Digital auditing method, device and related equipment applied in clinical trials

Abstract

A digital inspection method, device, electronic equipment and computer readable storage medium applied in a clinical trial. The digital inspection method applied in the clinical trial comprises the following steps: obtaining a target data record of a target object from a clinical trial electronic data acquisition system (S110); obtaining a source data record of the target object from full-amount EHR data (S120); performing automatic identification on the source data record to obtain a target time table of the source data record of the target object (S130); and comparing the target data record with the target time table to obtain a comparison result of the target object (S140). The method compares the target data record with the identified target time table to obtain a comparison result, which can realize a high-quality and high-efficiency digital inspection process in the clinical trial, adapt to a mass data environment, and reduce the cost of the clinical trial.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to a digital auditing method, apparatus, electronic device, and computer-readable storage medium for use in clinical trials. Background Technology

[0002] In traditional clinical trials, to ensure data quality, one to two manual audits are typically conducted during the trial. These audits mainly focus on operational compliance and data accuracy. Data accuracy audits primarily target the data within the Electronic Data Capture System (EDC). Since manual auditing requires both organizing and locating source data, and manually comparing the source data with the data entered into the EDC, it is not only time-consuming but also prone to human error. Therefore, traditional manual audits employ a patient sampling method. However, this sampling method has the following problems:

[0003] 1. Case Report Form (CRF), adverse event record form (AE), and concomitant and prior medication records (CM) involve a large amount of source data. Manually auditing the entire data for each patient would take a lot of time, and human error is unavoidable.

[0004] 2. Sampling audits of patients can lead to data discrepancies from unaudited patients not being corrected in a timely manner. Furthermore, manual auditing methods are difficult to accumulate and refine, hindering significant efficiency improvements.

[0005] 3. The storage and organization formats of the source data records and the records in the EDC differ significantly, which increases the difficulty of manual auditing and makes it highly dependent on the auditing experience of the auditors.

[0006] Therefore, how to achieve efficient and high-quality digital auditing in clinical trials is an urgent problem to be solved. Summary of the Invention

[0007] This disclosure provides a digital auditing method for clinical trials, comprising: acquiring target data records of a target object from a clinical trial electronic data acquisition system; acquiring source data records of the target object from full EHR data; automatically identifying the source data records to obtain a target timetable of the source data records of the target object; and comparing the target data records with the target timetable to obtain a comparison result of the target object.

[0008] In an exemplary embodiment, the method further includes: obtaining a target standard dictionary; and normalizing the source data records according to the target standard dictionary to obtain normalized source data records.

[0009] In an exemplary embodiment, the target timetable of the source data records includes the target case report visit form of the source data records; wherein, automatically identifying the source data records to obtain the target timetable of the source data records of the target object includes: obtaining a case report visit standard table for the target case report visit form in the clinical trial electronic data acquisition system; automatically identifying the normalized source data records according to the case report visit standard table to obtain the target case report visit form of the source data records of the target object.

[0010] In an exemplary embodiment, the target timetable of the source data records includes a target concomitant medication record table of the source data records; wherein, automatically identifying the source data records to obtain the target timetable of the target object includes: obtaining a concomitant medication standard table for the target concomitant medication visit form in the clinical trial electronic data acquisition system, the concomitant medication standard table including the start time and end time of the concomitant medication plan collection for the target object; and automatically identifying the normalized source data records according to the concomitant medication standard table to obtain the target concomitant medication record table of the source data records of the target object.

[0011] In an exemplary embodiment, the target timetable of the source data records includes a target adverse event record table of the source data records; wherein, automatically identifying the source data records to obtain the target timetable of the target object includes: obtaining an adverse event standard table for the target adverse event visit form in the clinical trial electronic data acquisition system, the adverse event standard table including the start time and end time of the planned adverse event collection for the target object; and automatically identifying the normalized source data records according to the adverse event standard table to obtain the target adverse event record table of the source data records of the target object.

[0012] In an exemplary embodiment, the method further includes: normalizing the target data record according to the target standard dictionary to obtain a normalized target data record.

[0013] In an exemplary embodiment, comparing the target data record with the target time schedule to obtain the comparison result of the target object includes: obtaining configuration information; comparing the target data record with the target time schedule according to the configuration information to obtain the comparison result of the target object; wherein, the configuration information includes the fields of the event primary key field, the event status field, and the event time field corresponding to the event in the target time schedule.

[0014] In an exemplary embodiment, comparing the target data record with the target time schedule according to the configuration information to obtain the comparison result of the target object includes: obtaining the target time schedule of the target data record from the target data record; obtaining the event primary key field, event status field, and event time field of a first event from the target time schedule of the target data record according to the configuration information; searching for a second event from the target time schedule of the source data record according to the event primary key field of the first event of the target data record; sorting the second events according to their occurrence time; searching for a target event whose occurrence time matches the event time field of the first event of the target data record from the sorted second events; and comparing the event status field of the target event with the event status field of the first event to obtain the comparison result of the target object.

