CN115374113A - Patient main index data generation method, system and device - Google Patents
Patient main index data generation method, system and device Download PDFInfo
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Abstract
The invention provides a method for generating patient main index data, which comprises the following steps: step 1, acquiring registration data of a patient; step 2, verifying whether the registered data is in compliance, and turning to step 3 if the registered data is in compliance; step 3, performing similarity matching query in a main index library according to the registration data, turning to step 4 if a query result meets an automatic merging condition, turning to step 5 if an automatic newly-built condition is met, and turning to step 6 if a manual processing condition is met; step 4, combining the registration data with corresponding patient index data, and covering the difference part of the registration data with the part corresponding to the patient index data; step 5, establishing the registration data as new patient index data and storing the new patient index data in a main index database; and step 6, providing a manual processing interface. The invention can improve the accuracy and efficiency of matching a large amount of data, and is beneficial to the integration and sharing of patient data of different hospital systems.
Description
Technical Field
The invention relates to the technical field of clinical medical datamation, in particular to a method, a system and a device for generating main index data of a patient.
Background
At present, in data systems of many hospitals, systems such as HIS, LIS, PACS, hand anesthesia and electrocardio are not products of a company. Many systems also have different representations of data from a business need perspective. If the data interaction and the service collaboration are not standardized and unified, the interpretation difference exists inevitably.
Chinese patent publication No. CN104699715A entitled "patient main index platform system construction method" discloses that by establishing a unified patient main index, patient identifiers dispersed in different systems are cross-indexed, thereby implementing complex and combined query of data by a main index system. However, this patent fails to solve the following problems, namely: the structure of the personnel data can also change along with the development of time, the accuracy of the matching rule can be reduced at the moment, the flow operations such as data acquisition and test need to be carried out again, and the labor cost and the time cost are needed for maintenance work.
Disclosure of Invention
The invention aims to provide a method, a system and a device for generating patient main index data, which can improve the accuracy and efficiency of matching a large amount of data and are beneficial to integration and sharing of patient data of different hospital systems.
In order to achieve the purpose, the invention provides the following technical scheme: a method of generating patient master index data, comprising the steps of:
step 1, acquiring registration data of a patient;
step 2, verifying whether the registered data is in compliance, and turning to step 3 if the registered data is in compliance;
step 3, performing similarity matching query in a main index library according to the registration data, turning to step 4 if a query result meets an automatic merging condition, turning to step 5 if an automatic newly-built condition is met, and turning to step 6 if a manual processing condition is met;
step 4, combining the registration data with corresponding patient index data, and covering the difference part of the registration data with the part corresponding to the patient index data;
step 5, establishing the registration data as new patient index data and storing the new patient index data in a main index database;
and 6, providing a manual processing interface.
Further, the step 2 comprises:
if the mandatory item in the registration data is a null value, judging that the mandatory item is not in compliance, generating a record and notifying a data source party;
if the data type of the necessary item in the registered data has an error type, judging that the data is not in compliance, and if other fields have error types, clearing, recording the operation and retaining the original data, and allowing the subsequent steps to be carried out;
if the identity card number in the registration data is not in compliance, judging that the identity card number is not in compliance, generating a record and notifying a data source party;
and clearing the mobile phone number in the registration data if the mobile phone number is not verified, recording the operation, retaining the original data and allowing the subsequent steps to be carried out.
Further, the step 3 comprises the following steps:
step 31, taking the first field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting an automatic merging condition, otherwise, turning to step 32; the first field combination is the combination of all fields with the minimum number that the sum of the weight values exceeds a first threshold value, and the weight value, the first threshold value and the first field combination are preset in a matching combination knowledge base;
step 32, taking the second field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting a manual processing condition, otherwise, meeting an automatic new condition; the second field combination is a combination of all fields with a minimum number of weighted values exceeding a second threshold value but not exceeding the first threshold value, and the second threshold value and the second field combination are preset in a matching combination knowledge base.
Further, the matching combined knowledge base is constructed by the following steps:
step a, collecting patient data;
b, checking the correctness of each field in the patient data, and calculating the correctness of each field;
step c, setting a weight value, a first threshold value and a second threshold value of each field according to the accuracy of each field;
step d, counting the first field combination and the second field combination;
step e, performing a matching test by using the patient data to obtain a test result, wherein the test result comprises a weight value, a first threshold value, a second threshold value, a first field combination and a second field combination of each field;
and f, constructing a matching combined knowledge base according to the test result.
