CN113869023A - Quality control data processing method and device and storage medium - Google Patents
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Abstract
The disclosure provides a processing method and device of quality control data and a storage medium, and relates to the technical field of computers. The specific implementation scheme is as follows: in the process of carrying out quality control processing on the data to be quality controlled, the corresponding quality control template is obtained by combining the attribute information of the data to be quality controlled, a quality control task is generated based on the data to be quality controlled and the quality control template, and a quality control result of the data to be quality controlled is determined based on the quality control review data of the quality control task. Therefore, quality control is conveniently carried out on the data to be quality controlled, the time for obtaining the quality control result of the data to be quality controlled is reduced, and the efficiency of quality control of the data to be quality controlled is improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for processing quality control data, and a storage medium.
Background
In the related art, quality control is usually performed on medical images and medical reports in the medical industry in a manual manner. However, the manual quality control method is labor-consuming and has low quality control efficiency.
Disclosure of Invention
The disclosure provides a method, an apparatus, a device and a storage medium for processing quality control data.
According to an aspect of the present disclosure, there is provided a method for processing quality control data, including: acquiring data to be quality controlled and acquiring attribute information of the data to be quality controlled; acquiring a quality control template matched with the attribute information; generating a quality control task according to the data to be quality controlled and the quality control template; acquiring quality control review data of the quality control task; and determining a quality control result of the data to be quality controlled according to the quality control review data.
In an embodiment of the present disclosure, the obtaining quality control review data of the quality control task includes: sending the quality control task to a designated quality control person; and receiving quality control review data fed back by the quality control personnel aiming at the quality control task.
In one embodiment of the present disclosure, before the sending the quality control task to the designated quality control personnel, the method further includes: acquiring a quality control personnel list matched with the attribute information; and acquiring the target quality control personnel selected from the quality control personnel list, and taking the target quality control personnel as the designated quality control personnel.
In an embodiment of the present disclosure, the acquiring data to be quality-controlled includes: and extracting data with specified quantity and/or proportion from a specified database as the data to be quality controlled according to a preset extraction strategy.
In an embodiment of the present disclosure, the determining the quality control result of the data to be quality controlled according to the quality control review data includes: for each quality control evaluation dimension, determining an evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension; and determining a quality control result of the data to be quality controlled according to the evaluation value of the data to be quality controlled in each quality control evaluation dimension.
In an embodiment of the present disclosure, the determining, according to the scores of the evaluation factors of the data to be quality-controlled in the quality control evaluation dimension, the evaluation value of the data to be quality-controlled in the quality control evaluation dimension includes: acquiring the weight of each evaluation factor on the quality control evaluation dimension; and determining the evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the weight of each evaluation factor and the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension.
In one embodiment of the present disclosure, the method further comprises: acquiring behavior data of the designated quality control personnel in the process of evaluating the quality control task; and determining the evaluation quality of the quality control personnel according to the behavior data.
In an embodiment of the present disclosure, the determining, according to the behavior data, the quality of review of the quality control staff includes: determining characteristic data of the designated quality control personnel on each preset evaluation dimension according to the behavior data; determining evaluation values of the designated quality control personnel in each preset evaluation dimension according to the characteristic data of the designated quality control personnel in each preset evaluation dimension; and determining the evaluation quality of the quality control personnel according to the evaluation values of the specified quality control personnel on the preset evaluation dimensions.
According to another aspect of the present disclosure, there is provided a processing apparatus of quality control data, including: the first acquisition module is used for acquiring data to be quality controlled and acquiring attribute information of the data to be quality controlled; the second acquisition module is used for acquiring the quality control template matched with the attribute information; the generation module is used for generating a quality control task according to the data to be quality controlled and the quality control template; the third acquisition module is used for acquiring the quality control review data of the quality control task; and the determining module is used for determining the quality control result of the data to be quality controlled according to the quality control review data.
