Real-time investigation method and system for clinical test

Abstract

The embodiment of the invention relates to the technical field of test investigation, in particular to a real-time investigation method and system for a clinical test, and the method comprises the steps: obtaining the test process information of the clinical test and the identity information of a subject participating in the clinical test; a clinical test questionnaire is constructed according to the test process information and the identity information, process information of a subject relative to a clinical test is monitored in real time, the clinical test questionnaire is adaptively adjusted according to the process information and sent to a specified terminal device, and performance data of the subject in the clinical test are collected through the terminal device. And performing comprehensive analysis on the investigation portraits of the subject in each process link of the clinical test to generate clinical test investigation information of the clinical test.

Description

Technical Field

[0001] The embodiments of this disclosure relate to the technical field of experimental investigation, and more specifically, the embodiments of this disclosure relate to a real-time investigation method and system for clinical trials. Background Technology

[0002] With the development of the medical industry, the requirements for the efficiency and quality of clinical trials are becoming increasingly higher. Traditional methods rely on manual recording and periodic reporting, which results in delays in data collection and makes it difficult to grasp the real-time situation of subjects in the trial. This is not conducive to timely adjustment of the trial protocol and response to emergencies. Summary of the Invention

[0003] In view of this, this disclosure provides a real-time investigation method and system for clinical trials to achieve real-time data investigation throughout the entire process.

[0004] According to a first aspect of this disclosure, a method for real-time investigation of clinical trials is provided, comprising: Obtain information on the trial process of the clinical trial and the identity information of the subjects participating in the clinical trial, and construct a clinical trial questionnaire based on the trial process information and the identity information; The progress information of the subjects relative to the clinical trial is monitored in real time, the clinical trial questionnaire is adaptively adjusted according to the progress information, and sent to the designated terminal device; The terminal device is used to collect the subject's performance data in the clinical trial in order to construct a survey profile of the subject relative to the clinical trial. A comprehensive analysis of the survey profiles of the subjects at each stage of the clinical trial is conducted to generate clinical trial survey information for the clinical trial.

[0005] According to a second aspect of this disclosure, a real-time investigation system for clinical trials is provided for implementing a real-time investigation method for clinical trials as described in any one of the first aspects, comprising: The questionnaire construction module is used to obtain the trial process information of the clinical trial and the identity information of the subjects participating in the clinical trial, and to construct the clinical trial survey questionnaire based on the trial process information and the identity information. The questionnaire sending module is used to monitor the progress information of the subjects relative to the clinical trial in real time, make adaptive adjustments to the clinical trial questionnaire based on the progress information, and send it to the designated terminal device. The questionnaire module is used to collect the subject's performance data in the clinical trial through the terminal device, so as to construct a survey profile of the subject relative to the clinical trial; The information integration module is used to comprehensively analyze the survey profiles of the subjects at each stage of the clinical trial and generate clinical trial survey information for the clinical trial.

[0006] The technical solution disclosed herein has the following beneficial effects: This publicly disclosed questionnaire design incorporates trial procedures and participant identification information, making the survey more targeted. Real-time monitoring of the process and questionnaire adjustments ensure the survey aligns with each trial stage. Data collection via terminal devices creates survey profiles, providing a comprehensive understanding of participant performance. Comprehensive analysis of these profiles at each stage generates survey information, allowing for in-depth data mining and providing precise evidence for trial evaluation. This improves the efficiency and quality of clinical trials and ensures participant safety. Attached Figure Description

[0007] Figure 1 A schematic diagram illustrating the steps of a real-time investigation method for a clinical trial in this exemplary embodiment is shown. Figure 2 A schematic diagram of the structure of a real-time survey system for a clinical trial is shown in this exemplary embodiment. Detailed Implementation

[0008] To make the objectives, technical solutions, and advantages of this disclosure clearer, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure. Unless otherwise specified, the embodiments and features in the embodiments of this disclosure can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0009] The term "comprising" and any variations thereof in the specification and claims of this disclosure are intended to cover non-exclusive protection. For example, a process, method, system, product, or apparatus that comprises a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0010] In this disclosure, there are one or more embodiments; "multiple" refers to two or more. "And / or" describes the relationship between the associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0011] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order, sequence, size, or priority. For example, the terms "first dialogue information" and "second dialogue information" in the embodiments of this disclosure are merely used to distinguish different dialogue information. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0012] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, which are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more implementations. In the following description, numerous specific details are provided to give a thorough description of the embodiments of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted when implementing the technical solutions of this disclosure, or other methods, components, devices, steps, etc., may be used to replace one or more specific details. It should be noted that in the embodiments of this disclosure, the dissemination and use of data comply with relevant national laws and regulations. Please see Figure 1 As shown in the embodiments of this disclosure, a real-time investigation method for clinical trials is provided, including: S1: Obtain the trial process information of the clinical trial and the identity information of the subjects participating in the clinical trial, and construct a clinical trial survey questionnaire based on the trial process information and the identity information; S2: Monitor the progress information of the subject relative to the clinical trial in real time, make adaptive adjustments to the clinical trial questionnaire based on the progress information, and send it to the designated terminal device; S3: Collect the subject's performance data in the clinical trial through the terminal device to construct a survey profile of the subject relative to the clinical trial; S4: Conduct a comprehensive analysis of the survey profiles of the subjects at each stage of the clinical trial to generate the clinical trial survey information for the clinical trial.

[0013] In step S1 of the embodiments provided in this disclosure, the trial process information is studied in detail, the entire clinical trial is divided into different process stages, the specific trial content to be carried out in each stage is clarified, and the terminal device configured for data collection and interaction in each stage is determined. Assuming a drug clinical trial includes a drug administration stage, a physical indicator detection stage, a side effect observation stage, etc., the terminal device configured for the drug administration stage is a smart pillbox, which is used to record the medication time; the terminal device configured for the physical indicator detection stage is a wearable device, which is used to monitor indicators such as heart rate and blood pressure in real time.

[0014] Clinical trials typically involve multiple complex stages, each with different content and focus. By analyzing each stage, we can identify the information that needs to be collected at each stage, thus enabling us to design targeted survey projects. Different stages require different types of terminal devices to collect data. Determining the terminal devices configured for each stage helps us design appropriate survey methods based on the characteristics of the devices.

[0015] Based on the progress relationship between each process stage, the expected experimental effect of the experimental content of each process stage is simulated in sequence to obtain the expected experimental effect of each process stage of the clinical trial. Combining the identity information and the expected experimental effect, the physical subject feedback performance of the subjects in each process stage of the clinical trial is analyzed to obtain the subject performance characteristics of each process stage.

