CN111080159A

CN111080159A - Risk monitoring method and system for quality supervision of clinical trial research center

Info

Publication number: CN111080159A
Application number: CN201911374216.3A
Authority: CN
Inventors: 段成辉
Original assignee: Mobilemd System Jiaxing Co ltd
Current assignee: Shanghai Yikai Intelligent Technology Co ltd
Priority date: 2019-12-27
Filing date: 2019-12-27
Publication date: 2020-04-28

Abstract

The invention relates to a risk monitoring method and a system for quality supervision of a clinical trial research center, wherein the method comprises the following steps: providing an index configuration setting page, and receiving a first input of a normal value range and weight of a risk index at the index configuration setting page; providing a docking configuration page, and selecting a clinical trial research center to be subjected to quality supervision on the docking configuration page; obtaining data relating to the risk indicator from the selected clinical trial research centre; calculating the risk indicator from the data; dividing the risk index into a plurality of risk grades according to the risk degree; and providing a result display page, simultaneously displaying a plurality of risk indexes of a plurality of clinical trial research centers on the result display page, and representing different risk files by using different colors. According to the method, quality supervision and risk monitoring can be timely and accurately carried out on the clinical trial research center.

Description

Risk monitoring method and system for quality supervision of clinical trial research center

Technical Field

The invention mainly relates to the field of clinical trial research, in particular to a risk monitoring method and a risk monitoring system for quality supervision of a clinical trial research center.

Background

The clinical trial research center is the subject of clinical trial research. In order to ensure the smooth progress of clinical trial research, quality supervision needs to be performed on each clinical trial research center, risk factors are found in time, and corresponding intervention measures are taken. Tools currently used for managing Clinical Trial Data include a Clinical Trial Management System (CTMS), an Electronic document management System (eTMF), and an Electronic Data Capture System (EDC). These tools may help researchers manage the flow, documentation, data of clinical trial studies. However, there is no system that can perform quality supervision and risk monitoring early warning for clinical trial research centers. Currently, the risk indicators of each clinical trial research center are mainly obtained by manually counting and calculating clinical trial data, and specifically include the following steps:

(1) the manager of the clinical trial research project sets data to be collected, such as group number, problem number, scheme violation number and the like, as specific work content according to risk occurrence points required to be managed by the project;

(2) the quality of each clinical trial research center is inspected by an inspector according to specific work content, a work-gathering form is filled according to the inspection result, and the work-gathering form is delivered to a project manager;

(3) the project manager collects all the work report forms, substitutes the data in the work report forms into a calculation formula of the risk index, and presents the calculation results through a perspective table and a color level function.

The above calculation method of the risk index needs to collect and calculate massive data, consumes huge manpower, and has the problems of inaccurate acquired data, untimely acquisition and the like.

Disclosure of Invention

The invention aims to provide a method and a system for timely and accurately monitoring quality and risk of a clinical trial research center.

The technical scheme adopted by the invention for solving the technical problems is a risk monitoring method for quality supervision of a clinical trial research center, which is characterized by comprising the following steps of: providing an index configuration setting page, and receiving a first input of a normal value range and weight of a risk index at the index configuration setting page; providing a docking configuration page, and selecting a clinical trial research center to be subjected to quality supervision on the docking configuration page; obtaining data relating to the risk indicator from the selected clinical trial research centre; calculating the risk indicator from the data; dividing the risk index into a plurality of risk grades according to the risk degree; and providing a result display page, simultaneously displaying a plurality of risk indexes of a plurality of clinical trial research centers on the result display page, and representing different risk files by using different colors.

In an embodiment of the invention, when the data of the clinical trial research centre is updated, the risk indicator is calculated from the updated data.

In an embodiment of the present invention, the method further includes receiving a second input of an intervention measure for the risk indicator on the indicator configuration setting page.

In one embodiment of the invention, a risk variation trend graph corresponding to the selected clinical trial research center is displayed on the result display page according to time periods.

In an embodiment of the invention, the risk profiles include low risk, medium risk and high risk.

In an embodiment of the present invention, the categories of the risk indicators include: progress, data, quality, grouping, and documentation.