In an embodiment of the disclosure, the third obtaining module includes: the sending unit is used for sending the quality control task to a designated quality control person; and the receiving unit is used for receiving the quality control review data fed back by the quality control personnel aiming at the quality control task.
In an embodiment of the disclosure, the third obtaining module further includes: the acquisition unit is used for acquiring a quality control personnel list matched with the attribute information; and the designated quality control personnel determining unit is used for acquiring the target quality control personnel selected from the quality control personnel list and taking the target quality control personnel as the designated quality control personnel.
In an embodiment of the disclosure, the first obtaining module is specifically configured to: and extracting data with specified quantity and/or proportion from a specified database as the data to be quality controlled according to a preset extraction strategy.
In an embodiment of the present disclosure, the quality control template includes a plurality of quality control evaluation dimensions and a plurality of evaluation factors corresponding to each of the quality control evaluation dimensions, the quality control review data includes a score of an evaluation factor of the data to be quality controlled in each of the quality control evaluation dimensions, and the determining module includes: the first determining unit is used for determining the evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension aiming at each quality control evaluation dimension; and the second determining unit is used for determining the quality control result of the data to be quality controlled according to the evaluation value of the data to be quality controlled in each quality control evaluation dimension.
In an embodiment of the disclosure, the first determining unit is specifically configured to: acquiring the weight of each evaluation factor on the quality control evaluation dimension; and determining the evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the weight of each evaluation factor and the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension.
In one embodiment of the present disclosure, the apparatus further comprises: the behavior acquisition module is used for acquiring behavior data of the specified quality control personnel in the process of evaluating the quality control task; and the evaluation quality determining module is used for determining the evaluation quality of the quality control personnel according to the behavior data.
In an embodiment of the disclosure, the review quality determination module is specifically configured to: determining characteristic data of the designated quality control personnel on each preset evaluation dimension according to the behavior data; determining evaluation values of the designated quality control personnel in each preset evaluation dimension according to the characteristic data of the designated quality control personnel in each preset evaluation dimension; and determining the evaluation quality of the quality control personnel according to the evaluation values of the specified quality control personnel on the preset evaluation dimensions.
According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the first aspect.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method of the first aspect.
The technical scheme provided by the embodiment can have the following beneficial effects:
in the process of carrying out quality control processing on the data to be quality controlled, the corresponding quality control template is obtained by combining the attribute information of the data to be quality controlled, a quality control task is generated based on the data to be quality controlled and the quality control template, and a quality control result of the data to be quality controlled is determined based on the quality control review data of the quality control task. Therefore, quality control is conveniently carried out on the data to be quality controlled, the time for obtaining the quality control result of the data to be quality controlled is reduced, and the efficiency of quality control of the data to be quality controlled is improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic flow chart of a method for processing quality control data according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart illustrating another quality control data processing method according to an embodiment of the present disclosure;
FIG. 3 is a schematic view of a refining process for determining a quality control result of data to be quality controlled according to quality control review data;
fig. 4 is a schematic flow chart illustrating another quality control data processing method according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a quality control data processing apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of another quality control data processing apparatus according to an embodiment of the present disclosure;
fig. 7 is a schematic block diagram of an electronic device provided by an embodiment of the disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
A method, an apparatus, and a storage medium for processing quality control data according to an embodiment of the present disclosure are described below with reference to the drawings.
Fig. 1 is a schematic flow chart of a method for processing quality control data according to an embodiment of the present disclosure. It should be noted that, an execution main body of the quality control data processing method provided in this embodiment is a processing device of quality control data, the processing device of quality control data may be configured in an electronic device, and the electronic device may include a terminal device, a server, and the like, and the embodiment does not specifically limit the electronic device.
As shown in fig. 1, the method for processing quality control data may include the following steps:
The attribute information may include a data source, a data type, and the like.
It should be understood that, when the services corresponding to the data to be quality controlled are different, the corresponding attribute information is different.
In some embodiments, the data source may include hospital information and corresponding grade information, where the service corresponding to the data to be quality-controlled is a medical service, and the data to be quality-controlled may be a medical image.
