CN112734281A - Decoupling processing method for quality control and task scheduling in medical data processing - Google Patents
Decoupling processing method for quality control and task scheduling in medical data processing Download PDFInfo
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- 238000003908 quality control method Methods 0.000 title claims abstract description 109
- 238000003672 processing method Methods 0.000 title claims abstract description 22
- 238000012545 processing Methods 0.000 title claims description 16
- 238000000034 method Methods 0.000 claims abstract description 13
- 238000010606 normalization Methods 0.000 claims description 13
- 238000013441 quality evaluation Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 4
- 206010022000 influenza Diseases 0.000 description 7
- 238000013523 data management Methods 0.000 description 3
- 238000003745 diagnosis Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
The invention discloses a decoupling processing method for quality control and task scheduling in medical data treatment, and belongs to the technical field of data treatment. The decoupling processing method for quality control and task scheduling in medical data treatment separates the quality control and the task scheduling, enables the quality control and the task scheduling to be executed respectively, summarizes quality control problem data according to individual requirements of a subject database, forms subject data and problem summary data of the quality control in the subject database, and combines the subject data and the problem summary data to realize data application service. The decoupling processing method for quality control and task scheduling in medical data treatment can reduce complex processes, can avoid the problem of the same quality control for the same data for multiple times, improves the quality control efficiency, and has good popularization and application values.
Description
Technical Field
The invention relates to the technical field of data treatment, and particularly provides a decoupling processing method for quality control and task scheduling in medical data treatment.
Background
The data management is to rationalize the data acquisition according to the existing standard of the platform and supervise the data acquisition, processing and use.
The normalization library is a data set formed by carrying out table normalization, field normalization and dictionary standardization on data governance.
And the subject library is a data set which is formed by taking required data from the normalizing library according to the application requirements and evaluating the quality of the data and can normally meet the application requirements.
The quality evaluation is to perform quality control of multiple service rules on the data in the normalization library to form a quality control qualified and unqualified data list. The business rules are quality control business units and are set from multiple dimensions such as timeliness, integrity, correctness, relevance, logicality and the like. Different application requirements have different requirements on data quality, and business rules needing quality control are different, so that the quality control range is established according to the application of the subject database, and the method has individuation.
The conventional data flow of entering a normalized library into a subject library is shown in fig. 1, and in the first step, data is taken out from the normalized library according to requirements to perform quality control evaluation of each service rule, and a quality control result is divided into an event number of qualified quality control data and an event number of unqualified quality control data. And secondly, taking qualified data out according to the event number of the quality control qualified data and entering the qualified data into a subject library. The method has two obvious disadvantages, one is that the quality evaluation process of the personalized demand is put into the data circulation process from the whole normalizing library to the theme library, so that the task scheduling process of the theme library becomes personalized, and a general flow cannot be abstracted. And secondly, different subject libraries only provide individuation for the service rule range of quality control, and different subject libraries have completely the same quality control for the same service rule, so that if a plurality of subject libraries exist, the quality control is repeated for the same rule for a plurality of times, resources are wasted, and the efficiency is reduced.
Disclosure of Invention
The technical task of the invention is to provide a decoupling processing method for quality control and task scheduling in medical data treatment, which can reduce complex processes, avoid the problem of multiple times of same quality control of the same data and improve the quality control efficiency.
In order to achieve the purpose, the invention provides the following technical scheme:
a decoupling processing method for quality control and task scheduling in medical data management separates quality control and task scheduling, enables quality control and task scheduling to be executed respectively, collects quality control problem data according to individual requirements of a subject database, forms subject data and problem collection data of quality control in the subject database, and combines the subject data and the problem collection data to realize data application service.
The quality control and task scheduling can be separated into a universal flow, the complexity of the flow is reduced, the problem of the same quality control for the same data for multiple times can be avoided, and the quality control efficiency is improved.