Further, the step e comprises:
e1, performing similarity matching on the patient data and the patient index data in a main index database one by one, and determining an input mode according to a matching result;
step e2, checking whether the patient index data in the main index database after passing the step e1 is reasonable, if so, turning to the step e3, otherwise, turning to the step c;
and e3, judging whether the testing times reach preset times, if so, outputting a testing result and turning to the step f, otherwise, turning to the step a.
Further, the e1 comprises the following steps:
step e11, using the first field combination as a query condition to query whether consistent main index data exists in a main index database, if so, turning to step e13, otherwise, turning to step e2;
step e12, using the second field combination as a query condition to query whether consistent main index data exists in a main index database, if so, turning to step e14, otherwise, turning to step e15;
step e13, inputting the patient data into a main index database in an automatic merging mode;
step e14, inputting the patient data into the main index database by adopting a manual input mode; the manual mode is manual combination or manual new construction;
and e15, inputting the patient data into the main index database by adopting an automatic new establishment mode.
The invention also provides a system for generating the patient main index data, which comprises:
the registration module is used for acquiring registration data of the patient;
the verification module is used for verifying whether the registration data is in compliance or not, and activating the matching module if the registration data is in compliance;
the matching module is used for performing similarity matching query in the main index database according to the registration data, activating the merging module if a query result meets an automatic merging condition, activating the newly-built module if an automatic newly-built condition is met, and activating the manual module if a manual processing condition is met;
a merging module, configured to merge the registration data with corresponding patient index data, and overlay a difference portion of the registration data with a portion corresponding to the patient index data;
the newly-built module is used for creating the registration data into new patient index data and storing the new patient index data into a main index database;
and the manual module is used for providing a manual processing interface.
Further, the matching module comprises:
the first matching submodule is used for taking the first field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting an automatic merging condition, and otherwise, activating a second matching submodule; the first field combination is the combination of all fields with the minimum number that the sum of the weight values exceeds a first threshold value, and the weight value, the first threshold value and the first field combination are preset in a matching combination knowledge base;
the second matching sub-module is used for taking the second field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting manual processing conditions, and otherwise, meeting automatic new conditions; the second field combination is a combination of all fields with a minimum number of weighted values exceeding a second threshold value but not exceeding the first threshold value, and the second threshold value and the second field combination are preset in a matching combination knowledge base.
Further, the matching combined knowledge base is constructed by a knowledge base system, and the knowledge base system comprises:
an acquisition module for acquiring patient data;
the calculation module is used for checking the correctness of each field in the patient data and calculating the correctness of each field;
the setting module is used for setting the weight value, the first threshold and the second threshold of each field according to the accuracy of each field;
the statistical module is used for counting the first field combination and the second field combination;
the testing module is used for carrying out matching test by utilizing the patient data to obtain a testing result, and the testing result comprises a weight value, a first threshold value, a second threshold value, a first field combination and a second field combination of each field;
and the construction module is used for constructing a matching combined knowledge base according to the test result.
The invention also provides a patient main index data generation device, which comprises a processor and a memory, wherein the memory stores a computer program, and the processor realizes the steps of the method when executing the computer program.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention can match and merge processes according to the data, and ensure the uniqueness of the main index database. Meanwhile, the correctness of the data is ensured through data verification.
2. The invention can create and generate the matching combined knowledge base according to the data acquisition mark calculation mode, and can improve the matching accuracy and efficiency.
3. The invention can deal with various patient data through the main index system, and integrates the patient data scattered in each hospital system, thereby providing favorable conditions for realizing data sharing.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a flowchart of a method for constructing a matching combined knowledge base according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for generating patient master index data includes the following steps:
step 1, registration data of a patient is obtained. The registration data includes basic data and visit data. The basic data includes name, sex, date of birth, identification card number, etc. The data of medical treatment includes the number of medical treatment card, the number of medical record, the account number of medical insurance, etc. The registration data for a patient is as follows (with "+" as mandatory):
name (c): wangzaijie medicine
Sex: woman
The mobile phone number is as follows: 13888888888
Date of birth: 31/12/1949
Identification number: 11010519491231002X
The number of the diagnosis card: air conditioner
Medical insurance account number: air conditioner
Case No. 2: air conditioner
And 2, verifying whether the registered data is in compliance, and turning to the step 3 if the registered data is in compliance. In order to prevent error data from entering, the patient data needs to be verified, the next flow can be entered after the verification is passed, and the flow exits after the verification is not passed. The specific method for data verification comprises the following steps:
step 21, verification of mandatory items: the mandatory item comprises an identity card number, a name, a gender, a birth date, a place of residence, a case number or a hospital number and the like (the actual situation needs to be established according to a patient database in a hospital). If the mandatory item is null, it is determined that the mandatory item is not compliant, and a record is generated and notified to the data source.