The hospital information may include hospital identification information, hospital name information, and the like.
The data type may include a type of an examination portion corresponding to the medical image and a classification of an examination method.
For example, in the case where the medical image is a CT medical image, the classification of the examination region of the CT medical image may include a primary region such as the head, abdomen, and chest, and a secondary region below the primary region such as the secondary region of the brain, the saddle region, and the sphenoid saddle, and the classification of the examination method may include a CT flat scan examination method, a CT enhancement examination method, and the like.
And 102, acquiring a quality control template matched with the attribute information.
In an embodiment of the present disclosure, the quality control template corresponding to the corresponding attribute information may be obtained according to a correspondence relationship between the attribute information and the quality control template that is stored in advance.
The quality control template comprises quality control evaluation dimension information for performing quality control on the data to be quality controlled, evaluation factor information under the corresponding quality control evaluation dimension information and the like, so that the quality control of the data to be quality controlled can be conveniently performed through the quality control template.
And 103, generating a quality control task according to the data to be quality controlled and the quality control template.
And 104, acquiring quality control review data of the quality control task.
And 105, determining a quality control result of the data to be quality controlled according to the quality control evaluation data.
In the quality control processing method for the quality control data according to the embodiment of the disclosure, in the process of performing quality control processing on the data to be quality controlled, the corresponding quality control template is obtained by combining the attribute information of the data to be quality controlled, a quality control task is generated based on the data to be quality controlled and the quality control template, and a quality control result of the data to be quality controlled is determined based on the quality control review data of the quality control task. Therefore, quality control is conveniently carried out on the data to be quality controlled, the time for obtaining the quality control result of the data to be quality controlled is reduced, and the efficiency of quality control of the data to be quality controlled is improved.
Fig. 2 is a schematic flow chart of another quality control data processing method according to an embodiment of the present disclosure.
As shown in fig. 2, the method for processing quality control data may include the following steps:
In some embodiments, the data to be quality-controlled may be obtained by: and extracting the specified amount of data from the specified database as the data to be quality controlled according to a preset extraction strategy.
In other embodiments, the data to be quality-controlled may be obtained by: and extracting data in a specified proportion from a specified database as the data to be quality controlled according to a preset extraction strategy.
In other embodiments, the data to be quality-controlled may be obtained by: and extracting data with specified quantity and specified proportion from a specified database as the data to be quality controlled according to a preset extraction strategy.
The extraction strategy comprises attribute information, an extraction mode and the like. The attribute information may include a data source, a data type, a sample type, and the like. For example. In the medical industry, the sample types may include medical image types, medical image report types, and the like.
The extraction manner may include an average extraction manner, a random extraction manner, and the like, and in practical applications, the extraction manner may be determined according to actual requirements, which is not specifically limited in this embodiment.
And step 202, acquiring a quality control template matched with the attribute information.
And step 203, generating a quality control task according to the data to be quality controlled and the quality control template.
And step 204, sending the quality control task to the designated quality control personnel.
The service attributes corresponding to different quality control personnel may be different, and in order to obtain the designated quality control personnel corresponding to the quality control task, the designated quality control personnel may be obtained by combining the attribute information of the data to be quality controlled. Here, it should be noted that the sending of the quality control task to the designated quality control personnel may include: and sending the quality control task to a client, a terminal or a web end and the like used by the designated quality control personnel. The quality control personnel need to log in the corresponding client, terminal or web terminal through the account.
Specifically, a quality control personnel list matched with the attribute information is obtained, a target quality control personnel selected from the quality control personnel list is obtained, and the target quality control personnel is used as the designated quality control personnel.
In some embodiments, the quality control person list matched with the attribute information may be obtained according to the correspondence between the attribute information and the quality control person stored in advance.
