Information management method and device for drug clinical test, medium and equipment

Abstract

The invention relates to an information management method and device for a drug clinical test, a medium and equipment, and relates to the technical field of information management. Determining an abnormal reason of the abnormal clinical test information according to the target abnormal dimension and the corresponding target fluctuation dimension in which the clinical test information is easy to be abnormal; when the abnormal reason is that an error occurs when the abnormal clinical test information is input, a suitable input form corresponding to the abnormal clinical test information is determined, and the clinical test information of the test abnormal dimension is obtained again based on the suitable input form; and when the abnormal reason is that the body of the target subject is abnormal in the drug clinical test, sending an abnormal early warning to a terminal of a clinical test worker. The method has the effect of improving the accuracy of the collected clinical test information.

Description

Technical Field

[0001] The present application relates to the field of information management technology, and specifically to an information management method, device, medium and equipment for drug clinical trials. Background Art

[0002] Drug clinical trials refer to any systematic study of drugs in humans (patients or healthy volunteers) to confirm or reveal the effects, adverse reactions and / or absorption, distribution, metabolism and excretion of the test drugs, with the aim of determining the efficacy and safety of the test drugs. Drug clinical trials are a key step for new drugs to move from the laboratory to the market, which is not only beneficial to individual patients, but also promotes the health and well-being of the entire society. In addition, information management of drug clinical trials is also a particularly important part. Information management of drug clinical trials refers to a series of activities during the clinical trial process to systematically and standardizedly collect, record, process, store and report test data, that is, clinical trial information and related information in various dimensions. Its purpose is to ensure the accuracy, completeness and traceability of the data, so as to support scientific decision-making and regulatory requirements.

[0003] At present, the method commonly used for information management of drug clinical trials is: during the clinical trial process of subjects, clinical trial staff need to manually enter the clinical trial information of the subjects to complete the information management of the drug clinical trials. However, under this method, once the volume of clinical trial information that needs to be recorded is large, manual recording methods are prone to input errors, etc., resulting in poor accuracy of the collected clinical trial information. Summary of the invention

[0004] In order to improve the accuracy of collected clinical trial information, the present application provides an information management method, device, medium and equipment for drug clinical trials.

[0005] In a first aspect of the present application, a method for information management of drug clinical trials is provided, which specifically includes: Obtain target clinical trial information of at least one dimension of target subjects of target drugs; If the target clinical trial information is not within the normal value range of the corresponding dimension, the corresponding target clinical trial information is determined as abnormal clinical trial information, and the dimension corresponding to the abnormal clinical trial information is determined as the test abnormality dimension; Determine the abnormal cause of the abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension, wherein the target fluctuation dimension is a dimension in which the clinical trial information is prone to abnormal fluctuation when the clinical trial information of the corresponding target abnormality dimension is abnormal; When the abnormal reason is an error in entering the abnormal clinical trial information, determining an appropriate entry form corresponding to the abnormal clinical trial information, and reacquiring the clinical trial information of the trial abnormality dimension based on the appropriate entry form; When the abnormality is caused by the physical abnormality of the target subject in the drug clinical trial, an abnormality warning is sent to the terminal of the clinical trial staff.

[0006] By adopting the above technical solution, after obtaining the target clinical trial information of at least one dimension of the target subject, if the target clinical trial information is not within the normal numerical range of the corresponding dimension, it is determined to be abnormal clinical trial information, indicating that the abnormal clinical trial information of the target subject is abnormal. It may be that the target subject has physical abnormalities when undergoing target drug treatment, or it may be that the staff made an error when entering the information, resulting in abnormal clinical trial information. In order to ensure the accuracy of the entered clinical trial information, the abnormal causes of the abnormal clinical trial information are investigated. If the abnormal cause is an error during entry, it may be that the entry form is not appropriate, then re-match the appropriate entry form, and re-acquire the clinical trial information of the abnormal dimension of this trial, thereby improving the accuracy of the collected clinical trial information; if the abnormal cause is physical abnormalities, not only can the physical condition of the target subject be checked in time by issuing an early warning, but also the entered clinical trial information can be verified to be correct, further improving the accuracy of the collected clinical trial information.

[0007] Optionally, the determining of the abnormal cause of the abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension specifically includes: Determine a target user profile of the target subject, and obtain historical abnormal dimensions of clinical trial information in which abnormalities have occurred when historical subjects of the target user profile have physical abnormalities in clinical trials of the target drug; Counting the first occurrence number of each of the historical abnormal dimensions, and selecting the first historical abnormal dimension from each of the historical abnormal dimensions in descending order of the first occurrence number as the target abnormal dimension, wherein the first occurrence number is the number of occurrences of a single historical abnormal dimension in all historical abnormal dimensions; Obtain other dimensions of abnormal fluctuations in clinical trial information when a single target abnormal dimension has an abnormality in historical subjects, count the second number of occurrences of each of the other dimensions, and select the second number of other dimensions from each of the other dimensions in descending order of the second number of occurrences to determine as the target fluctuation dimension of the corresponding target abnormal dimension, where the second number of occurrences is the number of occurrences of a single other dimension in all other dimensions; Calculate the first weight of each target abnormal dimension and the second weight of each corresponding target fluctuation dimension, wherein the first weight is the ratio of the first occurrence number of each target abnormal dimension to the sum of the first occurrence numbers of all target abnormal dimensions, and the second weight is the ratio of the second occurrence number of a single target fluctuation dimension corresponding to the target abnormal dimension to the sum of the second occurrence numbers of all corresponding target fluctuation dimensions; The abnormal cause of the abnormal clinical trial information is determined according to the test abnormality dimension, the first weight and the corresponding second weights.

[0008] By adopting the above technical solution, the larger the number of first occurrences, the more likely the clinical trial information of the corresponding historical abnormal dimension will be abnormal when the subject of the target user portrait is physically abnormal during the drug clinical trial, and then the target abnormal dimension will be determined; the larger the number of second occurrences, the more likely the corresponding other dimensions will be abnormally fluctuated when the target abnormal dimension is abnormal, and then the target fluctuation dimension will be determined. Finally, the first weight and the corresponding second weights are combined to determine the possibility that the current abnormal clinical trial information is caused by physical abnormality, and then the abnormal cause of the abnormal clinical trial information is accurately determined.

