CN109446192B - Data testing method and device - Google Patents
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- CN109446192B CN109446192B CN201811332051.9A CN201811332051A CN109446192B CN 109446192 B CN109446192 B CN 109446192B CN 201811332051 A CN201811332051 A CN 201811332051A CN 109446192 B CN109446192 B CN 109446192B
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Abstract
The disclosure relates to a data testing method and device. The data testing method comprises the following steps: automatically extracting on a first non-basic data version according to an input target sample number to obtain a current sample to be detected; automatically comparing the current sample to be detected with a corresponding standard template stored in a database to obtain a difference result between the current sample to be detected and the corresponding standard template; and automatically evaluating the difference result according to the configured index parameters to obtain an evaluation result of the current sample to be detected. The automatic execution of data testing can be realized, the efficiency of data quality detection is improved, and the subjective influence of human error and omission on the detection result can be avoided.
Description
Technical Field
The present disclosure relates to the field of data processing, and in particular, to a data testing method and a data testing apparatus.
Background
With the continuous development of internet technology, internet and medical treatment become a new development direction of the medical treatment industry, the transition from traditional medical treatment to medical informatization is promoted, and the deepening combination of the health industry and the information technology industry is promoted.
Medical informatization has been developed over a decade, and great achievements are achieved, and medical data accumulated and stored by a large number of medical institutions far exceeds the range which can be processed by manpower at present. Especially, under the promotion of precise medicine in recent years, the development of high-quality clinical scientific research based on big data technology has become a necessary trend. The production processing quality of the big data directly determines the reliability of the medical intelligent application of the big data.
The big data contains massive information, so that indexes, rules, flows and tools for data quality detection are abundant continuously, but the process from research and development to delivery and use of the general platform tool is slow, the flexibility and the maneuverability are not strong, and the defects are obviously highlighted for a refined quality control task.
Fig. 1 shows a schematic diagram of a data testing method in the prior art.
In the prior art, after a data quality detection platform automatically completes the detection of general indicators (e.g., normative (name violation, null value, non-standard) and transmission difference) of the latest version data, corresponding data sample extraction is performed according to a selected medical record number, and the medical record number is derived from a paper case record provided by a medical institution. The extracted case data is displayed in a page table form, and item-by-item check with paper case records is completed manually. FIG. 1 shows an example of a web page medical record data.
The above prior art has at least the following disadvantages:
firstly, the checking work mainly depends on manual work, the repeated work is carried out, the efficiency is low, and the manual mistake and the omission are difficult to avoid.
Secondly, the paper file is dependent on the storage management level, and once the paper file is lost or damaged and has no backup, the checking cannot be carried out.
Thirdly, the data quality detection platform is in a running-water type operation mode, after a new version is loaded, the historical version is not processed any more, the data sampling of the historical version is not sufficient when the data sampling of the historical version needs to be supplemented, and the solidification process lacks flexible maneuverability.
Therefore, under the target requirement of high data quality, a more efficient, more flexible and more accurate test method and tool are urgently needed in the test acceptance link.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The purpose of the present disclosure is to provide a data testing method and a data testing apparatus, which can implement automatic execution of data testing and improve the efficiency of data quality detection.
According to an aspect of the present disclosure, there is provided a data testing method, including: automatically extracting on a first non-basic data version according to an input target sample number to obtain a current sample to be detected; automatically comparing the current sample to be detected with a corresponding standard template stored in a database to obtain a difference result between the current sample to be detected and the corresponding standard template; and automatically evaluating the difference result according to the configured index parameters to obtain an evaluation result of the current sample to be detected.
In an exemplary embodiment of the present disclosure, further comprising: automatically extracting on a first basic data version according to the input target sample number to obtain a basic sample to be detected; generating the corresponding standard template according to the basic sample to be detected; wherein the first non-base data version and the first base data version correspond to a same version of a data structure.
