Clinical trial and test subject selection support system and selection support server used for the same

Abstract

To smoothly select a candidate suited to conditions for a clinical trial subject.SOLUTION: A clinical trial and test subject selection support system comprises: a candidate extraction unit 12 that extracts a candidate suited to subject conditions and notifies a pharmacy terminal 4 of the candidate, by using personal data including personal attribute information, diagnostic result information, case history information, and medication history information of potential clinical trial and test subjects; and a questionnaire answer creation unit 13 that creates answers to a questionnaire by using the personal data of the extracted candidate and the medication history information input from the pharmacy terminal 4. The clinical trial and test subject selection support system not only extracts the candidate suited to the subject conditions by using the personal data of the potential clinical trial and test subjects, but also creates the answers to the questionnaire that are to be subsequently created by the extracted candidate. The clinical trial and test subject selection support system creates the answers to the questionnaire on the basis of the accurate personal data of the candidate and the accurate medication history information additionally input from a pharmacy, and thereby can accurately determine the suitability of the candidate as a clinical trial and test subject on the basis of the details of the answers.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a selection support system for clinical trial / clinical study subjects and a selection support server used therein, and is particularly suitable for use in a system for supporting the process of selecting subjects for clinical trials or clinical trials (hereinafter referred to as clinical trial / clinical study subjects). [Background technology]

[0002] Generally, recruitment of subjects for clinical trials is carried out by patient recruitment organizations (PROs) commissioned by medical institutions, pharmaceutical companies, contract research organizations (CROs), site management organizations (SMOs), etc.

[0003] In order to expand the pool of candidates who can be selected as subjects, PROs widely solicit registrations through newspapers, magazines, television, websites, etc. Then, from the information acquired at the time of registration (age, sex, location, allergies, medical history, medical history, current medications, etc.), PROs extract candidates who meet the prerequisites for the clinical trial and provide them with information to encourage them to participate in the trial. After that, PROs conduct questionnaires, advance interviews, and medical examinations on the candidates who respond, and ultimately select those who meet the conditions for the clinical trial as test subjects and clinical trial subject candidates.

[0004] However, in recent clinical trials, the subject conditions have become more complex, making it more difficult to select suitable candidates and securing the required number of subjects. In particular, since the questionnaire contains many questions about specialized content and past test results, it is difficult for candidates to enter accurate answers to all questions. Therefore, candidates who are thought to meet the subject conditions based on the questionnaire results or who are unclear whether they meet the subject conditions are often not selected in the subsequent pre-interviews and medical examinations.

[0005] There are known systems that extract candidate subjects that meet certain conditions from patient information such as the name of the target disease, age, and sex, prescription and dispensing information, or electronic medical record information (see, for example, Patent Documents 1 to 3). There are also known systems that screen candidate clinical trial subjects using patient information extracted from a medical fee claim system (see, for example, Patent Document 4), and systems that screen candidate clinical trial subjects using medical checkup data of various measurements (blood pressure, body temperature, weight, BMI, blood glucose level, body fat, cholesterol level, neutral fat, GOT, GPT, uric acid level, Hba1c, uric acid level, eyesight, allergies, etc.) (see, for example, Patent Document 5).

[0006] However, even if subject candidates are extracted using the systems described in Patent Documents 1 to 5, it is necessary to select subjects who meet the subject conditions by conducting questionnaires, preliminary interviews, medical examinations, etc., and the above-mentioned problems cannot be solved. If a person proceeds to a subsequent preliminary interview or medical examination due to inaccurate answers to the questionnaire, and is often judged to be unsuitable as a subject, there is a problem that the subject selection process becomes wasteful and it takes a lot of time to secure the required number of subjects. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2007-26172 A [Patent Document 2] JP 2016-24663 A [Patent Document 3] Patent Publication No. 2022-10023 [Patent Document 4] JP 2003-337864 A [Patent Document 5] JP 2012-248005 A Summary of the Invention [Problem to be solved by the invention]

[0008] The present invention has been made to solve such problems, and aims to make it possible to more smoothly select candidates who meet the subject requirements for clinical trials. [Means for solving the problem]

[0009] In order to solve the above-mentioned problems, the present invention uses personal data including personal attribute information of potential clinical trial subjects, medical examination or health check diagnosis result information, medical history information, and medication history information to extract candidates who meet the set subject conditions, notify the pharmacy terminal of the information of the extracted candidates, and generate questionnaire responses using the personal data of the extracted candidates and additional medication history information entered from the pharmacy terminal. Effect of the Invention

