are for extracting subjects for clinical trials from patients who are already being treated by a doctor. On the other hand, from the test candidates collected through the recruitment by the development company of drugs, medical devices, treatment methods, etc. or the medical institution commissioned by the development company, the results of interviews, medical examinations, background surveys, etc. by doctors In some cases, subjects are extracted from the viewpoint of whether or not they satisfy a predetermined criterion for subject suitability through a conformity test conducted based on the above (see, for example, Patent Document 3).

Patent Document 3 discloses that a doctor or the like conducts an interview, a diagnosis, and a background check on a test candidate before starting a clinical trial, and selects an appropriate subject based on the result. Specifically, in the system described in Patent Document 3, whether the characteristic information at the start of the pre-observation period of the test candidate who has expressed his / her intention to participate in the clinical study meets the first subject conformity criterion. Along with the determination, it is determined whether the characteristic information at the end of the pre-observation period for the test candidate determined to match this meets the second subject suitability criteria, which also matches this. Register the test candidate as a subject.

By the way, due to the revision of the Medical Devices and Medical Devices Act (formerly the Pharmaceutical Affairs Law) in the fall of 2014, medical software is now handled as medical devices, and as a result, a dedicated application for disease treatment (hereinafter referred to as a therapeutic application). ) Is being used for disease treatment. In order to actually use the therapeutic application as a medical device, it is necessary to obtain approval from the Medical Products and Medical Devices Act. Then, in order to obtain the approval, it is necessary to conduct a clinical trial to verify the effectiveness of the therapeutic effect using the therapeutic application.

There are specific challenges in clinical trials of therapeutic apps regarding screening to select appropriate subjects when conducting clinical trials. The first is the problem of subject reliability. In general, participating in a clinical trial as a subject often provides some financial incentive as a reward. This also applies to clinical trials of therapeutic apps. However, since the therapeutic app has the property that it can be freely used anywhere (for example, the patient's home or workplace), the use of the therapeutic app by the test candidate is completely used by the medical institution. Difficult to keep under surveillance. Therefore, if a dishonest person who applied for the purpose of financial incentive is registered as a subject, there is a problem that the treatment application is not used in good faith or the information on the result of using the treatment application is not reported in good faith. May occur.

The second is the issue of suitability for use of therapeutic apps. Patients who are candidates for clinical trials have various attributes, including those who are unfamiliar with the operation of information processing devices. Those who are extremely proficient in operating information processing devices may not be suitable for treatment through the use of therapeutic apps, and are not suitable as subjects for clinical trials. Therefore, if a person who is considered to have low fitness for use of the therapeutic app is registered as a subject, there is a high possibility that the therapeutic app cannot be used correctly or withdrawal in the middle of a clinical trial. There is a problem.

In the future, it is expected that information processing devices using various types of medical software will be used as medical devices, not limited to therapeutic applications that are installed and used on smartphones. Regarding these information processing devices, it is considered that the above-mentioned problems also occur when conducting clinical trials.

Japanese Unexamined Patent Publication No. 2014-194595 Japanese Unexamined Patent Publication No. 2014-215935 Japanese Unexamined Patent Publication No. 2004-229894

The present invention has been made to solve the above problems, and an object of the present invention is to enable an appropriate determination as to whether or not a subject is eligible for clinical trials of medical software.

In order to solve the above-mentioned problems, in the clinical test eligibility determination system of the present invention, the user of the information processing apparatus in which the medical software is installed is instructed to execute a predetermined process using the medical software. , Acquires execution result information representing the result when a predetermined process is executed by the user in response to the instruction. Then, based on the acquired execution result information, a clinical trial of medical software is performed from the viewpoint of reliability of whether or not the person is intended to obtain an incentive and proficiency in operation of an information processing device. The eligibility as a subject to participate in is judged.

According to the present invention configured as described above, in conducting a clinical trial of medical software, when a test candidate actually uses the medical software and executes a process in response to a given instruction, the result is obtained. Based on the execution result information acquired as, the eligibility as a subject is determined from the viewpoint of reliability of whether or not the person aims to obtain incentives and from the viewpoint of proficiency in operating the information processing device. To. Thereby, according to the present invention, it is possible to solve a problem peculiar to a clinical trial of medical software and appropriately determine whether or not a user of an information processing apparatus is eligible as a subject.

It is a figure which shows the network configuration example of the clinical trial system which applied the clinical trial eligibility determination system by 1st Embodiment. It is a figure which shows the hardware configuration example of a user terminal and a clinical trial management server. It is a block diagram which shows the functional structure example of the user terminal by 1st Embodiment. It is a block diagram which shows the functional structure example of the clinical trial management server by 1st Embodiment. It is a flowchart which shows the operation example of the user terminal by 1st Embodiment. It is a flowchart which shows the operation example of the clinical trial management server by 1st Embodiment. It is a figure which shows the network configuration example of the clinical trial system which applied the clinical trial eligibility determination system by 2nd Embodiment. It is a block diagram which shows the functional structure example of the user terminal by 2nd Embodiment. It is a block diagram which shows the functional structure example of the clinical trial management server by 2nd Embodiment. It is a block diagram which shows the other function configuration example of the user terminal by 2nd Embodiment. It is a block diagram which shows the other functional configuration example of the clinical trial management server by 2nd Embodiment.

(First Embodiment)
Hereinafter, the first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing a network configuration example of a clinical trial system to which the clinical trial eligibility determination system according to the first embodiment is applied. The clinical trial eligibility determination system of the present embodiment is a system for determining eligibility as a subject participating in a clinical trial of medical software, and is configured by utilizing the configuration of a clinical trial system for conducting a clinical trial of medical software. Has been done. The clinical trial eligibility determination system may be configured separately from the clinical trial system.

The medical software is, for example, a therapeutic application installed and used in an information processing device. A specific example of a therapeutic application is an application aimed at treating diseases such as nicotine addiction, sleep disorders, alcoholism, and hypertension by improving the lifestyle of a patient. The therapeutic app may also be an application aimed at treating central neurological disorders such as depression, Parkinson's disease, and dementia. In the following, the medical software will be described as the above-mentioned therapeutic application, but the ones listed here are examples, and the present invention is not limited thereto.

For example, in a therapeutic app, information about a patient's symptoms and daily behavior can be entered at any time in the form of a questionnaire, or a predetermined behavior test that accompanies the patient's behavior can be performed, and the input information and behavior test can be performed. Information indicating the result is transmitted to the server device. Then, the server device performs a predetermined analysis based on this information, outputs a message regarding a predetermined advice to the treatment application, or executes a predetermined process for inducing the patient to take a predetermined action. Or Part of the processing of the predetermined analysis may be performed by the therapeutic application itself.

As shown in FIG. 1, the clinical trial system according to the first embodiment includes a user terminal 100 which is an information processing device in which a therapeutic application used by the user is installed, a clinical trial management server 200 which manages a clinical trial, and a clinical trial management server 200. A medical institution terminal 300 used by a medical institution is provided, and a user terminal 100, a clinical trial management server 200, and a doctor's terminal 300 are connected via a communication network 400. A user is a test candidate who uses a therapeutic app (becomes a subject after being determined to be eligible to participate in a clinical trial).

Candidates are those who have been recruited through recruitment by a development company for drugs, medical devices, treatment methods, etc. or a medical institution entrusted by the development company. All the applicants for the recruitment may be candidates for the test, or candidates for the test may be selected except for those who can be clearly judged to be non-conforming from the viewpoint of the doctor. As will be described in detail below, the clinical trial eligibility determination system of the present embodiment determines the eligibility of each of these test candidates as a subject of the therapeutic app.

The user terminal 100 is an information processing device on which a treatment application is installed, and is, for example, a smartphone, a tablet terminal, a personal computer, or the like. Any user terminal 100 can be applied as long as the treatment application can be installed and executed. However, when the treatment application is intended to be treated by improving the lifestyle of the subject, it is preferable to use a mobile terminal that can be carried around at all times.