[0015] In an exemplary embodiment, comparing the target data record with the target time schedule according to the configuration information to obtain the comparison result of the target object further includes at least one of the following: if the event primary key field, event status field, and occurrence time of the target event completely match the event primary key field, event status field, and event time field of the first event, then the comparison result is a complete match; if the event primary key field of the second event matches the event primary key field of the first event, and the occurrence time of the second event partially matches the event time field of the first event, then the comparison result is a partial match; if the search for the second event fails, or the occurrence time of the second event does not match the event time field of the first event at all, then the comparison result is no evidence found; if the source data record also includes a third event whose event primary key field does not match the first event of the target data record at all, or the source data record also includes a fourth event whose event primary key field matches the first event of the target data record, and the occurrence time does not match the event time field of the first event at all, then the comparison result is not reported.

[0016] In an exemplary embodiment, the method further includes: generating correction information based on the comparison result; and correcting the configuration information and the target standard dictionary based on the correction information.

[0017] In an exemplary embodiment, the method further includes: generating cause analysis information for the target record based on the comparison result; and displaying the comparison result and the cause analysis information of the target object on a display device.

[0018] This disclosure provides a digital auditing device for use in clinical trials, comprising: a first data acquisition module configured to acquire target data records of a target object from a clinical trial electronic data acquisition system; a second data acquisition module configured to acquire source data records of the target object from full EHR data; a source data identification module configured to automatically identify the source data records to obtain a target timetable of the source data records of the target object; and a data record comparison module configured to compare the target data records with the target timetable to obtain a comparison result of the target object.

[0019] This disclosure provides an electronic device, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute a digital auditing method as described in this disclosure for use in clinical trials by executing the executable instructions.

[0020] This disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the digital auditing method for clinical trials as described in this disclosure.

[0021] In some embodiments of the present disclosure, the target data records in the electronic data acquisition system for clinical trials are compared with the target timetable identified from the full EHR data to obtain the comparison results. This enables a high-quality and efficient digital audit process in clinical trials, adapting to the massive data environment and reducing the cost of clinical trials. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0024] Figure 2 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0025] Figure 3 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0026] Figure 4 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0027] Figure 5 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0028] Figure 6 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0029] Figure 7 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0030] Figure 8 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0031] Figure 9 This is a flowchart of a digital auditing method applied in a clinical trial according to an exemplary embodiment of the present disclosure;

[0032] Figure 10 This is a schematic diagram showing the distribution of cause analysis information in an adverse event record table according to an exemplary embodiment of the present disclosure;

[0033] Figure 11 This is a flowchart illustrating a digital auditing method applied in a clinical trial according to an exemplary embodiment of this disclosure;

[0034] Figure 12 This diagram illustrates the structure of a digital auditing device used in clinical trials, according to an exemplary embodiment of this disclosure.

[0035] Figure 13 A schematic diagram of the structure of a computer system suitable for implementing the embodiments of the present disclosure is shown. Detailed Implementation

[0036] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0037] Furthermore, the accompanying drawings are merely illustrative of this disclosure, and the same reference numerals in the drawings denote the same or similar parts, thus repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0038] In related technologies, EDC auditing primarily includes auditing Case Report Forms (CRFs), Adverse Event Records (AEs), and Concomitant and Prior Medication Records (CMs). An adverse event refers to an unfavorable medical event that occurs after a patient or clinical subject receives a drug, but it is not necessarily causally related to the treatment. Concomitant medication refers to the simultaneous or sequential use of two or more drugs to achieve a therapeutic goal, primarily to increase drug efficacy or reduce drug toxicity.

[0039] The exemplary embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0040] Figure 1 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0041] like Figure 1 As shown in the embodiments of this disclosure, the digital auditing method for clinical trials may include the following steps.

[0042] Step S110: Obtain the target data record of the target subject from the clinical trial electronic data acquisition system.

[0043] In this embodiment, the clinical trial electronic data acquisition system is a data acquisition system that allows direct remote collection of clinical trial data from the experimental center (Sites) via the Internet. The target subjects can be the patients currently requiring digital auditing. The target data records may include, but are not limited to, case report forms, adverse event record forms, and concomitant medication record forms.

[0044] Step S120: Obtain the source data record of the target object from the full EHR data (Electronic Health Record, EHR).

[0045] In this embodiment of the disclosure, the full EHR data is a digital health record primarily composed of hospital electronic medical records, with information sharing as its core. The source data record is the electronic medical record information of the target object within the full EHR data. In an exemplary embodiment, at least one electronic medical record from at least one hospital of the target object can be obtained, and this at least one electronic medical record information can be integrated to obtain the source data record of the target object.

[0046] Step S130: Automatically identify the source data records to obtain the target time schedule of the source data records of the target object.

[0047] In this embodiment, the target timetable may include, but is not limited to, case report forms, adverse event record forms, and combined medication record forms. The target timetable of the source data records can be obtained by automatically identifying the source data records based on a standard dictionary, preset rules, or semantics. Taking the identification of the combined medication record form based on a dictionary as an example, medication records are usually stored as structured information in medication orders. Since the writing style of medications is a finite dataset, a standard dictionary of medication writing styles can be obtained. The source data records are then identified based on this standard dictionary to obtain the combined medication record form. As shown in Table 1 below, different writing styles of levofloxacin are all covered in the standard dictionary of medication writing styles.

[0048] Table 1

[0049] Standard words Synonyms Levofloxacin levofloxacin Levofloxacin Zorofloxacin

[0050] Step S140: Compare the target data record with the target time schedule to obtain the comparison result of the target object.