Preferably, the decoupling processing method for quality control and task scheduling in medical data treatment specifically comprises the following steps:
s1, the task scheduling takes out the field data meeting the requirement of the theme library from the normalization library and puts the field data into a theme table;
s2, the quality evaluation task evaluates the quality control business rules of the full-scale data and the incremental data to form a data inventory table of the normalization database data which is qualified and unqualified under each quality control business rule;
and S3, applying and processing the theme library quality control data.
Preferably, in step S1, a standard data set is determined according to the application requirements, and a set of theme tables is formed.
Preferably, writing sql forms a script for taking each field data required for the theme table from the normalization library according to the field of the target theme table.
Preferably, the sql statement is executed by the task scheduler, and the data conforming to the fields of the topic table is fetched into each table of the topic library, wherein the topic table comprises the full data and the incremental data.
Preferably, in step S3, the quality control business rules are selected as the quality control rule formation tables for the respective subject libraries.
Preferably, for the quality control business rules of each topic library, the logic of the statistical summary is for a primary event, and all the qualification rules in the evaluation of the respective quality control business rules are qualified.
Preferably, when the theme base data is used, whether the record is qualified or not is checked in the quality control summary result table, and if the record is qualified, the theme base data is normally used.
Compared with the prior art, the decoupling processing method for quality control and task scheduling in medical data treatment has the following outstanding beneficial effects: according to the decoupling processing method for quality control and task scheduling in medical data treatment, task scheduling can be made into a general flow, only data in a normalization database is charged into a subject database according to field requirements, personalized quality control is not considered, and operation and maintenance cost and scheduling complexity are greatly reduced. All data in the normalized database are subjected to unified quality control after quality control decoupling, and only a quality control problem data summary table for each subject database needs to be formed by independent summarization aiming at the individualized quality control rule range of each subject database, so that the quality control can be separated and independently processed, mutual restriction influence is avoided, each rule of each data can be subjected to quality control once, the problem of quality control repetition caused by a plurality of subject databases is reduced, the quality control time is greatly reduced, the quality control efficiency is improved, and the method has good popularization and application values.
Drawings
FIG. 1 is a diagram illustrating a task scheduling and quality control process relationship in the prior art;
fig. 2 is a flowchart of a decoupling processing method of quality control and task scheduling in medical data processing according to the present invention.
Detailed Description
The decoupling processing method for quality control and task scheduling in medical data processing according to the present invention will be described in further detail with reference to the accompanying drawings and embodiments.
Examples
As shown in fig. 2, the decoupling processing method for quality control and task scheduling in medical data management separates quality control and task scheduling, so that quality control and task scheduling are executed respectively, quality control problem data are summarized according to personalized requirements of a subject library, subject data and problem summary data of quality control are formed in the subject library, and the subject data and the problem summary data are combined to realize data application service. The method specifically comprises the following steps:
s1, the task scheduling takes out the field data meeting the requirement of the theme library from the normalization library and puts the field data into the theme list, and the method comprises the following steps:
1) determining a standard data set according to application requirements to form a set of a theme table;
2) writing sql to form a script for taking out each field data required by the theme table from the normalizing library according to the field of the target theme table;
3) and executing the sql statement through a task scheduling program, and taking out data which accord with fields of the theme table into each table of the theme base, wherein the theme table comprises full data and incremental data, and qualified data and unqualified data exist in the theme table.
And S2, the quality evaluation task evaluates the quality control business rules of the full data and the incremental data to form a data inventory table of the normalization database data which is qualified and unqualified under each quality control business rule.
The quality evaluation task evaluates all quality control business rules of the total data and the subsequent incremental data to form a data inventory table of whether the normalized database data is qualified or unqualified under each quality control rule, for example, as follows, a patient generates complete registration data once and puts the registration data into a REGISTER table when registering and visiting a clinic in a central hospital, part of the data of the table is shown in table 1, five quality control business rules are currently set for the clinic registration table as shown in table 2, and quality control data detail data can be formed after the patient data is subjected to quality control according to the business rules, as shown in table 3.