The medical institution terminal 300 is a terminal on which a medical institution treatment application that operates in cooperation with the patient treatment application installed on the user terminal 100 is installed. Any terminal such as a smartphone, tablet, or personal computer that can install and execute this application can be applied. In the following description, unless otherwise specified, the term "therapeutic application" simply means an application for a patient.

The clinical trial management server 200 is a management device in which a dedicated application that operates in cooperation with each application installed in the user terminal 100 and the medical institution terminal 300 is installed. In particular, in the present embodiment, the clinical trial management server 200 executes a process necessary for determining eligibility as a subject participating in a clinical trial of the therapeutic application based on the information transmitted from the user terminal 100. .. The clinical trial management server 200 and the user terminal 100 constitute a clinical trial eligibility determination system according to the present embodiment.

FIG. 2 is a diagram showing a hardware configuration example of the user terminal 100 and the clinical trial management server 200. As shown in FIG. 2A, the user terminal 100 includes a CPU 101, a ROM 102, a RAM 103, an auxiliary storage device 104, an input unit 105, a display unit 106, and a communication unit 107 as its hardware configuration. The auxiliary storage device 104 stores medical software (treatment application) and various execution result information obtained when the user executes the treatment application.

The CPU 101 controls the operation of the user terminal 100 according to a program stored in the ROM 102 or the auxiliary storage device 104. The input unit 105 is composed of a touch panel, a keyboard, or the like, and is used for operations related to various information input and various processing executions by the user. The display unit 106 is composed of a liquid crystal display, an organic EL display, or the like, and displays various types of information. The communication unit 107 mutually performs data communication with the clinical trial management server 200 via a communication network 400 such as the Internet or a mobile phone network.

As shown in FIG. 2B, the clinical trial management server 200 includes a CPU 201, a ROM 202, a RAM 203, an auxiliary storage device 204, and a communication unit 205 as its hardware configuration. A clinical trial eligibility determination program is stored in the ROM 202 or the auxiliary storage device 204. The auxiliary storage device 204 also stores determination result information indicating the result of determination regarding the eligibility of the user as a subject.

The CPU 201 is qualified as a subject for a user (test candidate) who is using the therapeutic application on the user terminal 100 to participate in the clinical trial according to the clinical trial eligibility determination program stored in the ROM 202 or the auxiliary storage device 204. Performs the processing necessary to determine whether or not it has sex. The communication unit 205 mutually performs data communication with the user terminal 100 or the medical institution terminal 300 via the communication network 400. For example, the communication unit 205 receives various information sent from the user terminal 100. In addition, the communication unit 205 transmits information indicating the determination result regarding eligibility as a subject to the medical institution terminal 300 in response to the request from the medical institution terminal 300.

FIG. 3 is a block diagram showing a functional configuration example of the user terminal 100 according to the first embodiment. As shown in FIG. 3, the user terminal 100 includes a process execution instruction unit 11, a process execution unit 12, an execution result storage unit 13, and an execution result transmission unit 14 as its functional configuration. Each of these functional blocks 11 to 14 is realized by operating the therapeutic application stored in the auxiliary storage device 104 under the control of the CPU 101 shown in FIG. 2 (a).

The process execution instruction unit 11 instructs the user of the user terminal 100 to execute a predetermined process using the treatment application. The predetermined process using the therapeutic application is a process predetermined according to the disease to be treated by the therapeutic application, and is a process necessary for performing the treatment through improvement of lifestyle and the like. The predetermined process is, for example, a process for executing a predetermined action test accompanied by the action of the user using the input unit 105. Further, the predetermined process is a process for executing a predetermined questionnaire that involves the user inputting information using the input unit 105.

For example, in the case of a therapeutic app aimed at treating sleep disorders, a PVT test to measure the user's objective degree of drowsiness, current drowsiness, quality of life (QOL) status, and daytime activities. A questionnaire that asks questions about the user's health condition such as the situation corresponds to the predetermined process. The PVT test measures the reaction time until the user touches the touch panel of the input unit 105 with respect to a figure or the like randomly displayed on the display unit 106, and the arousal level decreases according to the reaction time ( This is a test to measure drowsiness.

The process execution instruction unit 11 instructs the execution of a predetermined process when the predetermined timing set in the treatment application is reached. As for the predetermined timing, an appropriate time is set according to the content of the predetermined process. For example, in the case of the above-mentioned PVT test, a time set before the bedtime set by the user by operating the input unit 105 is set as a predetermined timing, and when this timing is reached, the execution of the PVT test is instructed. .. The instruction is given, for example, by displaying a message prompting the execution of the process on the display unit 106. At this time, the announcement sound may be output from the speaker of the user terminal 100, or the vibrator may be vibrated.

The process execution instruction unit 11 instructs the user of the user terminal 100 to execute a predetermined process using the treatment application a plurality of times. The multiple times may be a plurality of times in a day, or may be a plurality of times over a plurality of days (for example, when an instruction once a day is given over a plurality of days). For example, the execution instruction of the PVT test may be given at a predetermined time during the day in addition to the time before the above-mentioned bedtime. In addition, in the case of a therapeutic application that requires the user's health condition questionnaire to be conducted multiple times a day by changing the content of the question, the execution instruction of the questionnaire is given at the predetermined time of the day. Do it multiple times.

The process execution unit 12 executes a predetermined process using the treatment application in response to the user's operation on the input unit 105. The predetermined processing is as described above, and is processing such as a behavior test or a questionnaire predetermined according to the disease to be treated by the treatment application. When the process execution instruction unit 11 gives an instruction to execute the process, the user executes a predetermined process according to the instruction. In executing the predetermined process, the user operates the input unit 105 to activate the execution function of the predetermined process, and executes the predetermined process according to the activated execution function.

The execution result storage unit 13 stores the execution result information representing the result when a predetermined process is executed by the user in response to the instruction from the process execution instruction unit 11 in the auxiliary storage device 104. The execution result information includes the execution result of the behavior test, the response content of the questionnaire, and the response time information indicating the response time when the user executes a predetermined process in response to the instruction. An example of the response time information is reaction time information indicating the reaction time until the user starts executing a predetermined process in response to an instruction. Further, another example of the response time information is the execution time information indicating the execution time required until the user finishes executing the predetermined process in response to the instruction.

For example, the process execution unit 12 measures the time taken from the instruction to execute the action test by the process execution instruction unit 11 until the user activates the execution function of the action test as the reaction time, and this is the execution result. The storage unit 13 stores the reaction time information in the auxiliary storage device 104. Further, the processing execution unit 12 determines the time taken from the instruction to execute the questionnaire by the processing execution instruction unit 11 or the activation of the questionnaire execution function by the user to the completion of the answer to the questionnaire (the execution time (). The response time) is measured, and the execution result storage unit 13 stores this as execution time information (response time information) in the auxiliary storage device 104.

The execution result transmission unit 14 transmits the execution result information (behavior test reaction time information and questionnaire response time information) stored in the auxiliary storage device 104 to the communication unit clinical trial management server 200. The execution result transmission unit 14 may transmit the stored execution result information each time the execution result information is stored in the auxiliary storage device 104, or may transmit the stored execution result information in a batch at a predetermined timing. You may do it. For example, the execution result information may be transmitted every day or every few days at a predetermined time, or may be transmitted when the execution result information for a predetermined number of times is stored in the auxiliary storage device 104. May be good. Alternatively, a certain period of time (for example, one week after the therapeutic application is installed on the user terminal 100) for determining the eligibility of each user as a subject of a clinical trial is set, and when a certain period of time elapses. The execution result information may be transmitted.

The execution result information transmitted by the execution result transmission unit 14 may be all of the execution result of the behavior test, the response content of the questionnaire, and the response time information, but may be only the response time information. For example, either the pre-use mode or the main use mode can be set in the treatment application. Then, the pre-use mode is set to the initial setting at the initial stage when the treatment application is installed on the user terminal 100, and when the pre-use mode is set, the execution result transmission unit 14 manages only the response time information in the clinical trial. It is transmitted to the server 200. After that, the mode setting of the treatment application is set by transmitting a mode switching signal from the clinical trial management server 200 to the user terminal 100 of the user who is determined to be qualified as a subject by analyzing the response time information. Switch from pre-use mode to main use mode. After setting this usage mode, the execution result transmission unit 14 transmits the execution result of the behavior test and the answer contents of the questionnaire to the clinical trial management server 200.