[0010] According to the present invention configured as described above, not only are candidates who meet the subject conditions extracted using the personal data stored in advance for a potential group of clinical trial subjects, but also the answers to the questionnaire that the extracted candidates will fill out later are generated. The contents of the questionnaire answers are generated based on accurate personal data including the candidate's personal attribute information, diagnosis result information, medical history information, and medication history information, and accurate medication history information additionally input from the dispensing pharmacy terminal, so that suitability as a clinical trial subject can be accurately determined based on the contents of the questionnaire answers. This makes it possible to prevent wasteful processing, such as moving the subject selection process beyond the questionnaire for candidates who are not suitable as clinical trial subjects, and makes it possible to more smoothly select candidates who meet the subject conditions. [Brief description of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of the overall configuration of a subject selection support system according to a first embodiment. [Diagram 2] 2 is a block diagram showing an example of a functional configuration of a selection support server according to the first embodiment. FIG. [Diagram 3] 4 is a flowchart showing an example of the operation of the selection support server and the dispensing pharmacy terminal according to the first embodiment. [Figure 4] FIG. 11 is a diagram illustrating an example of the overall configuration of a subject selection support system according to a second embodiment. [Diagram 5] 13] FIG. 13 is a block diagram showing an example of a functional configuration of a selection support server according to a second embodiment. [Figure 6] FIG. 11 is a diagram showing an example of a condition setting screen provided by a condition setting unit in the second embodiment. [Figure 7] FIG. 11 is a diagram showing another example of a condition setting screen provided by a condition setting unit in the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] (First embodiment) A first embodiment of the present invention will now be described with reference to the drawings. Fig. 1 is a diagram showing an example of the overall configuration of a clinical trial / clinical trial subject selection support system (hereinafter referred to as the subject selection support system) according to the first embodiment.

[0013] 1, the subject selection support system according to the first embodiment includes a selection support server 1, a personal data management server 2, a PRO server 3, and a dispensing pharmacy terminal 4 used in a plurality of pharmacies. The selection support server 1, the personal data management server 2, the PRO server 3, and the dispensing pharmacy terminal 4 are connected to a communication network 10 such as the Internet or a mobile phone network.

[0014] The personal data management server 2 includes a personal data storage unit 20, and stores and manages personal data of potential clinical trial subjects in the personal data storage unit 20. Potential clinical trial subjects are, for example, users who use a medicine notebook app. The medicine notebook app is a medicine notebook application that can be downloaded to a smartphone and has a basic function of recording when, where, what medicine, and how much was prescribed. In addition to the basic function, the medicine notebook app has various functions, including a function of sending a prescription and reserving dispensing, a function of managing the period of taking medicine and the record of taking medicine on a calendar, and a function of recording and managing information such as blood pressure, blood glucose level, pulse, weight, body fat percentage, body temperature, physical condition, and dietary content.

[0015] The personal data is data uploaded to the personal data management server 2 through, for example, a medicine notebook app, and includes personal attribute information, medical examination or health check diagnosis result information, medical history information, and medication history information. This information includes information recorded in the medicine notebook app, as well as information acquired by the medicine notebook app in cooperation with servers of related institutions such as My Number Portal, medical institutions, and dispensing pharmacies. As an example, the following information is stored in the personal data storage unit 20.

[0016] ◇ Basic information (name, gender, age, date of birth, blood type, height, weight, BMI, location, nationality, etc.) ◇Measured or entered information such as blood pressure, blood sugar level, pulse, weight, body fat percentage, body temperature, atopy, physical condition, diet, and activity (work, bathing, etc.) ◇Allergies, medical history, pregnancy, breastfeeding, medical history (prescribed medical institution, dispensing pharmacy), vaccination history, smoking status (smoking period), wearing glasses or contact lenses, clinical trial history, etc. ◇Prescription / prescription drug, OTC drug, or supplement usage history (medicine information, dispensing date, usage, dosage, start / end date of use, etc.) ◇Information on medical examination results, including specific medical examinations (blood test results and various evaluations, metabolic syndrome determination, medical interview results by examinees, subjective symptoms, medical history, etc.) ◇ Electronic medical history information managed by pharmacies (prescription history, patient condition at the time of medication instruction, usage status of OTC drugs and supplements, details of injections, infusions and treatments at medical institutions, etc.) ◇Information such as various test results and disease information managed by medical institutions (such as specimen test results, various evaluations, and disease-related information)

[0017] The PRO server 3 includes a subject condition storage unit 30, which stores and manages information indicating the subject conditions of clinical trials. The PRO server 3 makes at least some of these subject conditions available on a website or the like, and widely solicits member registrations. The subject conditions are also used in a candidate extraction process that is carried out prior to narrowing down candidates for clinical trial / clinical study subjects based on the answers to a questionnaire. In other words, the subject conditions are used as compatibility conditions (i.e., subject conditions that must be met before a questionnaire is administered) for extracting candidates who may become clinical trial / clinical study subjects from the database of the personal data storage unit 20 that stores personal data, and the contents of the subject conditions are arbitrarily set by the PRO in accordance with the clinical trial to be conducted.