TABLE 1 outpatient service hanging number table sample data
TABLE 2 outpatient clinic number-hanging table quality control rule
TABLE 3 quality control results details Table sample data
And S3, applying and processing the theme library quality control data.
Aiming at each subject library, such as two requirements of a health file open subject library and a flu prediction subject library, aiming at an outpatient registration list, all five rules in the health file selection table 2 are used as a quality control rule forming table 4 of the flu prediction, and four rules except for a non-empty identity card number are used as a quality control rule forming table 5 of the flu prediction.
TABLE 4 quality control rules for topical out-patient registration of health records
TABLE 5 flu prediction out-patient registration quality control rule
According to the quality control rules of all the subject libraries, the logic of statistics and summary is to aim at one-time treatment events, and if one is unqualified in the evaluation of the respective quality control rules, the treatment record data represented by the treatment event is finally unqualified, and all the qualified treatment record data are qualified. If the health file is opened, the quality control result details in the table 3 are counted and summarized according to the own quality control rule to form the quality control result shown in the table 6, and the influenza prediction is counted and summarized according to the own quality control rule to form the quality control result shown in the table 7.
TABLE 6 open quality control summary result table of health record
TABLE 7 summary results of influenza prediction and quality control
When the theme library data is used, whether a certain diagnosis record is qualified or not is checked in the quality control summary result table, if the diagnosis record is qualified, the diagnosis record can be normally used, for example, the data is shown above, when a health file is opened, only the information of registration of the Lifours patients in the table 1 is opened, and the information of Zhang III is unqualified data. Influenza predicts that both data of Zhang three and Li four are qualified and can be used normally.
The above-described embodiments are merely preferred embodiments of the present invention, and general changes and substitutions by those skilled in the art within the technical scope of the present invention are included in the protection scope of the present invention.
Claims (8)
1. A decoupling processing method for quality control and task scheduling in medical data processing is characterized in that: the method separates quality control and task scheduling, enables the quality control and the task scheduling to be executed respectively, summarizes quality control problem data according to individual requirements of a subject library, forms subject data and problem summary data of the quality control in the subject library, and combines the subject data and the problem summary data to realize data application service.
2. The decoupled processing method of quality control and task scheduling in medical data processing according to claim 1, characterized in that: the method specifically comprises the following steps:
s1, the task scheduling takes out the field data meeting the requirement of the theme library from the normalization library and puts the field data into a theme table;
s2, the quality evaluation task evaluates the quality control business rules of the full-scale data and the incremental data to form a data inventory table of the normalization database data which is qualified and unqualified under each quality control business rule;
and S3, applying and processing the theme library quality control data.
3. The decoupling processing method of quality control and task scheduling in medical data processing according to claim 2, characterized in that: in step S1, a standard data set is determined according to the application requirements, and a set of topic tables is formed.
4. The decoupled processing method of quality control and task scheduling in medical data processing according to claim 3, characterized in that: writing sql according to the fields of the target theme table to form a script for taking out each field data required by the theme table from the normalization library.
5. The decoupled processing method of quality control and task scheduling in medical data processing according to claim 4, characterized in that: and executing the sql statement through a task scheduling program, and taking out data conforming to the fields of the theme table to enter each table of the theme base, wherein the theme table comprises full data and incremental data.
6. The decoupled processing method of quality control and task scheduling in medical data processing according to claim 5, characterized in that: in step S3, for each topic library, a quality control business rule is selected as a quality control rule forming table for each topic library.
7. The decoupled processing method of quality control and task scheduling in medical data processing according to claim 6, characterized in that: and aiming at the quality control service rules of each subject library, the logic of statistics and summary is to aim at a primary event, and all the qualified matters in the evaluation of the respective quality control service rules are qualified.