Next, the functional configuration of the clinical trial management server 200 will be described. FIG. 4 is a block diagram showing a functional configuration example of the clinical trial management server 200 according to the first embodiment. As shown in FIG. 4, the clinical trial management server 200 includes an execution result acquisition unit 21, an execution result storage unit 22, a qualification determination unit 23, a determination result storage unit 24, and a determination result transmission unit 25 as its functional configuration. ing. Each of these functional blocks 21 to 25 is realized by operating a clinical trial eligibility determination program stored in the ROM 202 or the auxiliary storage device 204 under the control of the CPU 201 shown in FIG. 2 (b). ..

The execution result acquisition unit 21 acquires the execution result information transmitted by the execution result transmission unit 14 from the plurality of user terminals 100, respectively. For example, when the treatment application of the user terminal 100 is set to the pre-use mode, the execution result acquisition unit 21 acquires the response time information transmitted by the execution result transmission unit 14 of the user terminal 100. Further, when the treatment application of the user terminal 100 is set to the main use mode, the execution result acquisition unit 21 performs the execution result of the behavior test and the answer contents of the questionnaire transmitted by the execution result transmission unit 14 of the user terminal 100. To get.

The execution result storage unit 22 stores the execution result information acquired by the execution result acquisition unit 21 in the auxiliary storage device 204. For example, when the treatment application of the user terminal 100 is set to the pre-use mode, the execution result storage unit 22 stores the response time information acquired by the execution result acquisition unit 21 in the auxiliary storage device 204. Further, when the treatment application of the user terminal 100 is set to the main use mode, the execution result storage unit 22 stores the execution result of the behavior test acquired by the execution result acquisition unit 21 and the answer contents of the questionnaire as an auxiliary storage device. Store in 204.

The auxiliary storage device 204 stores the execution result information transmitted from the plurality of user terminals 100. The execution result storage unit 22 stores a plurality of execution result information in a manner capable of identifying which execution result information is transmitted from which user terminal 100 (or which user corresponds to). It is stored in the auxiliary storage device 204.

The clinical trial eligibility determination system according to the present embodiment aims to determine whether or not a user is eligible as a subject when conducting a clinical trial of a therapeutic application. The functional configuration shown in FIG. 4 relates to a process of determining the eligibility of a user as a subject based on the response time information acquired by the execution result acquisition unit 21 when the treatment application is set to the pre-use mode. Is shown. Regarding the functional configuration for executing the processing related to the treatment of the disease based on the execution result of the behavior test acquired by the execution result acquisition unit 21 and the answer contents of the questionnaire when the treatment application is set to this use mode. The illustration is omitted, and the explanation about it is omitted.

The eligibility determination unit 23 is a person who aims to acquire an incentive based on the execution result information (response time information) acquired by the execution result acquisition unit 21 and stored in the auxiliary storage device 204 by the execution result storage unit 22. The eligibility of the user as a subject is determined from at least one viewpoint of reliability of whether or not the information processing device is used and proficiency in operating the information processing device. Determining eligibility may mean determining whether or not the user is eligible as a subject, but in the present embodiment, how likely it is that the user is eligible (or not) as a subject. Is to be shown.

The reliability of whether or not a person aims to obtain an incentive is the degree of possibility that the person applied for the purpose of obtaining an economic incentive that will be rewarded when participating in a clinical trial as a subject. As shown, the reliability is low and the user's eligibility as a subject is low as it is presumed that the applicant is likely to have applied for the purpose of obtaining financial incentives.

Further, the proficiency level regarding the operation of the information processing device indicates the degree of possibility that the person has low IT literacy and is unfamiliar with the operation of the information processing device, and is a person who is unfamiliar with the operation of the information processing device. The more likely it is, the less proficient it is and the less qualified the user is as a subject.

The eligibility determination unit 23 calculates at least one of the reliability evaluation value and the proficiency evaluation value for the user by performing predetermined statistical processing based on the response time information stored in the auxiliary storage device 204. , The eligibility of the user as a subject is determined based on the calculated evaluation value.

For example, the eligibility determination unit 23 determines the relative evaluation value of the response time for one user with respect to the response time for another user based on the response time information acquired for a plurality of users, and the reliability for one user. Calculated as the evaluation value of. Here, the response time for one user is, for example, a statistical value of a plurality of response times obtained for executing a plurality of processes (for example, median value, average value, maximum value, minimum value, mode value, etc.). Is used.

More specifically, the eligibility determination unit 23 evaluates the relative evaluation value of the response time for one user with respect to the response time for another user based on the response time of the questionnaire, and evaluates the reliability for one user. Calculate as a value. This is because it is possible that users who have a certain difference in response time or more compared to the response time that is normally expected to take when a reliable user answers the questionnaire do not answer the questionnaire seriously. There is, and it is presumed that the reliability is low in that respect.

The relative evaluation value in this case can be calculated as follows, for example. That is, under the supervision of a doctor or the like, multiple users are asked to use the treatment application and answer the questionnaire. In this case, the user is preferably a patient who is known to have a disease for which the therapeutic application is to be treated, for example, a patient selected by a doctor. Such patients are reliable users because they are not the ones who use the therapeutic app for the financial incentives they get when they participate in clinical trials as subjects.

The eligibility determination unit 23 has statistical values (median, average, maximum, etc.) regarding the distribution of response times for users who responded to the questionnaire (corresponding to "other users" in the claims) under the supervision of a doctor or the like. Calculate the relative evaluation value according to the size of the difference between the minimum value, mode value, etc.) and the response time for one user who wants to judge eligibility. The relative evaluation value according to the magnitude of the difference can be calculated as, for example, the Euclidean distance. The larger the Euclidean distance, the lower the reliability of the user as a subject, and the smaller the Euclidean distance, the higher the reliability of the user as a subject.

For example, the eligibility determination unit 23 determines that a user whose Euclidean distance calculated as described above is larger than a predetermined value has low eligibility as a subject. Alternatively, a predetermined number of users counted from the one with the smallest Euclidean distance calculated as described above, or a predetermined percentage of users counted from the one with the smallest Euclidean distance are eligible as subjects. It may be determined that it is low. The Euclidean distance is only an example, and is not limited to this.

The eligibility determination unit 23 may calculate the relative evaluation value as follows. That is, the eligibility determination unit 23 performs machine learning using the response time of the user who responded to the questionnaire (corresponding to "other users" in the claims) as the correct answer data under the supervision of a doctor or the like, thereby performing machine learning. Generate a prediction model in advance so that the relative evaluation value is output when the response time is input. This prediction model shall output, for example, any numerical value between the value "0" indicating the lowest reliability and the value "1" indicating the highest reliability. Then, the eligibility determination unit 23 calculates the relative evaluation value for one user by inputting the response time of the questionnaire regarding one user who wants to determine eligibility into the prediction model.

In this case, the eligibility determination unit 23 determines that the user whose value output from the prediction model is smaller than the predetermined value has low eligibility as a subject. It should be noted that the prediction model is generated so as to output a value indicating one of the classifications when the degree of reliability is expressed in a plurality of stages (two stages or three or more stages), and the degree of reliability is the lowest. A user whose classification value is output from the prediction model may be judged to have low eligibility as a subject.

When calculating the relative evaluation value by machine learning in this way, the response content of the questionnaire may be used in addition to the response time of the questionnaire. For example, among the users who prepared multiple questions as checkpoints that should have a correlation with the answer results and used the treatment application under monitoring, there is no correlation in the answer contents of the checkpoint (or the correlation value is less than or equal to the predetermined value). ) An example is to perform processing that excludes the response time related to the user from the correct answer data.