Step 22, data type verification: such as numeric type, temporal type, literal type, etc., the data is to conform to the corresponding data type. If the necessary item has an error type, judging that the necessary item is not compliant, and if other fields have the error type, clearing, recording the operation, retaining the original data, and continuing the subsequent process.
Step 23, legality verification of the identification number: and verifying whether the identity card is correct and legal by adopting a check digit verification algorithm, judging that the identity card is not in compliance if the identity card is not verified, generating a record and informing a data source party. The identification card number is a unique number representing citizen data, and is composed of the following numbers:
(1) The 1 st and 2 nd digits represent: code of province (city, autonomous region) in direct jurisdiction;
(2) 3, 4 digit representation: code of the local city (autonomous state);
(3) 5 th and 6 th digit representation: code of the region (county, municipality, county-level city) in which it is located;
(4) Digit numbers 7-14 indicate: year, month, day of birth;
(5) Digit number 15, 16: the code of the place of residence;
(6) Number 17 indicates gender: odd numbers indicate males and even numbers indicate females;
(7) The 18 th digit is a check code: is calculated according to the regulation of the national identification number in the national standard GB11643-1999 of the people's republic of China and a precise calculation formula. The identity card number of the patient Wangzhijie is 11010519491231002X, and the legal verification steps of the identity card number are as follows:
step 231, calculating the sum of the products of the first 17 digits and its coefficientsSThe formula is as follows: (ii) a The nth digit of the identification number represents the coefficient corresponding to each digit, and n takes the values of 1-17 until the values are: 7. 9, 10, 5, 8, 4, 2, 1, 6, 3, 7, 9, 10, 5, 8, 4, 2. As can be seen from the calculations, the,S=1×7+1×9+0×10+1×5+0×8+5×4+1×2+9×1+4×6+9×3+1×7+2×9+3×10+1×5+0×8+0×4+2×2=167。
step 232, calculateSRemainder after division by 11AThe formula is as follows: ,Nindicating the quotient value. As can be seen from the calculations, the,A=167-11×15=2。
step 233, according to the remainderADetermining the 18 th digit, remainderAThe correspondence with the 18 th digit is shown in the following table:
and step 234, if the calculated 18 th digit is consistent with the 18 th digit of the identification number recorded in the registration data of the patient, the verification is passed, otherwise, the verification is not passed. As can be seen from the correspondence table in step 233,Awhen the number of the carbon atoms is 2,a 18 and (4) keeping the number of the identification card to be consistent with the eighteenth digit of the identification card number, and passing the verification.
4. And (3) legality verification of the mobile phone number: and judging the correctness of the mobile phone number by adopting a regular mode, clearing if the mobile phone number is not verified, recording the operation and retaining the original data, and continuing the subsequent process. Because the mobile phone numbers in China are issued by telecommunication, mobile and Unicom at present, the verification is more accurate by adopting a regular expression. The regular expression is ^1, [3 ] 4 non-conducting 5 gaming furnace 7 ([ 0-9] {9} $).
After verification, the registration data of the Wangzhijie patient is in compliance, and the subsequent process can be continued.
And 3, performing similarity matching query in the main index database according to the registered data, turning to the step 4 if the query result meets an automatic merging condition, turning to the step 5 if an automatic newly-built condition is met, and turning to the step 6 if a manual processing condition is met.
The step 3 comprises the following steps:
and step 31, taking the first field combination as a query condition, judging whether consistent main index data exists in the main index database, if so, meeting an automatic merging condition, otherwise, turning to step 32. The first field combination is a combination of all fields of a minimum number of which the sum of the weight values exceeds a first threshold, and the weight value, the first threshold and the first field combination are preset in the matching combination knowledge base. The weight values of the fields in the registration data are shown in the following table:
in this example, the first threshold is 99, and the first field combination is shown in the following table:
by performing the traversal query according to the field combinations in the table above, the patient index data matching the registered data of patient Wangjie cannot be found in the main index database, so the query needs to be continued, and the process goes to step 32.
And step 32, taking the second field combination as a query condition, judging whether consistent main index data exists in the main index database, if so, meeting a manual processing condition, otherwise, meeting an automatic new condition. The second field combination is a combination of all fields with minimum number, wherein the sum of the weighted values exceeds a second threshold value but does not exceed the first threshold value, and the second threshold value and the second field combination are preset in the matching combination knowledge base.
In this example, the second threshold is 49, and the second field combination is shown in the following table:
the patient index data matched with the registered data of Wangjie patient cannot be found in the main index database by performing traversal query according to the field combination in the table, so that the data of the patient needs to be newly created, and the process goes to step 5.