The invention also provides a risk monitoring system for quality supervision of a clinical trial research center for solving the technical problems, which is characterized by comprising the following components: the parameter setting module is used for setting a risk index, and comprises a normal value range and a weight of the risk index; the docking configuration module is used for selecting a clinical trial research center to be subjected to quality supervision and acquiring data related to the risk index from the selected clinical trial research center; a calculation module for calculating the risk indicator according to the data; and the display module is used for providing a result display page, simultaneously displaying a plurality of risk indexes of a plurality of clinical trial research centers on the result display page, and representing different risk files by using different colors.

In an embodiment of the present invention, when the data of the clinical trial research center is updated, the docking configuration module obtains the updated data in real time, and the calculation module calculates the risk indicator according to the updated data.

In an embodiment of the present invention, the parameter setting module is further configured to set an intervention measure for the risk indicator.

In an embodiment of the invention, the display module is further configured to display a risk variation trend corresponding to the selected clinical trial research center on the result display page according to a time period.

In an embodiment of the present invention, the categories of the risk indicators include: progress, grouping, quality, data, and documentation.

The invention also provides a risk monitoring system for quality supervision of a clinical trial research center for solving the technical problems, which comprises: a memory for storing instructions executable by the processor; a processor for executing the instructions to implement the method as described above.

The present invention also provides a computer readable medium storing computer program code, which when executed by a processor implements the method as described above.

According to the risk monitoring method and the system for quality supervision of the clinical test research center, the normal value range and the weight of each risk index can be flexibly set, the risk indexes are automatically calculated through an internally packaged calculation formula, the calculation results of the risk indexes of each clinical test research center are visually displayed in colors in a result display page, the risk indexes can be updated in real time, the whole process is convenient and rapid, the reliability is high, the automation degree is high, and the quality supervision and the risk monitoring of the clinical test research center can be timely and accurately carried out.

Drawings

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below, wherein:

FIG. 1 is an exemplary flow chart of a risk monitoring method of quality supervision of a clinical trial research center according to an embodiment of the present invention;

fig. 2A is a schematic diagram of an index configuration setting page in the risk monitoring method according to an embodiment of the present invention;

FIG. 2B is a second schematic diagram of an index configuration setting page in the risk monitoring method according to the embodiment of the invention;

fig. 3A is one of schematic diagrams of a docking configuration page in the risk monitoring method according to an embodiment of the present invention;

FIG. 3B is a second schematic diagram of a docking configuration page in the risk monitoring method according to the embodiment of the invention;

FIG. 4 is a diagram of a result display page in the risk monitoring method according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a risk trend graph in a risk monitoring method according to an embodiment of the present invention;

FIG. 6 is a block diagram of a risk monitoring system for quality supervision by a clinical trial research center in accordance with an embodiment of the present invention.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and thus the present invention is not limited to the specific embodiments disclosed below.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used herein to illustrate the operations performed by methods according to embodiments of the present invention. It should be understood that the preceding operations are not necessarily performed in the exact order in which they are performed. Rather, various steps may be processed in reverse order or simultaneously. Meanwhile, other operations are added to or removed from these processes.

FIG. 1 is an exemplary flow chart of a risk monitoring method for quality supervision of a clinical trial research center according to an embodiment of the present invention. Fig. 2A-5 are schematic diagrams of some of the pages involved in the execution of the risk monitoring method of this embodiment. The risk monitoring method of this embodiment is described below in conjunction with fig. 1 and fig. 2A-5. Specifically, referring to fig. 1, the risk monitoring method of this embodiment includes the steps of:

step 110, providing an index configuration setting page, and receiving a first input of the normal value range and the weight of the risk index on the index configuration setting page.

Fig. 2A is a schematic diagram of an index configuration setting page in the risk monitoring method according to an embodiment of the invention. Referring to fig. 2A, the index configuration setting page 200 includes a risk configuration area 210 and an index setting area 220.

It can be understood that the risk monitoring method of the present invention can be applied to clinical trial management systems such as CTMS described in the background art, and therefore, each page presented in the method can be embedded in an existing software system; the risk monitoring method of the present invention may also be run as a stand-alone program, independent of existing clinical trial management systems.

In addition, it should be noted that the risk monitoring method of the present invention is set up for a specific clinical trial study. The risk indexes of different clinical trial research projects to be subjected to risk monitoring can be different, so that the risk monitoring method can flexibly configure the risk indexes corresponding to the clinical trial research projects and monitor the quality and the risk of each clinical trial research center according to the risk indexes.