Further, the eligibility determination unit 23 determines the relative evaluation value of the response time for one user with respect to the response time for another user based on the response time information acquired for a plurality of users, and the proficiency level for one user. Calculated as the evaluation value of. For example, the eligibility determination unit 23 determines the relative evaluation value of the reaction time for one user to the reaction time for another user, based on the reaction time from the instruction is given to the start of execution of the behavior test. Is calculated as an evaluation value of proficiency level for one user.

This is more than a certain amount of reaction time compared to the reaction time that is normally expected to take for a user who has a level of proficiency in using an information processing device to activate the behavior test execution function in response to an instruction. For users who have a difference, it is possible that it takes time to operate the behavior test execution function, and it is estimated that the proficiency level of the information processing device is low in that respect.

The relative evaluation value in this case can be calculated as follows, for example. That is, the eligibility determination unit 23 determines the position of the reaction time for one user in the distribution of reaction times for a plurality of users (for example, one user counting from the slowest reaction time among all users). A value indicating the lower percentage of reaction time) is calculated as a relative evaluation value for one user whose eligibility is desired to be determined. In this case, the eligibility determination unit 23 determines that the eligibility as a subject is low for a predetermined number of users or users located within a predetermined ratio, with the one having the fastest reaction time as the upper rank.

<Modification example>
In the above embodiment, the evaluation calculated as the Euclidean distance as a relative evaluation value of the response time for one user with respect to the response time for another user based on the response time of the questionnaire acquired for a plurality of users. An example of calculating the value or the evaluation value output from the machine-learned prediction model has been described, but the position of the response time for one user in the distribution of the response time for multiple users is calculated. May be good. For example, among all users, the number of users counting from the fastest answer time or the users who are located within a predetermined ratio are trusted because they may answer the question without serious consideration. It is possible to determine that the property is low.

Further, in the above embodiment, based on the reaction time until the behavior test execution acquired for the plurality of users, the reaction time for one user is evaluated as a relative evaluation value for the reaction time for another user, and the reaction time is related to the plurality of users. An example of calculating the position of the reaction time for one user in the reaction time distribution has been described, but the evaluation value calculated as the Euclidean distance or the evaluation value output from the machine-learned prediction model is calculated. You may do so.

In addition, based on the response time of the questionnaire acquired for a plurality of users, the response time for one user was evaluated relative to the response time for another user (evaluation value calculated as Euclidean distance, machine learning). The evaluation value output from the prediction model or the evaluation value calculated as the position of the response time for one user in the distribution of the response time for multiple users) is calculated as the evaluation value for the proficiency level for one user. You may try to do it.

In addition, based on the reaction time until the start of execution of the questionnaire acquired for a plurality of users, the reaction time for one user is a relative evaluation value for the reaction time for another user (evaluation value calculated as the Euclidean distance). The evaluation value output from the machine-learned prediction model or the evaluation value calculated as the position of the reaction time for one user in the distribution of the reaction time for multiple users) is the reliability for one user. It may be calculated as an evaluation value or an evaluation value of proficiency level.

In addition, based on the reaction time until the behavior test execution acquired for a plurality of users, the reaction time for one user is a relative evaluation value for the reaction time for another user (evaluation value calculated as Euclidean distance, machine). The evaluation value output from the trained prediction model or the evaluation value calculated as the position of the reaction time for one user in the distribution of the reaction time for multiple users) is evaluated for the reliability of one user. It may be calculated as a value.

Furthermore, based on the execution time of the behavior test acquired for multiple users, the relative evaluation value (evaluation value calculated as the Euclidean distance) of the execution time for one user with respect to the execution time for another user is machine-learned. The evaluation value output from the prediction model or the evaluation value calculated as the position of the response time for one user in the distribution of the response time for multiple users) is the evaluation value for reliability for one user or It may be calculated as an evaluation value of proficiency level.

<Specific example 1 regarding modification>
For example, the eligibility determination unit 23 starts executing the answer to the questionnaire after the instruction is given, instead of calculating the evaluation value of the proficiency level based on the reaction time until the execution function of the behavior test is activated. Based on the reaction time up to the point, the relative evaluation value of the reaction time for one user with respect to the reaction time for another user may be calculated as the evaluation value of the proficiency level for one user.

As with the reaction time until the behavior test is executed, it is assumed that it usually takes a user who has a level of proficiency in using the information processing device to activate the questionnaire execution function in response to an instruction. For users whose reaction time is more than a certain difference from the reaction time, there is a possibility that it takes time to operate the questionnaire execution function, and in that respect, the proficiency level of the information processing device is low. It is possible to estimate.

In this way, the evaluation value of the reliability for one user is calculated based on the response time of the questionnaire, and the evaluation value of the proficiency level for one user is calculated based on the reaction time until the execution function of the questionnaire is activated. By calculating the above, there is an advantage that the eligibility of the user as a subject can be determined from the two viewpoints of reliability and proficiency by conducting the questionnaire.

<Specific example 2 regarding modification>
Instead of calculating the evaluation value of the proficiency level based on the reaction time until the execution function of the behavior test is activated, the eligibility determination unit 23 determines the response time for one user based on the response time of the questionnaire. Relative evaluation value to response time for other users (evaluation value calculated as Euclidean distance, evaluation value output from machine-learned prediction model, or one user in the distribution of response time for multiple users The evaluation value calculated as the position of the response time for one user) may be calculated as the evaluation value of the proficiency level for one user.

This is a constant response time compared to the response time that a user with a normal level of proficiency in using an information processing device would normally take to complete a series of questionnaires consisting of multiple questions. For users with the above differences, it is possible that it takes time to input information for answering the questionnaire, and it is estimated that the proficiency level of the information processing device is low in that respect.

In this case, both the evaluation value of reliability and the evaluation value of proficiency level for one user can be calculated based on the response time of the questionnaire, and the two viewpoints of reliability and proficiency level can be calculated by conducting the questionnaire. It has an advantage that the eligibility of the user as a subject can be determined from the above.

<Specific example 3 regarding modification>
Instead of calculating the reliability evaluation value for one user based on the response time of the questionnaire, the eligibility determination unit 23 takes the execution time of the behavior test (from the start to the end of the behavior test by the user). Relative evaluation value of the execution time for one user to the execution time for another user (evaluation value calculated as the Euclidean distance, evaluation value output from the machine-trained prediction model, or , The evaluation value calculated as the position of the response time for one user in the distribution of the response time for a plurality of users) may be calculated as the evaluation value for the reliability for one user.

Since the PVT test is a test for measuring the reaction time of the user from the time when the figure is presented at the timing determined by the treatment application, the execution time does not change depending on the user. However, depending on the content of the behavior test, the execution time may vary depending on the user. In the case of a behavioral test having such a property, a relative evaluation value regarding the execution time of the behavioral test can be used as an evaluation value of reliability for one user. It can be estimated that users who aim to obtain financial incentives do not take behavioral tests seriously and may finish in a shorter or longer time than usual.

In this case, the reliability evaluation value for one user is calculated based on the behavior test execution time, and the proficiency evaluation value for one user is calculated based on the reaction time until the behavior test execution function is activated. It has an advantage that the user's eligibility as a subject can be judged from the two viewpoints of reliability and proficiency by performing a behavior test.

<Specific example 4 regarding modification>
The eligibility determination unit 23 calculates the evaluation value of the proficiency level based on the reaction time until the execution function of the behavior test is activated, and instead of calculating the evaluation value of the proficiency level, the execution time for one user is based on the execution time of the behavior test. , The relative evaluation value for the execution time for another user may be calculated as the evaluation value for the proficiency level for one user. In the case of the PVT test, the execution time is almost the same regardless of the user's proficiency level, but the execution time may change depending on the content of the behavior test. Therefore, in the case of a behavior test having such a property, it is possible to use the relative evaluation value regarding the execution time of the behavior test as the evaluation value of the proficiency level for one user.