In an exemplary embodiment of the present disclosure, the generating the corresponding standard template according to the basic suspected sample includes: checking the basic sample to be detected with a corresponding paper case; and if the checking is passed, automatically storing the basic sample to be checked as the corresponding standard sample plate into the database.
In an exemplary embodiment of the present disclosure, further comprising: selecting a medical record set by an individual sampling method; the medical records in the selected medical record set are identified by unique sample numbers.
In an exemplary embodiment of the present disclosure, each sample number corresponds to a unique medical record number, which corresponds to a pair of patient number and visit number.
In an exemplary embodiment of the present disclosure, the difference result includes any one or more of a table level difference, a table structure difference, and a field value difference.
In an exemplary embodiment of the present disclosure, the indicator parameter comprises a qualitative and/or quantitative indicator parameter.
In an exemplary embodiment of the present disclosure, further comprising: and upgrading the version of the data structure to generate a second basic data version.
In an exemplary embodiment of the present disclosure, further comprising: updating the business data to generate a second non-basic data version; wherein the second non-base data version and the second base data version correspond to a same version of the data structure.
According to an aspect of the present disclosure, there is provided a data testing apparatus including: the sample extraction module is configured to automatically extract on the first non-basic data version according to the input target sample number to obtain a current sample to be detected; the automatic comparison module is configured to automatically compare the current sample to be detected with a corresponding standard template stored in a database to obtain a difference result between the current sample to be detected and the corresponding standard template; and the automatic evaluation module is configured to automatically evaluate the difference result according to the configured index parameters to obtain an evaluation result of the current sample to be detected.
According to the data testing method and the data testing device in the exemplary embodiment of the disclosure, a current sample to be tested is obtained by automatically extracting on a first non-basic data version according to an input target sample number; automatically comparing the current sample to be detected with a corresponding standard template stored in a database to obtain a difference result between the current sample to be detected and the corresponding standard template; and automatically evaluating the difference result according to the configured index parameters to obtain the evaluation result of the current sample to be tested, so that the automatic execution of data testing can be realized, the efficiency of data quality detection is improved, and the subjective influence of human error and omission on the detection result can be avoided.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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The above and other features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
Fig. 1 shows a schematic diagram of a data testing method in the prior art.
FIG. 2 illustrates a flow diagram of a data testing method according to an exemplary embodiment of the present disclosure.
Fig. 3 illustrates a flow chart of a data testing method according to another exemplary embodiment of the present disclosure.
Fig. 4 illustrates a flow chart of a data testing method according to yet another exemplary embodiment of the present disclosure.
Fig. 5 illustrates a flow chart of a data testing method according to yet another exemplary embodiment of the present disclosure.
FIG. 6 shows a schematic diagram of a data testing method according to an example embodiment of the present disclosure.
FIG. 7 shows a block diagram of a data testing device according to an example embodiment of the present disclosure.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus, a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the embodiments of the disclosure can be practiced without one or more of the specific details, or with other methods, components, materials, devices, steps, and so forth. In other instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in the form of software, or in one or more software-hardened modules, or in different networks and/or processor devices and/or microcontroller devices.
Some terms involved in the embodiments of the present invention are explained below.
The medical record is as follows: the records of the disease performance and the diagnosis and treatment condition of the patient are recorded according to the standard and are stored by the medical record management department of the medical institution according to the relevant regulations. The storage form of the paper, electronic documents, medical image examination films, pathological sections and the like also exists. The medical record is a file for medical staff to record the disease diagnosis and treatment process, objectively, completely and continuously records the disease condition change, diagnosis and treatment process, treatment effect and final outcome of patients, is the basic data of medical treatment, teaching and scientific research, and is the original file material of medical science.
It should be noted that the general medical record refers to a medical record of hospitalization, which is a running medical record and is not yet filed. All medical records of patients in the hospital are finally filed as medical records and are stored according to the specified years. The patient can request for the retrieval or the copy from the hospital case management department according to the program. The arrangement sequence of the medical records in the operation process and the medical record room is different, and the specific sequence is different from each teaching material, so that the 'Chinese hospital management' (medical record management part) can be referred to.