[0051] In this embodiment of the disclosure, the case report visit form, adverse event record form, and combined medication record form in the target data record can be compared with the case report visit form, adverse event record form, and combined medication record form in the target timetable to obtain the comparison results of the target object.

[0052] According to the digital auditing method applied in clinical trials according to the embodiments of this disclosure, the target data records in the electronic data acquisition system of clinical trials are compared with the target timetable identified from the full EHR data to obtain the comparison results. This enables a high-quality and efficient digital auditing process in clinical trials, adapting to the massive data environment and reducing the cost of clinical trials.

[0053] Figure 2 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0054] like Figure 2 As shown, in one embodiment, the digital auditing method used in clinical trials may include:

[0055] In step S210, target data records of the target subjects are obtained from the clinical trial electronic data acquisition system.

[0056] In step S220, the source data record of the target object is obtained from the full EHR data.

[0057] In step S230, the target standard dictionary is obtained.

[0058] In this embodiment of the disclosure, the target standard dictionary may be a preset medical dictionary or a medical dictionary specifically for the target object.

[0059] Step S240: Normalize the source data records according to the target standard dictionary to obtain normalized source data records.

[0060] In this embodiment of the disclosure, the specific object of the normalization operation may include, for example, key fields (such as test name, test value, drug name), etc.

[0061] In step S250, the normalized source data records are automatically identified to obtain the target timetable of the source data records of the target object.

[0062] In step S260, the target data record is compared with the target time schedule to obtain the comparison result of the target object.

[0063] In an exemplary embodiment, the target data records can also be normalized according to the target standard dictionary to obtain normalized target data records.

[0064] The digital auditing method used in clinical trials according to the present disclosure improves the accuracy of digital auditing by normalizing the source data records before automatic identification of the source data records, thereby unifying the various fields or field values ​​in the source data records into a consistent expression.

[0065] Figure 3This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0066] like Figure 3 As shown, in one embodiment, the target timeline of the source data recording includes the target case report visit form of the source data recording. Step S250 may include:

[0067] Step S310: Obtain the case report visit criteria form for the target case report visit form in the clinical trial electronic data acquisition system.

[0068] In this embodiment of the disclosure, the medical record report visit criteria table may include specific rules for visit time.

[0069] Step S320: Automatically identify the normalized source data records according to the case report visit standard table to obtain the target case report visit form of the source data records of the target object. The digital auditing method applied in clinical trials according to this embodiment automatically identifies the source data records based on the case report visit standard table for case report visit forms in the clinical trial electronic data acquisition system, enabling the acquisition of a target medical record report visit form with a format consistent with the target data records. This facilitates data comparison and improves the accuracy of digital auditing.

[0070] Figure 4 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0071] like Figure 4 As shown, in one embodiment, the target timetable of the source data records includes a target combined medication record table of the source data records. Step S250 may include:

[0072] Step S410: Obtain the concomitant medication criteria table for the target concomitant medication visit form in the clinical trial electronic data acquisition system. The concomitant medication criteria table includes the start time and end time of the concomitant medication plan collection for the target subjects.

[0073] In an exemplary embodiment, the combined medication standard table may further include a medication classification table, which describes detailed classification information of the drugs, such as specific drugs under the prohibited drugs category, specific drugs under the non-focused medication category that are not included in the combined medication, etc.

[0074] Step S420: Automatically identify the normalized source data records according to the combined medication standard table to obtain the target combined medication record table of the source data records of the target object.

[0075] The digital auditing method used in clinical trials according to this disclosure automatically identifies source data records based on the combined medication standard table (and medication classification table) of the combined medication visit form in the clinical trial electronic data acquisition system. This enables the acquisition of a target combined medication record table with the same format as the target data record, facilitating data comparison and improving the accuracy of digital auditing.

[0076] Figure 5 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0077] like Figure 5 As shown, in one embodiment, the target timetable of the source data records includes a target combined medication record table of the source data records. Step S250 may include:

[0078] Step S510: Obtain the adverse event standard table for the target adverse event visit form in the clinical trial electronic data acquisition system. The adverse event standard table includes the start time and end time of the adverse event planning collection for the target subject.

[0079] In this embodiment of the disclosure, the adverse event criteria table may be the Common Terminology Criteria Adverse Events (CTCAE). The Common Terminology Criteria is a descriptive term used in adverse event reporting. Each adverse event is categorized into severity levels.

[0080] Step S520: Automatically identify the normalized source data records according to the adverse event standard table to obtain a target adverse event record table of the source data records of the target object. The digital auditing method applied in clinical trials according to this embodiment automatically identifies the source data records based on the adverse event standard table for the adverse event visit form in the clinical trial electronic data acquisition system, thereby obtaining a target adverse event record table with a format consistent with the target data records. This facilitates data comparison and improves the accuracy of digital auditing.

[0081] Figure 6 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0082] like Figure 6 As shown, in one embodiment, step S140 may include the following steps.

[0083] Step S610: Obtain configuration information.

[0084] Step S620: Compare the target data record with the target time schedule according to the configuration information to obtain the comparison result of the target object; wherein, the configuration information includes the fields of the event primary key field, event status field, and event time field corresponding to the event in the target time schedule.

