CN109659034A - Data Quality Assessment Methodology, device, equipment and the storage medium of first page of illness case - Google Patents

Data Quality Assessment Methodology, device, equipment and the storage medium of first page of illness case Download PDF

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Publication number
CN109659034A
CN109659034A CN201811462378.8A CN201811462378A CN109659034A CN 109659034 A CN109659034 A CN 109659034A CN 201811462378 A CN201811462378 A CN 201811462378A CN 109659034 A CN109659034 A CN 109659034A
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value
page
points
field
illness case
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黄越
陈明东
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Ping An Medical and Healthcare Management Co Ltd
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Ping An Medical and Healthcare Management Co Ltd
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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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

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Abstract

The present invention is based on the thoughts of big data analysis processing, it is proposed Data Quality Assessment Methodology, device, equipment and the storage medium of a kind of first page of illness case, the described method includes: when receiving the first page of illness case of medical institutions' upload, read each field name in first page of illness case, and the field type according to corresponding to each field name, the field value of each field name is divided into different data groups；It detects and whether there is field value to be deducted points in each data group, if it exists field value to be deducted points, then according to the corresponding relationship between preset field type and deduction of points value, the data group for treating deduction of points field value source is deducted points, and generates target deduction of points value；According to the target deduction of points value of each data group, generate first page of illness case must score value, and according to must score value, assess the quality of data in first page of illness case.This programme by first page of illness case it is generated must score value come the quality of data in total evaluation first page of illness case, make to assess more accurate, improve assessment efficiency.

Description

Data Quality Assessment Methodology, device, equipment and the storage medium of first page of illness case
Technical field
The invention mainly relates to medical system technical fields, specifically, the quality of data for being related to a kind of first page of illness case is commented Estimate method, apparatus, equipment and storage medium.
Background technique
When Disease is gone to a doctor in hospital to medical institutions, medical institutions are for the ease of the medical feelings to each Disease Condition is managed, and is provided with first page of illness case, and the master data of Disease is recorded by first page of illness case, diagnostic data, is gone to a doctor Funds data etc..The Various types of data recorded in first page of illness case carries out the master of Medical Record registration, classification of diseases as medical institutions It will foundation；It is recorded in terms of the integrality and accuracy on quality height reflect the excellent of medical institutions' work quality It is bad, it is related to the accuracy of Medical Record registration and classification of diseases, to seem to the assessment of the quality of data in first page of illness case It is particularly important.But the main side manually to check of the quality at present to data in first page of illness case in terms of the integrality and accuracy Formula is assessed, and there is the Disease being largely hospitalized in medical institutions, is had the first page of illness case for largely needing to assess, is manually looked into It sees that needs take a significant amount of time, assesses low efficiency, and be easy error, quality evaluation is not accurate enough.
Summary of the invention
The main object of the present invention is to provide Data Quality Assessment Methodology, device, equipment and the storage of a kind of first page of illness case Medium, it is intended to solve the problems, such as in the prior art to the data quality accessment low efficiency of first page of illness case, inaccuracy.
To achieve the above object, the present invention provides a kind of Data Quality Assessment Methodology of first page of illness case, the first page of illness case Data Quality Assessment Methodology the following steps are included:
When receiving the first page of illness case of medical institutions' upload, each field name in the first page of illness case is read, and according to The field value of each field name is divided into different data groups by field type corresponding to each field name；
It detects and whether there is field value to be deducted points in each data group, if it exists field value to be deducted points, then according to default Field type and deduction of points value between corresponding relationship, deduct points to the data group in the field value source to be deducted points, Generate target deduction of points value；
According to the target deduction of points value of each data group, generate the first page of illness case must score value, and according to described total Score value assesses the quality of data in the first page of illness case.
Preferably, include: with the presence or absence of the step of field value to be deducted points in each data group of detection
Null value detection is carried out to the field value in each data group, is judged in each data group with the presence or absence of field value For the first field value of null value, field value is the first field value of null value if it exists, then by first field value be determined as to Deduction of points field value；
After each data group carries out the null value detection, numerical value class field is filtered out from each data group Value, and numberical range detection is carried out to each numerical value class field value, judge in each numerical value class field value with the presence or absence of number Value exceeds the second field value of preset range；
Numerical value exceeds the second field value of preset range if it exists, then second field value is determined as field to be deducted points Value.
Preferably, the corresponding relationship according between preset field type and deduction of points value, to the field to be deducted points The data group in value source is deducted points, generate target deduction of points value the step of include:
To possessed first field value and described second in the data group in the field value source to be deducted points Field value is counted, and the field total amount of the field value to be deducted points is generated；
Read the field type of the data group in the field value source to be deducted points, and according to preset field type with Corresponding relationship between deduction of points value determines type deduction of points value corresponding with the field type read；
According to the type deduction of points value and the field total amount, the data group in the field value source to be deducted points is generated Target deduction of points value.
Preferably, the target deduction of points value according to each data group, generate the first page of illness case must score value Include: after step
The more parts of first page of illness case are judged whether there is, if it exists the more parts of first page of illness case, then reads lower a medical record Homepage, and execute the step of reading each field name in the first page of illness case；
Described in being generated in each first page of illness case must after score value, to it is each it is described must score value integrate, generate institute The comprehensive score of each first page of illness case of medical institutions' upload is stated, and according to the data group each in each first page of illness case Target deduction of points value generates the average deduction of points accounting of each data group；
According to the comprehensive score and the accounting of averagely deducting points, it is first to possessed each medical record to assess the medical institutions The management quality that page is managed.
Preferably, it is described to it is each it is described must score value integrate, generate each medical record that the medical institutions upload The step of comprehensive score of homepage includes:
To it is each it is described must score value compare, determine it is each it is described must maximum score value and minimum score in score value Value, and to it is each it is described must score value be added, generate the whole score of each first page of illness case；
The medical record quantity for each first page of illness case that the medical institutions upload is counted, and according to the whole score and institute Medical record quantity is stated, the average scoring value of each first page of illness case is generated；
The maximum score value, the minimum score value and the average scoring value are determined as medical institutions' upload The comprehensive score of each first page of illness case.