[0016] In a clinical trial of a hypertension drug, it is expected that blood pressure will decrease after a period of drug use. If the subject is an elderly person, their physical function may recover more slowly, and the speed and magnitude of the decrease in blood pressure may differ from those of younger people. Therefore, the performance characteristics of elderly subjects in this process may be that their blood pressure decreases relatively slowly and fluctuates more.

[0017] Different subjects may react differently to the experiment due to differences in their identity information (such as age, gender, health status, etc.). Combining identity information and experiment content to analyze the characteristics of the subjects' performance can make the survey more in line with the actual situation of each subject and improve the accuracy of the survey results. By anticipating the effect of the simulated experiment, it is possible to predict the possible performance of the subjects in each process stage in advance, and provide a basis for designing the survey project.

[0018] Based on the previously obtained characteristics of the test subjects, we analyze what information each terminal device needs to collect to fully understand the subjects' situation, thereby determining the corresponding investigation items for each process stage and forming a list of investigation items. In the physical indicator detection stage, based on the characteristics of the test subjects, we determine that information such as heart rate, blood pressure, and blood oxygen saturation needs to be collected through wearable devices. This information constitutes the list of investigation items for this stage.

[0019] Determining the list of survey items based on the characteristics of the subjects' performance ensures that the survey content comprehensively and accurately reflects the subjects' situation at each stage of the process, avoiding the omission of important information. Each terminal device corresponds to a list of survey items, making the data collection work more organized and easier to operate and manage.

[0020] Each survey item list is marked with an identification identifier related to the subject's identity information to ensure the accuracy and traceability of the data. Then, the survey item lists of all process stages are combined to form a complete clinical trial questionnaire. Each survey item list is marked with the subject's name, ID number, and other identification identifiers. Finally, the survey item lists of drug administration, physical indicator testing, and side effect observation are integrated to obtain the final questionnaire.

[0021] Adding identity verification markers ensures that each survey item corresponds to a specific subject, avoiding data confusion and errors. In subsequent analysis and research, it enables accurate tracking of each subject's survey data. Combining the survey item lists of each process stage into a complete clinical trial survey questionnaire facilitates unified distribution and management, improving survey efficiency.

[0022] In step S2 of the embodiments provided in this disclosure, by real-time tracking and recording of the subject's relevant behaviors and events in the clinical trial, and based on the pre-set trial process, it is determined which specific process stage the subject is currently in. At the same time, according to the corresponding configuration of each process stage and terminal device in the trial process, the terminal device matched for data collection and interaction for that process stage is determined. In a vaccine clinical trial, the trial process includes pre-vaccination physical examination, vaccination, post-vaccination observation, etc. If real-time monitoring finds that the subject has just completed vaccination, then the current process stage is "post-vaccination observation". The terminal device matched for this stage may be a smart bracelet held by the subject for monitoring vital signs.

[0023] Different stages of the process have different focuses and require different information. Accurately determining the current stage of the process for the subjects can ensure that the selected survey items are closely related to the current stage of the experiment, thereby improving the relevance and effectiveness of the survey. Different terminal devices have different functions and characteristics. Matching the appropriate terminal devices can make full use of the advantages of the devices and collect data more conveniently and accurately.

[0024] From the previously constructed complete clinical trial questionnaire, identify the list of survey items corresponding to the current stage of the process. These survey item lists were specifically designed based on the trial content and subject performance characteristics of each stage when the questionnaire was constructed. For example, in the "post-vaccination observation" stage, select survey items related to this stage from the questionnaire, such as whether there are symptoms related to fever, fatigue, local redness and swelling, to form the survey item list for this stage.

[0025] A complete clinical trial questionnaire includes survey items for all stages of the process. If no screening is performed, sending too many irrelevant survey items to subjects at a specific stage will increase the subjects' burden, reduce the quality of their responses, and may even cause them to become resistant. Selecting only survey items that are relevant to the current stage of the process allows subjects to focus more on the information that needs to be provided at that moment, thereby improving the accuracy and reliability of the data.

[0026] Analyze the functional characteristics of the terminal device, such as whether it has automatic data collection capabilities, whether it supports human-computer interaction, screen size, and resolution. Based on these functions, determine how to execute each survey item in the survey item list on the terminal device. If the terminal device is a smart bracelet, it has the function of automatically collecting data such as heart rate and steps. For survey items related to these physiological indicators, it can be set to automatic collection. For some survey items related to subjective feelings, such as whether you feel dizzy, a prompt box can pop up on the bracelet screen, allowing the subject to manually select the answer.

[0027] Designing survey execution methods based on the functional characteristics of terminal devices can make the survey process smoother and more convenient. For example, for devices with automatic data collection functions, using automatic data collection methods can reduce manual operation by the subjects and improve the efficiency and accuracy of data collection. Appropriate survey execution methods can ensure that the survey items can be executed correctly on the terminal devices and avoid data errors or missing data due to device incompatibility or inconvenience of operation.

[0028] According to the determined survey execution method, the survey item list is converted into a questionnaire format suitable for display and execution on terminal devices. This includes adjusting the display format and order of questions, adding appropriate interactive interface elements, etc., and then sending the converted adaptive questionnaire to the designated terminal device. The questions in the survey item list are converted into a concise format suitable for display on the smart bracelet screen, presented in the form of pop-up boxes or menu options, and sent to the subject's smart bracelet. The subject can operate and answer the questions through the bracelet.

[0029] Different terminal devices have different display interfaces and interaction methods. Converting the survey item list into an adaptive questionnaire makes the questionnaire clear and easy to operate on terminal devices, increasing participant engagement. Sending the adaptive questionnaire to designated terminal devices allows participants to answer promptly, enabling researchers to obtain the necessary data in a timely manner for real-time monitoring and adjustment of clinical trials.

[0030] In step S3 of the embodiments provided in this disclosure, the process is divided into an experiment execution phase and an experiment observation phase, and different terminal devices and data acquisition methods are used for different phases.

[0031] The terminal equipment configured in the trial execution phase is an active observation device, which contains several active observation units. Each unit collects performance data from the subjects in the trial execution phase through different observation methods. The data collection process is divided into several progressively advancing collection gradients. In the initial collection gradient, the active observation device collects performance data from the subjects in a specified observation format, and analyzes the collected performance data to obtain the subjects' key performance characteristics. In subsequent collection gradients, the specified observation format is modified based on the key performance characteristics of the previous collection gradient, and then the subjects' performance data is collected in the modified specified observation format.