[0018] Subject conditions are a part of the various information contained in the personal data mentioned above. For example, in Phase I clinical trials conducted on a small number of healthy people to confirm safety, such as side effects, subject conditions are set regarding age, sex, location, nationality, weight, BMI, smoking status (smoking cessation period), drug holiday period, wearing of glasses or contact lenses, etc.

[0019] In Phase II clinical trials, which are conducted on a small number of patients to confirm effective and safe dosages and administration methods, and in Phase III clinical trials, which are conducted on a large number of patients to compare the efficacy and safety of existing drugs, subject conditions are set including conditions related to designated diseases, medications being taken, designated test values, etc., in addition to the conditions used in Phase I clinical trials. As described above, the PRO is free to decide what and what content to set as subject conditions in Phase I to Phase III clinical trials.

[0020] The subject conditions set here include extraction conditions and exclusion conditions. Extraction conditions are conditions that indicate that individuals who meet them will be extracted as candidates. On the other hand, exclusion conditions are conditions that indicate that individuals who meet them will be excluded from being candidates. When multiple extraction conditions and multiple exclusion conditions are set, individuals who meet all of the extraction conditions and do not meet all of the exclusion conditions will be extracted as candidates for clinical trial subjects.

[0021] The selection support server 1 performs a process of extracting candidates who meet the subject conditions stored in the subject condition storage unit 30 from the potential group of clinical trial / clinical trial subjects, based on the personal data of the potential group of clinical trial / clinical trial subjects stored in the personal data storage unit 20. The selection support server 1 also performs a process of generating responses to a questionnaire given to candidates as part of the selection process for clinical trial / clinical trial subjects, in cooperation with the dispensing pharmacy terminal 4. Details of the process performed by the selection support server 1 will be described with reference to the following FIG. 2.

[0022] Fig. 2 is a block diagram showing an example of a functional configuration of the selection support server 1 according to the first embodiment. As shown in Fig. 2, the selection support server 1 according to the first embodiment includes, as functional configurations, a subject condition acquisition unit 11, a candidate extraction unit 12, and a questionnaire response generation unit 13. As more specific functional configurations, the questionnaire response generation unit 13 includes a provisional response generation unit 13a and a final response generation unit 13b.

[0023] The functional blocks 11 to 13 can be configured by any of hardware, DSP (Digital Signal Processor), and software. For example, the functional blocks 11 to 13 are realized by the operation of a program stored in a storage medium such as a RAM, a ROM, a hard disk, or a semiconductor memory under the control of a microcomputer configured with a CPU, a RAM, a ROM, etc.

[0024] The subject condition acquisition unit 11 accesses the PRO server 3 and acquires information on the subject conditions stored in the subject condition storage unit 30. The candidate extraction unit 12 accesses the personal data management server 2 and uses the personal data of the potential clinical trial / clinical trial subjects stored in the personal data storage unit 20 to extract candidates who meet the subject conditions acquired by the subject condition acquisition unit 11 from the potential clinical trial / clinical trial subjects, and notifies the dispensing pharmacy terminal 4 of information on the extracted candidates.

[0025] Here, as described above, the candidate extraction unit 12 searches the personal data in the personal data storage unit 20 for individuals who meet all of the multiple extraction conditions included in the subject conditions and do not meet all of the multiple exclusion conditions, and extracts one or more of the applicable individuals as candidates for clinical trial / clinical trial subjects.

[0026] Furthermore, the candidate extraction unit 12 refers to the information on the medical visit history included in the personal data of the extracted candidate, and notifies the dispensing pharmacy terminal 4 of the dispensing pharmacy of the candidate information recorded as the medical visit history. The notified candidate information may be any information that allows the dispensing pharmacy to identify the candidate from among patients to whom the dispensing pharmacy has dispensed medicine in the past, such as name, sex, date of birth, and location.

