CN110827934A - CRF (conditional random access memory) monitoring method and device - Google Patents
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24564—Applying rules; Deductive queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
- G06F16/90344—Query processing by using string matching techniques
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Abstract
The invention discloses an inspection method and a device of CRF, wherein the method comprises reading a case report table CRF of an inspection object and reading a plurality of source data of the inspection object; respectively calculating the similarity of the CRF and the source data; and displaying the plurality of source data in the inspection area of the inspection object according to the similarity. According to the technical scheme, an easy-to-use and high-efficiency CRF monitoring process is constructed, the CRF monitoring process is suitable for a database environment of mass data, CRF can be monitored efficiently, the dependence on CRA capability in the whole process can be reduced, the clinical test cost is further reduced, the CRF data monitoring efficiency is improved, and the technical problem that the CRF data monitoring speed is low in the prior art is solved.
Description
Technical Field
The invention relates to the field of medical data processing, in particular to a method and a device for monitoring CRF.
Background
In traditional clinical trials, monitoring of CRF (Case report form) is an important link for guaranteeing the quality of clinical trial data.
After CRC (Clinical Coordinator) records the medical record data of the subject into the CRF according to the specification, CRA (Clinical inspector) needs to check whether the recorded CRF is correctly recorded, and this double-verification method ensures the quality of the data of the whole Clinical trial. However, in the current inspection method, the CRA performs the comparison between the CRF and the source data through the SDV on the manual site, and a lot of time is spent on searching the original medical record and comparing whether the original medical record is consistent with the CRF. The traditional manual inspection mode has the following two serious problems: the CRA has low medical record searching efficiency, and if the clinical test data volume is large, the CRA is difficult to complete the inspection of all data within a limited time, and the bottleneck of inspection efficiency is obvious. The CRA manual inspection method needs to search and compare in a large range of data, so that human errors are inevitable.
In view of the above problems in the prior art, no effective solution has been found.
Disclosure of Invention
The invention provides a CRF (CRF) monitoring method, a CRF monitoring device, a computer readable storage medium and computer equipment, which construct an easy-to-use and high-efficiency CRF monitoring process, can be suitable for a database environment of mass data, can monitor CRF efficiently, can reduce the dependence on CRA capability in the whole process, further reduce the clinical test cost, improve the CRF data monitoring efficiency and solve the technical problem of low CRF data monitoring speed in the prior art.
In a first aspect, the present invention provides a method of auditing a CRF, comprising:
reading a case report table (CRF) of an inspection object and reading a plurality of source data of the inspection object;
respectively calculating the similarity of the CRF and the source data;
and displaying the plurality of source data in the inspection area of the inspection object according to the similarity.
Preferably, the first and second electrodes are formed of a metal,
calculating the similarity of the CRF and the source data respectively comprises the following steps:
determining a number of first fields to be inspected in the CRF;
respectively searching a plurality of second fields corresponding to the first fields in the plurality of source data according to a preset mapping table;
and respectively calculating the similarity of the first field and the plurality of second fields.
Preferably, the first and second electrodes are formed of a metal,
calculating the similarity of the first field and the plurality of second fields respectively comprises:
extracting a first field value of the first field, and extracting a plurality of second field values of the plurality of second fields;
and calculating a plurality of similarities between the first field value and the plurality of second field values respectively by adopting a character string similarity algorithm.
Preferably, the first and second electrodes are formed of a metal,
displaying the plurality of source data in the inspection area of the inspection object according to the similarity comprises:
sorting the source data according to the similarity;
recording the sequenced source data in an inspection area of the CRF;
the inspection area and the CRF are shown in the same view of a visualization interface.
Preferably, the first and second electrodes are formed of a metal,
after searching a plurality of second fields corresponding to the first field in the plurality of source data according to a preset mapping table, the method further includes:
and carrying out field normalization processing on the plurality of second fields, and correcting the field names of the plurality of second fields into field names conforming to a standard dictionary, wherein the standard dictionary is a case dictionary used by the first field.
In a second aspect, the present invention provides an inspection apparatus for a CRF, comprising:
the system comprises a reading module, a case report table (CRF) reading module and a plurality of source data reading module, wherein the case report table (CRF) is used for reading an inspection object;
the calculating module is used for respectively calculating the similarity between the CRF and the source data;
and the display module is used for displaying the source data in the inspection area of the inspection object according to the similarity.
Preferably, the first and second electrodes are formed of a metal,
the calculation module comprises:
a determining unit, configured to determine that a number of first fields to be inspected in the CRF read the CRF;
a searching unit, configured to search, in the plurality of source data according to a preset mapping table, a plurality of second fields corresponding to the first field respectively;
and the calculating unit is used for respectively calculating the similarity of the first field and the plurality of second fields.