Preferably, the target deduction of points value according to the data group each in each first page of illness case generates each number According to group average deduction of points accounting the step of include:
According to the target deduction of points value of the data group each in each first page of illness case, each data group is generated corresponding Target deduction of points accounting in the first page of illness case；
The target deduction of points accounting of the identical each data group of field type in each first page of illness case is counted, it is raw At the target deduction of points accounting total amount of all kinds of data groups；
Each target deduction of points accounting total amount and the medical record quantity are done into ratio, generate being averaged for all kinds of data groups Deduction of points accounting.
Preferably, it is wrapped after the step of comprehensive score for generating each first page of illness case that the medical institutions upload It includes:
The comprehensive score and default score threshold are compared, judge whether the comprehensive score is greater than the default score Threshold value；
If the comprehensive score is greater than the default score threshold, the disease type word in each first page of illness case is read Section name, and according to the disease type field name, statistic of classification is carried out to each first page of illness case, with the determination medical institutions The accounting of middle various diseases.
In addition, to achieve the above object, the present invention also proposes a kind of data quality accessment device of first page of illness case, the disease The data quality accessment device of case homepage includes:
Read module, for reading each in the first page of illness case when receiving the first page of illness case of medical institutions' upload The field value of each field name is divided into different by field name, and the field type according to corresponding to each field name Data group；
Detection module whether there is field value to be deducted points for detecting, if it exists field to be deducted points in each data group Value, then according to the corresponding relationship between preset field type and deduction of points value, to the number in the field value source to be deducted points It deducts points according to group, generates target deduction of points value；
Evaluation module, for the target deduction of points value according to each data group, generate the first page of illness case must score value, And according to it is described must score value, assess the quality of data in the first page of illness case.
In addition, to achieve the above object, the present invention also proposes a kind of data quality accessment equipment of first page of illness case, the disease The data quality accessment equipment of case homepage includes: memory, processor, communication bus and the disease being stored on the memory The data quality accessment program of case homepage；
The communication bus is for realizing the connection communication between processor and memory；
The processor is used to execute the data quality accessment program of the first page of illness case, to perform the steps of
When receiving the first page of illness case of medical institutions' upload, each field name in the first page of illness case is read, and according to The field value of each field name is divided into different data groups by field type corresponding to each field name；
It detects and whether there is field value to be deducted points in each data group, if it exists field value to be deducted points, then according to default Field type and deduction of points value between corresponding relationship, deduct points to the data group in the field value source to be deducted points, Generate target deduction of points value；
According to the target deduction of points value of each data group, generate the first page of illness case must score value, and according to described total Score value assesses the quality of data in the first page of illness case.
In addition, to achieve the above object, the present invention also provides a kind of storage medium, the storage medium be stored with one or More than one program of person, the one or more programs can be executed by one or more than one processor with In:
When receiving the first page of illness case of medical institutions' upload, each field name in the first page of illness case is read, and according to The field value of each field name is divided into different data groups by field type corresponding to each field name；
It detects and whether there is field value to be deducted points in each data group, if it exists field value to be deducted points, then according to default Field type and deduction of points value between corresponding relationship, deduct points to the data group in the field value source to be deducted points, Generate target deduction of points value；
According to the target deduction of points value of each data group, generate the first page of illness case must score value, and according to described total Score value assesses the quality of data in the first page of illness case.
The Data Quality Assessment Methodology of the first page of illness case of the present embodiment will be in the first page of illness case of reading according to field type The field value of each field name be divided into different data groups；And each data group is detected, with judge wherein whether In the presence of field value to be deducted points, field value to be deducted points if it exists, then according to pair between preset field type and deduction of points value It should be related to, deduct points to the data group in the field value source to be deducted points, generate target deduction of points value；And then by each data group Target deduction of points value, generate first page of illness case must score value, according to this must score value, the quality of data in first page of illness case is commented Estimate.By detection by the field value to be deducted points in the formed data group of field value each in first page of illness case, to be determined as medical record head Page in data each field value integrality and accuracy, and by it is generated must score value come in total evaluation first page of illness case The quality of data reflects the integrality and accuracy height of data；It avoids carrying out checking assessment in a manual manner, so that medical record is first The assessment of the quality of data is more accurate in page, and improves the efficiency of assessment.
Detailed description of the invention
Fig. 1 is the flow diagram of the Data Quality Assessment Methodology first embodiment of first page of illness case of the invention；
Fig. 2 is the functional block diagram of the data quality accessment device first embodiment of first page of illness case of the invention；
Fig. 3 is the device structure schematic diagram for the hardware running environment that present invention method is related to.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present invention provides a kind of Data Quality Assessment Methodology of first page of illness case.
Fig. 1 is please referred to, Fig. 1 is the process signal of the Data Quality Assessment Methodology first embodiment of first page of illness case of the present invention Figure.In the present embodiment, the Data Quality Assessment Methodology of the first page of illness case includes:
Step S10 reads each field in the first page of illness case when receiving the first page of illness case of medical institutions' upload Name, and the field type according to corresponding to each field name, are divided into different data for the field value of each field name Group；
The Data Quality Assessment Methodology of first page of illness case of the invention is applied to server, is suitable for through server to medical treatment The data of first page of illness case carry out quality evaluation in mechanism；Wherein first page of illness case is substantially medical institutions to the disease gone to a doctor in hospital The record data that the medical situation of patient is recorded, the content recorded include that the basic information of Disease, disease are examined Disconnected information, fund information of going to a doctor etc..Establishing between server and each medical institutions has a communication connection, and medical institutions are by its medical record Homepage is uploaded onto the server；Server reads each field name therein when receiving the first page of illness case.Field name characterizes medical record The title of various data recorded in homepage, and different data have different data values, so that different field names pair Answer different field values；As for data recorded in first page of illness case: name-Xiao Wang, age -27, " name " and " age " Belong to field name, and " Xiao Wang " and " 27 " belongs to field value.
In view of data different types of in first page of illness case, reflect that the significance level of the medical situation of Disease is different, Wherein the information such as personal information, Main Diagnosis type and chief surgical for Disease go to a doctor situation reflection it is more important； And such information such as other information about doctor, home address does not weigh the reflection of the medical situation of Disease more It wants.First page of illness case is higher for the integrality and accuracy requirement of significant data, and to the integrality of significance level lower data It is relatively low with accuracy requirement；To characterize the field type of its significance level for different field name settings in advance, such as Important kind is set by the field type of field name " Gender ", " patient age ", " disease type ", " treatment means ", And inessential type is set by the field type of field name " intern ", " coder ".Read each field name it Afterwards, according to the corresponding relationship between the field name and field type, field value possessed by each field name to reading is carried out Data group divides, and the identical field value of important level will be characterized as through field type and is divided into same data group；Such as by above-mentioned word Section name " Gender ", " patient age ", " disease type ", " treatment means " corresponding field value are divided into same data group, And field name " intern ", " coder " corresponding field value are divided into another identical data group.