The determination result storage unit 24 stores the result determined by the eligibility determination unit 23 in the auxiliary storage device 204. The result determined by the eligibility determination unit 23 is information indicating a user who may not be eligible as a subject of a clinical trial of a therapeutic application, and may have eligibility. At least one of the information indicating the user determined to be. The evaluation value calculated by the eligibility determination unit 23 may be stored together with the information indicating such a user.

The determination result transmission unit 25 transmits the determination result information stored in the auxiliary storage device 204 by the determination result storage unit 24 to the medical institution terminal 300 in response to a request from the medical institution terminal 300. For example, the determination result transmission unit 25 transmits HTML data including the determination result information to the medical institution terminal 300 in response to a request from the web browser included in the medical institution terminal 300, and makes a determination on the web browser of the medical institution terminal 300. Display the result information.

Here, the eligibility of the user as a subject is judged from both the viewpoint of reliability of whether or not the person is intended to obtain an incentive and the viewpoint of proficiency in the operation of the information processing device. In this case, the determination result transmission unit 25 transmits information to the medical institution terminal 300 so that each determination result can be understood from both viewpoints. The medical institution refers to this determination result information to determine which user is excluded from the subject.

FIG. 5 is a flowchart showing an operation example of the user terminal 100 according to the first embodiment configured as described above. The flowchart shown in FIG. 5 is not the various modified examples described above, but shows an operation example related to the embodiment described before the modified example. The operation of the flowchart shown in FIG. 5 is executed in each of the plurality of user terminals 100.

The treatment application installed on the user terminal 100 operates in the background even when it is not started by clicking the start icon or the like, and is preset as a timing for instructing the execution of a predetermined process. It monitors whether or not the predetermined timing has been reached (step S1).

When the predetermined timing is reached, the process execution instruction unit 11 instructs the execution of the predetermined process by displaying a message on the display unit 106 (step S2). Next, the process execution unit 12 determines whether or not the process instructed by the process execution instruction unit 11 is related to the behavior test (step S3). When what is instructed by the process execution instruction unit 11 is the execution of the behavior test, the process execution unit 12 starts counting the elapsed time from the instruction (step S4).

After that, the process execution unit 12 monitors whether or not the instructed behavior test execution function has been activated by the user (step S5). When activated, the processing execution unit 12 notifies the execution result storage unit 22 of the count value. In response to this, the execution result storage unit 22 takes a reaction time (count value of elapsed time) from the instruction to execute the action test by the process execution instruction unit 11 to the activation of the action test execution function by the user. ) Is stored in the auxiliary storage device 104 (step S6).

In step S3, when it is determined that the process instructed by the process execution instruction unit 11 is not related to the behavior test (that is, it is related to the questionnaire), the process execution unit 12 has the instructed questionnaire execution function. Is monitored by the user (step S7). When activated, the process execution unit 12 starts counting the elapsed time from the activation of the questionnaire execution function (step S8).

After that, the processing execution unit 12 monitors whether or not the response to the questionnaire is completed (step S9). When the answer is completed, the processing execution unit 12 notifies the execution result storage unit 22 of the count value. In response to this, the execution result storage unit 22 stores the answer time (count value of elapsed time) taken from the start of the questionnaire execution function and the start of the answer by the user to the end of the answer in the auxiliary storage device 104. Is stored in (step S10).

After step S6 or S10, the execution result transmission unit 14 determines the eligibility as a subject of the clinical trial for a certain period of time (for example, one week after the therapeutic application is installed on the user terminal 100). Is determined (step S11). If a certain period has not yet elapsed, the process returns to step S1. On the other hand, when a certain period of time has elapsed, the execution result transmission unit 14 transmits the execution result information stored in the auxiliary storage device 104 to the communication unit clinical trial management server 200 (step S12). As a result, the processing of the flowchart shown in FIG. 5 is completed.

FIG. 6 is a flowchart showing an operation example of the clinical trial management server 200 according to the first embodiment configured as described above. The execution result acquisition unit 21 acquires the execution result information transmitted from the user terminal 100 by the execution result transmission unit 14 (step S21). The execution result storage unit 22 stores the execution result information acquired by the execution result acquisition unit 21 in the auxiliary storage device 204 (step S22).

The eligibility determination unit 23 determines whether or not a sufficient number of execution result information has been stored in the auxiliary storage device 204 (step S23). For example, the clinical trial management server 200 is made to grasp the number of therapeutic applications downloaded from a certain download site, and it is determined whether or not the same number of execution result information as the number of downloads is stored in the auxiliary storage device 204. You can do it. Alternatively, it may be determined whether or not the execution result information of a predetermined ratio or more is stored in the auxiliary storage device 204 with respect to the number of downloads, or the execution result information of a predetermined number or more as an absolute number may be stored in the auxiliary storage device 204. It may be determined whether or not it is stored in.

Here, if it is determined that a sufficient number of execution result information is not yet stored in the auxiliary storage device 204, the process returns to step S21. On the other hand, when it is determined that a sufficient number of execution result information has been stored, the eligibility determination unit 23 is a person who aims to obtain an incentive based on the execution result information stored in the auxiliary storage device 204. The eligibility of the user as a subject is determined from at least one viewpoint of reliability and proficiency in operating the information processing device (step S24), and the determination result is stored in the auxiliary storage device 204 (step). S25). As a result, the processing of the flowchart shown in FIG. 6 is completed. After that, when the medical institution terminal 300 requests to acquire the determination result at an arbitrary timing, the determination result transmission unit 25 transmits the determination result information stored in the auxiliary storage device 204 to the medical institution terminal 300. ..

As described in detail above, in the first embodiment, the user of the user terminal 100 on which the medical software (treatment application) is installed is instructed to execute a predetermined process using the treatment application. The clinical trial management server 200 acquires execution result information (response time information) representing the result when a predetermined process is executed by the user in response to the instruction. Then, based on the acquired execution result information, a clinical trial of medical software is performed from the viewpoint of reliability of whether or not the person is intended to obtain an incentive and proficiency in operation of an information processing device. The eligibility as a subject to participate in is judged.

According to the first embodiment configured in this way, in conducting a clinical trial of a therapeutic application, when the user actually uses the therapeutic application and executes a process in response to a given instruction, the result is obtained. Based on the execution result information acquired as, the eligibility as a subject is determined from the viewpoint of reliability of whether or not the person aims to obtain an incentive and from the viewpoint of proficiency in the operation of the information processing device. To. Thereby, according to the first embodiment, it is possible to solve a problem peculiar to a clinical trial of medical software and appropriately determine whether or not a user of an information processing apparatus is eligible as a subject.

In the above embodiment, the response time information (reaction time until the execution function of the instructed process is activated) is used as the execution result information indicating the result when the user executes the predetermined process in response to the instruction. An example of using (execution time taken to execute the instructed process) has been described, but the instruction compliance status information may be used in place of or in addition to this. The instruction compliance status information is information indicating the instruction compliance rate, which is the ratio of the number of times the user actually executed a predetermined process in response to a plurality of instructions.

In this case, the eligibility determination unit 23 calculates at least one of the reliability evaluation value and the proficiency evaluation value for the user by performing predetermined statistical processing based on the instruction compliance status information, and the calculated evaluation. The eligibility of the user as a subject is determined based on the value.

Specifically, the eligibility determination unit 23 refers to the instruction compliance rate for one user and the instruction compliance rate for other users based on the instruction compliance status information acquired by the execution result acquisition unit 21 for a plurality of users. The relative evaluation value is calculated as at least one of the reliability evaluation value and the proficiency evaluation value for one user.

The relative evaluation value in this case is an evaluation value calculated as an Euclidean distance, an evaluation value output from a machine-learned prediction model, or an instruction regarding a plurality of users, as in the case of calculation based on the response time information. It can be calculated as an evaluation value calculated as the position of the instruction compliance rate for one user in the distribution of the compliance rate. Regarding the position of the instruction compliance rate for one user, the eligibility determination unit 23 sets the one with the higher instruction compliance rate as the upper rank, and counts from the lowest to the predetermined number of users or the users located within the predetermined ratio as subjects. It is judged that the eligibility as is low.