[0027] The dispensing pharmacy terminal 4 to which the candidate information is notified from the candidate extraction unit 12 or the database of the in-pharmacy management server (not shown) connected thereto records medical history information of drugs that have been dispensed to the candidate in the past. The dispensing pharmacy terminal 4 that is notified of the candidate inputs the candidate's medical history information based on the operation of the pharmacy staff and transmits it to the selection support server 1. Alternatively, the dispensing pharmacy terminal 4 may automatically search for and input the candidate's medical history information from the database based on the candidate information received from the selection support server 1, and transmit this to the selection support server 1.

[0028] The questionnaire response generation unit 13 generates a questionnaire response using the personal data of the candidate extracted by the candidate extraction unit 12 and the additional medical history information input from the dispensing pharmacy terminal 4. The medical history information of the candidate input from the dispensing pharmacy terminal 4 may contain information that is not included in the personal data of the candidate stored in the personal data storage unit 20. Therefore, the questionnaire response generation unit 13 generates a questionnaire response using the additional medical history information input from the dispensing pharmacy terminal 4 in addition to the personal data of the candidate.

[0029] The questionnaire response generating unit 13 stores questionnaire form data including a plurality of questions, and generates questionnaire responses by setting responses to each of the plurality of questions. The plurality of questions include either or both of a multiple-choice format in which a user answers by selecting one of a plurality of options, and a descriptive format in which a user answers by writing any letters or numbers.

[0030] For multiple-choice questions, a selection algorithm is set in advance for determining which information to refer to among the candidate's personal data and additional medication history information and how to select an option according to the referred information. For written questions, a description algorithm is set in advance for determining which information to refer to among the candidate's personal data and additional medication history information and how to write using the referred information. The questionnaire answer generation unit 13 sets answers to each of the multiple questions according to these selection algorithms and description algorithms.

[0031] Even if additional medical history information is added to the candidate's personal data, there is a possibility that the information sufficient to answer all questions in the questionnaire will not be sufficient. Therefore, in this embodiment, the questionnaire answers can be generated by adding information added by the candidate himself / herself. This mechanism is realized by the provisional answer generating unit 13a and the final answer generating unit 13b.

[0032] The provisional answer generating unit 13a generates provisional questionnaire answers using the personal data of the candidates extracted by the candidate extracting unit 12 and additional medication history information input from the dispensing pharmacy terminal 4. For example, as described above, when the dispensing pharmacy terminal 4 receives notification of a candidate from the candidate extracting unit 12, the dispensing pharmacy terminal 4 uploads the medication history information of the candidate to the selection support server 1. The provisional answer generating unit 13a generates provisional questionnaire answers that set answers to questions to the extent that they can be answered, using the uploaded medication history information of the candidate and the personal data of the candidate stored in the personal data storage unit 20.

[0033] Alternatively, the following may be performed. That is, the provisional answer generating unit 13a first uses the personal data of the candidate to generate a first questionnaire answer in which answers to questions are set to the extent that the answer can be answered, and notifies the dispensing pharmacy terminal 4 of the generated first questionnaire answer information. The dispensing pharmacy that receives this notification at the dispensing pharmacy terminal 4 visually checks the contents of the first questionnaire answer and identifies unanswered questions. Then, the dispensing pharmacy terminal 4 specifies medication history information that is useful for answering the unanswered questions and uploads it to the selection support server 1. The provisional answer generating unit 13a generates a provisional version of the questionnaire answer by using this uploaded medication history information to additionally set answers to the unanswered questions in the first questionnaire answer.

[0034] The final answer generating unit 13b generates a final answer based on the provisional answer generated by the provisional answer generating unit 13a, using acquired information input from the dispensing pharmacy terminal 4 based on information acquired from the candidate by the dispensing pharmacy using the dispensing pharmacy terminal 4 that has received the notification of the candidate. For example, the provisional answer information generated by the provisional answer generating unit 13a is notified to the dispensing pharmacy terminal 4. The dispensing pharmacy that receives this notification at the dispensing pharmacy terminal 4 visually checks the contents of the provisional answer and grasps the unanswered questions. Then, information useful for answering the unanswered questions is acquired from the candidate, inputted into the dispensing pharmacy terminal 4, and uploaded to the selection support server 1. The final answer generating unit 13b generates a final answer by adding answers to the unanswered questions in the provisional answer using the uploaded acquired information.

[0035] Specifically, when the dispensing pharmacy receives a notification of a candidate from the candidate extraction unit 12 at the dispensing pharmacy terminal 4, the dispensing pharmacy explains the clinical trial when the candidate visits the dispensing pharmacy for a new dispensing purpose or when the candidate makes a dispensing reservation. Alternatively, the dispensing pharmacy may contact the candidate by means of telephone or e-mail to explain the clinical trial. After confirming that the candidate is willing to become a clinical trial subject, the dispensing pharmacy asks about matters not recorded in the medical history information of the dispensing pharmacy (for example, the taking status of medicines prohibited from being taken during the clinical trial), and inputs the information obtained in this way into the dispensing pharmacy terminal 4 and uploads it to the selection support server 1.