Step S20 is detected and be whether there is field value to be deducted points in each data group, if it exists field value to be deducted points, then According to the corresponding relationship between preset field type and deduction of points value, to the data group in the field value source to be deducted points into Row deduction of points, generates target deduction of points value；
Further, the present embodiment sets deduction of points mechanism to the integrality and accuracy of data each in first page of illness case, and again Deduction of points value corresponding to the data for wanting degree different is not also identical；The wherein higher data of significance level, corresponding deduction of points value It is more.After each field value carries out data group division in first page of illness case, each data group is detected, with each number of determination According to the integrality and accuracy of field value in group；Using imperfect or inaccurate field value as field value to be deducted points, that is, pass through The mode of detection judges in each data group with the presence or absence of field value to be deducted points.Specifically, detecting whether there is in each data group The step of field value to be deducted points includes:
Step S21 carries out null value detection to the field value in each data group, judges whether deposit in each data group In the first field value that field value is null value, field value is the first field value of null value if it exists, then by first field value It is determined as field value to be deducted points；
Understandably, the integrality of data is embodied in each data and all has data value in first page of illness case, i.e., each field name is equal There are corresponding field values；During whether there is field value to be deducted points in detecting each data, first to the word in each data group Segment value carries out null value detection, judges whether each field value in each data group is null value.All field values in each data group After carrying out null value detection, that is, it can determine whether with the presence or absence of the field value for null value in each data group, be the field of null value by such Value is used as the first field value；First field value if it exists then illustrates that the first field value lacks data value and field name carries out pair It answers, the data of the first field value are imperfect, it needs to carry out deduction of points operation to it, and first field value is determined as word to be deducted points Segment value.
Step S22 filters out numerical value from each data group after each data group carries out the null value detection Class field value, and numberical range detection is carried out to each numerical value class field value, judge in each numerical value class field value whether There are the second field values that numerical value exceeds preset range；
Further, the field value in each data group may be value type, such as " 30 ", it is also possible to character string type, Such as " Lao Wang "；Null value detection is being carried out to each data group, after finding out the first field value in each data group, because The numerical value that value type field value is characterized in a certain range, if the age is usually between 0~130 years old, and needs logarithm Numberical range where type field value is detected, to ensure the accuracy of the characterized numerical value of field value.Specifically, to each number It is screened according to the field value in group according to type identification, character string type field value therein is filtered, numerical value class is filtered out Field value；And numberical range detection is carried out to each numerical value class field value, judge that numerical value corresponding to each numerical value class field value is It is no within a preset range.Wherein preset range is, according to the different preset numberical ranges of field name type, such as characterizes The preset range of the field name at age is 0~150, and the preset range for characterizing the field name of time is 1990.01.01~current Time etc..In carrying out numberical range detection process, the value type that first field name as corresponding to each numerical value class field value characterizes, Determine the preset range of each numerical value class field value；And then compare each numerical value class field value and corresponding preset range, sentence Each numerical value class field value break whether in corresponding preset range.Each numerical value class field value filtered out and its is corresponding pre- If after range compares, can further judge to exceed the second of preset range with the presence or absence of numerical value in each numerical value class field value Field value, to determine the accuracy of each characterized numerical value of numerical value class field value by judgement.
It should be noted that for the data of the main and standby relation in the presence of first page of illness case, such as living in person for Disease The address of location and contact person can only fill in one main and standby relation between the two；Such data are divided into data splitting group, Each main and standby relation data are simply by the presence of any one field value in data splitting group；When being detected, it first detects active and standby It whether there is any one field value in relation data, then illustrate not to be null value if it exists, if it does not exist any one field value Then explanation is null value, and as the first field value；It is detecting there are any one field value and then further to judge the word Within a preset range whether segment value is numerical value class field value, if then carrying out numberical range detection, judge its numerical value.
Step S23, if it exists numerical value exceed preset range the second field value, then by second field value be determined as to Deduction of points field value.
If judge in each numerical value class field value there are numerical value exceed preset range the second field value, illustrate this second The numerical value inaccuracy that field value is characterized, needs to carry out deduction of points operation, and second field value is also determined as field to be deducted points Value.
Understandably, as carrying out the field value to be deducted points of deduction of points operation from each data group, and each number It is different to the influence degree of first page of illness case according to the integrality and accuracy of field value in group, wherein more important data group, word Segment value is imperfect or inaccurate bigger to the influence degree of first page of illness case；When deducting points operation, the number high to significance level is needed According to group more deduction of points value of setting.Because significance level is characterized by field type, to preset field type and deduction of points value Between corresponding relationship；There is the first field value and/or the second word as field value to be deducted points in judging each data group After segment value, according to the corresponding relationship between field type and deduction of points value, the data group for treating deduction of points field value institute source is carried out Deduction of points operation, and generate the target deduction of points value of the data group with field value to be deducted points；I.e. to possessed in each data group The field value that needs to be deducted points is deducted points, and the total penalties value in each data group is obtained.Specifically, according to preset field type with Corresponding relationship between deduction of points value deducts points to the data group in the field value source to be deducted points, and generates target deduction of points The step of value includes:
Step S24, to possessed first field value in the data group in the field value source to be deducted points and Second field value is counted, and the field total amount of the field value to be deducted points is generated；
Because having the quantity of field value to be deducted points related in the total penalties value and data group of each data group, quantity is more, Obtained total penalties value is bigger, i.e., target deduction of points value is bigger.And field value to be deducted points includes the first field value and the second field Value exists after field value of deducting points in determining each data group, treats the determined in deduction of points field value institute derived data group One field value and the second field value carry out cumulative statistics, that is, count in each data group for the field value of null value and beyond preset range Field value；Obtain the field total amount of field value to be deducted points in each data group with field value to be deducted points, i.e., in each data group Total amount with imperfect and/or inaccurate field value.