(Second embodiment)
Next, a second embodiment of the present invention will be described with reference to the drawings. In the second embodiment, in addition to determining eligibility as a subject from the viewpoint of reliability as to whether or not the person is intended to obtain an incentive and from the viewpoint of proficiency in operating the information processing device, the second embodiment determines eligibility as a subject. The eligibility of a user as a subject is determined from the viewpoint of whether or not the user is affected by a disease to be treated through the use of medical software.

Regarding screening to select appropriate subjects when conducting clinical trials, clinical trials of therapeutic apps also have the following specific problems. That is, in the case of a therapeutic application, a subject is often extracted from unspecified candidates who wish to use the application, and it is known that a doctor is already suffering from treatment as in Patent Documents 1 and 2. It is not always the case that the subject is extracted from the patients in the above. Therefore, there is a problem that it is difficult to objectively judge whether or not the person is suffering from the target disease. The second embodiment aims to solve such a problem as well.

FIG. 7 is a diagram showing a network configuration example of a clinical trial system to which the clinical trial eligibility determination system according to the second embodiment is applied. As shown in FIG. 7, the clinical trial system according to the second embodiment manages the user terminal 100'and the wearable terminal 110 (corresponding to the second information processing device within the scope of the patent claim) used by the user and the clinical trial. A clinical trial management server 200'to be performed and a medical institution terminal 300 used by a medical institution are provided, and a user terminal 100', a clinical trial management server 200', and a doctor's terminal 300 are connected via a communication network 400. ..

The user terminal 100'and the wearable terminal 110 are wirelessly connected by using a wireless communication technology such as Bluetooth (registered trademark). As a result, state information (details will be described later) representing the physical condition of the user detected by the wearable terminal 110 is wirelessly transmitted to the user terminal 100', and this state information is transmitted from the user terminal 100'to the clinical trial management server 200. It is supposed to be sent to'.

FIG. 8 is a block diagram showing a functional configuration example of the user terminal 100'according to the second embodiment. FIG. 9 is a block diagram showing a functional configuration example of the clinical trial management server 200'according to the second embodiment. It should be noted that, in FIGS. 8 and 9, those having the same reference numerals as those shown in FIGS. 3 and 4, respectively, have the same functions, and therefore, duplicate description will be omitted here.

As shown in FIG. 8, the user terminal 100'according to the second embodiment further includes a state information detection unit 15, a state information storage unit 16, and a state information transmission unit 17 as its functional configuration. Further, the clinical trial management server 200'according to the second embodiment further includes a state information acquisition unit 26 and a state information storage unit 27 as its functional configuration, and the eligibility determination unit 23 replaces the eligibility determination unit 23. 'Has.

The wearable terminal 110 shown in FIG. 7 is a wearable information processing device provided with a sensor that detects a user's physical condition. The sensor is, for example, an acceleration sensor, an angular velocity sensor, an activity amount sensor, or the like. When the user wears and uses the wearable terminal 110 (when the power is turned on), these sensors are used to detect the user's physical condition such as acceleration, angular velocity, and amount of activity associated with the user's physical activity. The represented state information is continuously detected. The state information detected by each sensor is transmitted to the user terminal 100'by wireless communication.

It should be noted that the configuration is such that the user's state information is detected, and it is not always necessary to use the wearable terminal 110. For example, if the portable user terminal 100'is provided with the above-mentioned sensor, the wearable terminal 110 can be omitted.

The state information detection unit 15 of the user terminal 100'detects the state information transmitted from the wearable terminal 110. When the user terminal 100'is provided with the above-mentioned sensor, the state information detection unit 15 detects the state information output from the sensor. The state information storage unit 16 stores the state information detected by the state information detection unit 15 in the auxiliary storage device 104.

The state information transmission unit 17 transmits the state information stored in the auxiliary storage device 104 to the clinical trial management server 200'. The timing at which the state information transmission unit 17 transmits the state information to the clinical trial management server 200'may be the same as the timing at which the execution result transmission unit 14 transmits the execution result information to the clinical trial management server 200'. That is, for example, the state information may be transmitted every day or every few days at a predetermined time, or the state information may be transmitted when a predetermined fixed period has elapsed.

The status information acquisition unit 26 of the clinical trial management server 200'acquires the status information transmitted by the status information transmission unit 17 from the plurality of user terminals 100'. That is, the state information acquisition unit 26 acquires state information representing the physical state of the user while the wearable terminal 110 is in use from the user terminal 100'. The state information storage unit 27 stores the state information acquired by the state information acquisition unit 26 in the auxiliary storage device 204.

The eligibility determination unit 23'performs the determination process described in the first embodiment. In addition to this, the eligibility determination unit 23'is performed through the use of medical software based on the state information acquired by the state information acquisition unit 26 and stored in the auxiliary storage device 204 by the state information storage unit 27. The eligibility of the user as a subject is determined from the viewpoint of whether or not the user is affected by the disease to be treated.

For example, the eligibility determination unit 23'sets the state information of a user who is known to be suffering from a specific disease among the state information stored in the auxiliary storage device 204 as correct answer data, and features the feature amount from the correct answer data. To build a prediction model by generating and performing machine learning. This prediction model is a model in which an evaluation value regarding the presence or absence of a disease is output when the user's state information is input.

The feature amount is appropriately set according to the type of target disease. For example, when the target disease is Parkinson's disease, a feature quantity representing tremor (hand tremor) is generated based on acceleration or angular velocity. In addition, when the target disease is sleep disorder, depression, dementia, etc., a feature amount such that the amount of activity during the day decreases is generated based on the amount of activity.

The eligibility determination unit 23'calculates an evaluation value for one user by inputting state information about one user who wants to determine eligibility into the prediction model, and based on the calculated evaluation value, suffers from a disease. The eligibility of the user as a subject is judged from the viewpoint of presence or absence.

It should be noted that, by performing predetermined statistical processing based on the length of time that the state information is acquired, at least one of the evaluation value of reliability and the evaluation value of proficiency with respect to the user is calculated, and the calculated evaluation value is obtained. In consideration of the above, the eligibility of the user as a subject may be determined from the viewpoint of at least one of reliability and proficiency.

It can be said that the length of time that the state information is acquired is the length of time that the user wears the wearable terminal 110. That is, this is to estimate whether or not the user is seriously wearing the wearable terminal 110, and can be considered in the same manner as the above-mentioned instruction compliance rate. For example, the eligibility determination unit 23'calculates the length of time for which the state information is acquired as the wearing time of the wearable terminal 110 based on the state information acquired for a plurality of users, and the calculated wearing time information. Based on, the relative evaluation value of the wearing time for one user with respect to the wearing time for another user is calculated as at least one of the reliability evaluation value and the proficiency evaluation value for one user.

The relative evaluation value in this case is the evaluation value calculated as the Euclidean distance, the evaluation value output from the machine-learned prediction model, or the wearing time for one user in the distribution of wearing time for multiple users. It is possible to calculate as an evaluation value calculated as the position of. Regarding the wearing position for one user, the eligibility determination unit 23'sets the one with the longer wearing time as the upper rank, and sets the predetermined number of users or the users located within the predetermined ratio as the subjects, counting from the lowest rank. Judged as low eligibility.

According to the second embodiment described above, whether or not the person aims to obtain an incentive based on the execution result information acquired through the use of the treatment application installed on the user terminal 100'. In addition to determining eligibility as a subject from the viewpoint of reliability and proficiency in operating the information processing device, the physical condition of the user detected by the sensor of the wearable terminal 110 or the user terminal 100'is determined. Based on the state information represented, the eligibility of the user as a subject can be determined from the viewpoint of whether or not the user is affected by the disease.

In addition, based on the length of time that the state information is acquired, the evaluation value of reliability and the evaluation value of proficiency of the user are calculated, and the calculated evaluation value is added to determine the eligibility of the user as a subject. When configured to determine, from the viewpoint of reliability, proficiency, and morbidity to illness, based on the state information representing the physical condition of the user detected by the sensor of the wearable terminal 110 or the user terminal 100'. The eligibility of the user as a subject can be determined from the viewpoint of the presence or absence of.