[0009] Optionally, determining the abnormal cause of the abnormal clinical trial information according to the test abnormality dimension, the first weight and the corresponding second weights specifically includes: Determine the dimensions of the target subject other than the test abnormality dimension as the remaining dimensions, and determine at least one actual abnormal fluctuation dimension from each of the remaining dimensions according to the target clinical trial information of each of the remaining dimensions; When the test abnormal dimension is the target abnormal dimension, at least one actual abnormal fluctuation dimension existing in each target fluctuation dimension corresponding to the test abnormal dimension is determined as a key abnormal fluctuation dimension, and the product of the first weight of the test abnormal dimension and the corresponding second weight of each of the key abnormal fluctuation dimensions is calculated to obtain a corresponding first product; summing the first products to obtain a sum of the first products, and comparing the sum of the first products with a preset first threshold; If the sum of the first products is greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial; If the sum of the first products is not greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is an error in entering the abnormal clinical trial information.

[0010] By adopting the above technical solution, the larger the first product is, the greater the possibility that the target subject will have physical abnormalities in the drug clinical trial when the abnormality dimension of the test actually occurs and the key abnormal fluctuation dimension has abnormal fluctuations. Further, the sum of the first products is summed to obtain the sum of the first products. The larger the sum of the first products is, the greater the overall possibility that the target subject will have physical abnormalities, and the more likely the abnormal cause of the abnormal clinical trial information is physical abnormalities. Finally, if the sum of the first products is greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is that the target subject has physical abnormalities in the drug clinical trial; conversely, if the sum of the first products is not greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is an error in the entry of the abnormal clinical trial information.

[0011] Optionally, the method further includes: Determine the dimensions of the target subject other than the test abnormality dimension as the remaining dimensions, and determine at least one actual abnormal fluctuation dimension from each of the remaining dimensions according to the target clinical trial information of each of the remaining dimensions; Obtaining historical entry forms in which entry errors have occurred in historical clinical trial information of the clinical trials of the target drug, counting the first occurrence frequency of each of the historical entry forms, and selecting the third-highest historical entry form from each of the historical entry forms in descending order of the first occurrence frequency to determine as an error-prone entry form; Obtaining the historical error dimensions that were wrong when the historical clinical trial information was entered in each of the error-prone entry forms, counting the second occurrence frequency of each of the historical error dimensions, and selecting the fourth number of historical error dimensions from each of the historical error dimensions in descending order of the second occurrence frequency to determine as the error-prone dimension of the corresponding error-prone entry form; Calculate the third weight of each of the error-prone input forms and the fourth weight of each of the corresponding error-prone input dimensions, wherein the third weight is the ratio of the first occurrence frequency of each error-prone input form to the sum of the first occurrence frequencies of all error-prone input forms, and the fourth weight is the ratio of the second occurrence frequency of a single error-prone input dimension corresponding to the error-prone input form to the sum of the second occurrence frequencies of all corresponding error-prone input dimensions; According to the actual input form of the target clinical trial information of each actual abnormal fluctuation dimension, the third weight and the corresponding fourth weights, the abnormal cause of the abnormal clinical trial information is verified.

[0012] By adopting the above technical solution, the greater the first occurrence frequency, the more likely the information entered will be wrong when the corresponding historical entry form is used to enter the historical clinical trial information of the target drug, and the error-prone entry form is determined; the greater the second occurrence frequency, the more likely the error is when the corresponding historical error dimension is entered in the error-prone entry form, and the error-prone dimension is determined. Finally, the third weight and the corresponding fourth weights are combined to analyze the possibility that the abnormal fluctuation of the actual abnormal fluctuation dimension is caused by the entry error, and then the rationality of the abnormal cause is verified.

[0013] Optionally, the verifying the abnormal cause of the abnormal clinical trial information according to the actual input form of the target clinical trial information of each actual abnormal fluctuation dimension, the third weight and the corresponding fourth weights specifically includes: Determine the error-prone entry form in which there is at least one actual abnormal fluctuation dimension among the corresponding error-prone dimensions as the key entry form, and when the key entry form is the corresponding actual entry form, calculate the second product of the third weight of each of the key entry forms and the fourth weight of the corresponding actual abnormal fluctuation dimension and sum them to obtain the sum of the second products; If the sum of the second products is not greater than a preset second threshold, it is determined that the abnormal cause of the abnormal clinical trial information is verified to be correct; If the sum of the second products is greater than a preset second threshold, the actual abnormal fluctuation dimension corresponding to the second product exceeding the preset product threshold is determined as the misrecorded fluctuation dimension, and if the misrecorded fluctuation dimension exists in each of the key abnormal fluctuation dimensions, the misrecorded fluctuation dimension is removed from each of the key abnormal fluctuation dimensions to obtain a calibrated fluctuation dimension; Calculating the third product of the first weight of the test abnormality dimension and the corresponding second weight of each calibration fluctuation dimension and summing them to obtain the sum of the third products; If the sum of the third products is not greater than the first threshold, then when the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial, the abnormal cause of the abnormal clinical trial information is calibrated as an error occurring during entry.

[0014] By adopting the above technical solution, the larger the sum of the second products, the greater the possibility that the target clinical trial information of the actual abnormal fluctuation dimension will be wrong during the actual entry. If the sum of the second products is not greater than the second threshold, it means that the possibility of error during entry is small, then the possibility of abnormal fluctuation in the actual abnormal fluctuation dimension due to the error in the target clinical trial information entry is small, and then the abnormal cause is verified to be correct; if the sum of the second products is greater than the second threshold, it means that the target clinical trial information of the actual abnormal fluctuation dimension is more likely to be wrong during the actual entry, and there is a high probability that the actual abnormal fluctuation dimension does not actually have abnormal fluctuations, but is caused by an error in recording. If the sum of the third products is not greater than the first threshold, it means that the target subject is less likely to have physical abnormalities, and the appearance of abnormal clinical trial information may be caused by an entry error. If the determined abnormal cause is physical abnormality, then the abnormal cause is calibrated to an error during entry. Thereby, not only can the false triggering of physical abnormality warnings be avoided, but also the problem of its entry error can be identified.

[0015] Optionally, the determining of an appropriate input form corresponding to the abnormal clinical trial information specifically includes: Determine the error-prone entry form in which the test abnormality dimension exists in the corresponding error-prone entry dimensions as a reference entry form, and calculate the fourth product of the third weight of each reference entry form and the fourth weight of the corresponding test abnormality dimension; A minimum fourth product is selected from each of the fourth products, and a reference entry form corresponding to the minimum fourth product is determined as a suitable entry form corresponding to the abnormal clinical trial information.

[0016] By adopting the above technical solution, the larger the fourth product is, the greater the possibility of error in entering the target clinical trial information of the trial abnormality dimension in the corresponding reference entry form. Therefore, the smallest fourth product is selected from each fourth product, and the reference entry form corresponding to the smallest fourth product is determined as the appropriate entry form corresponding to the abnormal clinical trial information. The clinical trial information of the trial abnormality dimension is re-entered in this appropriate entry form, and the possibility of entry errors is small.