Step S25 reads the field type of the data group in the field value source to be deducted points, and according to preset word Corresponding relationship between segment type and deduction of points value determines type deduction of points value corresponding with the field type read；
Further, after the field total amount in counting each data group with field value to be deducted points, then foundation is needed The field total amount calculates the total penalties value of each data group.The field type with the data group of field value to be deducted points is read, by this Corresponding relationship comparison between the field type of reading and preset field type and deduction of points value, determines in corresponding relationship and reads The consistent field type of field type；Consistent field type deduction of points value corresponding in corresponding relationship, as reads Field type corresponding to type deduction of points value；Data group corresponding with field type carries out deduction of points behaviour according to the type deduction of points value Make.
Step S26 generates the institute in the field value source to be deducted points according to the type deduction of points value and the field total amount State the target deduction of points value of data group.
Because of field value the to be deducted points sum of deduction of points required in field total amount characterize data group, and type deduction of points value is single The deduction of points value of field value to be deducted points, so that type deduction of points value is multiplied with field total amount, the obtained result that is multiplied is The total penalties value deducted points required for data group, i.e. target deduction of points value.
It should be noted that field value to be deducted points possessed by different data group is different, as long as determining in data group In the presence of field value to be deducted points, i.e., the field total amount of each data group is counted, and determines the corresponding type deduction of points of each data group Value；And then the target deduction of points value of each data group is obtained, until having each data group of field value to be deducted points in first page of illness case Obtain target deduction of points value.
Step S30, according to the target deduction of points value of each data group, generate the first page of illness case must score value, and root According to it is described must score value, assess the quality of data in the first page of illness case.
Further, target deduction of points value, i.e., each data group are generated in each data group with field value to be deducted points Total penalties value after, by each target deduction of points value, produce first page of illness case must score value.Specifically, pre- in server It is first provided with the highest score of first page of illness case, i.e., each field value is complete, accurate in first page of illness case, and there is no field values to be deducted points When score value；The target deduction of points value of each data group is added, obtains first page of illness case because field value is imperfect, inaccurate institute The total score of button；Subtract the total score detained with first page of illness case highest score again, can be obtained first page of illness case must score value, By this must score value characterize first page of illness case in the quality of data.When must score value it is higher, characterize first page of illness case in each field value More complete, more accurate, i.e., the data in first page of illness case are more complete, more accurate；Otherwise the data characterized in first page of illness case are more endless It is whole or inaccurate.
The Data Quality Assessment Methodology of the first page of illness case of the present embodiment will be in the first page of illness case of reading according to field type The field value of each field name be divided into different data groups；And each data group is detected, with judge wherein whether In the presence of field value to be deducted points, field value to be deducted points if it exists, then according to pair between preset field type and deduction of points value It should be related to, deduct points to the data group in the field value source to be deducted points, generate target deduction of points value；And then by each data group Target deduction of points value, generate first page of illness case must score value, according to this must score value, the quality of data in first page of illness case is commented Estimate.By detection by the field value to be deducted points in the formed data group of field value each in first page of illness case, to be determined as medical record head Page in data each field value integrality and accuracy, and by it is generated must score value come in total evaluation first page of illness case The quality of data reflects the integrality and accuracy height of data；It avoids carrying out checking assessment in a manual manner, so that medical record is first The assessment of the quality of data is more accurate in page, and improves the efficiency of assessment.
Further, described according to each institute in another embodiment of Data Quality Assessment Methodology of first page of illness case of the present invention The target deduction of points value for stating data group, generate the first page of illness case must score value the step of after include:
Step S40 judges whether there is the more parts of first page of illness case, if it exists the more parts of first page of illness case, then under reading A first page of illness case, and execute the step of reading each field name in the first page of illness case；
Understandably, the first page of illness case that medical institutions are uploaded may have more parts, to be sentenced by the more parts of first page of illness case The work quality of disconnected medical institutions.Generating in certain part of first page of illness case uploaded for medical institutions to judge to cure after score value It treats whether mechanism has uploaded more parts of first page of illness case, that is, whether there is more parts of first page of illness case；If judging there are more parts of first page of illness case, Next point of first page of illness case is then read, and reads each field name in lower a first page of illness case, to carry out field value grouping, and The target deduction of points value with each data group of field value to be deducted points is generated, and then is worth to obtain lower a medical record head by each target deduction of points Page must score value, specific step is consistent with above-mentioned first embodiment, and this will not be repeated here.So circulation is until more parts of medical records Homepage generates must score value.
Step S50, generated in each first page of illness case described in must after score value, to it is each it is described must score value carry out it is whole It closes, generates the comprehensive score for each first page of illness case that the medical institutions upload, and according to institute each in each first page of illness case The target deduction of points value of data group is stated, the average deduction of points accounting of each data group is generated；
Further, when the more parts of first page of illness case that medical institutions are uploaded generate must score value after, then to each total Score value is integrated, and the comprehensive score of each first page of illness case of medical institutions' upload is obtained；The comprehensive score includes each disease Case homepage must maximum value, minimum value and average value etc. in score value, to reflect disease in medical institutions by the comprehensive score The overall integrity and accuracy of case homepage data.Specifically, it is described to it is each it is described must score value integrate, generate the doctor Treat mechanism upload each first page of illness case comprehensive score the step of include:
Step S51, to it is each it is described must score value compare, determine it is each it is described must maximum score value in score value and most Small score value, and to it is each it is described must score value be added, generate the whole score of each first page of illness case；
By generation it is each must score value compare, determine maximum score value therein and minimum score value, that is, contain The first page of illness case of field value minimum number to be deducted points and containing needing the most first page of illness case of field value quantity of being deducted points；By maximum score This contains the integrality and accuracy of each field value in the first page of illness case for the field value minimum number that needs to be deducted points for value reflection, is obtained by minimum Score value reflects that this contains the integrality and accuracy of each field value in the most first page of illness case of field value quantity that needs to be deducted points；Work as maximum Score value and minimum score value are higher, then illustrate that each field value in first page of illness case gets over complete and accurate.Meanwhile also to each total score Value is added, and the whole score of each first page of illness case is obtained, with the whole field for reflecting had first page of illness case in medical institutions The integrality and accuracy of value.