In some embodiments, after the information of the plurality of quality control personnel is acquired, the information of the plurality of quality control personnel can be displayed in a list mode, the selection operation for the list is acquired, the information of the target quality control personnel selected from the list is acquired according to the selection operation, and the quality control task is sent based on the information of the target quality control personnel. Specifically, the quality control task is transmitted to the target quality control person corresponding to the information of the target quality control person.
The information of the quality control personnel may include, but is not limited to, identification information of the quality control personnel, name information of the quality control personnel, service attribute information corresponding to the quality control personnel, and the like.
And step 205, receiving quality control review data fed back by the quality control personnel aiming at the quality control task.
And step 206, determining a quality control result of the data to be quality controlled according to the quality control review data.
Based on any one of the above embodiments, in some embodiments, the quality control template includes a plurality of quality control evaluation dimensions and a plurality of evaluation factors corresponding to each quality control evaluation dimension, the quality control review data includes scores of the evaluation factors of the data to be quality controlled in each quality control evaluation dimension, and in order to accurately determine the quality control result of the data to be quality controlled, an exemplary implementation manner of determining the quality control result of the data to be quality controlled according to the quality control review data is described below with reference to fig. 3, and as shown in fig. 3, the implementation manner may include:
It is understood that, in the case where the data to be quality-controlled is medical data (e.g., medical image data), the quality-control evaluation dimensions may include dimensions such as "image artifact condition", "image display standard condition", "layout condition for editing inspection image", and the like. For example, the quality control evaluation dimension is an "image artifact condition," and the evaluation factors in the "image artifact condition" may include "no motion artifact and foreign artifact," "artifact located outside the region of interest," and "artifact located inside the region of interest," and other evaluation factors.
In some embodiments, in order to accurately determine the evaluation value of the data to be quality-controlled in the quality control evaluation dimension, the weight of each evaluation factor in the quality control evaluation dimension may be acquired, and the evaluation value of the data to be quality-controlled in the quality control evaluation dimension is determined according to the weight of each evaluation factor and the score of each evaluation factor of the data to be quality-controlled in the quality control evaluation dimension. Therefore, the evaluation value of the data to be quality controlled in the quality control evaluation dimension is accurately determined by combining the influence of different evaluation factors on the data to be quality controlled in the quality control evaluation dimension.
In some embodiments, one implementation manner of obtaining the weight of each evaluation factor in the quality control evaluation dimension may be: and acquiring the weight matched with the quality control evaluation dimension and the evaluation factor based on the corresponding relation among the pre-stored quality control evaluation dimension, the pre-stored evaluation factor and the pre-stored weight.
In some embodiments, in order to further determine the quality control result of the data to be quality controlled, the weight of each quality control evaluation dimension and the evaluation value of the data to be quality controlled in each quality control evaluation dimension may be combined to determine the quality control result of the data to be quality controlled. That is to say, the evaluation values of the data to be quality controlled in each quality control dimension can be weighted by the weight of each quality control dimension, so as to obtain the quality control result of the data to be quality controlled.
In some embodiments, the quality control result may include a quality control score value of the data to be quality controlled. In other embodiments, the quality control result may include a quality control level result of the data to be quality controlled. In other embodiments, the quality control result may include a quality control score value and a quality control grade result of the data to be quality controlled. Wherein, the quality control grade result of the data to be quality controlled can be determined according to the quality control grade value.
Based on the above embodiments, in order to accurately control the quality of the quality control service of the quality control personnel, in some embodiments, behavior data of the designated quality control personnel in the process of reviewing the quality control task may be acquired; and determining the evaluation quality of the quality control personnel according to the behavior data.
In some embodiments, in different application scenarios, the implementation manner of determining the quality of review of the quality control staff according to the behavior data is different, and the following is exemplified:
as an exemplary embodiment, the behavior data may be input into a preset review quality evaluation model to obtain the review quality of the quality controller through the review quality evaluation model.