[0017] Optionally, the method further includes: If there is no abnormal clinical trial information, determining at least one reference fluctuation dimension of abnormal fluctuation of target clinical trial information, and determining the target abnormal dimension in which at least one reference fluctuation dimension exists among the corresponding target fluctuation dimensions as a dimension requiring attention; Calculate the fifth product of the first weight of each dimension requiring attention and the second weight of each corresponding reference fluctuation dimension and sum them to obtain the corresponding sum of the products; The maximum sum of products is selected from the sums of the products. If the maximum sum of products is greater than a preset first threshold, then when there is no error in entering the target clinical trial information of the reference fluctuation dimension corresponding to the maximum sum of products, an error reminder is sent to the terminal for the dimension requiring attention corresponding to the maximum sum of products.

[0018] By adopting the above technical solution, the larger the sum of products, the greater the possibility of physical abnormalities of the target subject during the drug clinical trial, and the greater the possibility of abnormalities in the corresponding target clinical trial information of the dimension requiring attention. Further, the maximum sum of products is selected from the sums of various products. If the maximum sum of products is greater than the first threshold, it means that the dimension requiring attention corresponding to this maximum sum of products is more likely to be abnormal due to physical abnormalities. When there is no error in the entry of the target clinical trial information of the reference fluctuation dimension corresponding to the maximum sum of products, it means that there is a high probability that the dimension requiring attention corresponding to the maximum sum of products is entered incorrectly, and then a recording error reminder for the dimension requiring attention is sent to the terminal, thereby ensuring the accuracy of the entered clinical trial information.

[0019] In a second aspect of the present application, a device for managing information of a drug clinical trial is provided, specifically comprising: An information acquisition module, used to acquire target clinical trial information of at least one dimension of target subjects of a target drug; an abnormality determination module, configured to determine the corresponding target clinical trial information as abnormal clinical trial information if the target clinical trial information is not within the normal value range of the corresponding dimension, and determine the dimension corresponding to the abnormal clinical trial information as the test abnormality dimension; a cause determination module, for determining the abnormal cause of the abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension, wherein the target fluctuation dimension is the dimension in which the clinical trial information is prone to abnormal fluctuation when the clinical trial information of the corresponding target abnormality dimension is abnormal; An input adjustment module, used for determining a suitable input form corresponding to the abnormal clinical trial information when the abnormal reason is an error in inputting the abnormal clinical trial information, and re-acquiring the clinical trial information of the test abnormality dimension based on the suitable input form; The abnormality warning module is used to send an abnormality warning to the terminal of the clinical trial staff when the abnormality is caused by the physical abnormality of the target subject in the drug clinical trial.

[0020] By adopting the above technical solution, the information acquisition module obtains target clinical trial information of at least one dimension, the abnormality determination module determines the corresponding target clinical trial information as abnormal clinical trial information, then the cause determination module determines the abnormal cause of the abnormal clinical trial information, and then the input adjustment module determines the appropriate input form corresponding to the abnormal clinical trial information. Finally, the abnormal warning module sends an abnormal warning to the terminal of the clinical trial staff when the abnormal cause is a physical abnormality.

[0021] In a third aspect of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is loaded and executed by a processor, the method steps described in any one of the first aspects are performed.

[0022] In a fourth aspect of the present application, an electronic device is provided, specifically comprising: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the processor is used to load and execute the computer program stored in the memory so that the electronic device performs the method as described in any one of the first aspects.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: If the target clinical trial information is not within the normal numerical range of the corresponding dimension, it is determined to be abnormal clinical trial information, indicating that the abnormal clinical trial information of the target subject is abnormal. It may be that the target subject has a physical abnormality when undergoing the target drug treatment, or it may be that the staff made an error when entering the information, resulting in abnormal clinical trial information. In order to ensure the accuracy of the entered clinical trial information, the abnormal causes of the abnormal clinical trial information are investigated. If the abnormal cause is an error during entry, it may be that the entry form is not appropriate, then re-match an appropriate entry form, and re-acquire the clinical trial information of the abnormal dimension of this trial, thereby improving the accuracy of the collected clinical trial information; if the abnormal cause is a physical abnormality, not only can the physical condition of the target subject be checked in time by issuing an early warning, but also the entered clinical trial information can be verified to be correct, further improving the accuracy of the collected clinical trial information. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of an information management method for drug clinical trials provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of an information management device for drug clinical trials provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of another information management device for drug clinical trials provided in an embodiment of the present application.

[0025] Explanation of the accompanying drawings: 11. Information acquisition module; 12. Abnormality determination module; 13. Cause determination module; 14. Input adjustment module; 15. Abnormality warning module; 16. Cause verification module; 17. Recording error reminder module. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0028] See also Figure 1 The present application embodiment discloses a flowchart of a method for information management of drug clinical trials, which can be implemented by a computer program or run on an information management device for drug clinical trials based on the von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S101: Obtain target clinical trial information of at least one dimension of target subjects of a target drug.

[0029] Specifically, in an embodiment of the present application, the target drug is a new drug undergoing a clinical trial, and the target subject is a patient or volunteer participating in the clinical trial of the target drug. The target clinical trial information may be laboratory test information of various dimensions during the target drug treatment of the target subject, wherein the laboratory test information may be urine sugar data, blood lipid data, and blood sugar data, etc. In other embodiments, the target clinical trial information may also be vital sign data of various dimensions during the target drug treatment of the target subject, and illustratively, the vital sign data may be heart rate, body temperature, and blood pressure, etc.

[0030] Furthermore, the execution subject of the information management method for a drug clinical trial disclosed in the embodiment of the present application can be a server, the server is wirelessly connected to the terminal, and a client related to drug clinical trial information management is installed in the terminal. The server can be a background server of the client, specifically a physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal can be a personal computer or tablet computer of a clinical trial staff or researcher of the target drug. A feasible way to obtain target clinical trial information of at least one dimension of the target subject is: the clinical trial staff enters the target clinical trial information of the target subject locally, and sends it to the server through the client in the terminal, and the server finally obtains the target clinical trial information of each dimension, thereby collecting and saving the physical condition data of the subject when the target drug is treated, helping the researchers of the clinical trial to better evaluate the efficacy and safety of the target drug. It should be noted that the input form of the target clinical trial information by the clinical trial staff includes but is not limited to the image input form, the voice input form and the text input form. The target clinical trial information input by the terminal obtained is also multimodal data, that is, text data, image data or video data, etc.

[0031] S102: If the target clinical trial information is not within the normal value range of the corresponding dimension, the corresponding target clinical trial information is determined as abnormal clinical trial information, and the dimension corresponding to the abnormal clinical trial information is determined as the test abnormality dimension.