Step S52 counts the medical record quantity for each first page of illness case that the medical institutions upload, and according to the entirety Score and the medical record quantity generate the average scoring value of each first page of illness case；
The maximum score value, the minimum score value and the average scoring value are determined as therapeutic machine by step S53 The comprehensive score for each first page of illness case that structure uploads.
Further, the quantity of each first page of illness case uploaded to medical institutions carries out cumulative statistics, generates medical record quantity, And then the whole score counted with all first page of illness case and the medical record quantity do ratio, and it is first to obtain each part medical record in medical institutions The average value of the whole score of page, using the average value as average value score.By obtained maximum score value, minimum score value with And average value score is determined as the comprehensive score for each first page of illness case that medical institutions are uploaded, to reflect numerical value matter in medical institutions Measure best first page of illness case, the average quality of the worst first page of illness case of the quality of data and each first page of illness case.
In addition, in order to embody data imperfect and inaccurate in each first page of illness case of medical institutions, the present embodiment is also set It is equipped with the average deduction of points accounting to the detained target deduction of points value of data group each in each first page of illness case, i.e. the average deduction of points of total penalties value accounts for The generting machanism of ratio, to reflect the average deduction of points situation of each data group by each averagely deduction of points accounting.Wherein data group is flat Deduction of points accounting is bigger, illustrates in the data group that data are more imperfect accurate, and medical institutions are subsequent can be to generating the data group Field value carries out key monitoring.Specifically, the field name having in each first page of illness case is all the same, so that by field type institute The quantity and significance level of the data group of division are identical, i.e., each first page of illness case all refers to each significance level of identical quantity Data group；But the target deduction of points value detained between the identical each data group of significance level in each first page of illness case is different, and each It is worth by each target deduction of points that the total score detained formed is same in first page of illness case, so that the identical each data group of significance level There is also differences for target deduction of points accounting of the target deduction of points value in its respectively first page of illness case at place.The significance level is identical each Target deduction of points accounting of the data group in its respectively place first page of illness case, by the target deduction of points value of each data group in each first page of illness case It generates, and then institute in medical institutions is produced by the target of the identical each data group of significance level in each first page of illness case deduction of points accounting There is the average deduction of points accounting of each data group of first page of illness case.Can according to the target deduction of points value of data group each in each first page of illness case, The average deduction of points accounting for generating the identical each data group of significance level in all first page of illness case, specifically, according to each first page of illness case In each data group target deduction of points value, the step of generating the average deduction of points accounting of each data group includes:
Step S53 generates each data group according to the target deduction of points value of the data group each in each first page of illness case Target deduction of points accounting in the corresponding first page of illness case；
Understandably, each part first page of illness case includes each data group divided, in the detection process each data group institute The total score that the sum of target deduction of points value of button is detained by each part first page of illness case；And then the target deduction of points value detained with each data group and The total score does ratio, that is, produces target deduction of points accounting of each data group where it in first page of illness case.For example, for medical treatment First page of illness case A, B that mechanism is uploaded, wherein A includes data group a1 and a2, and B includes data group b1 and b2, and the word of a1 and b1 Segment type is identical, and the field type of important level having the same, a2 and b2 is identical, important level having the same.Through monitoring The target deduction of points value for obtaining a1 and a2 is respectively m1 and m2, and the target deduction of points value of b1 and b2 are respectively n1 and n2, so that a1, a2 exist Target deduction of points accounting in first page of illness case A is m1/ (m1+m2) and m2/ (m1+m2), the target button of b1, b2 in first page of illness case B Dividing accounting is n1/ (n1+n2) and n2/ (n1+n2).
Step S53, to the target of the identical each data group of field type in each first page of illness case deduct points accounting into Row statistics generates the target deduction of points accounting total amount of all kinds of data groups；
Further, identical to significance level after the target deduction of points accounting for each data group in each first page of illness case The target deduction of points accounting of each data group classify cumulative statistics, generate each significance level identical data group in medical institutions Target accounting deduction of points total amount, characterizes the deduction of points situation of each data group in the first page of illness case of medical institutions.Because of the important journey of data group Degree is characterized by field type, so that it is that field type is identical that significance level is identical, i.e., to field type phase in each first page of illness case The target deduction of points accounting of same each data group is counted, and the target deduction of points accounting total amount of Various types of data group is obtained.Such as upper First page of illness case A, B are stated, because the field type between a1 and b1 is identical, the field type between a2 and b2 is identical, by [a1, b1] institute The target deduction of points accounting total amount of the homogeneous data group of characterization is ((m1/ (m1+m2))+(n1/ (n1+n2))), and by [a2, b2] institute The target deduction of points accounting total amount of the homogeneous data group of characterization is ((m2/ (m1+m2))+(n2/ (n1+n2))).
Each target deduction of points accounting total amount and the medical record quantity are done ratio, generate all kinds of data by step S53 The average deduction of points accounting of group.
Further, the target deduction of points accounting total amount and medical record quantity of the Various types of data group of generation are done into ratio, gained To result be Various types of data group average deduction of points accounting, characterization medical institutions Various types of data group average deduction of points situation. Such as above-mentioned first page of illness case A, B, because medical record quantity is 2, then the average deduction of points accounting of homogeneous data group [a1, b1] is ((m1/ (m1+m2))+(n1/ (n1+n2)))/2, the average deduction of points accounting of homogeneous data group [a2, b2] is ((m2/ (m1+m2))+(n2/ (n1+n2)))/2.The size cases of the two characterize the average deduction of points situation between two categorical data groups, for average deduction of points The biggish data group of accounting carries out key monitoring, so as to the subsequent integrality and accuracy for improving its data.
In addition, checked for the ease of the quality of data to first page of illness case in medical institutions, by comprehensive score most The average deduction of points accounting of score value, minimum score value, average scoring value and Various types of data group greatly is shown.
Step S60 assesses the medical institutions to possessed according to the comprehensive score and the accounting of averagely deducting points The management quality that each first page of illness case is managed.