[0085] In an exemplary embodiment, the target data record may be, for example, a normalized target data record generated after normalizing the target data record according to a target standard dictionary.

[0086] Figure 7 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0087] like Figure 7 As shown, in one embodiment, step S620 may include the following steps.

[0088] Step S710: Obtain the target time schedule from the target data record.

[0089] In this embodiment of the disclosure, the target timetable for target data recording may include case report visit forms, adverse event record forms, and combined medication record forms. In an exemplary embodiment, the target data records may be pre-normalized according to a target standard dictionary to obtain normalized target data records, and step S710 is performed on the normalized target data records.

[0090] Step S720: Based on the configuration information, obtain the event primary key field, event status field, and event time field of the first event from the target time schedule of the target data record.

[0091] Step S730: Based on the event primary key field of the first event in the target data record, find the second event from the target time schedule of the source data record.

[0092] In an exemplary embodiment, the source data records can be normalized in advance according to the target standard dictionary to obtain normalized source data records, so as to perform step S730 on the source target data records.

[0093] Step S740: Sort the second events according to their occurrence time.

[0094] Step S750: From the sorted second events, find the target event whose occurrence time matches the event time field of the first event in the target data record.

[0095] Step S760: Compare the event status field of the target event with the event status field of the first event to obtain the comparison result of the target object.

[0096] In an exemplary embodiment, the comparison of adverse event record tables is taken as an example. Table 2 is a partial excerpt of the adverse event record table in the target data record (or normalized target data record).

[0097] Table 2

[0098]

[0099] Table 3 shows a portion of the target adverse event record table from the source data records (or normalized source data records).

[0100] Table 3

[0101]

[0102] As shown in Tables 2 and 3, in the target data records of the clinical trial electronic data acquisition system, events in the same state over a period of time are typically recorded as one event. In the source data records of the full EHR data, the same state occurring at different time points is typically recorded multiple times. For example, in step S720, the event primary key field in the target data record can be determined as AE name, the event status field as level, and the event time field as start and end time, based on the configuration information. As another example, in step S720, the event primary key field can be determined as AE name and level, based on the configuration information. The configuration information describes the fields corresponding to the event primary key field, event status field, and event time field in the target time table. When the event primary key field is AE name, in step S730, the field value of the event status field of the first event in the target data record in Table 2 is: nausea. A second event with the event primary key field "nausea" can be found in the target time table of the source data records in Table 3. Then, in the sorted second events, the target event whose occurrence time matches the event time field of the first event is searched. The event time field that meets the criteria for the first event can be: the occurrence time T satisfies the rule: start time <= T <= end time.

[0103] The digital auditing method applied in clinical trials according to embodiments of this disclosure utilizes configuration information to obtain an event primary key field, an event status field, and an event time field from a first event in a target data record. It then searches for a second event in a target timeline within the source data record based on the event primary key field, enabling matching based on the event primary key field. By sorting the second events according to their occurrence time and searching for the target event within the second events based on the event time field, it achieves time-series analysis and matching. In summary, the technical solution of this disclosure, based on a comparison process of target and source data records using three dimensions—event primary key field, event time field, and event status field—enables rapid and efficient comparison in the digital auditing process of clinical trials, yielding high-quality comparison results.

[0104] In one embodiment, step S620 may further include at least one of the following steps.

[0105] Step S761: If the primary key field, event status field, and occurrence time of the target event completely match the primary key field, event status field, and event time field of the first event, then the comparison result is a complete match.

[0106] Step S762: If the event primary key field of the second event matches the event primary key field of the first event, and the occurrence time of the second event partially matches the event time field of the first event, then the comparison result is a partial match.

[0107] Step S763: If the search for the second event fails, or if the occurrence time of the second event does not match the event time field of the first event at all, the comparison result is no evidence found.

[0108] In this embodiment of the disclosure, when the search for the second event fails, or when the occurrence time of the second event does not match the event time field of the first event at all, it can be determined that the target data record includes events that are not recorded in the source data record.

[0109] Step S764: If the source data record also includes a third event whose event primary key field does not match the first event of the target data record at all, or if the source data record also includes a fourth event whose event primary key field matches the first event of the target data record but whose occurrence time does not match the event time field of the first event at all, then the comparison result is not reported.

[0110] In this embodiment of the disclosure, when the source data record also includes a third event whose event primary key field does not match the first event of the target data record at all, or when the source data record also includes a fourth event whose event primary key field matches the first event of the target data record but whose occurrence time does not match the event time field of the first event at all, it can be determined that the target data record is missing the event recorded in the source data record.

[0111] In an exemplary embodiment, configuration information can be set, which includes the fields of the event primary key field, event status field, and event time field corresponding to the event in the target time schedule.

[0112] The digital auditing method used in clinical trials according to the present disclosure matches the target data record and the target source data record on a target timeline based on the event primary key field, event status field, and event time field. The comparison result is determined based on the matching result and is divided into complete match, partial match, no evidence found, and no report. It can accurately classify the comparison result based on three-dimensional data comparison, which makes it easier for operators to find the cause of data error in a timely manner based on the comparison result and improves user experience.

[0113] Figure 8 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0114] like Figure 8 As shown, in one embodiment, the digital auditing method used in clinical trials may further include the following steps.