[0032] Specifically, after the target clinical trial information of each dimension is obtained, the target clinical trial information of each dimension is compared with the normal value range of the corresponding dimension. The normal value range is the value range of the target clinical trial information of the corresponding dimension when the target subject is in normal physical condition. If the target clinical trial information is not within the normal value range of the corresponding dimension, it means that the target clinical trial information of the corresponding dimension of the target subject is abnormal. It may be that the target subject has physical abnormality when taking the target drug treatment, or it may be that the staff made an error when entering the data, resulting in abnormal target clinical trial information. In this case, the corresponding target clinical trial information is determined as abnormal clinical trial information, and the dimension corresponding to the abnormal clinical trial information is determined as the test abnormality dimension.

[0033] S103: Determine the abnormal cause of the abnormal clinical trial information based on the trial abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension.

[0034] Specifically, after the abnormal dimension of the test is determined, it is necessary to further determine the abnormal cause of the abnormal clinical trial information. In the embodiment of the present application, the abnormal causes are divided into errors during input and physical abnormalities in drug clinical trials. A feasible way to determine is to input the basic information registered by the target subject when signing up for the drug clinical trial into a preset portrait prediction model to obtain a corresponding target user portrait, wherein the basic information includes but is not limited to age, gender, weight, past medical history information, allergy history, etc. The portrait prediction model is a trained decision tree model, or it can be a trained deep neural network model. The training process is briefly described as follows: the basic information of historical subjects marked with user portraits is used as training samples, input into the model for training, and the model parameters are continuously optimized and adjusted through the loss function and reverse gradient algorithm until the model converges. This is a prior art and will not be repeated here.

[0035] Furthermore, the analysis records of the clinical trial information of historical subjects who have participated in the target drug are retrieved. The analysis records include historical abnormal dimensions in which abnormalities actually occurred in the clinical trial information of historical subjects and clinical trial information that simultaneously produced abnormal fluctuations. Abnormal fluctuations can be understood as situations where the fluctuation of values ​​exceeds the normal fluctuation range. Based on the above analysis records, the historical abnormal dimensions in which abnormalities occurred in the clinical trial information when the historical subjects of the target user portrait had physical abnormalities in the clinical trial of the target drug are obtained, and the first occurrence number of each historical abnormal dimension is counted. The larger the first occurrence number, the more likely the clinical trial information of the corresponding historical abnormal dimension will be abnormal when the subject of the target user portrait has physical abnormalities in the drug clinical trial. In order of the first occurrence number from large to small, the historical abnormal dimension with the first number is selected from each historical abnormal dimension to be determined as the target abnormal dimension. Further, based on the above analysis records, other dimensions with abnormal fluctuations in clinical trial information are obtained when a single target abnormal dimension of a historical subject is abnormal, and the second number of occurrences of each other dimension is counted. The larger the second number of occurrences, the more likely the corresponding other dimension is to have abnormal fluctuations when the target abnormal dimension is abnormal, and then, in descending order of the second number of occurrences, the second number of other dimensions is selected from each other dimension to be the target fluctuation dimension of the corresponding target abnormal dimension, that is, the dimension in which the clinical trial information is prone to abnormal fluctuations when the clinical trial information of the corresponding target abnormal dimension is abnormal. Among them, the first number of occurrences is the number of occurrences of a single historical abnormal dimension in all historical abnormal dimensions; the second number of occurrences is the number of occurrences of a single other dimension in all other dimensions.

[0036] Furthermore, the first weight of each target abnormality dimension and the second weight of each corresponding target fluctuation dimension are calculated, the first weight being the ratio of the first occurrence number of each target abnormality dimension to the sum of the first occurrence numbers of all target abnormality dimensions, and the second weight being the ratio of the second occurrence number of a single target fluctuation dimension corresponding to the target abnormality dimension to the sum of the second occurrence numbers of all corresponding target fluctuation dimensions.

[0037] Further, the dimension of the target subject other than the test abnormality dimension is determined as the remaining dimension. Based on the target clinical trial information of the single remaining dimension currently obtained and the clinical trial information previously entered, the data fluctuation curve of the remaining dimension is plotted through the preset MATLAB tool, and the data fluctuation curve is fitted with the corresponding normal fluctuation curve. If the fitting rate does not exceed the preset fitting rate threshold, it means that the similarity between the data fluctuation curve and the corresponding normal fluctuation curve is low, and then the corresponding remaining dimension is determined to be the actual abnormal fluctuation dimension of the target subject. When the test abnormality dimension is the target abnormality dimension, at least one actual abnormal fluctuation dimension existing in each target fluctuation dimension corresponding to the test abnormality dimension is determined as the key abnormal fluctuation dimension. Then, the product of the first weight of the test abnormality dimension and the second weight of each corresponding key abnormal fluctuation dimension is calculated to obtain the corresponding first product. The larger the first product is, the greater the possibility of physical abnormality in the target subject in the drug clinical trial when the test abnormality dimension is actually abnormal and the key abnormal fluctuation dimension has abnormal fluctuations. Further, each first product is summed to obtain the sum of the first products. The larger the sum of the first products is, the greater the overall possibility of physical abnormality in the target subject, and the abnormal cause of the abnormal clinical trial information is more likely to be physical abnormality. Finally, if the sum of the first products is greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial; conversely, if the sum of the first products is not greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is that an error occurred during the entry of the abnormal clinical trial information.

[0038] In one embodiment, after determining at least one actual abnormal fluctuation dimension from each remaining dimension of the target subject, based on the statistical record of the entry of the historical clinical trial information of the target drug, the historical entry form in which entry errors occurred in the historical clinical trial information of the clinical trial of the target drug is obtained. The statistical record of the entry situation includes, but is not limited to, the entry form when an error occurs in the entry of the historical clinical trial information and the dimensions of the wrongly entered information. The first occurrence frequency of each historical entry form is counted, and the greater the first occurrence frequency, the more likely the entered information is to be wrong when the corresponding historical entry form is used when entering the historical clinical trial information of the target drug. In the order of the first occurrence frequency from large to small, the historical entry form with the third number is selected from each historical entry form to be determined as an error-prone entry form, that is, an entry form in which the entered clinical trial information is prone to occur.

[0039] Furthermore, based on the above-mentioned statistical records of input situations, historical error dimensions that occur when historical clinical trial information is entered in an error-prone input form are obtained, and the second occurrence frequency of each historical error dimension is counted. The larger the second occurrence frequency, the easier it is to make mistakes when entering the corresponding historical error dimension in an error-prone input form. In order of the second occurrence frequency from large to small, the fourth number of historical error dimensions is selected from each historical error dimension to be determined as the error-prone dimension of the corresponding error-prone input form, that is, the dimension in which clinical trial information errors are likely to occur during entry.