Understandably, each part first page of illness case that medical institutions are uploaded is inputted by all kinds of personnel in medical institutions and is generated, The quality of data therein characterizes medical institutions to the management quality of first page of illness case, and the quality of data is better in each first page of illness case, Then medical institutions are better to the management quality of first page of illness case.Each first page of illness case of reason must score value comprehensive score table generated The data total quality of each first page of illness case in medical institutions is illustrated, and the average deduction of points accounting of Various types of data group also characterizes each number According to the quality of data of group, so as to pass through the comprehensive score and averagely deduction of points accounting, assessment medical institutions are specifically each to its institute The management quality that first page of illness case is managed.Each part that each first page of illness case possessed by medical institutions is uploaded in addition to medical institutions It can also include being stored in the first page of illness case not yet uploaded in medical institutions except first page of illness case.When comprehensive score is higher, The average deduction of points accounting of Various types of data group is lower or comprehensive score is higher, the average deduction of points of the higher data group of significance level Accounting is lower, then medical institutions are better to the management quality of first page of illness case, on the contrary then poorer.
Further, in another embodiment of Data Quality Assessment Methodology of first page of illness case of the present invention, described in the generation Include: after the step of comprehensive score for each first page of illness case that medical institutions upload
Step S70 compares the comprehensive score and default score threshold, and it is described to judge whether the comprehensive score is greater than Default score threshold；
Understandably, the medical institutions for the data quality accessment for carrying out first page of illness case are needed to may relate to more families, i.e., respectively A medical institutions upload onto the server the first page of illness case that quality evaluation is carried out required for it, are directed to each medical institutions by server First page of illness case generate comprehensive score respectively.The first page of illness case of different medical mechanism is different, so that comprehensive score generated Having differences property of the quality of data that is different, and then being assessed by comprehensive score.In order to characterize first page of illness case in each medical institutions The height of the quality of data, the present embodiment are previously provided with the default score threshold for characterizing the high quality of data, are being directed to any one family After medical institutions generate comprehensive score, by the comprehensive score and the default score threshold comparison, judge whether comprehensive score is big In default score threshold, to determine whether the first page of illness case of medical institutions has the high quality of data.
Step S80 reads the disease in each first page of illness case if the comprehensive score is greater than the default score threshold Sick type field name, and according to the disease type field name, statistic of classification is carried out to each first page of illness case, described in determination The accounting of various diseases in medical institutions.
Further, when judging that comprehensive score is greater than default score threshold by contrast, then illustrate the disease of medical institutions Case homepage has the high quality of data, and the data complete and accurate in first page of illness case can be used characterized in each first page of illness case Disease type classifies to disease.Specifically, disease type field name in each first page of illness case is read, the disease type field Name characterizes the corresponding disease type of each first page of illness case；And then according to the disease type field name, classify to each first page of illness case, The first page of illness case of same disease type field name is divided into same classification；And count possessed first page of illness case number in each classification Amount, the medical record quantity of each first page of illness case uploaded with all kinds of middle first page of illness case quantity and medical institutions does ratio, obtained Ratio result can embody the accounting of various diseases in medical institutions, disease personnel of the reflection with various diseases to medical institutions In medical accounting.
In addition, carrying out further division to the first page of illness case in all kinds of, the patient age word in all kinds of first page of illness case is read Segment value, gender field value and Region field value etc., and to the quantity of age field value in all kinds of first page of illness case, gender field value The quantity of quantity and Region field value carries out cumulative statistics, determines various diseases in the trouble at each age, each gender and each department Sick accounting.It such as counts in the first page of illness case classification that disease type is P, patient populations of the age between 40~50 years old, gender phase Same patient populations, identical patient populations in area etc.；Hereafter with the patient populations in each the range of age divided by sick in the type The quantity of case homepage suffers from the patient populations of disease P, determines illness accounting of the disease P in each the range of age；Similarly, With the patient populations of each gender divided by the quantity of the type first page of illness case, that is, it can determine illness accounting of the disease P in each gender； With the patient populations of each department divided by the quantity of the type first page of illness case, that is, it can determine illness accounting of the disease P in each department. And then the group of people at high risk of various diseases is determined by each illness accounting, and prompt information is propagated to such group of people at high risk, to remind it Pay attention to and prevents early.
In addition, referring to figure 2., the present invention provides a kind of data quality accessment device of first page of illness case, in medical record of the present invention In the data quality accessment device first embodiment of homepage, the data quality accessment device of the first page of illness case includes:
Read module 10, for reading in the first page of illness case when receiving the first page of illness case of medical institutions' upload The field value of each field name is divided into difference by each field name, and the field type according to corresponding to each field name Data group；
Detection module 20 whether there is field value to be deducted points for detecting, if it exists word to be deducted points in each data group Segment value, then according to the corresponding relationship between preset field type and deduction of points value, to described in the field value source to be deducted points Data group is deducted points, and target deduction of points value is generated；
Evaluation module 30 generates the total score of the first page of illness case for the target deduction of points value according to each data group Value, and according to it is described must score value, assess the quality of data in the first page of illness case.
The data quality accessment device of the first page of illness case of the present embodiment, read module 10 is according to field type, by reading The field value of each field name in first page of illness case is divided into different data groups；And by detection module 20 to each data group into Row detection wherein whether there is field value to be deducted points with judgement, if it exists field value to be deducted points, then according to preset field Corresponding relationship between type and deduction of points value deducts points to the data group in the field value source to be deducted points, and generates target deduction of points Value；And then by evaluation module 30 according to the target deduction of points value of each data group, generate first page of illness case must score value, it is total according to this Score value assesses the quality of data in first page of illness case.By detecting by the formed data of field value each in first page of illness case Field value to be deducted points in group, to be determined as the integrality and accuracy of each field value of data in first page of illness case, and by institute Generate must score value carry out the quality of data in total evaluation first page of illness case, reflect data integrality and accuracy height；It keeps away Exempt to carry out checking assessment in a manual manner, so that the assessment of the quality of data is more accurate in first page of illness case, and improves assessment Efficiency.
Further, in another embodiment of data quality accessment device of first page of illness case of the present invention, the detection module Further include:
Detection unit judges in each data group for carrying out null value detection to the field value in each data group It is the first field value of null value with the presence or absence of field value, field value is the first field value of null value if it exists, then by described first Field value is determined as field value to be deducted points；
Screening unit, for being screened from each data group after each data group carries out the null value detection Numerical value class field value out, and numberical range detection is carried out to each numerical value class field value, judge each numerical value class field value In with the presence or absence of numerical value exceed preset range the second field value；
Determination unit exceeds the second field value of preset range for numerical value if it exists, then second field value is true It is set to field value to be deducted points.