[0032] Different active observation units (AUDs) can observe subjects from multiple perspectives, thus obtaining more comprehensive performance data. For example, in the drug administration phase of a clinical trial, some AUDs can monitor physiological indicators, while others can record behavioral actions. By using progressive acquisition gradients and adjusting subsequent observation methods based on the key performance characteristics obtained in the previous gradient, the important performance of subjects can be captured more accurately, improving the targeting and effectiveness of data collection. For instance, if a subject's physiological indicator is found to fluctuate significantly in the initial acquisition gradient, subsequent gradients can focus on the changes in that indicator.

[0033] In the experimental observation phase, data is collected by the smart terminal held by the participants. The smart terminal displays an interactive window to the participants, which is used to display a specified personalized question set. The steps for generating the personalized question set are as follows: Obtain the survey profiles collected in each process step before the experimental observation phase, and parse the question layout format of the adaptive questionnaire based on these survey profiles to obtain several question layout formats of the adaptive questionnaire. Vectorize the various question layout formats to obtain each question format matrix. Through the analysis of the similarity and correlation of each question format matrix, select the initial layout format from each question layout format. According to the initial layout format, transform and arrange the questions of the adaptive questionnaire according to the question item order to obtain a personalized question set obtained by sequentially arranging several personalized questions. After the participants complete the interactive response of the first round of personalized question set, interpret the interactive response information of the personalized question set to construct a temporary profile of the user. Deploy the parameters of the pre-deployed questionnaire distribution algorithm according to the temporary profile. Modify the question description and question order of the initial layout format according to each question layout format through the questionnaire distribution algorithm to obtain a new round of personalized question set. Repeat the steps several times to obtain several rounds of personalized question set.

[0034] Personalized question sets are generated based on the participants' previous survey profiles. The questions are more relevant to the participants' actual situation, which can improve the participants' enthusiasm and seriousness in answering the questions. Through multiple rounds of interaction with the personalized question sets, the questions are continuously adjusted based on the participants' answers, which can provide a deeper understanding of the participants' feelings, experiences and other subjective information during the experiment, and enrich the content of the survey profile.

[0035] Active observation devices interpret the collected performance data based on adaptive questionnaires to obtain a survey profile of the subject at this stage. Smart terminals interpret the interactive instructions and performance data provided by the subject through the interactive window based on adaptive questionnaires to obtain corresponding survey profiles. The collected raw performance data is often fragmented and needs to be interpreted based on adaptive questionnaires to transform it into a meaningful survey profile that can reflect the subject's situation in the clinical trial. For example, physiological indicator data can be interpreted as an assessment of health status, and the subject's subjective answers can be transformed into feedback on the trial effect.

[0036] By integrating the survey profiles obtained from the trial execution and observation phases, a complete survey profile of the subjects relative to the entire clinical trial can be constructed. Different phases of the clinical trial reflect the subjects' conditions at different stages. Integrating the survey profiles from each phase can create a comprehensive and complete survey profile of the subjects relative to the entire clinical trial, providing richer and more accurate evidence for subsequent comprehensive analysis.

[0037] In step S4 of the embodiments provided in this disclosure, the survey profiles formed by the subjects at each process stage are carefully compared and analyzed to identify recurring information areas and unique information areas. The recurring information is sorted and refined to form basic survey units. At the same time, each basic survey unit is assigned a corresponding confidence parameter based on factors such as the reliability and stability of the information. The confidence parameter is used to measure the credibility of the basic survey unit.

[0038] For example, in a drug clinical trial, if the survey profiles at multiple stages show that the subjects experience mild dizziness after taking the drug, then "mild dizziness after taking the drug" can be used as a basic survey unit. If this symptom consistently occurs in multiple stages of the survey, it can be assigned a high confidence parameter.

[0039] By identifying overlapping and non-overlapping areas in the survey profile, scattered information can be integrated and classified, and the most critical and stable information can be extracted as basic survey units. This avoids information redundancy and confusion, making subsequent analysis more focused and efficient. Assigning confidence parameters to basic survey units can quantify the reliability of information and help researchers better determine which information is worth focusing on and relying on in subsequent analysis and decision-making.

[0040] Using data analysis and logical reasoning methods, we study the inherent connections between various basic survey units, such as causal relationships and accompanying relationships. Based on these potential correlations, we select related in-depth survey units from a pre-established database. In-depth survey units are usually further expansions and in-depth explorations of basic survey units. Similarly, we generate corresponding confidence parameters for these in-depth survey units to reflect their credibility.

[0041] If the basic investigation unit shows "blood pressure decreases after taking medication" and "fatigue symptoms appear after taking medication", and analysis reveals a potential correlation between the two, the "association mechanism between blood pressure decrease and fatigue symptoms" is retrieved from the pre-set database as a deep investigation unit. Based on the reliability of relevant studies in the database and the degree of matching with the current trial, a confidence parameter is assigned to this deep investigation unit.

[0042] Basic survey units often only present surface phenomena and data. By analyzing the potential correlations between them, deeper causal relationships and patterns can be discovered. Retrieving in-depth survey units can further expand the depth and breadth of research, providing more comprehensive and in-depth insights for clinical trials. In-depth survey units are obtained from pre-set databases, which can introduce external professional knowledge and research results, enrich the content of clinical trial survey information, and make the research results more scientific and authoritative.

[0043] The basic and advanced survey units were sorted and weighted according to their confidence parameters, and then organically combined to form a complete and hierarchical clinical trial survey information. Units with higher confidence parameters occupy a more important position in the combination and have a greater impact on the final survey information. The basic survey unit "effective improvement of sleep quality after drug administration" and the advanced survey unit "neurobiological mechanism of drug improvement of sleep quality" with higher confidence parameters were placed in a prominent position and combined with other units with relatively lower confidence parameters to form clinical trial survey information, comprehensively reflecting the drug's effects and related mechanisms in clinical trials.

[0044] Confidence parameters reflect the credibility and importance of each unit. Combining units according to confidence parameters ensures that important and reliable information is highlighted in the final survey data, enabling researchers to quickly grasp key points. By rationally combining basic and in-depth survey units, a systematic and complete clinical trial survey information system can be constructed, comprehensively demonstrating the effects, mechanisms, and related influencing factors of clinical trials, and providing strong support for subsequent decision-making and research.

[0045] In one possible implementation, the step of constructing a clinical trial questionnaire based on the trial process information and the identity information includes: S11: Based on the experimental process information, analyze the execution process of each stage of the clinical trial to obtain the experimental content and configured terminal equipment of each stage; S12: Based on the identity information and the test content, the subject's performance characteristics in each stage of the clinical trial are obtained, and the survey items of each terminal device are analyzed according to the subject's performance characteristics to generate a list of survey items for each stage of the clinical trial. S13: Attach an identity authentication identifier to each of the survey item lists based on the identity information, so as to combine the survey item lists to obtain a clinical trial survey questionnaire.