FIG. 2 illustrates a flow diagram of a data testing method according to an exemplary embodiment of the present disclosure.
As shown in fig. 2, the data testing method provided by the embodiment of the present invention may include the following steps.
In step S210, a current sample to be examined is obtained by automatically extracting on the first non-basic data version according to the input target sample number.
In the embodiment of the invention, the data version can correspond to a case data batch. The non-basic data version is based on the basic data version, that is, the basic data version is updated with the service data, and then the generated new version data is generated.
In step S220, the current sample to be examined is automatically compared with the corresponding standard template stored in the database, so as to obtain a difference result between the current sample to be examined and the corresponding standard template.
In an exemplary embodiment, the difference result may include any one or more of a table level difference, a table structure difference, a field value difference, and the like.
In step S230, the difference result is automatically evaluated according to the configured index parameter, so as to obtain an evaluation result of the current sample to be evaluated.
In an exemplary embodiment, the indicator parameter comprises a qualitative and/or quantitative indicator parameter.
In the embodiment of the invention, qualitative means that the evaluation result is "pass" or "fail".
For example, if the key field in the current suspected sample is extracted as empty, the current suspected sample is regarded as an unqualified batch or version.
In embodiments of the invention, quantification is typically statistical data, such as throughput or error rate.
For example, 150 case samples are taken, and 50 passes, the pass rate is one third.
For another example, for a case sample, the key fields for marking the emphasis are assumed to be 500 in total, and the error rate is 20% when 100 deviations occur.
It should be noted that the calculation of the pass rate or the error rate is only an example, and may be more complicated than this in practical cases.
Fig. 3 illustrates a flow chart of a data testing method according to another exemplary embodiment of the present disclosure.
As shown in fig. 3, the data testing method provided by the embodiment of the present invention may include the following steps.
In step S310, a basic to-be-inspected sample is obtained by automatically extracting on the first basic data version according to the input target sample number.
For example, a batch on the data structure _ V3.1 is called V3.1_20180103_ bjhospital, and the batch is selected as the base version through strict quality control.
In step S320, the corresponding standard template is generated according to the basic sample to be inspected.
In an exemplary embodiment, the generating the corresponding standard template according to the base suspected sample may include: checking the basic sample to be detected with a corresponding paper case; and if the checking is passed, automatically storing the basic sample to be checked as the corresponding standard sample plate into the database.
In step S330, the current sample to be examined is obtained by automatically extracting on the first non-basic data version according to the input target sample number.
In an exemplary embodiment, the first non-base data version and the first base data version correspond to the same version of a data structure.
In step S340, the current sample to be examined is automatically compared with the corresponding standard template stored in the database, so as to obtain a difference result between the current sample to be examined and the corresponding standard template.
In the embodiment of the invention, the automatic comparison and detection link only needs to depend on a standard template in a database system. The standard template is a copy of the paper archive.
In step S350, automatically evaluating the difference result according to the configured index parameter to obtain an evaluation result of the current sample to be examined.
The steps S330 to S350 may refer to the steps S210 to S230 of the embodiment shown in fig. 2.
In an exemplary embodiment, the method may further include: and upgrading the version of the data structure to generate a second basic data version.
In an exemplary embodiment, the method may further include: and updating the business data to generate a second non-basic data version. Wherein the second non-base data version and the second base data version correspond to a same version of the data structure.
In the embodiment of the present invention, there are multiple basic data versions, the version of the data structure may be continuously updated, for example, a batch on the data structure _ V3.1 before 6 months is called V3.1_20180103_ bjhospital, the batch may be selected as the basic data version after strict quality control, the hospital service data may also be continuously updated, and batches with other dates, for example, V3.1_20180203_ bjhospital, at this time, V3.1_20180203_ bjhospital is a non-basic data version of the basic data version of V3.1_20180103_ bjhospital.