[0040] Further, the third weight of each error-prone input form and the corresponding fourth weight of each error-prone input dimension are calculated, the third weight is the ratio of the first occurrence frequency of each error-prone input form to the sum of the first occurrence frequencies of all error-prone input forms, and the fourth weight is the ratio of the second occurrence frequency of a single error-prone input dimension corresponding to the error-prone input form to the sum of the second occurrence frequencies of all error-prone input dimensions. Further, according to the actual input form, the third weight and the corresponding fourth weights of the target clinical trial information of each actual abnormal fluctuation dimension, the determined abnormal cause is verified, thereby improving the accuracy of the abnormal cause.

[0041] A feasible verification method is: determine the error-prone entry form in which there is at least one actual abnormal fluctuation dimension among the corresponding easily-entered error dimensions as the key entry form. When the key entry form is the actual entry form corresponding to the existing actual abnormal fluctuation dimension, calculate the second product of the third weight of each key entry form and the fourth weight of the corresponding actual abnormal fluctuation dimension and sum them to obtain the sum of the second products. The larger the sum of the second products, the greater the possibility that the target clinical trial information of the actual abnormal fluctuation dimension will be wrong during the actual entry. If the sum of the second products is not greater than the preset second threshold, it means that the possibility of error during entry is small, then the possibility of abnormal fluctuation caused by error in the target clinical trial information entry of the actual abnormal fluctuation dimension is small, and then verify that the abnormal cause determined above is correct. At the same time, it can also be verified that there is no entry error problem in the target clinical trial information entered this time in the actual abnormal fluctuation dimension.

[0042] If the sum of the second products is greater than the preset second threshold, it means that the target clinical trial information of the actual abnormal fluctuation dimension is more likely to be entered incorrectly during the actual entry, and there is a high probability that the actual abnormal fluctuation dimension does not actually experience abnormal fluctuations, but is caused by an error in entry. Then, each second product is compared with the preset product threshold. If the second product exceeds the product threshold, the corresponding actual abnormal fluctuation dimension is determined as an incorrectly recorded fluctuation dimension, that is, a dimension with a greater possibility of an entry error. At the same time, the personnel are reminded that the target clinical trial information of this incorrectly recorded fluctuation dimension has the risk of being recorded incorrectly.

[0043] Furthermore, the incorrectly recorded fluctuation dimensions in the above-mentioned key abnormal fluctuation dimensions are eliminated to obtain the calibration fluctuation dimension, which is the key abnormal fluctuation dimension with a lower risk of input error. Then, the third product of the first weight of the test abnormality dimension and the second weight of each corresponding calibration fluctuation dimension is recalculated and summed to obtain the sum of the third products. Finally, the sum of the third products is compared with the first threshold. If the sum of the third products is not greater than the first threshold, it means that the target subject is less likely to have physical abnormalities, and the appearance of abnormal clinical trial information may be caused by input errors. If the determined abnormal cause is that the target subject has physical abnormalities in the drug clinical trial, then the abnormal cause is calibrated to an error in input. This can not only avoid the false triggering of physical abnormality warnings, but also identify the problem of input errors.

[0044] S104: When the abnormal reason is an error in entering abnormal clinical trial information, determine an appropriate entry form corresponding to the abnormal clinical trial information, and re-acquire the clinical trial information of the trial abnormality dimension based on the appropriate entry form.

[0045] Specifically, after determining that the cause of the abnormality is an error in the input of abnormal clinical trial information, it is necessary to determine the appropriate input form corresponding to the abnormal clinical trial information. A feasible determination method is: determine the error-prone input form of the test abnormality dimension in the corresponding error-prone input dimensions as the reference input form, calculate the fourth product of the third weight of each reference input form and the fourth weight of the corresponding test abnormality dimension, the larger the fourth product, the greater the possibility of error in inputting the target clinical trial information of the test abnormality dimension in the corresponding reference input form, then select the minimum fourth product from each fourth product, determine the reference input form corresponding to the minimum fourth product as the appropriate input form corresponding to the abnormal clinical trial information, re-enter the clinical trial information of the test abnormality dimension in this appropriate input form, and the possibility of input error is small. Further, send a re-recording reminder message of the test abnormality dimension to the terminal, and the re-recording reminder message includes the appropriate input form, so as to re-acquire the clinical trial information of the test abnormality dimension based on the appropriate input form, thereby ensuring the accuracy of the collected clinical trial information. In other embodiments, the actual target input form of the abnormal clinical trial information is obtained. When the target input form is an error-prone input form, the weight product of the third weight of the target input form and the fourth weight of the corresponding test abnormality dimension is calculated. If the weight product is greater than the preset product threshold, there is a high possibility of error when entering the target clinical trial information of the test abnormality dimension in the target input form, then it is verified again that the cause of the abnormality is indeed an error in the input of the abnormal clinical trial information. At the same time, if the minimum fourth product is less than this weight product, it can also be verified that the appropriate input form is more reasonable. It should be noted that the cause of the abnormality can also be the abnormal cause after verification in step S103.

[0046] S105: When the cause of the abnormality is that the target subject has a physical abnormality during the drug clinical trial, an abnormality warning is sent to a terminal of the clinical trial staff.

[0047] Specifically, when the cause of the abnormality is that the target subject has a physical abnormality during the drug clinical trial, an abnormal warning of the drug clinical trial of the target subject is sent to the terminal of the clinical trial staff, so that they can go to check the physical condition of the target subject in time to avoid physical problems of the target subject during the drug clinical trial.

[0048] In other embodiments, if there is no abnormal clinical trial information in the target clinical trial information of each dimension of the target subject, then the reference fluctuation dimension of the abnormal fluctuation in the target clinical trial information of each dimension is determined. The determination method of the abnormal fluctuation can be referred to step S103, which will not be repeated here. Further, the target abnormal dimension of at least one reference fluctuation dimension existing in the corresponding target fluctuation dimensions is determined as the dimension to be concerned. The fifth product of the first weight of each dimension to be concerned and the second weight of each corresponding reference fluctuation dimension is calculated and summed to obtain the corresponding sum of products. The larger the sum of products, the greater the possibility of physical abnormality of the target subject when conducting drug clinical trials, and the greater the possibility of abnormality of the target clinical trial information of the corresponding dimension to be concerned. Further, the maximum sum of products is selected from the sums of each product. If the maximum sum of products is greater than the first threshold, it means that the dimension to be concerned corresponding to the maximum sum of products is likely to be abnormal due to physical abnormality. When the target clinical trial information of the reference fluctuation dimension corresponding to the maximum sum of products is not wrong when entering, it means that there is a high probability that the dimension to be concerned corresponding to the maximum sum of products is wrong, then a recording error reminder for the dimension to be concerned is sent to the terminal, thereby ensuring the accuracy of the entered clinical trial information. It should be noted that there was no error in entering the target clinical trial information of the reference fluctuation dimension corresponding to the maximum sum of products. The determination method can be found in step S103 and will not be repeated here.