[0115] Step S810: Generate correction information based on the comparison results.

[0116] Step S820: Correct the configuration information and target standard dictionary according to the correction information.

[0117] In this embodiment of the disclosure, the configuration information and target standard dictionary are corrected according to the correction information, which can continuously optimize the configuration information and target standard dictionary and improve the accuracy of digital auditing.

[0118] Figure 9 This is a flowchart of a digital auditing method applied in clinical trials according to an exemplary embodiment of the present disclosure.

[0119] like Figure 9 As shown, in one embodiment, the digital auditing method used in clinical trials may further include the following steps.

[0120] Step S910: Generate cause analysis information for the target record based on the comparison results.

[0121] Step S920: Display the comparison results and cause analysis information of the target object on the display device.

[0122] In this embodiment of the disclosure, the cause analysis information may be as follows:

[0123] 1. Perfect match: No need to worry about it.

[0124] 2. Partial match: The source data record may not be completely present in the target data record, such as paper evidence (e.g., paper medical records from other hospitals).

[0125] 1) Correct paper evidence: Authentic evidence was found in the paper evidence, and a perfect match was finally confirmed.

[0126] 2) Confirmation of recording error: No authentic evidence was found in the paper evidence, and it was finally confirmed that the CRC entry was incorrect.

[0127] 3. No evidence found: The target data record may not be fully present in the source data record, such as paper evidence (e.g., paper medical records from other hospitals).

[0128] 1) Paper Covering: Find the real evidence in the paper evidence and finally make a perfect match.

[0129] 2) Confirmation of data entry error: When no real evidence was found in the paper evidence, it was finally confirmed that the data was entered incorrectly by the Clinical Research Coordinator (CRC).

[0130] 3) Unknown: If no real evidence is found in the paper evidence, the case is eventually reported to a Clinical Research Associate (CRA) for further confirmation.

[0131] 4) Algorithm issues: There are still algorithmic issues in machine learning for natural language recognition that need to be addressed.

[0132] 4. Not reported: This is likely to exist in the source data record, but was not detected by CRC during data entry.

[0133] 1) Confirm missing entries: The researcher has confirmed the record to be entered, but the CRC did not enter it, which is a human error.

[0134] 2) Missed judgment: The researcher has not yet judged the abnormal data, the CRC did not ask the researcher to judge, and it was a human error.

[0135] 3) No reporting required: Reporting is not required as confirmed by the researcher.

[0136] Figure 10 This is a schematic diagram illustrating the distribution of cause analysis information in an exemplary adverse event record table according to this disclosure. For example... Figure 10 As shown, the cause analysis information can be found below:

[0137] 1. Exact match

[0138] 1) Perfect match 901: Inspectors no longer need to pay any attention, saving all their time.

[0139] 2. Partial Matching

[0140] 2) Confirmed error 902: The AE level is actually level 2 but was mistakenly entered as level 1, and needs to be corrected.

[0141] 3) Paper record is correct 903: The AE level is level 1 in the source data record and level 2 in the paper record, which is correct.

[0142] 3. No evidence found

[0143] 4) Paper Coverage 904: The actual evidence is in the paper medical records.

[0144] 5) Algorithm Problem 905: There are some problems with the machine algorithm in the inspector's judgment. The algorithm needs to be further improved.

[0145] 6) Unknown 906: The investigators also found no evidence and the CRA needs to investigate further.

[0146] 7) Error entry 907: AE record has two duplicate entries.

[0147] 4. Not reported

[0148] 8) AE omission 908: Researchers have confirmed that it is AE, but CRC did not enter it into EDC, resulting in an entry error.

[0149] 9) AE omission judgment 909: The researcher failed to judge the suspected AE, which needs to be judged before processing.

[0150] 10) NAE910: It was determined that it is not AE, so no data entry is required. The algorithm needs further improvement.

[0151] In an exemplary embodiment, corrective information can be determined based on cause analysis information. The configuration information and target standard dictionary can then be corrected based on this corrective information, improving the accuracy of digital auditing and reducing the degree of manual intervention. For example, consider a dictionary used in combined drug use:

[0152] There was a combined medication record in the EDC: levofloxacin; February 2, 2018. However, according to the technical solution of this disclosure embodiment, the comparison result showed no evidence found. Upon investigation, the auditor verified that the record existed in the outpatient medication order. It was later discovered that the physician had misspelled the medication as levofloxacin, a misspelling that word not found in the target standard dictionary, leading to incorrect classification as levofloxacin. This was an algorithmic error. The problem was resolved after updating the dictionary with levofloxacin. The accuracy of the entire combined medication identification process improved during this iteration.

[0153] Figure 11 This is a flowchart illustrating a digital auditing method applied in clinical trials according to an exemplary embodiment of this disclosure. Figure 11 As shown, in one embodiment, the digital auditing method used in clinical trials may include the following steps. Step S1110, scheme breakdown.

[0154] In this embodiment of the disclosure, the case report visit criteria table, combined medication criteria table, adverse event criteria table, medication classification table, and target criteria dictionary for the target subjects can be determined according to the clinical trial protocol of the target subjects.

[0155] The process of obtaining the case report visit criteria form can be similar to step S310, and will not be repeated here.