In the embodiment shown in FIG. 2A, a user may select a risk indicator in the risk configuration area 210 that needs to be monitored. In some embodiments, the risk indicators may be divided by type: progress, data, quality, grouping and documentation, etc. Some specific risk indicators are also included among the different types of risk indicators. Table one lists 5 classes of 17 different risk indicators, their respective meanings, and the calculation method. The first row lists the total score and its calculation, which is used to evaluate the overall risk for a clinical trial study center. The weight used therein is the "weight" set in the index setting area 220 shown in fig. 2A. The calculation of the total risk score shown in Table one is merely an example.

Watch 1

Below the first row in table one, the first column is 5 risk categories, the second column is the name of the risk indicator in each risk category, and the third column shows the meaning of the risk indicator and its calculation formula. Table one is not used to limit the number of risk indicators to be set in the risk monitoring method of the present invention. In other embodiments, the risk indicator may further include other categories and specific indicator names, for example, the category of the risk indicator may further include security, and the security includes risk indicators such as SAE (severe Adverse Events) occurrence rate, SAE reporting timeliness rate, SAE delay unreported number, and the like.

In the embodiment shown in FIG. 2A, the user may click on the "close" button in the risk configuration area 210 to close the undesired risk indicators. When a user selects a certain risk index in the risk configuration area 210, a weight and a normal value range may be set for the selected risk index in the index setting area 220. A weight setting area 221 and a normal value range setting area 222 are included in the index setting area 220. Wherein, an integer of 0-10 can be entered in the input box in the weight setting area 221 to indicate the weight of the risk indicator in the clinical trial research project. In the normal value range setting area 222, there are two input boxes that can fill in the upper and lower limits of the normal value of the risk indicator, respectively. The present invention refers to the input received in the index configuration setting page 200 for the normal value range and weight of the risk index as the first input.

In the embodiment shown in FIG. 2A, the selected risk indicator, i.e., the risk indicator that appears gray in the risk configuration area 210, is the "milestone delay days" in the category "progress". The weight setting area 221 sets the weight of the risk indicator to "8"; the normal value range in which the risk indicator is set in the normal value range setting area 222 is "5 days ≦ normal range value <15 days". The unit of this risk index is "day", and therefore, the unit of this risk index displayed in the normal value range setting area 222 is "day". The unit may be adjusted according to the unit of the selected risk indicator. A text comment 223 is also given in the normal value range setting area 222, which indicates that if the risk indicator is smaller than the normal value range, it is superior, and in the result display page of step 160, it can be represented by green; if the risk index is within the normal value range and is normal, the risk index is represented by yellow in a result display page; if the risk index is greater than the normal value range, the index is abnormal and is represented by red. The content of the segment of textual annotation 223 may also be different for different risk indicators.

In some embodiments, the risk monitoring method of the present invention also receives a second input of intervention measures for the risk indicator in the indicator configuration settings page 200. Fig. 2B is a second schematic diagram of an index configuration setting page in the risk monitoring method according to the embodiment of the invention. As shown in fig. 2B, an intervention measure area 230 is further included in the index configuration setting page 200. The user may add intervention individually in the intervention zone 230 by clicking the add button 231. In this embodiment, the intervention measures generated in the intervention measures area 230 are given in the form of a list, which includes 6 items in total, i.e., the head line of the list, which is the scope (%), the related problem, the suggested measure, the required duration for taking the measure, the issued task, and the operation, respectively. All of the contents of the list in the intervention measures area 230 serve as a second input.

In the embodiment shown in FIG. 2B, the risk indicator in the selected state in the risk configuration area 210 is "logging and time rate" in the category "data". The weight of the risk indicator is set to "10" in the indicator setting area 220, and the normal value range of the risk indicator is set to "70% to less than 90% of the normal range value" in the normal value range setting area 222. The risk profile area 210 shown in fig. 2B further includes a special setting area 223, and the "expected entry required time length" of the risk indicator "entry timeliness rate" may be set in the special setting area 223. Note that, for all risk indicators, the contents to be set in the indicator setting area 220 of the indicator configuration setting page 200 include normal value ranges and weights, and besides, for some risk indicators, special parameters relating to the risk indicators may be set in the special setting area 223. The present invention is not limited to the contents and number of parameters to be set in the special setting area 223.