[0046] Study the trial process information in detail and break down the entire clinical trial into multiple independent and continuous process stages according to the time sequence and logical sequence. For example, for a clinical trial of a new drug, it includes the subject screening stage, the initial drug administration stage, the interim observation stage, the drug dosage adjustment stage, and the final evaluation stage.

[0047] For each stage of the process, the specific experimental content is clearly defined. For example, in the initial drug administration stage, the experiment involves having subjects take the drug according to the prescribed dosage and time. In the mid-term observation stage, a series of physical examinations are conducted on the subjects, including blood tests and imaging examinations. The terminal devices configured for data collection and interaction at each stage are determined. For example, in the subject screening stage, a computer is configured to enter the subjects' basic information; in the drug administration stage, a smart pillbox is configured to record the medication time and reminders; and in the physical examination stage, professional medical testing equipment is configured to collect various physiological indicators.

[0048] Clinical trials are a complex process, with different stages focusing on different aspects and requiring different information collection. By analyzing the execution process of each stage, we can clarify the specific trial content and data to be collected at each stage, thereby designing targeted survey projects and avoiding information omissions and redundancies. Different stages require different types of terminal devices to collect data. Determining the terminal devices configured for each stage helps to design appropriate survey methods based on the functions and characteristics of the devices, thereby improving the efficiency and accuracy of data collection.

[0049] Taking into account the participants' identity information, such as age, gender, basic health status, and lifestyle habits, and combining the content of each stage of the trial, we can predict the possible performance of the participants. For example, elderly participants may have a slower recovery of their physical functions after taking the medication and a relatively higher probability of adverse reactions; while younger participants may have a stronger ability to recover, but their tolerance to the medication may also differ.

[0050] Based on the progress relationship between each process stage, the expected experimental effects of each process stage are simulated sequentially. For example, in the drug dosage adjustment stage, it is expected that different drug dosages will have different effects on the degree of symptom improvement and the occurrence of adverse reactions in the subjects. Through this expected simulation, the expected experimental effects of each process stage are obtained.

[0051] By combining identity information and expected trial results, the physical feedback performance of subjects at each stage of the trial is analyzed. For example, after a period of drug use, based on the subject's age and health status, possible changes in physiological indicators and subjective feelings are analyzed to obtain the subject's performance characteristics at each stage of the trial.

[0052] Based on the characteristics of the test subjects, we analyze what information each terminal device needs to collect to fully understand the subjects' situation. For example, for smart pillboxes, we need to collect information such as whether the subjects take their medication on time and whether the dosage is correct; for medical testing devices, we need to collect various physiological indicator data. We organize this information into specific survey items and generate a corresponding survey item list for each process stage.

[0053] Different subjects may react differently to the experiment due to differences in their identity information. Combining identity information and experiment content to analyze the subject's performance characteristics can make the survey more relevant to each subject's actual situation and improve the accuracy of the survey results. Determining the survey items for each terminal device based on the subject's performance characteristics can ensure that the survey content comprehensively and accurately reflects the subject's situation at each stage. For example, by analyzing the subject's performance characteristics, it can be determined that a certain physiological indicator of the subject needs to be focused on at a certain stage, and relevant content can be added to the survey item list of the corresponding terminal device.

[0054] Add authentication identifiers related to the participant's identity information, such as the participant's name, ID number, and trial number, to each survey item list. These identifiers ensure that each survey item can be accurately matched with a specific participant, guaranteeing the accuracy and traceability of the data. Combine the survey item lists of all process stages in a certain order to form a complete clinical trial survey questionnaire. The survey item lists of each stage can be arranged according to the chronological order of the trial process, making it convenient for participants and researchers to conduct surveys and collect data in sequence according to the trial process.

[0055] Adding identification markers to the survey item list ensures that each data point accurately corresponds to a specific subject, avoiding data confusion and errors. In subsequent data analysis and research, it facilitates the tracking and comparison of each subject's situation. Combining the survey item lists of each process stage into a complete questionnaire facilitates unified management and use. Researchers can conduct surveys on subjects sequentially according to the trial process, ensuring the orderly progress of the entire clinical trial survey.

[0056] In one possible implementation, the step of analyzing the subject's performance characteristics at each stage of the clinical trial based on the identity information and the trial content includes: S121: Based on the progress relationship between each process stage, the expected experimental effect of each process stage is simulated sequentially to obtain the expected experimental effect of each process stage of the clinical trial. S122: Combining the identity information and the expected trial effect, analyze the physical feedback performance of the subjects at each stage of the clinical trial to obtain the subject performance characteristics at each stage.

[0057] A detailed analysis of each stage of a clinical trial is necessary to clarify their sequence, logical connections, and time intervals. For example, in a drug clinical trial, there is first a subject screening stage, followed by the drug introduction period, the dosage adjustment period, and the stabilization observation period. Each stage has its specific tasks and objectives, and the results of the next stage often depend on the results of the previous stage.

[0058] For each stage of the experiment, specific indicators should be determined to measure the effectiveness of the experiment. These indicators can be physiological indicators (such as blood pressure, blood sugar, heart rate, etc.), symptom manifestations (such as pain level, fatigue, etc.), and functional indicators (such as exercise capacity, cognitive ability, etc.). For example, in clinical trials of drug treatment for hypertension, blood pressure is an important indicator of the trial's effectiveness.

[0059] Based on medical knowledge, data from similar past clinical trials, and the current trial design, the expected effects of each stage of the trial can be simulated. Mathematical models, statistical analysis, and other methods can be used to predict the range of indicator values ​​that subjects will achieve at each stage under normal circumstances. For example, based on the drug's mechanism of action and previous studies, it can be predicted that after the drug introduction period, the subjects' blood pressure will decrease to a certain extent, within a certain range.

[0060] By anticipating the experimental results of each stage, researchers can gain a general understanding of the overall direction of the experiment before it begins. They can plan ahead for the key indicators and potential problems that need to be focused on at each stage, which helps to allocate resources and develop response strategies. The anticipated experimental results provide a reference standard for subsequent evaluation of the subjects' actual performance. Researchers can compare the subjects' actual indicators at each stage with the anticipated indicators to determine whether the experiment has achieved the expected results and whether the subjects' responses are normal.

[0061] By combining the subject's identity information (such as age, gender, underlying diseases, lifestyle habits, etc.) with the expected experimental results of each process stage, different identity information can affect the subject's response and performance in the experiment. For example, the elderly have poorer tolerance to drugs, and their physiological indicators change differently from those of younger people at the same drug dosage; subjects with underlying diseases will experience more complications or adverse reactions.