[0036] The final answer generating unit 13b generates the final questionnaire answer using the uploaded acquired information. Although the information used in generating the final questionnaire answer is acquired from the candidate, it is acquired by an interview by the dispensing pharmacy, and therefore can be said to be objective and useful information for creating an answer.

[0037] The questionnaire response information generated by the questionnaire response generating unit 13 is provided to the PRO. For example, it is possible to configure the PRO so that the selection support server 1 can be accessed from a terminal used by the PRO to acquire the questionnaire response information. Alternatively, the questionnaire response information generated by the questionnaire response generating unit 13 may be provided to the PRO server 3, and the PRO can access the PRO server 3 from a terminal used by the PRO to acquire the questionnaire response information. Based on the contents of the accurately generated questionnaire responses, the PRO can determine whether or not a candidate is suitable as a clinical trial subject, and only those who are deemed suitable can proceed with the selection process, such as a pre-interview and medical examination.

[0038] 3 is a flow chart showing an example of the operation of the selection support server 1 and the dispensing pharmacy terminal 4 according to the first embodiment configured as described above. First, the subject condition acquisition unit 11 of the selection support server 1 accesses the PRO server 3 and acquires information on the subject conditions stored in the subject condition storage unit 30 (step S1). Next, the candidate extraction unit 12 accesses the personal data management server 2 and uses the personal data of the potential clinical trial subjects stored in the personal data storage unit 20 to extract candidates who meet the subject conditions acquired by the subject condition acquisition unit 11 (step S2), and notifies the dispensing pharmacy terminal 4 of the information on the extracted candidates (step S3).

[0039] The dispensing pharmacy terminal 4 that has received the notification of the candidate uploads the candidate's medication history information to the selection support server 1 (step S4). The provisional answer generating unit 13a of the selection support server 1 uses the uploaded candidate's medication history information and the candidate's personal data stored in the personal data storage unit 20 to generate provisional questionnaire answers that set answers to questions to the extent that they can be answered (step S5), and notifies the dispensing pharmacy terminal 4 of the generated provisional questionnaire answer information (step S6).

[0040] Thereafter, the dispensing pharmacy terminal 4 inputs the information acquired by interviewing the candidates, and determines whether an instruction to upload has been given (step S7). If an instruction to upload has been given, the dispensing pharmacy terminal 4 uploads the input acquired information from the candidates to the selection support server 1 (step S8). The final answer generating unit 13b uses the uploaded acquired information to additionally set answers to unanswered questions in the provisional questionnaire answers, thereby generating final questionnaire answers (step S9). This ends the processing of the flowchart shown in FIG. 3.

[0041] As described above in detail, in the first embodiment, the selection support server 1 extracts candidates who meet the subject conditions using the personal data of the potential clinical trial / clinical trial subject group, and notifies the dispensing pharmacy terminal 4 of the information on the extracted candidates. Then, the selection support server 1 generates responses to the questionnaire using the personal data of the extracted candidates and additional medical history information input from the dispensing pharmacy terminal 4.

[0042] According to the first embodiment configured as described above, not only are candidates who meet the subject conditions extracted by using the personal data stored in advance for the potential group of clinical trial subjects, but also the answers to the questionnaire that the extracted candidates will fill out later are generated. The contents of the answers to the questionnaire are generated based on accurate personal data including the candidate's personal attribute information, diagnosis result information, medical history information, and medication history information, and accurate medication history information additionally input from the dispensing pharmacy terminal 4, so that suitability as a clinical trial subject can be accurately determined based on the answers to the questionnaire. This makes it possible to prevent wasteful processing, such as moving the subject selection process beyond the questionnaire for candidates who are not suitable as clinical trial subjects, and makes it possible to more smoothly select candidates who meet the subject conditions.

[0043] Second embodiment Next, a second embodiment of the present invention will be described with reference to the drawings. The second embodiment further includes a function for making it easier to secure the required number of clinical trial subjects.

[0044] Figure 4 is a diagram showing an example of the overall configuration of a subject selection support system according to a second embodiment. In this figure, components having the same functions as those shown in Figure 1 are given the same reference numerals. As shown in Figure 4, the subject selection support system according to the second embodiment includes a selection support server 1' instead of the selection support server 1, and further includes a CRO terminal 5 used by a CRO or the like that requests clinical trials.