[0156] The process of obtaining the combined medication standard table can be similar to step S410, and will not be described again here.

[0157] The process of obtaining the adverse event criteria table can be similar to step S510, and will not be described again here.

[0158] The target standard dictionary can be obtained by integrating clinical trial protocols for the target subjects from the standard dictionary.

[0159] Step S1120: Data standardization.

[0160] In this embodiment of the disclosure, the target data record can be normalized. The source data record is normalized and automatically identified to obtain the target timetable of the source data record. The normalization and automatic identification process of the source data record can take steps similar to steps S240 and S250, and will not be described again here.

[0161] Step S1130: Data comparison.

[0162] In this embodiment of the disclosure, the target timeline of the normalized target data record can be compared with the target timeline of the normalized source data record to obtain the comparison result of the target object. The data comparison process can take steps similar to steps S140 or steps S710 to S760, S761 to S764, which will not be described in detail here.

[0163] Step S1140, data analysis.

[0164] In this embodiment of the disclosure, cause analysis information of the target record can be generated based on the comparison results; the comparison results and cause analysis information of the target object can be displayed on a display device.

[0165] Step S1150, iterative feedback.

[0166] In this embodiment of the disclosure, correction information can be generated based on the comparison results; and the configuration information and target standard dictionary can be corrected based on the correction information.

[0167] In an exemplary embodiment, if the automatic identification of source data records is based on rules, the rules can be modified according to the correction information.

[0168] In an exemplary embodiment, an audit report may also be generated. This audit report can be generated based on comparison results and cause analysis information; the audit report is then sent to the applicant of the target entity.

[0169] Based on the same concept as the embodiments of the method of the present invention Figure 12 This diagram illustrates the structure of a digital auditing device used in clinical trials, according to an exemplary embodiment of this disclosure. Please refer to... Figure 12 This invention also provides a digital auditing device for use in clinical trials. For example... Figure 12As shown, the digital auditing device 1200 used in clinical trials may include a first data acquisition module 1210, a second data acquisition module 1220, a source data identification module 1230, and a data record comparison module 1240.

[0170] In the digital auditing device 1200 used in clinical trials, the first data acquisition module 1210 can be configured to acquire target data records of the target object from the clinical trial electronic data acquisition system.

[0171] The second data acquisition module 1220 can be configured to acquire source data records of the target object from the full EHR data.

[0172] The source data identification module 1230 can be configured to automatically identify source data records and obtain the target time schedule of the source data records of the target object.

[0173] In an exemplary embodiment, the target timetable of the source data records may include the target case report visit form of the source data records. The source data identification module may include a case report visit standard form acquisition unit and a medical record visit form identification unit. The case report visit standard form acquisition unit may be configured to acquire a case report visit standard form for the target case report visit form in the clinical trial electronic data acquisition system. The medical record visit form identification unit may be configured to automatically identify the normalized source data records according to the case report visit standard form to obtain the target case report visit form of the source data records of the target object.

[0174] In an exemplary embodiment, the target timetable of the source data records may include a target concomitant medication record table for the source data records. The source data identification module may include a concomitant medication standard table acquisition unit and a concomitant medication record table identification unit. The concomitant medication standard table acquisition unit may be configured to acquire a concomitant medication standard table for the target concomitant medication visit form in the clinical trial electronic data acquisition system. The concomitant medication standard table includes the start time and end time of the concomitant medication plan collection for the target object. The concomitant medication record table identification unit may be configured to automatically identify the normalized source data records according to the concomitant medication standard table to obtain the target concomitant medication record table of the source data records for the target object.

[0175] In an exemplary embodiment, the target timeline for source data recording may include a target adverse event record table for the source data recording. The source data identification module may include an adverse event standard table acquisition unit and an adverse event record table identification unit. The adverse event standard table acquisition unit may be configured to acquire an adverse event standard table for the target adverse event visit form in the clinical trial electronic data acquisition system. The adverse event standard table includes the start and end times of the planned adverse event collection for the target object. The adverse event record table identification unit may be configured to automatically identify the normalized source data records based on the adverse event standard table to obtain the target adverse event record table for the source data records of the target object.

[0176] The data record comparison module 1240 can be configured to compare the target data record with the target time schedule to obtain the comparison result of the target object.

[0177] In an exemplary embodiment, the data record comparison module 1240 may include a configuration information acquisition unit and a data comparison unit. The configuration information acquisition unit may be configured to acquire configuration information. The data comparison unit may be configured to compare the target data record with the target time schedule based on the configuration information to obtain the comparison result of the target object; wherein the configuration information includes the fields of the event primary key field, event status field, and event time field corresponding to the event in the target time schedule.

[0178] In an exemplary embodiment, the data comparison unit may include a target timetable acquisition unit, a field acquisition unit, a primary key field comparison unit, a time sorting unit, a time field comparison unit, and a status field comparison unit. The target timetable acquisition unit may be configured to acquire the target timetable of a target data record from the target data record. The field acquisition unit may be configured to acquire the event primary key field, event status field, and event time field of a first event from the target timetable of the target data record according to configuration information. The primary key field comparison unit may be configured to search for a second event from the target timetable of the source data record based on the event primary key field of the first event in the target data record. The time sorting unit may be configured to sort the second events according to their occurrence time. The time field comparison unit may be configured to search for a target event whose occurrence time matches the event time field of the first event in the target data record from the sorted second events. The status field comparison unit may be configured to compare the event status field of the target event with the event status field of the first event to obtain the comparison result of the target object.