As another exemplary embodiment, according to the behavior data, determining feature data of the designated quality control personnel on each preset evaluation dimension; determining evaluation values of the designated quality control personnel in each preset evaluation dimension according to the characteristic data of the designated quality control personnel in each preset evaluation dimension; and determining the evaluation quality of the quality control personnel according to the evaluation values of the specified quality control personnel on the preset evaluation dimensions. Therefore, the evaluation of the quality control personnel on the quality control service performance can be accurately determined. The evaluation dimension is preset in combination with an actual service requirement, for example, the evaluation dimension may include, but is not limited to, a quality control task progress, a quality control duration, a quality control average, and the like.
In order to make it clear for those skilled in the art to understand the present application, the following describes the processing method of quality control data according to this embodiment with reference to fig. 4, where the present embodiment takes the quality control data to be taken as a medical image for example to be exemplarily described, as shown in fig. 4, the method may include:
The attribute information may include information such as a data source and a data type.
The data source may include hospital information, and corresponding level information, region information, and other information.
The data type may include an image/examination type, an examination part type, and an examination method classification corresponding to the medical image.
For example, in the case where the medical image is a CT medical image, the classification of the examination region of the CT medical image may include a primary region such as the head, abdomen, and chest, and a secondary region below the primary region such as the secondary region of the brain, the saddle region, and the like, and the classification of the examination method may include a CT flat scan examination, a CT enhancement examination, and the like.
In some embodiments, in order to improve the fairness of quality control, data extraction may be performed from a preset medical image database based on the input sampling number according to a screening rule such as a data source and a data type, and each extracted medical image is used as a medical image to be quality controlled.
The extraction method of the medical image database may include an average extraction method and a random extraction method, and the extraction method is not particularly limited in this embodiment.
And step 403, acquiring a quality control template matched with the attribute information.
The quality control template may include a plurality of quality control evaluation dimensions and a plurality of evaluation factors corresponding to each quality control evaluation dimension.
And step 404, generating a quality control task according to the quality control template and the medical image to be quality controlled, and sending the quality control task to a target expert corresponding to the target expert information.
In some embodiments, for the quality control task, an end time may also be set for the quality control task, after the quality control task is sent to the target expert corresponding to the target expert information, whether the target expert information processes the quality control task before the end time may be monitored, if the target expert information does not process the quality control task before the end time, other expert information that can process the quality control task may be obtained, and the quality control task may be sent to other expert information.
And 405, acquiring quality control review data fed back by the target expert aiming at the quality control task.
Specifically, after the expert corresponding to the target expert information acquires the quality control task, the expert may perform quality control on the medical image to be quality controlled according to the quality control template in the quality control task to form quality control evaluation data corresponding to the quality control task, and send the quality control evaluation data to the processing device of the quality control data, so that the processing device of the quality control data acquires the quality control evaluation data for the quality control task.
For example, one quality control dimension in the quality control template is an image artifact condition dimension, and the corresponding evaluation factors in the image artifact condition dimension are "no motion artifact and foreign object artifact", "artifact is located outside the region of interest", and "artifact is located in the region of interest", at this time, the expert may determine, based on the medical image to be quality controlled, the scores corresponding to the three evaluation factors of "no motion artifact and foreign object artifact", "artifact is located outside the region of interest", and "artifact is located in the region of interest".
And step 406, determining a quality control result of the medical image to be quality controlled according to the quality control review data.
In some embodiments, after the quality control result of any one medical image to be quality controlled is obtained based on the above manner, the quality control results of a plurality of medical images with the same data source may be obtained, and the quality control result of the data source for the medical image is determined according to the quality control results of the plurality of medical images with the same data source.
In this embodiment, the quality control task is sent to the corresponding expert in an online quality control task manner, and the quality control result of the medical image corresponding to the quality control is determined by combining the quality control review data of the expert on the quality control task, so that the online quality control of the quality control data is realized, the quality control cost of the medical image to be quality controlled can be reduced, and the offline running wave can be avoided.
It should be noted that, in the processing procedure using the data to be quality controlled as the medical image report, the processing procedure is similar to the above-mentioned processing procedure for the medical image, and details are not repeated here.