[0045] Fig. 5 is a block diagram showing an example of the functional configuration of a selection support server 1' according to the second embodiment. In Fig. 5, the same reference numerals as those shown in Fig. 2 have the same functions, and therefore repeated explanations will be omitted here. As shown in Fig. 5, the selection support server 1' according to the second embodiment further includes a condition setting unit 14 and a search unit 15 as functional components.

[0046] The condition setting unit 14 arbitrarily sets subject conditions according to the specifications of the CRO operating the CRO terminal 5. As described above, the subject conditions set by the CRO include extraction conditions and exclusion conditions related to at least some of the personal attribute information, medical examination or health check diagnosis result information, medical history information, and medication history information. Of these, the settings of the extraction conditions are variable. Variable settings mean that the CRO can relax the conditions while checking the search results (described later) by the search unit 15. On the other hand, the settings of the exclusion conditions are non-variable and cannot be relaxed.

[0047] 6 is a diagram showing an example of a condition setting screen provided to the CRO terminal 5 by the condition setting unit 14. The condition setting screen shown in FIG. 6 includes a subject target number setting field 601, an extraction condition initial setting field 602, an extraction condition variable setting field 603, an exclusion condition setting field 604, a matching person number display field 605, and a confirm button 606.

[0048] The subject target number setting field 601 is an input field for setting the target number of clinical trial subjects to be selected. The CRO inputs an arbitrary target number of subjects into the subject target number setting field 601.

[0049] The extraction condition initial setting field 602 is an input field for setting the initial setting value of the extraction condition. The CRO selects any one or more information items from personal attribute information, diagnosis result information, medical history information, and medication history information to initialize the extraction condition. Figure 6 shows an example of the state in which the extraction conditions are initially set for four information items: location, BMI, smoking time, and drug holiday period.

[0050] The variable extraction condition setting field 603 is an input field for setting variable setting values ​​for the extraction conditions. The CRO performs settings to relax the conditions for one or more initially set extraction conditions for information items as necessary. In the example of FIG. 6, multiple relaxed conditions that can be set by checking check boxes for each of four information items are presented as options. For each relaxed condition, the number of potential clinical trial subjects that meet the relaxed condition is also displayed.

[0051] For example, for the location extraction condition initially set as "Fukuoka City, Fukuoka Prefecture," 12 people live within 1 hour of that location, 17 people live within 1.5 hours, and 30 people live within 2 hours. The number of people who meet these relaxed conditions is obtained by the search unit 15 searching the personal data in the personal data storage unit 20. The same applies to other information items (BMI, smoking time, drug holiday period).

[0052] The exclusion condition setting field 604 is an input field for setting the exclusion condition. The CRO sets the exclusion condition by selecting any one or more information items from personal attribute information, diagnosis result information, medical history information, and medication history information. FIG. 6 shows an example of a state in which two exclusion conditions are set. Note that the exclusion condition setting field 604 may be configured to present a plurality of pre-prepared exclusion conditions as options in the form of a pull-down menu or pop-up menu, etc., so that the exclusion condition can be set by selecting one of the options.

[0053] The number of matching persons display field 605 displays the number of potential clinical trial subjects who meet the subject conditions set in the extraction condition initial setting field 602, the extraction condition variable setting field 603, and the exclusion condition setting field 604. In the example of FIG. 6, the number of matching persons searched by the search unit 15 using the extraction conditions initially set in the extraction condition initial setting field 602 and the exclusion conditions set in the exclusion condition setting field 604 as AND conditions, and the number of matching persons searched by the search unit 15 using the relaxed extraction conditions variably set in the extraction condition variable setting field 603 and the exclusion conditions set in the exclusion condition setting field 604 as AND conditions are displayed. The number in parentheses is the difference in number from the target number of subjects set in the target number of subjects setting field 601.

[0054] The search unit 15 uses the personal data stored in the personal data storage unit 20 to search for persons who meet the subject conditions set by the condition setting unit 14, obtains the number of persons who meet the conditions, and displays the result in the number of persons who meet the conditions display field 605. As described above, the search unit 15 searches for persons who meet the conditions using the initially set extraction conditions and exclusion conditions as AND conditions, and displays the number of persons who meet the conditions. If relaxed conditions are set, the search unit 15 searches for persons who meet the conditions using the relaxed extraction conditions and exclusion conditions as AND conditions, and displays the number of persons who meet the conditions. In addition, the search unit 15 searches for persons who meet the conditions for each of a plurality of relaxed conditions presented as options for one or more initially set information items, and displays the number of persons who meet the conditions in the extraction condition variable setting field 603.