[0062] Based on the integrated information, the physical feedback of the subjects at each stage of the process was analyzed. Considering individual differences, these feedbacks included abnormal fluctuations in physiological indicators, the appearance or relief of symptoms, and changes in psychological state. For example, for subjects with diabetes, after receiving a certain drug treatment, in addition to paying attention to changes in blood glucose levels, it is also necessary to consider whether hypoglycemia will occur.

[0063] The various possible physical feedbacks obtained from the analysis are summarized and generalized to determine the subject's performance characteristics at each stage of the process. These characteristics can be expressed in specific descriptive language or quantitative indicators so that they can be used to design survey projects and evaluate the subject's condition. For example, at a certain stage of the process, the subject's performance characteristics are "large fluctuations in blood pressure, accompanied by mild dizziness".

[0064] Different subjects may react very differently to the experiment due to differences in their identity information. Analyzing the identity information can more accurately predict the performance of each subject at each stage of the process, avoiding misjudgment of the test results due to ignoring individual differences. After clarifying the subject's performance characteristics, more targeted survey projects can be designed based on these characteristics to ensure that the information of the subject during the experiment can be collected comprehensively and accurately, thereby improving the quality and efficiency of the survey.

[0065] In one possible implementation, the step of adaptively adjusting the clinical trial questionnaire based on the process information and sending it to the designated terminal device includes: S21: Determine the current process stage and matching terminal device of the subject based on the process information; S22: Based on the aforementioned process steps, select a corresponding list of survey items from the clinical trial questionnaire, and analyze the survey method of the list of survey items according to the device functions of the terminal device to obtain the survey execution method of the list of survey items; S23: Convert the survey item list according to the survey execution method to obtain an adaptive questionnaire, and send it to the designated terminal device.

[0066] The system collects real-time progress information of subjects participating in clinical trials. This information can come from various channels, such as trial record systems and data feedback from terminal devices. The collected progress information is analyzed, and based on the pre-set clinical trial process, it is determined which specific stage the subject is currently in. For example, in a vaccine clinical trial, the process includes pre-vaccination preparation, vaccination, and post-vaccination observation period. By analyzing whether the subject has completed the vaccination procedure and the time stage they are in, it can be determined that they are currently in the post-vaccination observation period.

[0067] Based on the determined process steps, the pre-set correspondence is searched to determine the terminal device matched for that step. Different process steps may require different types of terminal devices to complete data collection and interaction tasks. For example, in the pre-vaccination preparation step, a tablet computer is used to allow the subject to fill in personal information and a health questionnaire; in the post-vaccination observation period, wearable devices are used to monitor the subject's vital signs in real time.

[0068] Different stages of the process have different focuses and require different information. Accurately identifying the current stage of the process ensures that the selected survey items are closely related to the current stage of the trial, improving the relevance and effectiveness of the survey. For example, the information needed before and after vaccination is completely different. Only by accurately identifying the stage can irrelevant questions be avoided. Different terminal devices have different functions and characteristics. Matching the appropriate terminal device can make full use of the device's advantages and collect data more conveniently and accurately. For example, wearable devices can collect physiological data in real time and continuously, making them suitable for use in stages requiring long-term monitoring; while smartphones have powerful interactive functions, making them suitable for collecting subjective feedback and text information from subjects.

[0069] From a pre-constructed complete clinical trial questionnaire, a list of survey items relevant to the current stage of the process is selected. The complete questionnaire covers all survey items in each stage of the entire clinical trial. By selecting items, it can be ensured that only the questions that need to be answered in the current stage are shown to the subjects, avoiding information redundancy. For example, in the post-vaccination observation period, only survey items related to adverse reactions after vaccination and physical condition are selected.

[0070] Learn in detail about the functions of the matching terminal device, including input / output methods, data storage capacity, and communication capabilities. Different terminal devices have different characteristics. For example, smartphones can be operated through a touch screen and support the display and uploading of pictures and videos; while wearable devices are better at collecting physiological data in real time.

[0071] Based on the functions of the terminal device, analyze how to execute each survey item in the survey item list on that device. This involves how questions are displayed, how answers are entered, and how data is transmitted. For example, multiple-choice questions can be displayed as radio buttons or checkboxes on a smartphone; for questions requiring text input, a virtual keyboard can be provided for participants to input their answers. Data collected by wearable devices can be set up to automatically upload to a server.

[0072] A complete clinical trial questionnaire includes survey items for all stages. If no screening is performed, sending too many irrelevant survey items to subjects at a specific stage will increase their burden, reduce the quality of their responses, and even lead to resistance. By selecting an appropriate list of survey items, key information can be focused on, improving survey efficiency. Designing the survey execution method according to the functional characteristics of the terminal device can make the survey process smoother and more convenient. For example, using input and output methods suitable for the terminal device can reduce the difficulty of operation for subjects and improve the accuracy and completeness of their responses. At the same time, a reasonable survey execution method also helps to improve the quality and reliability of data collection.

[0073] According to the established survey execution method, the survey item list is transformed in terms of format and content. This includes adjusting the display order of questions, modifying the wording of questions, and adding appropriate interactive elements to ensure that the questionnaire can be displayed and executed smoothly on terminal devices. For example, the questions in the survey item list are converted into a concise format suitable for smartphone screens, and guiding prompts are added to facilitate the understanding and answers of the respondents.

[0074] The transformed adaptive questionnaire is sent to the designated terminal device. During transmission, it is crucial to ensure the accuracy and integrity of the data, while also considering the network connectivity and data receiving capabilities of the terminal device. Secure and reliable communication protocols, such as HTTPS, can be used to encrypt and transmit the questionnaire data to the terminal device.

[0075] Different terminal devices have different display and operation requirements. Converting the survey item list into an adaptive questionnaire ensures that the questionnaire can be displayed and executed correctly on the designated terminal devices, avoiding problems such as formatting errors and operational inconveniences. Sending the adaptive questionnaire to the terminal devices allows participants to answer promptly, enabling researchers to obtain the necessary data in a timely manner for real-time monitoring and adjustments to the clinical trial. Rapid data feedback allows for timely identification of problems and implementation of corresponding measures, ensuring the smooth progress of the clinical trial. In one possible implementation, the process is divided into a trial execution phase and a trial observation phase. The terminal device configured in the trial execution phase is an active observation device, which is used to collect performance data of the subjects during the trial execution process and interpret the performance data according to the adaptive questionnaire to obtain a survey profile of the subjects. The terminal device configured in the trial observation phase is a smart terminal held by the subjects. The smart terminal is used to display an interactive window to the subjects according to the adaptive questionnaire to receive interactive instructions from the subjects to collect performance data and interpret the performance data according to the adaptive questionnaire to obtain a survey profile.