If the data structure is upgraded to V3.2, the data structure can be switched to V3.2_20180703_ bjhospital as a new basic data version, generally called a base _ database version. Similarly, the hospital business data is updated continuously, and there are lots with other dates, for example, v3.2_20180803_ bjhospital, and at this time, v3.2_20180803_ bjhospital is a non-basic data version of the basic data version, v3.2_20180703_ bjhospital.
It should be noted that, in the embodiment of the present invention, the version of the data structure is not a database version. The data version mainly corresponds to a batch of databases.
Fig. 4 illustrates a flow chart of a data testing method according to yet another exemplary embodiment of the present disclosure.
As shown in fig. 4, the data testing method provided by the embodiment of the present invention may include the following steps.
In step S410, a medical record set is selected by an individual sampling method.
The individual sampling method refers to an epidemic statistical analysis method, the sampling range relates to patients of different sexes and different age groups, the clinic cases of different years, and the medical record samples are selected from multiple dimensions of departments, disease types, medical service systems and the like.
The departments may include general departments of a comprehensive hospital, special departments of a hospital, and key characteristic departments for a single hospital, for example: hernia surgery, etc.
The disease species can include several systemic conventional disease species and special disease species of human body, and the disease species are mainly used in a single hospital, such as: leukemia, Fallo tetrad (congenital heart disease), etc.
The medical business system may include, but is not limited to: routine tests, unconventional tests, hand anesthesia systems, blood transfusion systems, physical examination systems, nursing systems, ICU (Intensive Care Unit) systems, and the like.
In step S420, the medical records in the selected medical record set are identified by the unique sample number.
In an exemplary embodiment, each sample number corresponds to a unique medical record number, which corresponds to a pair of a patient number and a visit number.
In the embodiment of the invention, the sample number corresponds to a unique medical record number, the medical record number corresponds to a unique pair of patient number patient _ sn (which can be abbreviated as psn) and visit number visi _ sn (which can be abbreviated as vsn), the patient number is stored in an excel format and can correspond to a corresponding medical record number after being transmitted to the sample number, the psn and the vsn can be automatically read in a database according to a corresponding medical record numbering program, the two fields are main keys of all data tables, a patient id and a visit id can be understood, the patient id and the visit id are a set of complete medical record data, and the medical record data can be stored in more than 30 tables, such as clinic, registration, hospitalization, examination and the like. Database queries are then executed according to the psn and vsn. The records equal to the patient number and the treatment number are taken out from the database, a plurality of tables are formed, and each table obtains a key of which the record is analyzed into a field English name and a field value: the value format, whereas the prior art is web platform exposed, as shown in FIG. 1 above.
For example, S0001 and S0002 are sample numbers of sample No. 1 and sample No. 2, respectively, and since hospital numbers, psns and vsns in the medical record numbers are long and difficult to identify, the medical record numbers and the sample numbers are in one-to-one correspondence, which is a process from business data to programming, and thus, the medical record numbers can be simplified. In the following comparison link, the comparison result of sample number 1 is diff of S0001, which is simple.
It should be noted that, in the prior art, the extracted medical records are presented in the form of a page table, which describes the functions provided by the existing data quality control platform, and the functions are described in terms of business. In the embodiment of the invention, non-service function description terms are used, and the terms are used in terms of pure data.
In step S430, a basic to-be-inspected sample is obtained by automatically extracting on the first basic data version according to the input target sample number.
In step S440, the corresponding standard template is generated according to the basic sample to be inspected.
In step S450, the current sample to be examined is obtained by automatically extracting on the first non-basic data version according to the input target sample number.
In an exemplary embodiment, the first non-base data version and the first base data version correspond to the same version of a data structure.
In the embodiment of the invention, the business data is not static, and new batches can be continuously generated according to the continuous update of the business data or the upgrade of the data structure, namely, new version data is generated to be used as a non-basic data version.