[0055] While checking the number of applicable persons displayed in the extraction condition variable setting field 603 and the number of applicable persons display field 605, the CRO variably sets the extraction conditions so that the number of applicable persons for the subject conditions is equal to or greater than the target number of subjects, and then operates the confirm button 606. When the confirm button 606 is operated, the subject conditions set at that time are transmitted to the PRO server 3 and stored in the subject condition storage unit 30. The candidate extraction unit 12 uses the personal data stored in the personal data storage unit 20 to extract candidates who meet the subject conditions set by the condition setting unit 14, including the extraction conditions that have been variably set so that the number of applicable persons is equal to or greater than the target number of subjects.

[0056] According to the second embodiment configured as described above, it is possible to appropriately set the subject conditions so that the number of candidates extracted by the candidate extraction unit 12 is equal to or greater than the target number of subjects, after grasping in advance the situation of how many people who meet the subject conditions are included in the potential group of clinical trial and clinical trial subjects. In addition, it is possible to variably set the relaxed conditions for each of one or more information items set as the extraction conditions, and the number of people who meet the relaxed conditions presented as options is automatically searched for and presented, so it is possible to predict how much the number of people who meet the conditions will increase if the extraction conditions of each information item are relaxed to what extent, and it is easy to set appropriate extraction conditions. Then, the processing of the candidate extraction unit 12 can be performed based on the subject conditions set in this way. In addition, it is possible to solicit member registrations on a website or the like based on the subject conditions set in this way.

[0057] In the second embodiment, it is also possible to set further database search conditions when extracting candidates from the potential group of clinical trial subjects. For example, it is also possible to set search conditions that limit the search to those who have confirmed in advance that they will be willing to become candidates for clinical trial subjects if selected by the subject selection support system. It is also possible to set search conditions that exclude those who have already been extracted and limit the search to only those who have not been extracted.

[0058] Fig. 7 is a diagram showing another example of a condition setting screen provided to the CRO terminal 5 by the condition setting unit 14. The condition setting screen shown in Fig. 7 further includes a search condition setting field 701. In the example of Fig. 7, an example is shown including both a check box for instructing whether or not to limit the search to those whose intention has been confirmed in advance, and a check box for instructing whether or not to limit the search to those who have not been extracted, but only one of them may be used.

[0059] The advance confirmation of intention can be performed, for example, by displaying an inquiry screen in the medicine notebook app. Based on the answer from the user inputted through the inquiry screen, the medicine notebook app stores flag information indicating whether or not the user is willing to become a candidate for a clinical trial / clinical study subject, and uploads the personal data including this flag information to the personal data management server 2. When an instruction is given in the search condition setting field 701 to limit the search to those who have confirmed their intention in advance (when a check box is checked), the candidate extraction unit 12 searches only for those who have flag information indicating intention set, and extracts candidates who meet the subject conditions.

[0060] In this way, it is possible to grasp in advance the situation of how many people who meet the subject conditions are included among the potential clinical trial / clinical trial subjects, particularly those whose intention has been confirmed in advance, and then to appropriately set the subject conditions so that the number of candidates extracted by the candidate extraction unit 12 is equal to or greater than the target number of subjects. This makes it possible to reduce the possibility that candidates who meet the subject conditions are extracted by the subject selection support system but the candidates do not agree to become subjects, and makes it possible to more smoothly select candidates who can become subjects.

[0061] Furthermore, when the candidate extraction unit 12 extracts a candidate in response to the operation of the confirm button 606, the candidate extraction unit 12 notifies the personal data management server 2 of the extracted candidate. The personal data management server 2 sets extracted flag information to the personal data of the notified candidate. Thereafter, when an instruction is given in the search condition setting field 701 to limit the search to only those who have not been extracted, the candidate extraction unit 12 searches only for those who do not have extracted flag information set, and extracts candidates who satisfy the subject conditions.

[0062] The method of identifying unextracted persons is not limited to the above example. For example, the following method may be used. That is, the candidate extraction unit 12 sets and stores extracted flag information in association with a personal ID (common to that used in the personal data management server 2) that identifies the extracted candidate. Thereafter, when an instruction is given in the search condition setting field 701 to limit the search to unextracted persons only, the candidate extraction unit 12 uses the stored personal ID and extracted flag information to execute a search targeting only persons for whom extracted flag information is not set.

[0063] In this way, for example, when subject conditions are changed and candidate extraction is re-executed, it is possible to prevent duplicate extraction of people who have already been extracted. Also, even when candidate extraction is re-executed using the same subject conditions as last time after personal data of potential clinical trial subjects is additionally stored in the personal data storage unit 20, it is possible to prevent duplicate extraction of people who have already been extracted.