Further, in another embodiment of data quality accessment device of first page of illness case of the present invention, the detection module Further include:
Statistic unit, for possessed first field in the data group to the field value source to be deducted points Value and second field value are counted, and the field total amount of the field value to be deducted points is generated；
Reading unit, the field type of the data group for reading the field value source to be deducted points, and according to pre- If field type and deduction of points value between corresponding relationship, determine the corresponding type deduction of points value of the field type with reading；
Generation unit, for generating the field value to be deducted points according to the type deduction of points value and the field total amount The target deduction of points value of the data group in source.
Further, in another embodiment of data quality accessment device of first page of illness case of the present invention, the first page of illness case Data quality accessment device further include:
Judgment module, for judging whether there is the more parts of first page of illness case, the more parts of first page of illness case, then read if it exists A first page of illness case is removed, and executes the step of reading each field name in the first page of illness case；
Integrate module, for described in being generated in each first page of illness case must after score value, to it is each it is described must score value into Row integration, generates the comprehensive score for each first page of illness case that the medical institutions upload, and according in each first page of illness case The target deduction of points value of each data group generates the average deduction of points accounting of each data group；
The evaluation module is also used to assess the medical institutions according to the comprehensive score and the accounting of averagely deducting points The management quality that possessed each first page of illness case is managed.
Further, described to integrate module in another embodiment of data quality accessment device of first page of illness case of the present invention It is also used to:
To it is each it is described must score value compare, determine it is each it is described must maximum score value and minimum score in score value Value, and to it is each it is described must score value be added, generate the whole score of each first page of illness case；
The medical record quantity for each first page of illness case that the medical institutions upload is counted, and according to the whole score and institute Medical record quantity is stated, the average scoring value of each first page of illness case is generated；
The maximum score value, the minimum score value and the average scoring value are determined as medical institutions' upload The comprehensive score of each first page of illness case.
Further, described to integrate module in another embodiment of data quality accessment device of first page of illness case of the present invention It is also used to:
According to the target deduction of points value of the data group each in each first page of illness case, each data group is generated corresponding Target deduction of points accounting in the first page of illness case；
The target deduction of points accounting of the identical each data group of field type in each first page of illness case is counted, it is raw At the target deduction of points accounting total amount of all kinds of data groups；
Each target deduction of points accounting total amount and the medical record quantity are done into ratio, generate being averaged for all kinds of data groups Deduction of points accounting.
Further, in another embodiment of data quality accessment device of first page of illness case of the present invention, the first page of illness case Data quality accessment device further include:
Contrast module judges whether the comprehensive score is big for comparing the comprehensive score and default score threshold In the default score threshold；
Statistical module reads each first page of illness case if being greater than the default score threshold for the comprehensive score In disease type field name statistic of classification is carried out to each first page of illness case, with true and according to the disease type field name The accounting of various diseases in the fixed medical institutions.
Wherein, each virtual functions module of the data quality accessment device of above-mentioned first page of illness case is stored in medical record shown in Fig. 3 In the memory 1005 of the data quality accessment equipment of homepage, processor 1001 executes the data quality accessment program of first page of illness case When, realize the function of modules in embodiment illustrated in fig. 2.
Referring to Fig. 3, Fig. 3 is the device structure schematic diagram for the hardware running environment that present invention method is related to.
The data quality accessment equipment of first page of illness case of the embodiment of the present invention can be PC (personal computer, individual Computer), it is also possible to the terminal devices such as smart phone, tablet computer, E-book reader, portable computer.
As shown in figure 3, the data quality accessment equipment of the first page of illness case may include: processor 1001, such as CPU (Central Processing Unit, central processing unit), memory 1005, communication bus 1002.Wherein, communication bus 1002 for realizing the connection communication between processor 1001 and memory 1005.Memory 1005 can be high-speed RAM (random access memory, random access memory), is also possible to stable memory (non-volatile ), such as magnetic disk storage memory.Memory 1005 optionally can also be the storage dress independently of aforementioned processor 1001 It sets.
Optionally, the data quality accessment equipment of the first page of illness case can also include user interface, network interface, camera shooting Head, RF (Radio Frequency, radio frequency) circuit, sensor, voicefrequency circuit, WiFi (Wireless Fidelity, no line width Band) module etc..User interface may include display screen (Display), input unit such as keyboard (Keyboard), can be selected Family interface can also include standard wireline interface and wireless interface.Network interface optionally may include standard wireline interface, Wireless interface (such as WI-FI interface).
It will be understood by those skilled in the art that the data quality accessment device structure of first page of illness case shown in Fig. 3 is not The restriction to the data quality accessment equipment of first page of illness case is constituted, may include than illustrating more or fewer components or group Close certain components or different component layouts.
As shown in figure 3, as may include operating system, network communication module in a kind of memory 1005 of storage medium And the data quality accessment program of first page of illness case.Operating system is to manage and control the data quality accessment equipment of first page of illness case The program of hardware and software resource supports the data quality accessment program of first page of illness case and the fortune of other softwares and/or program Row.Network communication module is for realizing the communication between the 1005 each component in inside of memory, and the data matter with first page of illness case It is communicated between other hardware and softwares in amount assessment equipment.
In the data quality accessment equipment of first page of illness case shown in Fig. 3, processor 1001 is for executing memory 1005 The data quality accessment program of the first page of illness case of middle storage realizes each embodiment of the Data Quality Assessment Methodology of above-mentioned first page of illness case In step.
The present invention provides a kind of storage medium, the storage medium is preferably computer readable storage medium, the meter Calculation machine readable storage medium storing program for executing is stored with one or more than one program, and the one or more programs can also be by one Or more than one processor executes in each embodiment of Data Quality Assessment Methodology for realizing above-mentioned first page of illness case Step.
It should also be noted that, herein, the terms "include", "comprise" or its any other variant are intended to non- It is exclusive to include, so that the process, method, article or the device that include a series of elements not only include those elements, It but also including other elements that are not explicitly listed, or further include solid by this process, method, article or device Some elements.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including There is also other identical elements in the process, method of the element, article or device.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art The part contributed out can be embodied in the form of software products, which is stored in one as described above In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone, Computer, server or network equipment etc.) execute method described in each embodiment of the present invention.
The above description is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all at this Under the design of invention, using equivalent structure transformation made by description of the invention and accompanying drawing content, or directly/it is used in it indirectly He is included in scope of patent protection of the invention relevant technical field.