In addition, in order to evaluate the work of the quality control personnel, in the process of evaluating the quality control task by the expert, behavior data of the expert in the evaluation process can be obtained, and evaluation data corresponding to the work of the expert can be determined based on the behavior data.
In order to implement the above embodiments, the present embodiment provides a processing apparatus of quality control data.
Fig. 5 is a schematic structural diagram of a quality control data processing apparatus according to an embodiment of the present disclosure.
As shown in fig. 5, the quality control data processing device 500 may include: a first obtaining module 501, a second obtaining module 502, a generating module 503, a third obtaining module 504 and a determining module 505, wherein:
the first obtaining module 501 is configured to obtain data to be quality controlled and obtain attribute information of the data to be quality controlled.
And a second obtaining module 502, configured to obtain a quality control template matched with the attribute information.
And a generating module 503, configured to generate a quality control task according to the data to be quality controlled and the quality control template.
And a third obtaining module 504, configured to obtain quality control review data of the quality control task.
And the determining module 505 is configured to determine a quality control result of the data to be quality controlled according to the quality control review data.
In an embodiment of the disclosure, on the basis of fig. 5, as shown in fig. 6, the third obtaining module 504 includes:
and a sending unit 5041, configured to send the quality control task to a designated quality control person.
The receiving unit 5042 is configured to receive quality control review data fed back by the quality control staff for the quality control task.
In an embodiment of the disclosure, as shown in fig. 6, the third obtaining module 504 further includes:
an obtaining unit 5043, configured to obtain a quality control staff list matched with the attribute information; and acquiring the target quality control personnel selected from the quality control personnel list, and taking the target quality control personnel as the designated quality control personnel.
In an embodiment of the present disclosure, the first obtaining module 501 is specifically configured to: and extracting data with specified quantity and/or proportion from a specified database as the data to be quality controlled according to a preset extraction strategy.
In an embodiment of the present disclosure, the quality control template includes a plurality of quality control evaluation dimensions and a plurality of evaluation factors corresponding to each quality control evaluation dimension, the quality control review data includes scores of the evaluation factors of the data to be quality controlled in each quality control evaluation dimension, and the determining module 505 may include:
the first determining unit 5051 is configured to determine, for each quality control evaluation dimension, an evaluation value of the data to be quality controlled in the quality control evaluation dimension according to a score of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension.
The second determining unit 5052 is configured to determine a quality control result of the data to be quality controlled according to the evaluation value of the data to be quality controlled in each quality control evaluation dimension.
In an embodiment of the present disclosure, the first determining unit 5051 is specifically configured to: acquiring the weight of each evaluation factor in a quality control evaluation dimension; and determining the evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the weight of each evaluation factor and the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension.
In an embodiment of the present disclosure, in order to manage quality control quality of a quality control person, the apparatus may further include: a behavior obtaining module (not shown in the figure) for obtaining behavior data of the designated quality control personnel in the process of evaluating the quality control task; and the review quality determining module (not shown in the figure) is used for determining the review quality of the quality control personnel according to the behavior data.
In an embodiment of the disclosure, the review quality determination module is specifically configured to: determining characteristic data of the designated quality control personnel on each preset evaluation dimension according to the behavior data; determining evaluation values of the designated quality control personnel in each preset evaluation dimension according to the characteristic data of the designated quality control personnel in each preset evaluation dimension; and determining the evaluation quality of the quality control personnel according to the evaluation values of the specified quality control personnel on the preset evaluation dimensions.
It should be noted that the foregoing explanation of the method embodiment is also applicable to the apparatus of this embodiment, and the principle is the same, and is not repeated in this embodiment.
In the process of performing quality control processing on the data to be quality controlled, the processing device for the quality control data of this embodiment acquires the corresponding quality control template in combination with the attribute information of the data to be quality controlled, generates a quality control task based on the data to be quality controlled and the quality control template, and determines the quality control result of the data to be quality controlled based on the quality control review data of the quality control task. Therefore, quality control is conveniently carried out on the data to be quality controlled, the time for obtaining the quality control result of the data to be quality controlled is reduced, and the efficiency of quality control of the data to be quality controlled is improved.