In step S460, the current sample to be examined is automatically compared with the corresponding standard template stored in the database, so as to obtain a difference result between the current sample to be examined and the corresponding standard template.
In step S470, automatically evaluating the difference result according to the configured index parameter, so as to obtain an evaluation result of the current sample to be tested.
The steps S430 to S470 refer to the steps S310 to S350 of the embodiment shown in fig. 3.
Fig. 5 illustrates a flow chart of a data testing method according to yet another exemplary embodiment of the present disclosure.
As shown in fig. 5, the data testing method provided by the embodiment of the present invention may include the following steps.
In step S510, a real medical record set is selected by an individual sampling method, and the selected medical record is identified by a unique sample number.
In step S520, a sample number is input, and the automation program is triggered to extract a sample on a certain basic data version.
In step S530, the sample to be examined obtained after successful extraction is performed, and the total amount of paper case records is checked.
In step S540, it is determined whether the sample to be examined obtained in step S530 is qualified; if the sample to be detected obtained in the step S530 is qualified, the process proceeds to a step S560; otherwise, the process proceeds to step S550.
In step S550, if the sample to be examined obtained in step S530 is not qualified after being checked against the total amount of paper case records, the difference between the sample to be examined obtained in step S530 and the paper case records is fed back to the data production department for tracing and positioning to repair the problem, and then the process returns to step S540 to determine whether the repaired sample is qualified, and the steps S540 and S550 are executed in a circulating manner until a qualified sample is obtained.
Specifically, the sample to be detected obtained after successful extraction is subjected to full-scale check of paper case records, and if the sample is unqualified, the difference is manually fed back to a data production department for tracing and positioning until a qualified sample can be obtained after problem recovery. The qualified samples will be stored as standard templates in the database via an automated program.
In the embodiment of the present invention, the quality of the full amount of data includes, but is not limited to: integrity (including record level, field base), normalization (naming violation, null, non-standard); in content quality control, the records of the original paper medical records or electronic medical records of the hospital are generally compared with corresponding sample data extracted from a large database, and whether the data processing has serious quality defects or not is checked.
In the embodiment of the invention, the sample is qualified and unqualified according to the test case or experience of a tester, for example, if the main key field is empty, the problem is definitely existed; some, such as a department name change, may be normal or not a problem. If the data is judged to be problematic, the data cannot be delivered. The data production engineer locates the repair, recreates the new batch database, and then takes a sample and checks.
In step S560, the qualified sample obtained in the above step is stored as a standard template in a database via an automated program.
In step S570, the same sample number as that in step S520 is input, and an automation program is triggered to extract samples from other data versions, thereby obtaining a sample to be examined.
In step S580, the automated program is triggered to compare the sample to be detected in step S570 with the standard template stored in the database, and a difference result is output.
In an embodiment of the present invention, the difference result may include: comparing according to table names according to table level differences; table structure differences, field levels, missing fields or added fields; the values are different, the field names are the same, and the values are different.
For example, the standard template key in the case data with the new version and the basic version extracted: and (4) directly comparing the value data with diff, comparing key firstly, and then comparing value, and finding out the difference part.
In step S590, the difference result may be analyzed qualitatively or quantitatively, and qualitative or quantitative index parameters are configured in an evaluation program, so as to directly output a corresponding index evaluation result, which may be used for quality evaluation or quality grading.
The data testing method provided by the embodiment of the invention is a sample comparison automatic detection method based on real case individual sampling, the verified standard sample plate is stored, and an automatic comparison detection program is matched to replace a repeated process of manual detection, so that the detection execution efficiency of the data sampling method is automatically improved, the subjective influence of human mistakes and omissions on the detection result is avoided, the flexibility and the maneuverability are strong, the time cost and the labor cost are reduced, and the quality index measurement is promoted.
FIG. 6 shows a schematic diagram of a data testing method according to an example embodiment of the present disclosure.