[0064] In addition, for example, if some subjects drop out after a clinical trial has started and there is a shortage of subjects, by setting both search conditions that limit the subjects to those whose willingness has been confirmed in advance and search conditions that limit the subjects to those who have not been extracted, it is possible to extract candidates who meet the subject conditions and who are unlikely to be in a state where consent cannot be obtained, and quickly fill the shortage of subjects.In this case, since the CRO extracts the candidates, the PRO who receives a contact request for the extracted candidates may contact the candidates to explain the clinical trial and confirm their willingness to become clinical trial subjects.

[0065] In the above first and second embodiments, the selection support server 1 and the personal data management server 2 are configured separately, but the present invention is not limited to this. For example, the personal data management server 2 may have the functions of the selection support server 1.

[0066] In the above first and second embodiments, the questionnaire response generating unit 13 is described as having a configuration including the provisional response generating unit 13a and the final response generating unit 13b, but the present invention is not limited to this. For example, the questionnaire response generating unit 13 may have only the function of the provisional response generating unit 13a, and the questionnaire responses generated by the provisional response generating unit 13a may be presented to the PRO with the candidate's consent. In this case, some questions may have questionnaire responses to which no answers are set, but it is possible to determine suitability as a clinical trial subject based on the answers to the other questions.

[0067] In addition, the above-mentioned embodiments are merely examples of the implementation of the present invention, and the technical scope of the present invention should not be interpreted as being limited thereby. In other words, the present invention can be implemented in various forms without departing from the gist or main characteristics thereof. [Explanation of symbols]

[0068] 1,1' Selection support server 2. Personal data management server 3 PRO Server 4. Pharmacy terminal 5 CRO terminal 11 Subject condition acquisition section 12 Candidate extraction department 13. Questionnaire response generation section 13a Provisional answer generator 13b Definite answer generator 14 Condition setting section 1 15 Search section

Claims

1. a personal data storage unit for storing personal data including personal attribute information of a potential group of clinical trial subjects, diagnostic result information of medical examinations or health checkups, medical history information, and medication history information; a candidate extraction unit that uses the personal data stored in the personal data storage unit to extract candidates who meet the set subject conditions and notifies the dispensing pharmacy terminal of information on the extracted candidates; a questionnaire response generating unit that generates responses to a questionnaire using the personal data of the candidates extracted by the candidate extracting unit and additional medical history information input from the dispensing pharmacy terminal. A clinical trial subject selection support system characterized by:

2. The questionnaire response generation unit a provisional answer generating unit that generates provisional questionnaire answers using the personal data of the candidates extracted by the candidate extracting unit and the additional medication history information input from the dispensing pharmacy terminal; a final answer generation unit that generates a final questionnaire answer based on the provisional questionnaire answer by using acquired information input from the dispensing pharmacy terminal based on information acquired from the candidate by the dispensing pharmacy that uses the dispensing pharmacy terminal that has received the notification.

2. The clinical trial subject selection support system according to claim 1.

3. a condition setting unit, the subject conditions including extraction conditions and exclusion conditions for the candidate, the extraction conditions being variable and setting the subject conditions; a search unit that searches for persons who meet the subject conditions set by the condition setting unit using the personal data stored in the personal data storage unit, and acquires the number of such persons; The candidate extraction unit uses the personal data stored in the personal data storage unit to extract candidates who meet the subject conditions set by the condition setting unit, including the extraction conditions that are variably set so that the number of applicable candidates is equal to or greater than the target number of subjects.

3. The clinical trial subject selection support system according to claim 1 or 2.

4. The condition setting unit is capable of further setting search conditions when the candidate extraction unit extracts candidates who meet the subject conditions, The search conditions are at least one of the following: limiting the search to those who have confirmed their intention to become candidates for the clinical trial or clinical trial subjects in advance, and limiting the search to those who have not been selected.

4. The clinical trial subject selection support system according to claim 3.

5. a candidate extraction unit that uses a database that stores personal data including personal attribute information, medical examination or health check diagnosis result information, medical history information, and medication history information of a potential group of clinical trial / clinical trial subjects to extract candidates that meet the set subject conditions and notify the dispensing pharmacy terminal of the information of the extracted candidates; a questionnaire response generating unit that generates responses to a questionnaire using the personal data of the candidates extracted by the candidate extracting unit and additional medical history information input from the dispensing pharmacy terminal. A server for supporting the selection of clinical trial subjects.

Images