In the intervention zone 230 of FIG. 2B, an intervention is shown corresponding to the selected risk indicator "enter timeliness". When the range of the risk indicator is '50 < abnormality < 70', it indicates that the problem related to the occurrence of the abnormality is 'subject recruitment/termination', and when an abnormality occurs, the recommended measures to be taken for subject recruitment, subject screening failure, and subject shedding are respectively:

"subject recruitment 1. defining the reason of group entry delay and taking measures for the reason 2. analyzing the central recruitment rate and closing the center with poor recruitment rate 3. increasing the recruitable number of the center with high recruitment rate within the allowable range of the statistical plan;

the screening of the subject fails 1, the screening skill is retrained 2, the reason of the screening failure is tracked, and corresponding screening and correcting measures are considered;

subject drop 1. notify and associate with investigator/CRC discussion 2. confirm whether the center has sufficient resources ", etc.

The required time for taking measures is set to be 3 days. The issued task is an inspection plan, namely a work plan made before going to a hospital for inspection.

The action column includes an "edit/delete" button, and the user can click "edit" to edit the contents of the list of intervention measures, or "delete" to delete the action.

In some embodiments, as shown in fig. 2A and 2B, the pointer configuration setting page 200 further includes a save button 240. After the user has completed setting the normal value range, the weight and/or the intervention measure of the required risk indicator in the indicator configuration setting page 200, all the input contents stored in the indicator configuration setting page 200 can be saved by clicking the save button 240.

Step 120, providing a docking configuration page, and selecting a clinical trial research center to be subjected to quality supervision on the docking configuration page.

Fig. 3A is one of schematic diagrams of a docking configuration page in the risk monitoring method according to an embodiment of the present invention. Referring to FIG. 3A, a clinical trial research center to be quality supervised may be selected in the docking configuration page 300. The user may select the clinical trial research center for which quality supervision is desired by clicking on center filing button 320. In the embodiment shown in FIG. 3A, after clicking on center archive button 320, the area below the center archive button 320 lists the names of all relevant clinical trial research centers. When the name of one of the clinical trial research centers is clicked, all relevant data of the research center are shown in the central data area 330, and the data can be classified into the categories of central research, inspection reports, confirmation information and the like, and each category comprises relevant files and data. The user can set the relevant data to be used for risk monitoring item by item. For example, as shown in FIG. 3A, when a central research report 331 for a particular clinical trial research center is selected, the archive settings for the central research report are shown in the central data area 330. The archive settings include the folder 332 in which the central research report resides. By checking the checkboxes in the folder 332, the central research report may be selected as a source of risk monitoring data.

Referring to the example shown in fig. 3A, the user may select each clinical trial research center and the documents and data contained therein, and use the selected documents and data as the data source for the risk monitoring.

Fig. 3A shows that in the docking configuration page 300, the data source of the risk monitoring is set at the central level. In some embodiments, the data source for risk monitoring may also be set at the project level. Fig. 3B is a second schematic diagram of a docking configuration page in the risk monitoring method according to the embodiment of the invention. Fig. 3B shows that in the configuration page 300, the data source of the risk monitoring is set at the project level. As shown in FIG. 3B, when the user clicks on the item archive button 310, the name of the archive file in the item, i.e., the hand-over report 311 shown in FIG. 3B, appears below the item archive button 310. The handover report 311 is selected, and the folder 333 in the handover report 311 is shown in the central data area 330. As shown in fig. 3B, the file 333 includes folders of different hierarchies, wherein the folder name of the higher hierarchy is "TM 001 item folder", and two folders, i.e., "temporary folder" and "formal folder", are included in the next hierarchy of the folder of the higher hierarchy. In the embodiment shown in fig. 3B, the check box of the "temporary folder" is in a check state, which indicates that the content in the "temporary folder" is selected as the data source for the current risk monitoring. Typically, a temporary folder holds one hand of data obtained from a clinical trial study.

It is to be understood that the illustrations in fig. 3A and 3B are merely examples and are not intended to limit the specific contents of the docking configuration page 300 of the risk monitoring method of the present invention. The content included at both the project level and the central level may be different for different clinical trial research projects. These data sources may be interview schedules, interview question schedules, protocol violation schedules, time schedules, etc. obtained from clinical trial research projects.