Preferably, the calculation unit includes:
an extracting subunit operable to extract a first field value of the first field, and extract a plurality of second field values of the plurality of second fields;
a calculating subunit, configured to calculate, by using a string similarity algorithm, a plurality of similarities between the first field value and the plurality of second field values, respectively.
Preferably, the first and second electrodes are formed of a metal,
the display module comprises:
the sorting unit is used for sorting the source data according to the similarity;
a recording unit, for recording the sequenced source data in the inspection area of the CRF;
and the display unit is used for displaying the inspection area and the CRF in the same view of a visual interface.
Preferably, the calculation module further comprises:
and a normalizing unit, configured to, after the searching unit searches, according to a preset mapping table, a plurality of second fields corresponding to the first field in the plurality of source data, perform field normalization processing on the plurality of second fields, and correct field names of the plurality of second fields into field names conforming to a standard dictionary, where the standard dictionary is a case dictionary used by the first field.
In a third aspect, the invention provides a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method according to any one of the first aspect.
In a fourth aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method according to any one of the first aspect when executing the computer program.
The invention provides a CRF (CRF) monitoring method, a CRF monitoring device, a computer readable storage medium and computer equipment, which construct an easy-to-use and high-efficiency CRF monitoring process, can be suitable for a database environment of mass data, can monitor CRF efficiently, can reduce the dependence on CRA capability in the whole process, further reduce the clinical test cost, improve the CRF data monitoring efficiency and solve the technical problem of low CRF data monitoring speed in the prior art.
Drawings
In order to more clearly illustrate the embodiments or the prior art solutions of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a schematic flow chart of a CRF inspection method according to an embodiment of the present invention;
FIG. 2 is a logic flow diagram of an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an inspection apparatus for CRF according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for monitoring a CRF, which includes the following steps:
102, respectively calculating the similarity of the CRF and the source data;
and 103, displaying the plurality of source data in the inspection area of the inspection object according to the similarity.
As shown in fig. 1, in the embodiment, a case report table CRF of an inspection object is read, a plurality of source data of the inspection object are read, then the similarity between the CRF and the plurality of source data is respectively calculated, and finally the plurality of source data are displayed in an inspection area of the inspection object according to the similarity, so that an easy-to-use and efficient CRF inspection process is constructed, the CRF inspection process is applicable to a database environment of mass data, the CRF can be efficiently inspected, the dependence on the capacity of a CRA in the whole process can be reduced, the clinical test cost is reduced, the efficiency of CRF data inspection is improved, and the technical problem of low CRF data inspection speed in the prior art is solved.
FIG. 2 is a logic flow diagram of an embodiment of the present invention, as shown in FIG. 2, including a source data read module, an EDC access module, and a similarity calculation module.
And an EDC access module for reading the CRF, reading the CRF from an Electronic Data Capture (EDC) system, and accessing all CRFs of a certain subject according to the globally unique ID of the subject (subject to be monitored) through an API (Application Programming Interface) provided by the EDC. The source data reading module reads source data, reads all original data of the testee according to the serial number of the testee under the security authorization, the source data in the source database can be subjected to irreversible encryption and desensitization processing, after CRF is read, the ID needs to be subjected to irreversible encryption processing to identify and match the ID in the source database, the original medical record data of the testee is stored in the database, and the original medical record data is generally composed of a plurality of database two-dimensional tables and is numbered for the testee. And the similarity calculation module is used for calculating the similarity between the CRF data acquired by the EDC access module and the source data read by the source data reading module, and displaying according to the calculation result so as to facilitate the CFA to monitor.
According to an embodiment of the present disclosure, calculating the similarity of the CRF and the plurality of source data, respectively, includes:
s11, determining a plurality of first fields to be inspected in the CRF;
s12, respectively searching a plurality of second fields corresponding to the first fields in the plurality of source data according to a preset mapping table;
and S13, respectively calculating the similarity of the first field and the plurality of second fields.
When the number of the first fields is multiple, each source data also corresponds to multiple second fields, the similarity degree of each field is calculated, and finally, the average calculation is carried out.
In an implementation manner of this embodiment, the calculating the similarity between the first field and the plurality of second fields respectively includes: extracting a first field value of the first field, and extracting a plurality of second field values of the plurality of second fields; and calculating a plurality of similarities between the first field value and the plurality of second field values respectively by adopting a character string similarity algorithm.
Mapping configuration is carried out on data fields to be inspected in the CRF and fields in the original data in advance, and a mapping relation is established. There may be more than one field involved, except that the subject numbers must be the same. Taking the white blood cell count in the test as an example, it is noted as LBNAME field in LB table in CRF, and lab _ name field in labexam table in the original database. Performing semantic similarity calculation on the matched fields, performing similarity calculation by adopting a character string similarity calculation method, scoring the similarity degree of each field, finally performing average calculation on the scores, outputting the original record of TOPN before scoring, and taking the first field as the white blood cell count for example:
subject 001 is recorded in LB table in CRF table as shown in table 1, where "LBNAME" is the first field and the first field value is "6".