8. The decoupled processing method of quality control and task scheduling in medical data processing according to claim 7, characterized in that: when the theme library data is used, whether the record is qualified or not is checked in the quality control summary result table, and if the record is qualified, the theme library data is normally used.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103246574A (en) * | 2012-02-10 | 2013-08-14 | 阿里巴巴集团控股有限公司 | Verification method and verification device for data accuracy |
| CN104753721A (en) * | 2015-03-30 | 2015-07-01 | 浪潮通信信息系统有限公司 | Method for automatically checking universally-configurable table data |
| CN104820720A (en) * | 2015-05-26 | 2015-08-05 | 北京京东尚科信息技术有限公司 | Data quality detecting method and device |
| CN105975616A (en) * | 2016-05-19 | 2016-09-28 | 上海市疾病预防控制中心 | Data quality control system based on public health refinement management |
| CN107484189A (en) * | 2017-07-27 | 2017-12-15 | 北京市天元网络技术股份有限公司 | LTE data handling systems |
| CN107895013A (en) * | 2017-11-13 | 2018-04-10 | 医渡云（北京）技术有限公司 | Quality of data rule control method and device, storage medium, electronic equipment |
| CN110197705A (en) * | 2019-04-25 | 2019-09-03 | 胡盛寿 | A kind of clinical data service system and method based on cloud platform |
| CN110750596A (en) * | 2019-10-28 | 2020-02-04 | 山东健康医疗大数据有限公司 | Process design method for realizing information sharing of medical institution |
| CN111161815A (en) * | 2019-12-27 | 2020-05-15 | 深圳中兴网信科技有限公司 | Medical data detection method, device, terminal and computer-readable storage medium |
| CN111241086A (en) * | 2020-01-17 | 2020-06-05 | 甘肃省卫生健康统计信息中心(西北人口信息中心) | Data quality improvement method and system based on medical big data |
| CN111460045A (en) * | 2020-03-02 | 2020-07-28 | 心医国际数字医疗系统(大连)有限公司 | Modeling method, model, computer device and storage medium for data warehouse construction |
| CN111984684A (en) * | 2020-08-20 | 2020-11-24 | 北京捷报金峰数据技术有限公司 | Data processing method and device |
-
2021
- 2021-01-21 CN CN202110079381.7A patent/CN112734281A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103246574A (en) * | 2012-02-10 | 2013-08-14 | 阿里巴巴集团控股有限公司 | Verification method and verification device for data accuracy |
| CN104753721A (en) * | 2015-03-30 | 2015-07-01 | 浪潮通信信息系统有限公司 | Method for automatically checking universally-configurable table data |
| CN104820720A (en) * | 2015-05-26 | 2015-08-05 | 北京京东尚科信息技术有限公司 | Data quality detecting method and device |
| CN105975616A (en) * | 2016-05-19 | 2016-09-28 | 上海市疾病预防控制中心 | Data quality control system based on public health refinement management |
| CN107484189A (en) * | 2017-07-27 | 2017-12-15 | 北京市天元网络技术股份有限公司 | LTE data handling systems |
| CN107895013A (en) * | 2017-11-13 | 2018-04-10 | 医渡云（北京）技术有限公司 | Quality of data rule control method and device, storage medium, electronic equipment |
| CN110197705A (en) * | 2019-04-25 | 2019-09-03 | 胡盛寿 | A kind of clinical data service system and method based on cloud platform |
| CN110750596A (en) * | 2019-10-28 | 2020-02-04 | 山东健康医疗大数据有限公司 | Process design method for realizing information sharing of medical institution |
| CN111161815A (en) * | 2019-12-27 | 2020-05-15 | 深圳中兴网信科技有限公司 | Medical data detection method, device, terminal and computer-readable storage medium |
| CN111241086A (en) * | 2020-01-17 | 2020-06-05 | 甘肃省卫生健康统计信息中心(西北人口信息中心) | Data quality improvement method and system based on medical big data |
| CN111460045A (en) * | 2020-03-02 | 2020-07-28 | 心医国际数字医疗系统(大连)有限公司 | Modeling method, model, computer device and storage medium for data warehouse construction |
| CN111984684A (en) * | 2020-08-20 | 2020-11-24 | 北京捷报金峰数据技术有限公司 | Data processing method and device |
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