As shown in fig. 6, first, the actual medical records are selected by the individual sampling method, and the medical record numbers of the selected medical records are output.
Then, the corresponding patient number and the visit number in the database can be inquired according to the medical record number.
And automatically extracting a sample on the data version according to the inquired patient number and the visit number so as to output the sample to be detected.
Judging whether the obtained sample to be detected is on a basic data version to determine a standard template; if so, checking the sample to be checked and the paper case record, and judging whether the checking result of the sample to be checked and the paper case record passes or not; if the standard sample passes, the qualified sample is taken as a standard sample and stored in a database; if the data version fails, returning to the step of automatically extracting the sample on the data version, continuing to extract the sample, and obtaining a new sample to be detected again.
And if the automatically extracted sample to be detected is not the standard template determined on the basic data version, automatically comparing and detecting the obtained sample to be detected and the standard template stored in the database, and outputting a difference result between the sample to be detected and the standard template.
And automatically evaluating the difference result according to the configured qualitative or quantitative index parameters, and outputting an evaluation result.
According to the data testing method provided by the embodiment of the invention, for a medical record, a production data sample corresponding to a basic version is extracted on the basis of the basic version, the qualified data sample is stored in a database system as a standard template and is retained, manual work only needs to check the standard template, and after a subsequent new version is generated, the medical record data with the same number is sampled, so that the retained standard template can be directly taken for comparison and detection. The three links of extraction, storage and detection are automatic, and do not depend on the original data quality detection platform, so that the repeated labor of manual checking is greatly reduced, the human errors are eliminated, the electronic informatization backup of the paper files is convenient for centralized management and acquisition, and the medical record numbers can be replaced at any time on different data versions, namely the extraction and the checking are carried out without being limited by the solidification process.
It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
FIG. 7 shows a block diagram of a data testing device 700 according to another exemplary embodiment of the present disclosure.
As shown in fig. 7, the data testing apparatus 700 may include: a sample extraction module 710, an automatic comparison module 720, and an automatic evaluation module 730. Wherein:
the sample extraction module 710 may be configured to automatically extract on the first non-base data version based on the input target sample number to obtain the current suspect sample.
The automatic comparison module 720 may be configured to automatically compare the current suspected sample with a corresponding standard template stored in a database to obtain a difference result between the current suspected sample and the corresponding standard template.
The automatic evaluating module 730 may be configured to automatically evaluate the difference result according to the configured index parameter to obtain an evaluation result of the current sample to be examined.
In an exemplary embodiment, the data test apparatus 700 may further include: the basic sample to be detected obtaining module can be configured to automatically extract on a first basic data version according to the input target sample number to obtain a basic sample to be detected; a standard template generation module configured to generate the corresponding standard template from the basic to-be-inspected sample; wherein the first non-base data version and the first base data version correspond to a same version of a data structure.
In an exemplary embodiment, the standard template generation module may further include: a sample checking unit which can be configured to check the basic sample to be checked with the corresponding paper case; and the template storage unit can be configured to automatically store the basic sample to be detected as the corresponding standard template in the database if the check is passed.
In an exemplary embodiment, the data test apparatus 700 may further include: a medical record set selection module configured to select a medical record set by an individual sampling method; the medical record identification module can be configured to identify the medical records in the selected medical record set by unique sample numbers.
In an exemplary embodiment, each sample number corresponds to a unique medical record number, which corresponds to a pair of a patient number and a visit number.
In an exemplary embodiment, the difference result may include any one or more of a table level difference, a table structure difference, a field value difference, and the like.
In an exemplary embodiment, the indicator parameter may comprise a qualitative and/or quantitative indicator parameter.
In an exemplary embodiment, the data test apparatus 700 may further include: a data structure upgrade module may be configured to upgrade a version of the data structure to generate a second base data version.
In an exemplary embodiment, the data test apparatus 700 may further include: the data updating module can be configured to update the business data and generate a second non-basic data version; wherein the second non-base data version and the second base data version correspond to a same version of the data structure.