[0076] Active monitoring devices undergo self-testing and calibration to ensure they are in normal working order and that all functions are accurate and reliable. For example, if the active monitoring device includes a heart rate monitoring module, the heart rate sensor needs to be calibrated to ensure the accuracy of the measurement data. The types of performance data to be collected and the collection frequency are determined based on the adaptability questionnaire. For instance, in drug clinical trials, it is necessary to collect physiological indicators such as blood pressure and heart rate data every 15 minutes.

[0077] Active observation devices collect data on the performance of subjects during the trial according to a preset collection frequency and method. Active observation devices usually contain several active observation units, each of which collects data on the subjects through different observation methods. For example, some observation units monitor physiological indicators through sensors, while others record the subjects' behavior and actions through cameras.

[0078] The data acquisition process is divided into several progressively advancing acquisition gradients. In the initial acquisition gradient, the active observation device collects performance data of the subject in a specified observation format. Based on the collected performance data, the key performance characteristics of the subject are analyzed. In subsequent acquisition gradients, the specified observation format is modified according to the key performance characteristics of the previous acquisition gradient, so as to collect performance data of the subject in the modified specified observation format. For example, if a certain physiological indicator of the subject is found to fluctuate greatly in the initial acquisition gradient, the subsequent gradients will focus on the changes of that indicator and adjust the acquisition parameters to obtain more accurate data.

[0079] The active observation device interprets the collected performance data based on the adaptive questionnaire, which contains analysis rules and standards for various performance data. The device processes and analyzes the data according to these rules. For example, based on the normal physiological index range set in the questionnaire, it judges whether the subject's various indicators are normal. Based on the interpretation results, it constructs a survey profile of the subject, which records the subject's various performance characteristics and status information during the trial.

[0080] Equipment self-testing and calibration ensure the authenticity and reliability of the collected data, providing a solid foundation for subsequent analysis and decision-making. Determining the type and frequency of data collection makes the collection work more targeted, avoiding the collection of too much irrelevant data or the omission of important data. Multiple active observation units collect data from different angles, enabling a comprehensive understanding of the subjects' conditions. Progressive collection gradients can adjust the observation focus in a timely manner based on the results of previous collections, improving the accuracy of data collection and more accurately capturing the key performance characteristics of the subjects. Through the interpretation and profiling of the collected data, researchers can understand the subjects' status during the trial, determine whether the trial is proceeding as expected, and whether adjustments to the trial protocol are necessary.

[0081] The smart terminal displays an interactive window to the subjects based on the adaptive questionnaire. The interactive window is used to display a specified personalized question set. The steps for generating this personalized question set are as follows: First, obtain the survey profiles collected in each process stage before the experimental observation stage, and then parse the question layout format of the adaptive questionnaire based on these survey profiles to obtain several question layout formats. Second, vectorize the various question layout formats to obtain each question format matrix, and select the initial layout format from the question layout formats by analyzing the similarity and correlation of each question format matrix. Third, transform and arrange the survey items of the adaptive questionnaire according to the initial layout format to obtain a personalized question set obtained by sequentially arranging several personalized questions.

[0082] Participants interact with a smart terminal through an interactive window, answering questions from a personalized question set. The smart terminal receives the participants' interactive commands, records their responses, and interprets the responses after the first round of personalized question set interaction to construct a temporary user profile. Based on this profile, parameters are deployed to a pre-deployed questionnaire distribution algorithm. The algorithm then modifies the initial question layout format, adjusting the question wording and order according to the question layout format, resulting in a new round of personalized question set. This process is repeated several times to obtain multiple rounds of personalized question sets, continuously collecting participant performance data.

[0083] The smart terminal interprets the interactive responses and performance data of the subjects based on the adaptive questionnaire. For example, based on the definitions and analysis rules of different responses in the questionnaire, it judges the subjects' subjective feelings and experiences, and constructs a survey profile of the subjects in the experimental observation stage based on the interpretation results.

[0084] Personalized question sets are generated based on the participants' previous survey profiles. The questions are more relevant to the participants' actual situation, which can improve the participants' enthusiasm and seriousness in answering the questions and reduce perfunctory answers caused by questions that are irrelevant to them. Through multiple rounds of interaction with the personalized question sets, the questions are continuously adjusted based on the participants' answers, which can provide a deeper understanding of the participants' feelings, experiences and other subjective information during the experiment, enrich the content of the survey profile, interpret the participants' interactive response information and construct profiles, which helps researchers accurately grasp the participants' status and reactions in the experimental observation phase, and provide important basis for evaluating the experimental effect.

[0085] In one possible implementation, the active observation device includes several active observation units. Each active observation unit collects performance data of the subjects during the trial execution phase through different observation methods. The active observation device divides the process of collecting performance data of the subjects into several progressively advancing acquisition gradients. In the initial acquisition gradient, the active observation device collects performance data of the subjects in a specified observation format to analyze the key performance characteristics of the subjects based on the collected performance data. In subsequent acquisition gradients, the specified observation format is modified based on the key performance characteristics of the previous acquisition gradient to collect performance data of the subjects in the modified specified observation format.

[0086] In one possible implementation, the interactive window displayed by the smart terminal to the subject is used to display a specified personalized question set, the generation step of which includes: Obtain the survey profiles collected in each process stage before the execution of the experimental observation stage, and parse the question layout format of the adaptive questionnaire based on the survey profiles to obtain several question layout formats of the adaptive questionnaire. Various problem layout formats are vectorized to obtain a matrix of each problem format, and an initial layout format is selected from each problem layout format by analyzing the similarity and correlation of the problem format matrices. The adaptive questionnaire is transformed and its order is arranged according to the initial layout format to obtain a personalized question set consisting of several personalized questions arranged in sequence. After the subjects completed the first round of interactive responses to the personalized question set, the interactive response information of the personalized question set was interpreted to construct a temporary user profile; Based on the temporary profile, the parameters of the pre-deployed questionnaire distribution algorithm are deployed. The questionnaire distribution algorithm modifies the question description and question order of the initial layout format according to the question layout format to obtain a new round of personalized question set. This step is repeated several times to obtain several rounds of personalized question set.