In order to implement the above embodiments, the present embodiment provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of the foregoing method embodiments.
To implement the above embodiments, the present embodiment provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the methods of the foregoing method embodiments.
In order to implement the above embodiments, the present embodiment provides a computer program product comprising a computer program which, when executed by a processor, implements the method of the aforementioned method embodiments.
Fig. 7 is a schematic block diagram of an electronic device provided by an embodiment of the disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the device 700 includes a computing unit 701, which can perform various appropriate actions and processes in accordance with a computer program stored in a ROM (Read-Only Memory) 702 or a computer program loaded from a storage unit 708 into a RAM (Random Access Memory) 703. In the RAM703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM702, and the RAM703 are connected to each other by a bus 704. An I/O (Input/Output) interface 705 is also connected to the bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be realized in digital electronic circuitry, Integrated circuitry, FPGAs (Field Programmable Gate arrays), ASICs (Application-Specific Integrated circuits), ASSPs (Application Specific Standard products), SOCs (System On Chip, System On a Chip), CPLDs (Complex Programmable Logic devices), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or flash Memory, an optical fiber, a CD-ROM (Compact Disc Read-Only-Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a Display device (e.g., a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), internet, and blockchain Network.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (12)
1. A method for processing quality control data, the method comprising;
acquiring data to be quality controlled and acquiring attribute information of the data to be quality controlled;
acquiring a quality control template matched with the attribute information;
generating a quality control task according to the data to be quality controlled and the quality control template;
acquiring quality control review data of the quality control task;
and determining a quality control result of the data to be quality controlled according to the quality control review data.
2. The method of claim 1, wherein the obtaining quality control review data for the quality control task comprises:
sending the quality control task to a designated quality control person;
and receiving quality control review data fed back by the designated quality control personnel aiming at the quality control task.
3. The method of claim 2, wherein prior to said sending the quality control task to the designated quality control personnel, the method further comprises:
acquiring a quality control personnel list matched with the attribute information;
and acquiring the target quality control personnel selected from the quality control personnel list, and taking the target quality control personnel as the designated quality control personnel.
4. The method of claim 1, wherein the obtaining the data to be quality controlled comprises:
and extracting data with specified quantity and/or proportion from a specified database as the data to be quality controlled according to a preset extraction strategy.
5. The method according to any one of claims 1 to 4, wherein the quality control template includes a plurality of quality control evaluation dimensions and a plurality of evaluation factors corresponding to each of the quality control evaluation dimensions, the quality control review data includes a score of an evaluation factor of the data to be quality controlled in each of the quality control evaluation dimensions, and the determining the quality control result of the data to be quality controlled according to the quality control review data includes:
for each quality control evaluation dimension, determining an evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension;
and determining a quality control result of the data to be quality controlled according to the evaluation value of the data to be quality controlled in each quality control evaluation dimension.
6. The method of claim 5, wherein the determining the evaluation value of the data to be quality-controlled in the quality control evaluation dimension according to the rating of each evaluation factor of the data to be quality-controlled in the quality control evaluation dimension comprises:
acquiring the weight of each evaluation factor on the quality control evaluation dimension;
and determining the evaluation value of the data to be quality controlled in the quality control evaluation dimension according to the weight of each evaluation factor and the grade of each evaluation factor of the data to be quality controlled in the quality control evaluation dimension.
7. The method of claim 2, wherein the method further comprises:
acquiring behavior data of the designated quality control personnel in the process of evaluating the quality control task;
and determining the evaluation quality of the quality control personnel according to the behavior data.