[0049] The implementation principle of the information management method of the drug clinical trial in the embodiment of the present application is: if the target clinical trial information is not within the normal numerical range of the corresponding dimension, it is determined to be abnormal clinical trial information, indicating that the abnormal clinical trial information of the target subject is abnormal. It may be that the target subject has physical abnormalities when undergoing the target drug treatment, or it may be that the staff made an error when entering the information, resulting in abnormal clinical trial information. In order to ensure the accuracy of the entered clinical trial information, the abnormal causes of the abnormal clinical trial information are investigated. If the abnormal cause is an error during entry, it may be that the entry form is not appropriate, then re-match the appropriate entry form, and re-acquire the clinical trial information of the abnormal dimension of this trial, thereby improving the accuracy of the collected clinical trial information; if the abnormal cause is physical abnormalities, not only can the physical condition of the target subject be checked in time by issuing an early warning, but also the entered clinical trial information can be verified to be correct, further improving the accuracy of the collected clinical trial information.

[0050] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0051] See also Figure 2, which is a schematic diagram of the structure of the information management device for drug clinical trials provided in the embodiment of the present application. The information management device for drug clinical trials can be implemented as all or part of the device through software, hardware or a combination of both. The device includes an information acquisition module 11, an abnormality determination module 12, a cause determination module 13, an input adjustment module 14 and an abnormality warning module 15.

[0052] An information acquisition module 11 is used to acquire target clinical trial information of at least one dimension of target subjects of a target drug; The abnormality determination module 12 is used to determine the corresponding target clinical trial information as abnormal clinical trial information if the target clinical trial information is not within the normal value range of the corresponding dimension, and determine the dimension corresponding to the abnormal clinical trial information as the test abnormality dimension; A cause determination module 13 is used to determine the abnormal cause of abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension, wherein the target fluctuation dimension is the dimension in which the clinical trial information is prone to abnormal fluctuation when the clinical trial information of the corresponding target abnormality dimension is abnormal; An input adjustment module 14, for determining a suitable input form corresponding to the abnormal clinical trial information when the abnormal reason is an error in inputting the abnormal clinical trial information, and reacquiring the clinical trial information of the test abnormality dimension based on the suitable input form; The abnormality warning module 15 is used to send an abnormality warning to the terminal of the clinical trial staff when the abnormality is caused by the physical abnormality of the target subject in the drug clinical trial.

[0053] Optionally, the cause determination module 13 is specifically configured to: Determine the target user profile of the target subject, and obtain the historical abnormality dimension of the clinical trial information when the historical subject of the target user profile has physical abnormalities in the clinical trial of the target drug; Count the first occurrence times of each historical abnormal dimension, and select the first historical abnormal dimension from each historical abnormal dimension in descending order of the first occurrence times to determine it as the target abnormal dimension. The first occurrence times is the number of occurrences of a single historical abnormal dimension in all historical abnormal dimensions. Obtain other dimensions of abnormal fluctuations in clinical trial information when historical subjects have abnormalities in a single target abnormal dimension, count the second number of occurrences of each other dimension, and select the second number of other dimensions from each other dimension in descending order of the second number of occurrences as the target fluctuation dimension of the corresponding target abnormal dimension, and the second number of occurrences is the number of occurrences of a single other dimension in all other dimensions; Calculate the first weight of each target abnormal dimension and the second weight of each corresponding target fluctuation dimension, the first weight is the ratio of the first occurrence number of each target abnormal dimension to the sum of the first occurrence numbers of all target abnormal dimensions, and the second weight is the ratio of the second occurrence number of a single target fluctuation dimension corresponding to the target abnormal dimension to the sum of the second occurrence numbers of all corresponding target fluctuation dimensions; The abnormal cause of the abnormal clinical trial information is determined based on the test abnormality dimension, the first weight and the corresponding second weights.

[0054] Optionally, the cause determination module 13 is specifically configured to: Determine the dimensions of the target subject other than the test abnormality dimension as the remaining dimensions, and determine at least one actual abnormal fluctuation dimension from each remaining dimension according to the target clinical trial information of each remaining dimension; When the test abnormal dimension is the target abnormal dimension, at least one actual abnormal fluctuation dimension existing in each target fluctuation dimension corresponding to the test abnormal dimension is determined as the key abnormal fluctuation dimension, and the product of the first weight of the test abnormal dimension and the second weight of each corresponding key abnormal fluctuation dimension is calculated to obtain the corresponding first product; Summing the first products to obtain a sum of the first products, and comparing the sum of the first products with a preset first threshold; If the sum of the first products is greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial; If the sum of the first products is not greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is an error in entering the abnormal clinical trial information.

[0055] Optional, such as Figure 3 As shown, the device also includes a cause verification module 16, which is specifically used to: Determine the dimensions of the target subject other than the test abnormality dimension as the remaining dimensions, and determine at least one actual abnormal fluctuation dimension from each remaining dimension according to the target clinical trial information of each remaining dimension; Obtain the historical input forms in which input errors have occurred in the historical clinical trial information of the clinical trials of the target drug, count the first occurrence frequency of each historical input form, and select the third historical input form from each historical input form in descending order of the first occurrence frequency to determine it as an error-prone input form; Obtain the historical error dimensions that were wrong when entering historical clinical trial information in each error-prone entry form, count the second occurrence frequency of each historical error dimension, and select the fourth historical error dimension from each historical error dimension in descending order of the second occurrence frequency to determine it as the error-prone dimension of the corresponding error-prone entry form; Calculate the third weight of each error-prone input form and the fourth weight of each corresponding error-prone input dimension, the third weight is the ratio of the first occurrence frequency of each error-prone input form to the sum of the first occurrence frequencies of all error-prone input forms, and the fourth weight is the ratio of the second occurrence frequency of a single error-prone input dimension corresponding to the error-prone input form to the sum of the second occurrence frequencies of all corresponding error-prone input dimensions; According to the actual input form, the third weight and the corresponding fourth weights of the target clinical trial information of each actual abnormal fluctuation dimension, the abnormal cause of the abnormal clinical trial information is verified.