[0087] In one possible implementation, the step of comprehensively analyzing the survey profiles of the subjects at each stage of the clinical trial to generate clinical trial survey information includes: S41: Analyze the overlapping and non-overlapping regions of the survey profiles of the subjects at each stage of the clinical trial to obtain several basic survey units of the subjects and corresponding confidence parameters. S42: Analyze the potential correlation of each basic survey unit and the corresponding confidence parameters, and retrieve several deep survey units from the preset database based on the analysis results and generate the corresponding confidence parameters; S43: Combine each of the basic investigation units and each of the in-depth investigation units according to the confidence parameters to obtain the clinical trial investigation information of the clinical trial.

[0088] Integrate the survey profiles formed by subjects at various stages of clinical trials, and compare and analyze the data and information in these profiles. For example, combine the survey profiles of subjects in the pre-medication physical examination, the observation during medication, and the follow-up examination after medication in drug clinical trials.

[0089] By comparing the data, we can identify the information regions that appear repeatedly in each survey profile, i.e., the overlapping regions. At the same time, we can identify the unique information regions that appear only in some profiles, i.e., the non-overlapping regions. For example, if the blood pressure of the subjects is shown to be in a relatively stable range in multiple survey profiles, this is an overlapping region. However, if the mild headache symptoms appear in a specific profile, this is a non-overlapping region.

[0090] Information from overlapping and non-overlapping areas is extracted and organized to form several basic investigation units. A basic investigation unit is a general description of a subject's condition in a clinical trial. For example, "blood pressure is stable within [specific range]" or "mild headache symptoms have occurred" can be used as a basic investigation unit.

[0091] Each basic survey unit is assigned a corresponding confidence parameter based on factors such as the reliability and stability of the information. Confidence parameters are usually expressed numerically; the higher the value, the higher the credibility of the basic survey unit. For overlapping information that appears consistently in multiple stages, the confidence parameter can be set higher; while for non-overlapping information that appears only in a few stages and is not very clear, the confidence parameter is relatively lower.

[0092] Clinical trials generate a large amount of data and information. By analyzing overlapping and non-overlapping regions, complex information can be simplified and refined, extracting the most critical and valuable basic investigation units. This avoids redundancy and confusion, allowing subsequent analysis to be more focused. Assigning confidence parameters to basic investigation units quantifies the reliability of information, helping researchers better determine which information deserves priority and reliance in subsequent analysis and decision-making. For example, when evaluating trial results, basic investigation units with high confidence parameters can be given priority.

[0093] By using data analysis methods and professional knowledge, we can conduct in-depth analysis of the potential correlations between various basic survey units. For example, we can analyze whether there is a causal or accompanying relationship between "blood pressure is stable within [specific range]" and "has experienced mild headache symptoms". The strength of the correlation can be judged through statistical analysis, logical reasoning and other methods.

[0094] Based on the results of the correlation analysis, several in-depth investigation units related to the correlation are retrieved from the pre-set database. The pre-set database stores a large amount of professional knowledge and past research results related to clinical trials. For example, if a correlation is found between blood pressure and headache, detailed research content on the relationship between blood pressure changes and headache is retrieved from the database as an in-depth investigation unit.

[0095] Similarly, corresponding confidence parameters are generated for the retrieved in-depth investigation units. The determination of confidence parameters takes into account factors such as the reliability of the information source in the database and the degree of matching with the current clinical trial. For in-depth investigation units from authoritative studies that are highly matched with the current trial, higher confidence parameters are assigned.

[0096] Basic survey units often only present surface phenomena and data. By analyzing the potential correlations between them, deeper causal relationships and patterns can be discovered. Retrieving in-depth survey units can further expand the depth and breadth of research, providing more comprehensive and in-depth insights for clinical trials. For example, by exploring the correlation between blood pressure and headaches and related in-depth research, we can better understand the mechanisms by which drugs affect the body of subjects. The professional knowledge and past research results stored in the pre-set database can provide reference and support for current clinical trials. Retrieving relevant in-depth survey units can integrate external professional information into the survey information, enhancing the scientific rigor and authority of the survey results.

[0097] The basic survey units and in-depth survey units are sorted according to the confidence parameters, with units having higher confidence parameters ranked first and given more importance. At the same time, each unit is weighted according to the confidence parameters, with units having higher confidence parameters having greater weight in the combination.

[0098] The sorted and weighted basic and in-depth survey units are organically combined to form a complete and hierarchical clinical trial survey information. During the combination process, attention should be paid to the logic and coherence of the information so that the final survey information can clearly present the overall situation of the subjects in the clinical trial and related professional analysis.

[0099] Confidence parameters reflect the credibility and importance of each unit. Sorting and weighting according to confidence parameters ensures that important and reliable information is highlighted in the final survey data, enabling researchers to quickly grasp key points and make accurate decisions. By rationally combining basic and in-depth survey units, a systematic and complete clinical trial survey information system can be constructed, comprehensively demonstrating the effects, mechanisms, and related influencing factors of clinical trials, and providing strong support for subsequent research and applications.

[0100] Please see Figure 2 As shown, this disclosure provides a real-time investigation system for clinical trials, used to implement the real-time investigation method for clinical trials as described in any one of the first aspects, including: The questionnaire construction module is used to obtain the trial process information of the clinical trial and the identity information of the subjects participating in the clinical trial, and to construct the clinical trial survey questionnaire based on the trial process information and the identity information. The questionnaire sending module is used to monitor the progress information of the subjects relative to the clinical trial in real time, make adaptive adjustments to the clinical trial questionnaire based on the progress information, and send it to the designated terminal device. The questionnaire module is used to collect the subject's performance data in the clinical trial through the terminal device, so as to construct a survey profile of the subject relative to the clinical trial; The information integration module is used to comprehensively analyze the survey profiles of the subjects at each stage of the clinical trial and generate clinical trial survey information for the clinical trial.

[0101] In this embodiment, the specific implementation of each module in the above system embodiment is described in the above method embodiment, and will not be repeated here.

[0102] As can be seen from the above, the technical solutions disclosed herein can be implemented as methods, apparatus, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will understand that various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be referred to as "circuit," "module," or "system," respectively.

[0103] It should be understood that this disclosure is not limited to the specific methods, steps, or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily conceive of other embodiments based on the specific implementations provided in this disclosure. Therefore, the specific implementations provided in this disclosure are merely exemplary, and the scope and spirit of this disclosure are indicated by the claims, and should cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary technical means in the art not disclosed in this disclosure.

Claims

1. A method of real-time investigation of a clinical trial, characterized in that, The method comprises the following steps: acquiring trial process information of a clinical trial and identity information of a subject participating in the clinical trial, and constructing a clinical trial questionnaire according to the trial process information and the identity information; monitoring progress information of the subject relative to the clinical trial in real time, adaptively adjusting the clinical trial questionnaire according to the progress information, and sending the clinical trial questionnaire to a designated terminal device; collecting performance data of the subject in the clinical trial through the terminal device to construct a survey portrait of the subject relative to the clinical trial; comprehensively analyzing the survey portraits of the subject at each process link of the clinical trial to generate clinical trial survey information of the clinical trial.