In some embodiments, the docking configuration page 300 in fig. 3A and 3B further includes a

save button

341, 342, respectively, and the user may save the content input in the docking configuration page 300 by clicking on the

save button

341, 342.

Data relating to the risk indicator is obtained from the selected clinical trial research centre, step 130.

After the selection of the data source to be used for risk monitoring in the docking configuration page 300 in step 120, the acquisition of data related to risk indicators from the selected clinical trial research center is performed in this step 130.

In some embodiments, the docking configuration page 300 may directly obtain data in the CTMS, eTMF, EDC, etc. systems, for example, the docking configuration page 300 may interface with API interfaces of the systems to directly enter folders in the systems. When the risk monitoring method of the present invention operates in an independent program independent of these systems, a user can save data locally, and the docking configuration page 300 can directly obtain required data locally, and in addition, docking with systems such as CTMS, eTMF, EDC, etc., to obtain data from these systems, so that the risk monitoring method of the present invention can comprehensively obtain required data.

And step 140, calculating a risk index according to the data.

In this step 140, each risk indicator may be calculated with reference to the calculation formula for each risk indicator listed in table one. In some embodiments, these calculation formulas are internally packaged, and after all data are obtained through step 130, a background calculation program is directly triggered to calculate and obtain the value of each risk indicator.

In some embodiments, the data used to calculate the risk indicator may be updated. For example, in the CTMS, if the related data is updated, the risk monitoring method of the present invention performs real-time monitoring on the data, for example, reads the related data according to a certain period, and when it is found that the data is updated, immediately acquires the updated data and calculates an updated risk indicator.

And 150, dividing the risk indexes into a plurality of risk grades according to the risk degree.

Based on the calculation result of step 140, and in comparison with the first input obtained in step 110, i.e., the weight and normal value ranges set in fig. 2A, each risk indicator is divided into a plurality of risk levels according to the degree.

In a preferred embodiment of the invention, the risk indicator is divided into three risk profiles, low risk, medium risk and high risk, respectively.

And step 160, providing a result display page, simultaneously displaying a plurality of risk indexes of a plurality of clinical trial research centers on the result display page, and representing different risk files by using different colors.

Fig. 4 is a schematic diagram of a result display page in the risk monitoring method according to an embodiment of the present invention. Referring to fig. 4, a plurality of risk indicators for a plurality of clinical trial centers are simultaneously displayed in a list in a result display area 420 in the result display page 400. Where the names of all relevant clinical trial study centers are listed in the title row 421 of the list. The total score for each clinical trial study center is shown in the first row 422 of the list. As shown in table one, the total score is obtained by a calculation formula of the total risk score, and the weight of each risk indicator is set in the indicator configuration setting page 200. In the title column 423 below the first row 422, the names of several types of risk indicators for risk monitoring and the names of the specific risk indicators under each type of risk indicator are shown in a form similar to table one, and the numerical values of the risk indicators of the respective clinical trial research centers are shown in the corresponding rows. These values are derived from the calculation in step 140.

Referring to FIG. 4, a color label area 410 is also included in the results display page 400, wherein the colors and their representative meanings are shown. For example: yellow indicates "normal", green indicates "good", and red indicates "abnormal". Here, "normal", "good", and "abnormal" correspond to "medium risk", "low risk", and "high risk", respectively, in the risk profile. Fig. 4 shows a black and white diagram illustrating the different colors represented by the different filled shades.

Based on these color labels, in the result display area 420, for each risk indicator, the range of normal values set in step 110 according to it can be classified as "normal", "good", and "abnormal", and expressed by corresponding colors, so that the user can see the result of the risk indicator at a glance.

In some embodiments, as shown with reference to FIG. 4, a sort mode box 430 is also included in the results display page 400, where the user can select the various centers to be sorted from high to low, or from low to high, in their total score in the sort mode box 430. For example, if "high-low" is selected in fig. 4, i.e., sorted from high to low, the total score of each center decreases from left to right in the result display area 420, and the corresponding colors are red, yellow, and green from left to right, respectively.

Note that only a portion of the results display page 400 is shown in fig. 4, subject to the page size. The user may display more results through various operations of moving the page.