[0179] In an exemplary embodiment, the data comparison unit may further include at least one of the following: a first result unit, a second result unit, a third result unit, and a fourth result unit. The first result unit may be configured such that if the event primary key field, event status field, and occurrence time of the target event completely match the event primary key field, event status field, and event time field of the first event, the comparison result is a complete match. The second result unit may be configured such that if the event primary key field of the second event matches the event primary key field of the first event, and the occurrence time of the second event partially matches the event time field of the first event, the comparison result is a partial match. The third result unit may be configured such that if finding the second event fails, or if the occurrence time of the second event does not match the event time field of the first event, the comparison result is no evidence found. The fourth result unit may be configured such that if the source data record also includes a third event whose event primary key field does not match the first event of the target data record, or if the source data record also includes a fourth event whose event primary key field matches the first event of the target data record, and its occurrence time does not match the event time field of the first event, the comparison result is no report.

[0180] In an exemplary embodiment, the digital auditing device 1200 used in clinical trials may further include a dictionary acquisition module and a source data normalization module. The dictionary acquisition module may be configured to acquire a target standard dictionary. The source data normalization module may be configured to normalize source data records according to the target standard dictionary to obtain normalized source data records.

[0181] In an exemplary embodiment, the digital auditing device 1200 used in clinical trials may further include a target data normalization module, wherein the target data normalization module may be configured to normalize the target data records according to a target standard dictionary to obtain normalized target data records.

[0182] In an exemplary embodiment, the digital auditing device 1200 used in clinical trials may further include a configuration information setting module. The configuration information setting module can be configured to set configuration information, including the fields of the event primary key field, event status field, and event time field corresponding to the event in the target time schedule.

[0183] In an exemplary embodiment, the digital auditing device 1200 used in clinical trials may further include a correction information generation module and a data correction module. The correction information generation module is configured to generate correction information based on the comparison results. The data correction module is configured to correct the configuration information and the target standard dictionary based on the correction information.

[0184] In an exemplary embodiment, the digital auditing device 1200 used in clinical trials may further include a cause analysis information generation module and a cause analysis information display module. The cause analysis information generation module can be configured to generate cause analysis information for the target record based on the comparison results. The cause analysis information display module can be configured to display the comparison results and cause analysis information of the target object on a display device.

[0185] The digital auditing device used in clinical trials according to embodiments of this disclosure compares the target data records in the clinical trial electronic data acquisition system with the target timetable identified from the full EHR data to obtain the comparison results. This enables a high-quality and efficient digital auditing process in clinical trials, adapting to massive data environments and reducing clinical trial costs.

[0186] For ease of description, the above device embodiments are described by function as various units or modules. When implementing the present invention, the functions of each unit or module can be implemented in one or more software and / or hardware.

[0187] Figure 13 A schematic diagram of a computer system suitable for implementing embodiments of the present disclosure is shown. It should be noted that... Figure 13 The computer system 1500 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0188] like Figure 13 As shown, the computer system 1300 includes a central processing unit (CPU) 1301, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 1302 or programs loaded from storage portion 1308 into random access memory (RAM) 1303. The RAM 1303 also stores various programs and data required for system operation. The CPU 1301, ROM 1302, and RAM 1303 are interconnected via a bus 1304. An input / output (I / O) interface 1305 is also connected to the bus 1304.

[0189] The following components are connected to I / O interface 1305: an input section 1306 including a keyboard, mouse, etc.; an output section 1307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1308 including a hard disk, etc.; and a communication section 1309 including a network interface card such as a LAN card, modem, etc. The communication section 1309 performs communication processing via a network such as the Internet. Drive 1310 is also connected to I / O interface 1305 as needed. Removable media 1311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1310 as needed so that computer programs read from them can be installed into storage section 1308 as needed.

[0190] In particular, according to embodiments of this disclosure, the processes described below with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1309, and / or installed from removable medium 1311. When the computer program is executed by central processing unit (CPU) 1301, it performs various functions defined in the system of this application.

[0191] It should be noted that the computer-readable medium disclosed herein may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0192] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0193] The modules and / or units and / or sub-units described in the embodiments of this disclosure can be implemented in software or hardware, and the described modules and / or units and / or sub-units can also be located in a processor. The names of these modules and / or units and / or sub-units do not, in some cases, constitute a limitation on the module and / or unit and / or sub-unit itself.

[0194] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: entirely hardware implementations, entirely software implementations (including firmware, microcode, etc.), or implementations combining hardware and software aspects, collectively referred to herein as “circuits,” “modules,” or “systems.”

[0195] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0196] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0197] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0198] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0199] In the embodiments provided in this disclosure, it should be understood that the disclosed electronic devices, computer-readable storage media, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, or they may be electrical, mechanical, or other forms of connection.

[0200] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of this disclosure, depending on actual needs.