8. The method of claim 7, wherein determining the quality of review of the quality control personnel based on the behavioral data comprises:
determining characteristic data of the designated quality control personnel on each preset evaluation dimension according to the behavior data;
determining evaluation values of the designated quality control personnel in each preset evaluation dimension according to the characteristic data of the designated quality control personnel in each preset evaluation dimension;
and determining the evaluation quality of the quality control personnel according to the evaluation values of the specified quality control personnel on the preset evaluation dimensions.
9. An apparatus for processing quality control data, the apparatus comprising;
the first acquisition module is used for acquiring data to be quality controlled and acquiring attribute information of the data to be quality controlled;
the second acquisition module is used for acquiring the quality control template matched with the attribute information;
the generation module is used for generating a quality control task according to the data to be quality controlled and the quality control template;
the third acquisition module is used for acquiring the quality control review data of the quality control task;
and the determining module is used for determining the quality control result of the data to be quality controlled according to the quality control review data.
10. An electronic device, comprising:
memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-8 when executing the program.
11. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 8.
12. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114927199A (en) * | 2022-02-28 | 2022-08-19 | 北京一脉阳光医学信息技术有限公司 | Medical image report and image quality control management system, method and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104050275A (en) * | 2014-06-25 | 2014-09-17 | 国家电网公司 | Method and system for reviewing project |
| US20150039367A1 (en) * | 2013-07-31 | 2015-02-05 | Bank Of America Corporation | Quality assurance and control tool |
| CN107122483A (en) * | 2017-05-05 | 2017-09-01 | 国家测绘地理信息局四川测绘产品质量监督检验站 | Fundamental Geographic Information Data quality detecting method, apparatus and system |
| CN110826900A (en) * | 2019-11-01 | 2020-02-21 | 中国人民解放军军事科学院国防科技创新研究院 | Crowd-sourcing-based crowd-sourcing contribution review method |
| CN111881207A (en) * | 2020-06-15 | 2020-11-03 | 广东省科技创新监测研究中心 | Expert information sharing method, device, equipment and storage medium based on block chain |
| CN111951913A (en) * | 2020-07-13 | 2020-11-17 | 上海森亿医疗科技有限公司 | Medical record document quality control method and system based on electronic medical record management system |
| CN111967241A (en) * | 2020-09-03 | 2020-11-20 | 卫宁健康科技集团股份有限公司 | Medical record writing quality control method and system |
| CN113035329A (en) * | 2021-03-22 | 2021-06-25 | 杭州联众医疗科技股份有限公司 | Medical image quality control system |
-
2021
- 2021-09-27 CN CN202111134510.4A patent/CN113869023A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150039367A1 (en) * | 2013-07-31 | 2015-02-05 | Bank Of America Corporation | Quality assurance and control tool |
| CN104050275A (en) * | 2014-06-25 | 2014-09-17 | 国家电网公司 | Method and system for reviewing project |
| CN107122483A (en) * | 2017-05-05 | 2017-09-01 | 国家测绘地理信息局四川测绘产品质量监督检验站 | Fundamental Geographic Information Data quality detecting method, apparatus and system |
| CN110826900A (en) * | 2019-11-01 | 2020-02-21 | 中国人民解放军军事科学院国防科技创新研究院 | Crowd-sourcing-based crowd-sourcing contribution review method |
| CN111881207A (en) * | 2020-06-15 | 2020-11-03 | 广东省科技创新监测研究中心 | Expert information sharing method, device, equipment and storage medium based on block chain |
| CN111951913A (en) * | 2020-07-13 | 2020-11-17 | 上海森亿医疗科技有限公司 | Medical record document quality control method and system based on electronic medical record management system |
| CN111967241A (en) * | 2020-09-03 | 2020-11-20 | 卫宁健康科技集团股份有限公司 | Medical record writing quality control method and system |
| CN113035329A (en) * | 2021-03-22 | 2021-06-25 | 杭州联众医疗科技股份有限公司 | Medical image quality control system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114927199A (en) * | 2022-02-28 | 2022-08-19 | 北京一脉阳光医学信息技术有限公司 | Medical image report and image quality control management system, method and storage medium |
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