In some embodiments of the present invention, a risk trend graph for a selected clinical trial research center may also be displayed on the results display page 400 over a period of time. Fig. 5 is a schematic diagram of a risk variation trend chart in the risk monitoring method according to an embodiment of the present invention. The present invention is not limited to how to select a certain clinical trial research center in the result display page 400 and how to provide instructions for displaying the risk variation trend graph, and those skilled in the art can implement such a function in any manner. For example: clicking a certain clinical trial research center with a left mouse button on the result display page 400 shown in fig. 4 to place the clinical trial research center in a selected state; an option to display a risk trend graph is presented in the right mouse button menu, and upon selection of this option, a risk trend graph 510 as shown in fig. 5 may be presented. Referring to fig. 5, the risk trend graph 510 shows the trend of the risk indicator, in which the incidence of problems in a certain clinical trial research center is plotted from 2018, 8, to 2019, 10, as well as the dotted line is used as the incidence of problems. Of these, the occurrence rate of problems after 0% from 12 months in 2018 was 100%. Of course, the illustration in FIG. 5 is merely an example and is not intended to limit the scope of the present invention. Those skilled in the art may present the risk variation trend graph in other ways. For example, the trend of the multiple risk indicators is displayed in one page, and the risk profile of the risk indicator at the moment is represented by a point without using colors.

It should be noted that, in the result display page 400 shown in fig. 4, the displayed values of the risk indicators all correspond to a predetermined time, which may be derived from the data obtained in step 130, and which may be the time closest to the present time. In order to display the trend of the risk indicator, historical data of the risk indicator is needed, and the historical data can be automatically obtained in step 130.

According to the risk monitoring method for quality supervision of the clinical trial research center, normal value ranges and weights of all risk indexes can be flexibly set, the risk indexes are automatically calculated through an internally packaged calculation formula, calculation results of the risk indexes of all the clinical trial research centers are visually displayed in colors in a result display page, the risk indexes can be updated in real time, the whole process is convenient and rapid, the reliability is high, the automation degree is high, and the quality supervision and risk monitoring of the clinical trial research center can be timely and accurately carried out.

FIG. 6 is a block diagram of a risk monitoring system for quality supervision by a clinical trial research center in accordance with an embodiment of the present invention. The risk monitoring method described above can be implemented in the risk monitoring system, and therefore the above and the corresponding drawings can be used to illustrate the risk monitoring system of the present invention. Referring to fig. 6, the risk monitoring system 600 includes a parameter setting module 610, a docking configuration module 620, a calculation module 630, and a display module 640. The parameter setting module 610 is configured to set a risk indicator, including setting a normal value range and a weight of the risk indicator. The parameter setting module 610 can perform the step 110 described above. As shown in fig. 2A, a normal value range and a weight of the wind direction index are set in the index arrangement setting page 200.

In some embodiments, the categories of risk indicators include: progress, grouping, quality, data and documentation, for a total of 17 risk indicators, of 5 categories, as noted in table one.

In some embodiments, the parameter setting module 610 is further configured to set intervention measures for the risk indicator. Such as the setup of the intervention zone 230 in fig. 2A.

The docking configuration module 620 is used to select a clinical trial research center for quality supervision and to obtain data related to the risk indicator from the selected clinical trial research center. The docking configuration module 620 may perform

steps

120 and 130 as previously described.

The calculation module 630 is configured to calculate a risk indicator according to the data acquired by the docking configuration module 620. The calculation module 630 may perform steps 140 and/or 150 as described above.

The display module 640 is configured to provide a result display page, and simultaneously display a plurality of risk indicators of a plurality of clinical trial research centers on the result display page, and represent different risk profiles with different colors. The display module 640 may perform the steps 150 and/or 160 described above.

In some embodiments, when the data of the clinical trial research center is updated, the docking configuration module 620 obtains the updated data in real time, and the calculation module 630 calculates the risk indicator according to the updated data. Obviously, the display module 640 also updates the results of its displayed risk indicators accordingly.

In some embodiments, the display module 640 is further configured to display a trend of risk changes corresponding to the selected clinical trial research center on the results display page over a period of time. Such as risk trend graph 510 shown in fig. 5.

In some embodiments, the risk profiles include low risk, medium risk, and high risk, and are represented on the results display page in green (good), yellow (normal), and red (abnormal), respectively.