Since each functional module of the data testing apparatus 700 according to the exemplary embodiment of the present disclosure corresponds to the step of the exemplary embodiment of the data testing method, it is not described herein again.
It should be noted that although in the above detailed description several modules or units of the data testing device are mentioned, this division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (9)
1. A method for testing data, comprising:
automatically extracting on a first non-basic data version according to an input target sample number to obtain a current sample to be detected;
automatically comparing the current sample to be detected with a corresponding standard template stored in a database to obtain a difference result between the current sample to be detected and the corresponding standard template;
automatically evaluating the difference result according to the configured index parameters to obtain an evaluation result of the current sample to be detected;
the method further comprises the following steps:
automatically extracting on a first basic data version according to the input target sample number to obtain a basic sample to be detected;
generating the corresponding standard template according to the basic sample to be detected;
the first basic data version comprises a database corresponding to a target version, the first non-basic data version comprises a database after business data corresponding to the target version is updated, and the first non-basic data version and the first basic data version correspond to the same version of a data structure.
2. The data testing method of claim 1, wherein the generating the corresponding standard template from the base suspected sample comprises:
checking the basic sample to be detected with a corresponding paper case;
and if the checking is passed, automatically storing the basic sample to be checked as the corresponding standard sample plate into the database.
3. The data testing method of claim 1, further comprising:
selecting a medical record set by an individual sampling method;
the medical records in the selected medical record set are identified by unique sample numbers.
4. The data testing method of claim 3, wherein each sample number corresponds to a unique medical record number, said medical record number corresponding to a pair of a patient number and a visit number.
5. The data testing method of claim 1, wherein the difference result comprises any one or more of a table level difference, a table structure difference, and a field value difference.
6. The data testing method of claim 1, wherein the indicator parameter comprises a qualitative and/or quantitative indicator parameter.
7. The data testing method of claim 1, further comprising:
and upgrading the version of the data structure to generate a second basic data version.
8. The data testing method of claim 7, further comprising:
updating the business data to generate a second non-basic data version;
wherein the second non-base data version and the second base data version correspond to a same version of the data structure.
9. A data testing apparatus, comprising:
the sample extraction module is configured to automatically extract on the first non-basic data version according to the input target sample number to obtain a current sample to be detected;
the automatic comparison module is configured to automatically compare the current sample to be detected with a corresponding standard template stored in a database to obtain a difference result between the current sample to be detected and the corresponding standard template;
the automatic evaluation module is configured to automatically evaluate the difference result according to the configured index parameters to obtain an evaluation result of the current sample to be detected;
the data testing apparatus further includes:
the basic sample to be detected obtaining module is configured to automatically extract on a first basic data version according to the input target sample number to obtain a basic sample to be detected;
a standard template generating module configured to generate the corresponding standard template according to the basic sample to be inspected;
the first basic data version comprises a database corresponding to a target version, the first non-basic data version comprises a database after business data corresponding to the target version is updated, and the first non-basic data version and the first basic data version correspond to the same version of a data structure.
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| CN108389621A (en) * | 2018-02-08 | 2018-08-10 | 山东康网网络科技有限公司 | Medical record database quality determining method and system |
| CN108597565A (en) * | 2018-04-11 | 2018-09-28 | 浙江大学 | It is a kind of that method of calibration is cooperateed with the clinical queuing data of name entity extraction technology based on OCR |
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| CN108389621A (en) * | 2018-02-08 | 2018-08-10 | 山东康网网络科技有限公司 | Medical record database quality determining method and system |
| CN108597565A (en) * | 2018-04-11 | 2018-09-28 | 浙江大学 | It is a kind of that method of calibration is cooperateed with the clinical queuing data of name entity extraction technology based on OCR |
| CN108389606A (en) * | 2018-05-08 | 2018-08-10 | 灵玖中科软件（北京）有限公司 | A kind of the data quality control system and its control method of electronic medical record homepage |
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