[0056] Optionally, the cause verification module 16 is specifically used for: Determine the error-prone entry form in which there is at least one actual abnormal fluctuation dimension among the corresponding error-prone dimensions as the key entry form, and when the key entry form is the corresponding actual entry form, calculate the second product of the third weight of each key entry form and the fourth weight of the corresponding actual abnormal fluctuation dimension and sum them to obtain the sum of the second products; If the sum of the second products is not greater than a preset second threshold, it is determined that the abnormal cause of the abnormal clinical trial information is verified to be correct; If the sum of the second products is greater than a preset second threshold, the actual abnormal fluctuation dimension corresponding to the second product exceeding the preset product threshold is determined as the misrecorded fluctuation dimension. If there is a misrecorded fluctuation dimension in each key abnormal fluctuation dimension, the misrecorded fluctuation dimension is removed from each key abnormal fluctuation dimension to obtain a calibrated fluctuation dimension. Calculate the third product of the first weight of the test anomaly dimension and the second weight of each corresponding calibration fluctuation dimension and sum them to obtain the sum of the third products; If the sum of the third products is not greater than the first threshold, then when the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial, the abnormal cause of the abnormal clinical trial information is calibrated as an error in entry.

[0057] Optionally, the input adjustment module 14 is specifically used for: Determine the error-prone entry form with the test abnormality dimension in the corresponding error-prone entry dimensions as the reference entry form, and calculate the fourth product of the third weight of each reference entry form and the fourth weight of the corresponding test abnormality dimension; The smallest fourth product is selected from the fourth products, and the reference entry form corresponding to the smallest fourth product is determined as the appropriate entry form corresponding to the abnormal clinical trial information.

[0058] Optionally, the device further includes a recording error reminder module 17, which is specifically used to: If there is no abnormal clinical trial information, determining at least one reference fluctuation dimension of abnormal fluctuation of target clinical trial information, and determining the target abnormal dimension in which at least one reference fluctuation dimension exists among the corresponding target fluctuation dimensions as a dimension requiring attention; Calculate the fifth product of the first weight of each dimension to be concerned and the second weight of each corresponding reference fluctuation dimension and sum them up to obtain the corresponding sum of the products; The maximum sum of products is selected from the sums of all products. If the maximum sum of products is greater than a preset first threshold, when there is no error in entering the target clinical trial information of the reference fluctuation dimension corresponding to the maximum sum of products, an error reminder is sent to the terminal for the dimension that requires attention corresponding to the maximum sum of products.

[0059] It should be noted that the information management device for drug clinical trials provided in the above embodiment only uses the division of the above functional modules as an example when executing the information management method for drug clinical trials. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the information management device for drug clinical trials provided in the above embodiment and the information management method embodiment for drug clinical trials belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0060] An embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, an information management method for a drug clinical trial of the above embodiment is adopted.

[0061] Among them, the computer program can be stored in a computer-readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or certain middleware, etc. The computer-readable medium includes any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer-readable medium includes but is not limited to the above-mentioned components.

[0062] Among them, through this computer-readable storage medium, an information management method for a drug clinical trial of the above embodiment is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0063] An embodiment of the present application also discloses an electronic device, in which a computer program is stored in a computer-readable storage medium. When the computer program is loaded and executed by a processor, the above-mentioned information management method for clinical trials of drugs is adopted.

[0064] The electronic device may be a desktop computer, a laptop computer, a cloud server or other electronic device, and the electronic device includes but is not limited to a processor and a memory. For example, the electronic device may also include input and output devices, a network access device, and a bus.

[0065] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0066] Among them, the memory can be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device, or it can be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD) or a flash memory card (FC) equipped on the electronic device. Moreover, the memory can also be a combination of an internal storage unit and an external storage device of the electronic device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0067] Among them, through this electronic device, an information management method for a drug clinical trial of the above embodiment is stored in the memory of the electronic device, and is loaded and executed on the processor of the electronic device for easy use.

[0068] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for information management of drug clinical trials, characterized in that: The method comprises: Obtain target clinical trial information of at least one dimension of target subjects of target drugs; If the target clinical trial information is not within the normal value range of the corresponding dimension, the corresponding target clinical trial information is determined as abnormal clinical trial information, and the dimension corresponding to the abnormal clinical trial information is determined as the test abnormality dimension; Determine the abnormal cause of the abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension, wherein the target fluctuation dimension is a dimension in which the clinical trial information is prone to abnormal fluctuation when the clinical trial information of the corresponding target abnormality dimension is abnormal; When the abnormal reason is an error in entering the abnormal clinical trial information, determining an appropriate entry form corresponding to the abnormal clinical trial information, and reacquiring the clinical trial information of the trial abnormality dimension based on the appropriate entry form; When the abnormality is caused by the physical abnormality of the target subject in the drug clinical trial, an abnormality warning is sent to the terminal of the clinical trial staff.

2. The information management method for drug clinical trials according to claim 1, characterized in that: The determining of the abnormal cause of the abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension specifically includes: Determine a target user profile of the target subject, and obtain historical abnormal dimensions of clinical trial information in which abnormalities have occurred when historical subjects of the target user profile have physical abnormalities in clinical trials of the target drug; Counting the first occurrence number of each of the historical abnormal dimensions, and selecting the first historical abnormal dimension from each of the historical abnormal dimensions in descending order of the first occurrence number as the target abnormal dimension, wherein the first occurrence number is the number of occurrences of a single historical abnormal dimension in all historical abnormal dimensions; Obtain other dimensions of abnormal fluctuations in clinical trial information when a single target abnormal dimension has an abnormality in historical subjects, count the second number of occurrences of each of the other dimensions, and select the second number of other dimensions from each of the other dimensions in descending order of the second number of occurrences to determine as the target fluctuation dimension of the corresponding target abnormal dimension, where the second number of occurrences is the number of occurrences of a single other dimension in all other dimensions; Calculate the first weight of each target abnormal dimension and the second weight of each corresponding target fluctuation dimension, wherein the first weight is the ratio of the first occurrence number of each target abnormal dimension to the sum of the first occurrence numbers of all target abnormal dimensions, and the second weight is the ratio of the second occurrence number of a single target fluctuation dimension corresponding to the target abnormal dimension to the sum of the second occurrence numbers of all corresponding target fluctuation dimensions; The abnormal cause of the abnormal clinical trial information is determined according to the test abnormality dimension, the first weight and the corresponding second weights.