2. The method of real-time investigation of a clinical trial of claim 1, wherein, The step of constructing a clinical trial questionnaire according to the trial process information and the identity information comprises the following steps: analyzing the execution process of each process link of the clinical trial according to the trial process information to obtain trial content of each process link and configured terminal devices; analyzing subject performance characteristics of the subject at each process link of the clinical trial based on the identity information and the trial content, and analyzing survey items of each terminal device according to the subject performance characteristics to generate a survey item list of each process link; attaching an identity authentication mark to each survey item list according to the identity information to combine each survey item list to obtain a clinical trial questionnaire.

3. The method of real-time investigation of a clinical trial of claim 2, wherein, The step of analyzing subject performance characteristics of the subject at each process link of the clinical trial based on the identity information and the trial content comprises the following steps: sequentially performing expected simulation of trial effects on trial content of each process link based on a progress relationship between each process link to obtain expected trial effects of each process link of the clinical trial; combining the identity information and the expected trial effects to analyze physical subject feedback performance of the subject at each process link of the clinical trial to obtain subject performance characteristics of the subject at each process link.

4. The method of claim 1, wherein the clinical trial is a real-time investigation. The step of adaptively adjusting the clinical trial questionnaire according to the progress information and sending the clinical trial questionnaire to a designated terminal device comprises the following steps: determining a process link in which the subject is located at a current time and a matched terminal device according to the progress information; selecting a corresponding survey item list from the clinical trial questionnaire based on the process link, and analyzing a survey method of the survey item list according to a device function of the terminal device to obtain a survey execution method of the survey item list; converting the survey item list according to the survey execution method to obtain an adaptive questionnaire, and sending the adaptive questionnaire to the designated terminal device.

5. The method of claim 4, wherein the clinical trial is a Phase I, II, III, or IV clinical trial. The process link is divided into a test execution link and a test observation link. The terminal device configured in the test execution link is an active observation device. The active observation device is used to collect performance data of the subject during the test execution process and interpret the performance data according to the adaptive questionnaire to obtain a survey portrait of the subject. The terminal device configured in the test observation link is an intelligent terminal held by the subject. The intelligent terminal is used to display an interactive window to the subject according to the adaptive questionnaire to receive an interactive instruction of the subject to collect performance data and interpret the performance data according to the adaptive questionnaire to obtain a survey portrait.

6. The method of real-time investigation of a clinical trial of claim 5, wherein, The active observation device includes a plurality of active observation units. Each active observation unit collects performance data of the subject in the test execution link through different observation approaches. The process of the active observation device collecting performance data of the subject is divided into a plurality of sequentially progressive collection gradients. In the most initial collection gradient, the active observation device collects performance data of the subject in a specified observation form to analyze the key performance characteristics of the subject based on the collected performance data. In the subsequent collection gradients, the specified observation form is modified according to the key performance characteristics of the previous collection gradient to collect performance data of the subject in the modified specified observation form.

7. The method of claim 5, wherein the clinical trial is a Phase I, II, III, or IV clinical trial. The interactive window displayed by the intelligent terminal to the subject is used to display a specified personalized question set. The generation of the personalized question set includes the following steps: Obtaining the survey portraits collected in each process link before the test observation link and analyzing the adaptive questionnaire according to the survey portraits to obtain a plurality of question layout formats of the adaptive questionnaire; Vectorizing each question layout format to obtain a question format matrix and selecting an initial layout format from each question layout format by analyzing the similarity and correlation of each question format matrix; Converting the questions of the survey items of the adaptive questionnaire according to the initial layout format and arranging the order to obtain a personalized question set in which a plurality of personalized questions are sequentially arranged; After the subject completes the interactive answers of the first round of the personalized question set, interpreting the interactive answer information of the personalized question set to construct a temporary portrait of the user; Deploying parameters of a pre-deployed questionnaire distribution algorithm according to the temporary portrait, modifying the question expression and the question order of the initial layout format according to each question layout format through the questionnaire distribution algorithm to obtain a new round of personalized question set, and repeating the step for several times to obtain several rounds of personalized question sets.

8. The method of claim 1, wherein the clinical trial is a real-time survey method. The steps of generating the clinical trial survey information of the clinical trial by comprehensively analyzing the survey portraits of the subject in each process link of the clinical trial include: Analyzing the overlapping area and the non-overlapping area of the survey portraits of the subject in each process link of the clinical trial to obtain a plurality of basic survey units of the subject and corresponding confidence parameters; The potential correlation of each of the basic investigation units and the corresponding confidence parameters is analyzed, and according to the analysis result, a plurality of depth investigation units are called from a preset database and corresponding confidence parameters are generated; According to the confidence parameters, each of the basic investigation units and each of the depth investigation units are combined to obtain the clinical trial investigation information of the clinical trial.

9. A real-time investigation system for clinical trials, characterized by, A real-time investigation method for implementing the clinical trial of any one of claims 1-8, comprising: A questionnaire construction module configured to acquire trial process information of a clinical trial and identity information of a subject participating in the clinical trial, and to construct a clinical trial questionnaire according to the trial process information and the identity information; A questionnaire sending module configured to monitor in real time progress information of the subject relative to the clinical trial, to adaptively adjust the clinical trial questionnaire according to the progress information, and to send to a designated terminal device; A questionnaire investigation module configured to collect performance data of the subject in the clinical trial through the terminal device to construct an investigation portrait of the subject relative to the clinical trial; An information synthesis module configured to comprehensively analyze the investigation portraits of the subject at each progress link of the clinical trial to generate clinical trial investigation information of the clinical trial. A real-time investigation method for implementing the clinical trial of any one of claims 1-8, comprising: A questionnaire construction module configured to acquire trial process information of a clinical trial and identity information of a subject participating in the clinical trial, and to construct a clinical trial questionnaire according to the trial process information and the identity information; A questionnaire sending module configured to monitor in real time progress information of the subject relative to the clinical trial, to adaptively adjust the clinical trial questionnaire according to the progress information, and to send to a designated terminal device; A questionnaire investigation module configured to collect performance data of the subject in the clinical trial through the terminal device to construct an investigation portrait of the subject relative to the clinical trial; An information synthesis module configured to comprehensively analyze the investigation portraits of the subject at each progress link of the clinical trial to generate clinical trial investigation information of the clinical trial.

Images