The present invention also includes a risk monitoring system for quality supervision of a clinical laboratory research center, comprising a memory for storing instructions executable by a processor, and a processor for executing the instructions to implement the risk monitoring method for quality supervision of a clinical laboratory research center of the present invention as described above.

The invention also includes a computer readable medium having stored thereon computer program code which, when executed by a processor, implements a method of risk monitoring for quality supervision of a clinical laboratory research center as described above. When the risk monitoring method for quality supervision of the clinical trial research center is implemented as a computer program, the computer program can also be stored in a computer readable storage medium as a product. For example, computer-readable storage media can include but are not limited to magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips), optical disks (e.g., Compact Disk (CD), Digital Versatile Disk (DVD)), smart cards, and flash memory devices (e.g., electrically Erasable Programmable Read Only Memory (EPROM), card, stick, key drive). In addition, various storage media described herein can represent one or more devices and/or other machine-readable media for storing information. The term "machine-readable medium" can include, without being limited to, wireless channels and various other media (and/or storage media) capable of storing, containing, and/or carrying code and/or instructions and/or data.

It should be understood that the above-described embodiments are illustrative only. The embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, and/or other electronic units designed to perform the functions described herein, or a combination thereof. Although the present invention has been described with reference to the present specific embodiments, it will be appreciated by those skilled in the art that the above embodiments are merely illustrative of the present invention, and various equivalent changes and substitutions may be made without departing from the spirit of the invention, and therefore, it is intended that all changes and modifications to the above embodiments within the spirit and scope of the present invention be covered by the appended claims.

Claims

1. A risk monitoring method for quality supervision of a clinical trial research center is characterized by comprising the following steps:

providing an index configuration setting page, and receiving a first input of a normal value range and weight of a risk index at the index configuration setting page;

providing a docking configuration page, and selecting a clinical trial research center to be subjected to quality supervision on the docking configuration page;

obtaining data relating to the risk indicator from the selected clinical trial research centre;

calculating the risk indicator from the data;

dividing the risk index into a plurality of risk grades according to the risk degree;

and providing a result display page, simultaneously displaying a plurality of risk indexes of a plurality of clinical trial research centers on the result display page, and representing different risk files by using different colors.

2. The risk monitoring method of claim 1, wherein the risk indicator is calculated based on updated data when the data of the clinical trial research center is updated.

3. The risk monitoring method of claim 1, further comprising receiving a second input of an intervention measure for the risk indicator at the indicator configuration settings page.

4. The risk monitoring method of claim 1, wherein a risk variation trend graph corresponding to a selected clinical trial research center is displayed on the results display page according to a time period.

5. The risk monitoring method of claim 1, wherein the risk profiles include low risk, medium risk, and high risk.

6. The risk monitoring method of claim 1, wherein the categories of risk indicators include: progress, data, quality, grouping, and documentation.

7. A risk monitoring system for quality supervision of a clinical trial research center, comprising:

the parameter setting module is used for setting a risk index, and comprises a normal value range and a weight of the risk index;

the docking configuration module is used for selecting a clinical trial research center to be subjected to quality supervision and acquiring data related to the risk index from the selected clinical trial research center;

a calculation module for calculating the risk indicator according to the data;

and the display module is used for providing a result display page, simultaneously displaying a plurality of risk indexes of a plurality of clinical trial research centers on the result display page, and representing different risk files by using different colors.

8. The risk monitoring system of claim 7, wherein the docking configuration module obtains updated data in real-time as the data of the clinical trial research center is updated, and the calculation module calculates the risk indicator based on the updated data.

9. The risk monitoring system of claim 7, wherein the parameter setting module is further configured to set an intervention measure for the risk indicator.

10. The risk monitoring system of claim 7, wherein the display module is further configured to display on the results display page a trend of risk changes corresponding to a selected clinical trial research center over a period of time.

11. The risk monitoring system of claim 7, wherein the risk profiles include low risk, medium risk, and high risk.

12. The risk monitoring system of claim 7, wherein the categories of risk indicators include: progress, grouping, quality, data, and documentation.

13. A risk monitoring system for quality supervision of a clinical trial research center, comprising:

a memory for storing instructions executable by the processor;

a processor for executing the instructions to implement the method of any of claims 1-6.

14. A computer-readable medium having stored thereon computer program code which, when executed by a processor, implements the method of any of claims 1-6.