[0201] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0202] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0203] The above are merely specific embodiments of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this disclosure, and these modifications or substitutions should all be covered within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A digital auditing method for use in clinical trials, characterized in that, include: The target data records of the target subjects are obtained from the clinical trial electronic data acquisition system; wherein, the target data records include at least one of the following: case report visit form, adverse event record form, and concomitant medication record form; The source data record of the target object is obtained from the full EHR data; the source data record is the electronic medical record information of the target object in the full EHR data; The source data records are automatically identified to obtain the target timeline of the source data records of the target object. The target data record is compared with the target time schedule to obtain the comparison result of the target object, including: Obtain configuration information; the configuration information includes the event primary key field, event status field, and event time field, which correspond to the event in the target time schedule; The target timetable of the target data record is obtained from the target data record; according to the configuration information, the event primary key field, event status field, and event time field of the first event are obtained from the target timetable of the target data record; according to the event primary key field of the first event of the target data record, the second event is searched from the target timetable of the source data record; the second event is sorted according to the occurrence time of the second event; from the sorted second events, the target event whose occurrence time matches the event time field of the first event of the target data record is searched; the event status field of the target event is compared with the event status field of the first event to obtain the comparison result of the target object.

2. The method as described in claim 1, characterized in that, The method further includes: Obtain the target standard dictionary; The source data records are normalized according to the target standard dictionary to obtain normalized source data records.

3. The method as described in claim 2, characterized in that, The target timeline of the source data records includes the target case report visit form of the source data records; wherein, automatically identifying the source data records to obtain the target timeline of the source data records of the target object includes: Obtain the case report visit criteria form for the target case report visit form in the clinical trial electronic data acquisition system; The normalized source data records are automatically identified based on the case report visit criteria table to obtain the target case report visit table for the target object.

4. The method as described in claim 2, characterized in that, The target timetable of the source data records includes the target combined medication record table of the source data records; wherein, automatically identifying the source data records to obtain the target timetable of the target object includes: Obtain the concomitant medication criteria table for the target concomitant medication visit form in the electronic data acquisition system for the clinical trial. The concomitant medication criteria table includes the start time and end time of the concomitant medication plan collection for the target subject. The normalized source data records are automatically identified based on the combined medication standard table to obtain the target combined medication record table of the source data records of the target object.

5. The method as described in claim 2, characterized in that, The target timeline of the source data records includes a target adverse event record table of the source data records; wherein, automatically identifying the source data records to obtain the target timeline of the target object includes: Obtain an adverse event standard table for the target adverse event visit form in the electronic data acquisition system of the clinical trial, wherein the adverse event standard table includes the start time and end time of the planned adverse event collection for the target subject; The normalized source data records are automatically identified based on the adverse event standard table to obtain the target adverse event record table of the source data records of the target object.

6. The method as described in claim 2, characterized in that, The method further includes: Based on the target standard dictionary, the target data records are normalized to obtain normalized target data records.

7. The method as described in claim 1, characterized in that, The comparison of the target data record with the target time schedule based on the configuration information to obtain the comparison result of the target object also includes at least one of the following: If the primary key field, event status field, and occurrence time of the target event completely match the primary key field, event status field, and event time field of the first event, then the comparison result is a complete match. If the primary key field of the second event matches the primary key field of the first event, and the occurrence time of the second event partially matches the event time field of the first event, then the comparison result is a partial match. If the search for the second event fails, or if the occurrence time of the second event does not match the event time field of the first event at all, then the comparison result is no evidence found. If the source data record also includes a third event whose event primary key field does not match the first event of the target data record at all, or if the source data record also includes a fourth event whose event primary key field matches the first event of the target data record but whose occurrence time does not match the event time field of the first event at all, then the comparison result is not reported.

8. The method as described in claim 1, characterized in that, The method further includes: Correction information is generated based on the comparison results; The configuration information and target standard dictionary are corrected based on the correction information.

9. The method as described in claim 1, characterized in that, The method further includes: Based on the comparison results, generate cause analysis information for the target record; The comparison results and cause analysis information of the target object are displayed on the display device.

10. A digital auditing device for use in clinical trials, characterized in that, include: The first data acquisition module is configured to acquire target data records of the target object from the clinical trial electronic data acquisition system; wherein, the target data records include at least one of the following: case report visit form, adverse event record form, and combined medication record form; The second data acquisition module is configured to acquire the source data record of the target object from the full EHR data; the source data record is the electronic medical record information of the target object in the full EHR data; The source data identification module is configured to automatically identify the source data records and obtain the target time schedule of the source data records of the target object; The data record comparison module is configured to compare the target data record with the target time schedule to obtain the comparison result of the target object, including: obtaining configuration information; the configuration information includes the fields of the event primary key field, event status field, and event time field corresponding to the event in the target time schedule; The target timetable of the target data record is obtained from the target data record; according to the configuration information, the event primary key field, event status field, and event time field of the first event are obtained from the target timetable of the target data record; according to the event primary key field of the first event of the target data record, the second event is searched from the target timetable of the source data record; the second event is sorted according to the occurrence time of the second event; from the sorted second events, the target event whose occurrence time matches the event time field of the first event of the target data record is searched; the event status field of the target event is compared with the event status field of the first event to obtain the comparison result of the target object.

11. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the digital auditing method for use in clinical trials as described in any one of claims 1-9 by executing the executable instructions.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the digital auditing method for clinical trials as described in any one of claims 1-9.

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