TABLE 1
| ID | LBDATE | LBNAME | LBVALUE |
| 001 | 2018.1.1 | White blood cell count | 6 |
In the original record table, subject 001 is recorded in the labexam table as shown in table 2, where "lab _ name" is the second field corresponding to "LBNAME", and the second field values are "6", "5", and so on.
In an implementation manner of this embodiment, after searching, according to a preset mapping table, a plurality of second fields corresponding to the first field in the plurality of source data, respectively, the method further includes: and carrying out field normalization processing on the plurality of second fields, and correcting the field names of the plurality of second fields into field names conforming to a standard dictionary, wherein the standard dictionary is a case dictionary used by the first field. The names and the numerical ranges in the standard dictionary are unified and standard, and only one name is used for the same disease species, disease symptoms, indications, parameters and the like.
In the application scenario of a clinical trial, each CRF has its own field, and the corresponding primary key field is found from the source data according to the known field name. Since many field names in the source data are written with irregular names, such as checking names, field normalization is required. The embodiment adopts two modes of rule matching or semantic matching. The normalization process for the second field may be, but is not limited to, the following modes:
rule matching pattern: carrying out normalization processing on the writing rule of the field name of the second field through a regular expression;
regular matching is performed by regular expressions or combinations of regular expressions, such as regular matching with regular expression (white blood cell count | WBC) for irregular white blood cell count writing ([ white blood cell count ], WBC, etc.);
semantic matching mode: splitting the second field into a plurality of subfields; calculating semantic similarity (between the sub-fields and fields in a standard dictionary) by adopting a character string similarity algorithm according to the field characteristics of each sub-field; and when the sum of the semantic similarity of a plurality of second fields exceeds a preset threshold value, converting the second fields into the third fields matched with the standard dictionaries.
For example, counting white blood cells, carrying out similarity matching through a plurality of characteristics of the white blood cell counting, for example, a plurality of characteristics of the white blood cell counting, such as the name, the unit (10^9/ml) and the upper limit of 10, and the like, respectively carrying out similarity calculation by adopting a character string similarity calculation method, and when the total score exceeds a set value, representing that the matching is successful, carrying out normalization.
S13, calculating the similarity between the first primary key information and the plurality of second primary key information, respectively.
In an implementation manner of this embodiment, the displaying the plurality of source data in the inspection area of the inspection object according to the similarity includes:
s21, sorting the source data according to the similarity; the sorting can be carried out according to the descending or ascending rule, so that the checking is convenient. The sorted source data are shown in table 3:
and performing similarity score sorting on the normalized original medical records and the CRF, and labeling the data with the highest similarity. Similarity matching is carried out on the source data and CRF data, matching degree sorting is carried out, the number of finally displayed results can be controlled according to a threshold value, N (N is larger than or equal to 1) source data with the highest similarity can be set as key inspection data of the CRF, the result with the highest similarity is marked, remark information is added, or a label is marked.
S22, recording the sequenced source data in the inspection area of the CRF;
s23, displaying the inspection area and the CRF in the same view of a visual interface.
And displaying the marked original data and the CRF in one view, so that the CRA can conveniently conduct inspection work.
In the scheme of the embodiment of the disclosure, in order to solve the problem of CRA (crack growth cycle) monitoring efficiency, an easy-to-use and high-efficiency CRF (crack growth cycle) monitoring process is constructed. Under the environment of increasingly complex clinical tests and the like, how to efficiently monitor CRF enables the whole process to reduce the dependence on CRA capability and further reduces the cost of clinical tests. The direct effect is that the CRF data monitoring efficiency is greatly improved, and the working efficiency of CRA can be improved by at least 50% in clinical tests in the aspect of efficiency.
Based on the same concept as the method embodiment of the present invention, referring to fig. 3, an embodiment of the present invention further provides an inspection apparatus for CRF, which specifically includes:
a reading module 30, configured to read a case report table CRF of an inspection object, and read a plurality of source data of the inspection object;
a calculating module 32, configured to calculate similarities between the CRF and the source data respectively;
and the display module 34 is configured to display the plurality of source data in the inspection area of the inspection object according to the similarity.
In one embodiment of the present invention, the calculation module includes: a determining unit, configured to determine that a number of first fields to be inspected in the CRF read the CRF; a searching unit, configured to search, in the plurality of source data according to a preset mapping table, a plurality of second fields corresponding to the first field respectively; and the calculating unit is used for respectively calculating the similarity of the first field and the plurality of second fields.