Claims (10)

1. a kind of Data Quality Assessment Methodology of first page of illness case, which is characterized in that the data quality accessment side of the first page of illness case Method the following steps are included:
When receiving the first page of illness case of medical institutions' upload, each field name in the first page of illness case is read, and according to each institute Field type corresponding to field name is stated, the field value of each field name is divided into different data groups；
It detects and whether there is field value to be deducted points in each data group, if it exists field value to be deducted points, then according to preset word Corresponding relationship between segment type and deduction of points value deducts points to the data group in the field value source to be deducted points, and generates Target deduction of points value；
According to the target deduction of points value of each data group, generate the first page of illness case must score value, and according to the total score Value, assesses the quality of data in the first page of illness case.
2. the Data Quality Assessment Methodology of first page of illness case as described in claim 1, which is characterized in that each number of detection Include: according to the step of whether there is field value to be deducted points in group
Null value detection is carried out to the field value in each data group, is judged in each data group with the presence or absence of field value for sky First field value of value, field value is the first field value of null value if it exists, then first field value is determined as wait deduct points Field value；
After each data group carries out the null value detection, numerical value class field value is filtered out from each data group, and Numberical range detection is carried out to each numerical value class field value, judges to exceed in each numerical value class field value with the presence or absence of numerical value Second field value of preset range；
Numerical value exceeds the second field value of preset range if it exists, then second field value is determined as field value to be deducted points.
3. the Data Quality Assessment Methodology of first page of illness case as claimed in claim 2, which is characterized in that described according to preset word Corresponding relationship between segment type and deduction of points value deducts points to the data group in the field value source to be deducted points, and generates The step of target deduction of points value includes:
To possessed first field value and second field in the data group in the field value source to be deducted points Value is counted, and the field total amount of the field value to be deducted points is generated；
The field type of the data group in the field value source to be deducted points is read, and according to preset field type and deduction of points Corresponding relationship between value determines type deduction of points value corresponding with the field type read；
According to the type deduction of points value and the field total amount, the mesh of the data group in the field value source to be deducted points is generated Mark deduction of points value.
4. the Data Quality Assessment Methodology of first page of illness case as described in claim 1, which is characterized in that described according to each number According to the target deduction of points value of group, generate the first page of illness case must score value the step of after include:
The more parts of first page of illness case are judged whether there is, if it exists the more parts of first page of illness case, then read lower a first page of illness case, And execute the step of reading each field name in the first page of illness case；
Described in being generated in each first page of illness case must after score value, to it is each it is described must score value integrate, generate the doctor The comprehensive score for each first page of illness case that mechanism uploads is treated, and according to the target of the data group each in each first page of illness case Deduction of points value generates the average deduction of points accounting of each data group；
According to the comprehensive score and it is described averagely deduct points accounting, assess the medical institutions to possessed each first page of illness case into The management quality of row management.
5. the Data Quality Assessment Methodology of first page of illness case as claimed in claim 4, which is characterized in that it is described to it is each it is described must The step of score value is integrated, and the comprehensive score for each first page of illness case that the medical institutions upload is generated include:
To it is each it is described must score value compare, determine it is each it is described must maximum score value and minimum score value in score value, and To it is each it is described must score value be added, generate the whole score of each first page of illness case；
The medical record quantity for each first page of illness case that the medical institutions upload is counted, and according to the whole score and the disease Case quantity generates the average scoring value of each first page of illness case；
The maximum score value, the minimum score value and the average scoring value are determined as to each institute of medical institutions' upload State the comprehensive score of first page of illness case.
6. the Data Quality Assessment Methodology of first page of illness case as claimed in claim 5, which is characterized in that described according to each disease The target deduction of points value of each data group in case homepage, the step of generating the average deduction of points accounting of each data group include:
According to the target deduction of points value of the data group each in each first page of illness case, each data group is generated corresponding described Target deduction of points accounting in first page of illness case；
The target deduction of points accounting of the identical each data group of field type in each first page of illness case is counted, is generated each The target deduction of points accounting total amount of data group described in class；
Each target deduction of points accounting total amount and the medical record quantity are done into ratio, generate the average deduction of points of all kinds of data groups Accounting.
7. the Data Quality Assessment Methodology of first page of illness case as claimed in claim 4, which is characterized in that described to generate the medical treatment Include: after the step of comprehensive score for each first page of illness case that mechanism uploads
The comprehensive score and default score threshold are compared, judge whether the comprehensive score is greater than the default score threshold Value；
If the comprehensive score is greater than the default score threshold, the disease type field in each first page of illness case is read Name, and according to the disease type field name, statistic of classification is carried out to each first page of illness case, in the determination medical institutions The accounting of various diseases.
8. a kind of data quality accessment device of first page of illness case, which is characterized in that the data quality accessment of the first page of illness case fills It sets and includes:
Read module, for reading each field in the first page of illness case when receiving the first page of illness case of medical institutions' upload Name, and the field type according to corresponding to each field name, are divided into different data for the field value of each field name Group；
Detection module whether there is field value to be deducted points for detecting, if it exists field value to be deducted points, then in each data group According to the corresponding relationship between preset field type and deduction of points value, to the data group in the field value source to be deducted points into Row deduction of points, generates target deduction of points value；
Evaluation module, for the target deduction of points value according to each data group, generate the first page of illness case must score value, and root According to it is described must score value, assess the quality of data in the first page of illness case.
9. a kind of data quality accessment equipment of first page of illness case, which is characterized in that the data quality accessment of the first page of illness case is set Standby includes: the data quality accessment journey of memory, processor, communication bus and the first page of illness case being stored on the memory Sequence；
The communication bus is for realizing the connection communication between processor and memory；
The processor is used to execute the data quality accessment program of the first page of illness case, to realize as appointed in claim 1-7 The step of Data Quality Assessment Methodology of first page of illness case described in one.
10. a kind of storage medium, which is characterized in that be stored with the data quality accessment journey of first page of illness case on the storage medium Sequence is realized as described in any one of claim 1-7 when the data quality accessment program of the first page of illness case is executed by processor First page of illness case Data Quality Assessment Methodology the step of.
CN201811462378.8A 2018-11-30 2018-11-30 Data Quality Assessment Methodology, device, equipment and the storage medium of first page of illness case Pending CN109659034A (en)

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