In the second embodiment, the user is qualified as a subject from the viewpoint of whether or not he / she is afflicted with a disease based on the state information continuously acquired while the user is using the wearable terminal 110 or the user terminal 100'. Although an example of determining sex has been described, the present invention is not limited thereto. For example, in a configuration in which the user terminal 100'is provided with an acceleration sensor or an angular velocity sensor, the wearable terminal 110 is omitted, and when a predetermined process is executed by the user in response to an instruction from the process execution instruction unit 11 of the user terminal 100'. The state information indicating the physical state of the user may be acquired.

In this case as well, the eligibility determination unit 23'is a person who aims to acquire an incentive based on the execution result information acquired by the execution result acquisition unit 21 and the state information acquired by the state information acquisition unit 26. Eligibility as a user's subject in terms of reliability and at least one proficiency in the operation of information processing equipment and whether or not they are affected by the disease to be treated through the use of medical software. To judge.

Further, in the second embodiment, the wearable terminal 110 or the portable user terminal 100'provides an acceleration sensor, an angular velocity sensor, and an activity amount sensor, and the user's acceleration, angular velocity, activity amount, etc. detected by these sensors. Although an example of determining the eligibility of a user as a subject from the viewpoint of the presence or absence of illness based on the state information representing the physical state has been described, the present invention is not limited to this. For example, as shown in FIGS. 10 and 11, the wearable terminal 110 or the portable user terminal 100 ”is further provided with a position detection sensor such as GPS, and position information indicating the user's existing position detected by the position detection sensor. Is transmitted from the user terminal 100 "to the clinical trial management server 200" so that the eligibility of the user as a subject is determined from the viewpoint of the presence or absence of illness based on the location information in addition to the user's status information. May be good.

10 and 11 are block diagrams showing a functional configuration example of the user terminal 100 "and the clinical trial management server 200" in this case. Note that, in FIGS. 10 and 11, those having the same reference numerals as those shown in FIGS. 8 and 9, respectively, have the same functions, and therefore, duplicate description will be omitted here.

The user terminal 100 ”shown in FIG. 10 further includes a position information detection unit 15A, a position information storage unit 16A, and a position information transmission unit 17A as its functional configuration. Further, the clinical trial management server 200 ”shown in FIG. Further includes a position information acquisition unit 26A and a position information storage unit 27A as its functional configuration, and also includes a qualification determination unit 23 "instead of the qualification determination unit 23'.

The position information detection unit 15A of the user terminal 100 "detects the user's position information transmitted from the wearable terminal 110. When the user terminal 100" includes a position detection sensor, the state information detection unit 15A is a user. The user's position information output from the position detection sensor of the terminal 100 "is detected. The position information storage unit 16A stores the user's position information detected by the position information detection unit 15A in the auxiliary storage device 104.

The location information transmission unit 17A transmits the location information stored in the auxiliary storage device 104 to the clinical trial management server 200 ”. The timing at which the location information transmission unit 17A transmits the location information to the clinical trial management server 200” is executed. The timing may be the same as the timing at which the result transmission unit 14 and the status information transmission unit 17 transmit the execution result information and the status information to the clinical trial management server 200 ”.

The location information acquisition unit 26A of the clinical trial management server 200 "acquires the user's location information transmitted by the location information transmission unit 17A from the plurality of user terminals 100", respectively. That is, the position information acquisition unit 26A acquires the position information indicating the user's existing position while the wearable terminal 110 is in use from the user terminal 100 ”. The position information storage unit 27A is the user acquired by the position information acquisition unit 26A. The position information of is stored in the auxiliary storage device 204.

The eligibility determination unit 23 "performs the determination process described in the first embodiment. In addition, the eligibility determination unit 23" is acquired by the state information acquisition unit 26 and assisted by the state information storage unit 27. Treatment performed through the use of medical software based on the state information stored in the storage device 204 and the position information acquired by the position information acquisition unit 26A and stored in the auxiliary storage device 204 by the position information storage unit 27A. The eligibility of the user as a subject is determined from the viewpoint of whether or not the user is affected by the target disease.

For example, the eligibility determination unit 23 ”sets the state information and position information of a user known to be suffering from a specific disease as correct answer data among the state information and position information stored in the auxiliary storage device 204. A prediction model is constructed by generating feature quantities from this correct answer data and performing machine learning. This prediction model outputs an evaluation value regarding the presence or absence of a disease when the user's state information and position information are input. It is a model like.

The feature amount is appropriately set according to the type of target disease. As described above, when the target disease is Parkinson's disease, a feature amount representing tremor (hand tremor) is generated based on acceleration or angular velocity. In addition, when the target disease is sleep disorder, depression, dementia, etc., a feature amount such that the amount of activity during the day decreases is generated based on the amount of activity.

In addition, when the target illness is a part of psychiatric illness such as bipolar disorder, the geographical movement distance and movement pattern peculiar to the case of suffering from bipolar disorder are represented based on the user's location information. Generate such features. Specifically, when the depressive symptom becomes severe in bipolar disorder, the movement distance becomes short and the movement pattern becomes monotonous. Therefore, a feature amount representing such a movement distance or movement pattern is generated. Regarding the movement pattern, for example, the number of places visited and the number of visits are detected based on the location information, and the entropy of a small value calculated from these detected values is used as the movement pattern when suffering from bipolar disorder. Can be generated as a feature quantity indicating that is monotonous. In addition, since the amount of activity decreases as the depressive symptom becomes more severe in bipolar disorder, it is possible to use the feature amount related to the activity amount together as the feature amount in the case of suffering from bipolar disorder.

The eligibility determination unit 23 ”calculates the evaluation value for one user by inputting the state information and the position information for one user who wants to determine eligibility into the prediction model, and based on the calculated evaluation value, the disease. The eligibility of the user as a subject is determined from the viewpoint of the presence or absence of morbidity.

It should be noted that the reliability of the user is evaluated by performing predetermined statistical processing based on the length of time that the state information and the position information are acquired (the length of time that the user wears the wearable terminal 110). At least one of the value and the proficiency evaluation value may be calculated, and the calculated evaluation value may be added to determine the eligibility of the user as a subject from at least one viewpoint of reliability and proficiency. ..

Further, in the first and second embodiments, the reliability evaluation value and the proficiency evaluation value are both calculated relative evaluation values compared with other users, and the user is based on the relative evaluation values. Although an example of determining the eligibility of a user as a subject has been described, the eligibility of a user as a subject may be determined based on an absolute evaluation value that is not a comparison with other users.

For example, whether the reaction time from when the instruction is given until the execution function of the predetermined process is activated is longer (or shorter) than the predetermined value, and whether the execution time of the predetermined process is longer than the predetermined value. Reliability or proficiency may be evaluated based on whether or not (or whether or not it is short), whether or not the wearing time of the wearable terminal 110 is longer than a predetermined value (or whether or not it is shorter), and the like. ..

When determining the eligibility of a user as a subject based on the absolute evaluation value in this way, the execution result acquisition unit 21, the eligibility determination unit 23, 23', 23 ", the state information acquisition unit 26, and the position information acquisition unit The user terminals 100, 100', 100 "may have the function of 26A, and the eligibility determination process may be performed on the user terminals 100, 100', 100". In this case, the eligibility determination result is managed in the clinical trial. It is transmitted to the server 200, 200', 200 ", and the determination result information is stored in the auxiliary storage device 204.

Further, in the first and second embodiments, as an example of the medical software, a therapeutic application aimed at treating the patient through improvement of the lifestyle has been described, but the therapeutic application is a living application. It is not limited to those intended to be treated through improvement of habits. In addition, medical software does not treat diseases by itself, but even if it is an information-providing application that collects patient's biological information, behavior information, questionnaire response information, etc. and sends it to a server device. Good.