In one embodiment of the present invention, the calculation unit includes: an extracting subunit operable to extract a first field value of the first field, and extract a plurality of second field values of the plurality of second fields; a calculating subunit, configured to calculate, by using a string similarity algorithm, a plurality of similarities between the first field value and the plurality of second field values, respectively.
In one embodiment of the present invention, the display module comprises: the sorting unit is used for sorting the source data according to the similarity; a recording unit, for recording the sequenced source data in the inspection area of the CRF; and the display unit is used for displaying the inspection area and the CRF in the same view of a visual interface.
In an embodiment of the present invention, the computing module further includes: and a normalizing unit, configured to, after the searching unit searches, according to a preset mapping table, a plurality of second fields corresponding to the first field in the plurality of source data, perform field normalization processing on the plurality of second fields, and correct field names of the plurality of second fields into field names conforming to a standard dictionary, where the standard dictionary is a case dictionary used by the first field.
For convenience of description, the above device embodiments are described with functions divided into various units or modules, and the functions of the units or modules may be implemented in one or more software and/or hardware when implementing the present invention.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the CRF monitoring method provided in any one of the embodiments of the present invention.
Referring to fig. 4, an embodiment of the present invention further provides a computer apparatus, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the method for monitoring a CRF according to any embodiment of the present invention is implemented.
Specifically, the memory may include a memory and a nonvolatile memory.
Optionally, the computer device further comprises an internal bus, a network interface.
Of course, the computer device may also include hardware required for other services.
The Memory may be a Random-Access Memory (RAM); the non-volatile memory (non-volatile memory) may be 1 or more disk memories.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.
In a possible implementation manner, the processor reads a corresponding computer program from the nonvolatile memory to the processor for running, and the processor executes the computer program stored in the memory, so as to implement the CRF checking method provided in any embodiment of the invention through the executed computer program.
The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules (i.e., computer programs) may be located in ram, flash memory, rom, prom, eprom, or eeprom, registers, or other computer-readable storage media as is known in the art.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A method of auditing a CRF, comprising:
reading a case report table (CRF) of an inspection object and reading a plurality of source data of the inspection object;
respectively calculating the similarity of the CRF and the source data;
and displaying the plurality of source data in the inspection area of the inspection object according to the similarity.
2. The method of claim 1, wherein separately calculating the similarity of the CRF and the plurality of source data comprises:
determining a number of first fields to be inspected in the CRF;
respectively searching a plurality of second fields corresponding to the first fields in the plurality of source data according to a preset mapping table;
and respectively calculating the similarity of the first field and the plurality of second fields.
3. The method of claim 2, wherein calculating the similarity between the first field and the plurality of second fields comprises:
extracting a first field value of the first field, and extracting a plurality of second field values of the plurality of second fields;
and calculating a plurality of similarities between the first field value and the plurality of second field values respectively by adopting a character string similarity algorithm.
4. The method of claim 1, wherein presenting the plurality of source data in the inspection area of the inspection object according to the similarity comprises:
sorting the source data according to the similarity;
recording the sequenced source data in an inspection area of the CRF;
the inspection area and the CRF are shown in the same view of a visualization interface.
5. The method of claim 2, wherein after searching the plurality of source data for the plurality of second fields corresponding to the first field according to a preset mapping table, the method further comprises:
and carrying out field normalization processing on the plurality of second fields, and correcting the field names of the plurality of second fields into field names conforming to a standard dictionary, wherein the standard dictionary is a case dictionary used by the first field.
6. An inspection apparatus for a CRF, comprising:
the system comprises a reading module, a case report table (CRF) reading module and a plurality of source data reading module, wherein the case report table (CRF) is used for reading an inspection object;
the calculating module is used for respectively calculating the similarity between the CRF and the source data;
and the display module is used for displaying the source data in the inspection area of the inspection object according to the similarity.
7. The apparatus of claim 6, wherein the computing module comprises:
a determining unit, configured to determine that a number of first fields to be inspected in the CRF read the CRF;
a searching unit, configured to search, in the plurality of source data according to a preset mapping table, a plurality of second fields corresponding to the first field respectively;
and the calculating unit is used for respectively calculating the similarity of the first field and the plurality of second fields.
8. The apparatus of claim 6, wherein the display module comprises:
the sorting unit is used for sorting the source data according to the similarity;
a recording unit, for recording the sequenced source data in the inspection area of the CRF;
and the display unit is used for displaying the inspection area and the CRF in the same view of a visual interface.
9. 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 1-5.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-5 when executing the computer program.
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| CN111540432A (en) * | 2020-07-07 | 2020-08-14 | 嘉兴太美医疗科技有限公司 | Method and device for generating mobile terminal interface of CRF (format conversion function) form |
| WO2021226895A1 (en) * | 2020-05-13 | 2021-11-18 | 医渡云（北京）技术有限公司 | Digital inspection method and apparatus applied in clinical trials, and related device |
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