3. The information management method for drug clinical trials according to claim 2, characterized in that: The determining the abnormal cause of the abnormal clinical trial information according to the test abnormality dimension, the first weight and the corresponding second weights specifically includes: Determine the dimensions of the target subject other than the test abnormality dimension as the remaining dimensions, and determine at least one actual abnormal fluctuation dimension from each of the remaining dimensions according to the target clinical trial information of each of the remaining dimensions; When the test abnormal dimension is the target abnormal dimension, at least one actual abnormal fluctuation dimension existing in each target fluctuation dimension corresponding to the test abnormal dimension is determined as a key abnormal fluctuation dimension, and the product of the first weight of the test abnormal dimension and the corresponding second weight of each of the key abnormal fluctuation dimensions is calculated to obtain a corresponding first product; summing the first products to obtain a sum of the first products, and comparing the sum of the first products with a preset first threshold; If the sum of the first products is greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial; If the sum of the first products is not greater than the first threshold, it is determined that the abnormal cause of the abnormal clinical trial information is an error in entering the abnormal clinical trial information.

4. The information management method for drug clinical trials according to claim 3, characterized in that: The method further comprises: Determine the dimensions of the target subject other than the test abnormality dimension as the remaining dimensions, and determine at least one actual abnormal fluctuation dimension from each of the remaining dimensions according to the target clinical trial information of each of the remaining dimensions; Obtaining historical entry forms in which entry errors have occurred in historical clinical trial information of the clinical trials of the target drug, counting the first occurrence frequency of each of the historical entry forms, and selecting the third-highest historical entry form from each of the historical entry forms in descending order of the first occurrence frequency to determine as an error-prone entry form; Obtaining the historical error dimensions that were wrong when the historical clinical trial information was entered in each of the error-prone entry forms, counting the second occurrence frequency of each of the historical error dimensions, and selecting the fourth number of historical error dimensions from each of the historical error dimensions in descending order of the second occurrence frequency to determine as the error-prone dimension of the corresponding error-prone entry form; Calculate the third weight of each of the error-prone input forms and the fourth weight of each of the corresponding error-prone input dimensions, wherein the third weight is the ratio of the first occurrence frequency of each error-prone input form to the sum of the first occurrence frequencies of all error-prone input forms, and the fourth weight is the ratio of the second occurrence frequency of a single error-prone input dimension corresponding to the error-prone input form to the sum of the second occurrence frequencies of all corresponding error-prone input dimensions; According to the actual input form of the target clinical trial information of each actual abnormal fluctuation dimension, the third weight and the corresponding fourth weights, the abnormal cause of the abnormal clinical trial information is verified.

5. The information management method for drug clinical trials according to claim 4, characterized in that: The verifying the abnormal cause of the abnormal clinical trial information according to the actual input form of the target clinical trial information of each actual abnormal fluctuation dimension, the third weight and the corresponding fourth weights specifically includes: Determine the error-prone entry form in which there is at least one actual abnormal fluctuation dimension among the corresponding error-prone dimensions as the key entry form, and when the key entry form is the corresponding actual entry form, calculate the second product of the third weight of each of the key entry forms and the fourth weight of the corresponding actual abnormal fluctuation dimension and sum them to obtain the sum of the second products; If the sum of the second products is not greater than a preset second threshold, it is determined that the abnormal cause of the abnormal clinical trial information is verified to be correct; If the sum of the second products is greater than a preset second threshold, the actual abnormal fluctuation dimension corresponding to the second product exceeding the preset product threshold is determined as the misrecorded fluctuation dimension, and if the misrecorded fluctuation dimension exists in each of the key abnormal fluctuation dimensions, the misrecorded fluctuation dimension is removed from each of the key abnormal fluctuation dimensions to obtain a calibrated fluctuation dimension; Calculating the third product of the first weight of the test abnormality dimension and the corresponding second weight of each calibration fluctuation dimension and summing them to obtain the sum of the third products; If the sum of the third products is not greater than the first threshold, then when the abnormal cause of the abnormal clinical trial information is that the target subject has a physical abnormality in the drug clinical trial, the abnormal cause of the abnormal clinical trial information is calibrated as an error occurring during entry.

6. The information management method for drug clinical trials according to claim 4, characterized in that: The determining of the appropriate input form corresponding to the abnormal clinical trial information specifically includes: Determine the error-prone entry form in which the test abnormality dimension exists in the corresponding error-prone entry dimensions as a reference entry form, and calculate the fourth product of the third weight of each reference entry form and the fourth weight of the corresponding test abnormality dimension; A minimum fourth product is selected from each of the fourth products, and a reference entry form corresponding to the minimum fourth product is determined as a suitable entry form corresponding to the abnormal clinical trial information.

7. The information management method for drug clinical trials according to claim 2, characterized in that: The method further comprises: If there is no abnormal clinical trial information, determining at least one reference fluctuation dimension of abnormal fluctuation of target clinical trial information, and determining the target abnormal dimension in which at least one reference fluctuation dimension exists among the corresponding target fluctuation dimensions as a dimension requiring attention; Calculate the fifth product of the first weight of each dimension requiring attention and the second weight of each corresponding reference fluctuation dimension and sum them to obtain the corresponding sum of the products; The maximum sum of products is selected from the sums of the products. If the maximum sum of products is greater than a preset first threshold, then when there is no error in entering the target clinical trial information of the reference fluctuation dimension corresponding to the maximum sum of products, an error reminder is sent to the terminal for the dimension requiring attention corresponding to the maximum sum of products.

8. An information management device for drug clinical trials, characterized in that: include: An information acquisition module (11) is used to acquire target clinical trial information of at least one dimension of target subjects of a target drug; An abnormality determination module (12), configured to determine the corresponding target clinical trial information as abnormal clinical trial information if the target clinical trial information is not within the normal value range of the corresponding dimension, and determine the dimension corresponding to the abnormal clinical trial information as the test abnormality dimension; A cause determination module (13) is used to determine the abnormal cause of the abnormal clinical trial information based on the test abnormality dimension, the target abnormality dimension in which the clinical trial information is prone to abnormality when the target subject has physical abnormality during the drug clinical trial, and the corresponding target fluctuation dimension, wherein the target fluctuation dimension is the dimension in which the clinical trial information is prone to abnormal fluctuation when the clinical trial information of the corresponding target abnormality dimension is abnormal; An input adjustment module (14), configured to determine a suitable input form corresponding to the abnormal clinical trial information when the abnormal reason is an error in inputting the abnormal clinical trial information, and to reacquire the clinical trial information of the test abnormality dimension based on the suitable input form; The abnormality warning module (15) is used to send an abnormality warning to a terminal of a clinical trial staff member when the abnormality is caused by a physical abnormality of the target subject in the drug clinical trial.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is loaded and executed by a processor, the method according to any one of claims 1 to 7 is adopted.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor loads and executes the computer program, the method according to any one of claims 1 to 7 is adopted.

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