In addition, the first and second embodiments are merely examples of embodiment of the present invention, and the technical scope of the present invention should not be interpreted in a limited manner by these. It is something that does not become. That is, the present invention can be implemented in various forms without departing from its gist or its main features.

11 Processing execution instruction unit 12 Processing execution unit 13 Execution result storage unit 14 Execution result transmission unit 15 Status information detection unit 15A Position information detection unit 16 Status information storage unit 16A Position information storage unit 17 Status information transmission unit 17A Position information transmission unit 21 Execution result acquisition unit 22 Execution result storage unit 23, 23', 23 "Eligibility judgment unit 24 Judgment result storage unit 25 Judgment result transmission unit 26 Status information acquisition unit 26A Position information acquisition unit 27 State information storage unit 27A Position information storage unit 100, 100', 100 "user terminal (information processing device)
110 Wearable terminal (second information processing device)
200, 200', 200 "Clinical trial management server 300 Medical institution terminal

Claims (16)

A system that determines eligibility as a subject to participate in clinical trials of medical software.
A process execution instruction unit that instructs a user of an information processing device in which the medical software is installed to execute a predetermined process using the medical software.
An execution result acquisition unit that acquires execution result information representing the result when the predetermined process is executed by the user in response to an instruction from the process execution instruction unit, and an execution result acquisition unit.
Based on the execution result information acquired by the execution result acquisition unit, from the viewpoint of reliability of whether or not the person is intended to acquire an incentive and at least one viewpoint of proficiency in operation of the information processing apparatus. A clinical trial eligibility determination system including an eligibility determination unit for determining the eligibility of the user as a subject. The execution result information includes the response time information indicating the response time when the user executes the predetermined process in response to the instruction.
The eligibility determination unit calculates at least one of the reliability evaluation value and the proficiency evaluation value for the user by performing predetermined statistical processing based on the response time information, and the calculated evaluation. The clinical trial eligibility determination system according to claim 1, wherein the eligibility of the user as a subject is determined based on the value. Based on the response time information acquired by the execution result acquisition unit for a plurality of users, the eligibility determination unit determines the relative evaluation value of the response time for one user to the response time for another user. The clinical trial eligibility determination system according to claim 2, further comprising calculating as at least one of the reliability evaluation value and the proficiency evaluation value for the one user. The eligibility determination unit responds to the size of the difference between the statistical value regarding the distribution of the response time for the other user who executed the predetermined process under monitoring and the value of the response time for the one user. The clinical trial eligibility determination system according to claim 3, wherein the relative evaluation value is calculated. The eligibility determination unit performs machine learning using the response time of the other user who has executed the predetermined process under monitoring as correct answer data, and when the response time information is input, the relative evaluation is performed. Claim 3 is characterized in that a relative evaluation value for the one user is calculated by generating a prediction model for which a value is output and inputting the response time information for the one user into the prediction model. The clinical trial eligibility determination system described in. The eligibility determination unit is characterized in that a value indicating the position of the response time for the one user in the distribution of the response time for the plurality of users is calculated as a relative evaluation value for the one user. The clinical trial eligibility determination system according to claim 3. The clinical trial eligibility determination according to claim 2, wherein the response time information includes reaction time information indicating the reaction time until the user starts executing the predetermined process in response to the instruction. system. The clinical trial eligibility according to claim 2, wherein the response time information includes execution time information indicating the execution time required for the user to complete the execution of the predetermined process in response to the instruction. Judgment system. The process execution instruction unit instructs the user of the information processing apparatus to execute a predetermined process using the medical software a plurality of times.
The execution result information includes instruction compliance status information indicating an instruction compliance rate, which is a ratio of the number of times the user actually executed the predetermined process in response to a plurality of instructions.
The eligibility determination unit calculates and calculates at least one of the reliability evaluation value and the proficiency evaluation value for the user by performing predetermined statistical processing based on the instruction compliance status information. The clinical trial eligibility determination system according to claim 1 or 2, wherein the eligibility of the user as a subject is determined based on the evaluation value. Based on the instruction compliance status information acquired by the execution result acquisition unit for a plurality of users, the eligibility determination unit relatives the instruction compliance rate for one user to the instruction compliance rate for other users. The clinical trial eligibility determination system according to claim 9, wherein the evaluation value is calculated as at least one of the reliability evaluation value and the proficiency evaluation value for the one user. A state information acquisition unit that acquires state information representing the physical state of the user when the predetermined process is executed by the user in response to an instruction from the process execution instruction unit is further provided.
Whether or not the eligibility determination unit is a person who aims to acquire an incentive based on the execution result information acquired by the execution result acquisition unit and the status information acquired by the status information acquisition unit. Eligibility as a subject of the user in terms of reliability and at least one of the proficiency levels regarding the operation of the information processing device, and whether or not the user is affected by a disease to be treated through the use of the medical software. The clinical study eligibility determination system according to claim 1, wherein the determination is made. Further provided with a state information acquisition unit for acquiring state information representing the physical state of the user while using the information processing device or the portable or wearable second information processing device.
The above eligibility judgment unit
Based on the state information acquired by the state information acquisition unit, the eligibility of the user as a subject is determined from the viewpoint of whether or not the user is affected by the disease to be treated through the use of the medical software. With
By performing a predetermined statistical process based on the length of time during which the state information is acquired, at least one of the reliability evaluation value and the proficiency evaluation value for the user was calculated and calculated. The clinical trial eligibility determination system according to claim 2 or 9, wherein the eligibility of the user as a subject is determined from at least one viewpoint of the reliability and the proficiency level in consideration of the evaluation value. .. Further, a position information acquisition unit for acquiring position information indicating the existence position of the user while the information processing device or the second information processing device is in use is provided.
The above eligibility judgment unit
Based on the state information acquired by the state information acquisition unit and the position information acquired by the position information acquisition unit, the eligibility of the user as a subject is determined from the viewpoint of the presence or absence of morbidity with the disease. ,
By performing predetermined statistical processing based on the length of time during which the state information and the location information are acquired, at least one of the reliability evaluation value and the proficiency evaluation value for the user is calculated. The clinical trial eligibility according to claim 12, wherein the eligibility of the user as a subject is determined from at least one viewpoint of the reliability and the proficiency level in consideration of the calculated evaluation value. Judgment system. A computer-based method of determining eligibility as a subject to participate in clinical trials of medical software.
A step in which a process execution instruction unit of an information processing device in which the medical software is installed instructs a user of the information processing device to execute a predetermined process using the medical software.
It represents the result when the execution result acquisition unit of the information processing device or the server device connected to the information processing device via the communication network executes the predetermined process by the user in response to an instruction from the process execution instruction unit. Steps to get execution result information and
The reliability of whether or not the eligibility determination unit of the information processing device or the server device is a person who aims to acquire an incentive based on the execution result information acquired by the execution result acquisition unit, and the above. A method for determining eligibility for a clinical test, which comprises a step of determining eligibility of the user as a subject from at least one viewpoint of proficiency in operating an information processing device. A device that determines eligibility as a subject to participate in clinical trials of medical software.
Execution result representing the result when the predetermined process is executed by the user of the information processing apparatus in which the medical software is installed in response to the instruction to execute the predetermined process using the medical software. Execution result acquisition unit to acquire information and
Based on the execution result information acquired by the execution result acquisition unit, from at least one viewpoint of reliability of whether or not the person is intended to acquire an incentive and proficiency in operation of the information processing apparatus. A clinical trial eligibility determination device including an eligibility determination unit for determining the eligibility of the user as a subject. A program to determine eligibility as a subject to participate in clinical trials of medical software.
Execution result representing the result when the predetermined process is executed by the user of the information processing apparatus in which the medical software is installed in response to the instruction to execute the predetermined process using the medical software. Based on the execution result information acquisition means for acquiring information and the execution result information acquired by the execution result information acquisition means, the reliability of whether or not the person aims to acquire an incentive and the information processing apparatus. A clinical test eligibility determination program for operating a computer as an eligibility determination means for determining the eligibility of the user as a subject from at least one viewpoint of proficiency in the operation of the above.

Images