And 4, combining the registration data with the corresponding patient index data, and covering the difference part of the registration data with the corresponding part of the patient index data. And generating a merging record after merging, and backing up the original data so as to restore the original data.
For example: the patient index data is missing data such as work unit name, work unit-province, work unit-city, work unit-county, work unit zip code, work unit telephone number, etc., and if the data is in the registered data, the old data in the patient index data is filled with the new data in the registered data. Another example is: inconsistencies in the mobile number field in the registration data and patient index data may also overwrite old data because the patient changed the new mobile number.
And 5, creating the registration data as new patient index data and storing the new patient index data in a main index database. And a main index number is allocated while creating, is an indexed ID (identity) and is provided for a third-party service system to inquire main index information. In this example, since the patient index data matching the registration data of Wangjie patient cannot be found even after two queries in step 3, the patient index data of the patient is directly created in the main index database according to the registration data of the patient and matches a main index number.
And 6, providing a manual processing interface. If the patient index data for the patient is found via step 32, it indicates that there is a potential for duplication of the data, and therefore a manual decision is made as to whether to create new data or merge the data. For example, a query of "name + date of birth" finds a matching piece of patient index data in the primary index database, as follows:
name: wangzaijie medicine
Sex: air conditioner
Mobile phone number: air conditioner
Date of birth: 31/12/1949
Identification number: 11010519491230002X
The number of the diagnosis card: air conditioner
Medical insurance account number: air conditioner
Case number: air conditioner
If the similarity between the patient index data and the identity card number in the registration data of the patient is extremely high through manual comparison, the identity card number in the patient index data is wrongly filled in through manual verification, at the moment, the two data are judged to belong to the same patient, therefore, the two data are merged according to the merging principle, and the wrong identity card number is covered by the correct identity card number.
If the similarity between the patient index data and the identity card number in the registration data of the patient is extremely high through manual comparison, the identity card number in the patient index data is correctly filled through manual verification, at the moment, the two data are judged to belong to the two patients respectively, and therefore the registration data is newly added into the main index database according to a new establishment principle to form new patient index data.
As shown in fig. 2, the invention also provides a method for constructing a matching combined knowledge base, which comprises the following steps:
step a, collecting patient data. Historical patient information data is collected in a plurality of business systems of a hospital, for example, 5 ten thousand pieces of patient data are collected at a time. Data are extracted from different systems, repeatability is high, and the method is convenient to use for matching tests.
And b, checking the correctness of each field in the patient data, and calculating the correctness of each field. For example: in 5 ten thousand pieces of collected data, 4.9 thousands of correct name data exist, and the correct rate of the name field is 98%; the native field has a large number of null values and many wrong data types, such as numbers, english letters, etc., and the accuracy is low.
And c, setting a weight value, a first threshold and a second threshold of each field according to the accuracy of each field. And assigning a higher weight value to the field with the unique identifier, and otherwise, assigning a lower weight value.
And d, counting the first field combination and the second field combination. The first field combination is a combination of all fields of a minimum number whose sum of weight values exceeds a first threshold, and the second field combination is a combination of all fields of a minimum number whose sum of weight values exceeds a second threshold but does not exceed the first threshold.
And e, performing matching test by using the patient data to obtain a test result. The method comprises the following steps:
and e1, performing similarity matching on the patient data and the patient index data in the main index database one by one, and determining an input mode according to a matching result. More specifically, the steps include:
and e11, using the first field combination as a query condition to query whether consistent main index data exists in the main index database, if so, turning to the step e13, otherwise, turning to the step e2.
And e12, using the second field combination as a query condition to query whether consistent main index data exists in the main index database, if so, turning to the step e14, otherwise, turning to the step e15.
Step e13, inputting the patient data into a main index database in an automatic merging mode;
step e14, inputting the patient data into the main index database by adopting a manual input mode; the manual mode is manual combination or manual new construction.
And e15, inputting the patient data into the main index database by adopting an automatic new establishment mode.
And e2, checking whether the patient index data in the main index database after passing the e1 is reasonable, if so, turning to the step e3, otherwise, turning to the step c.
And e3, judging whether the testing times reach preset times, if so, outputting a testing result and turning to the step f, otherwise, turning to the step a.
And f, judging whether the testing times reach preset times, if so, outputting a testing result and turning to the step g, otherwise, turning to the step a. The test result comprises the weight value of each field, a first threshold value, a second threshold value, a first field combination and a second field combination. In this example, the predetermined number of times is 5 times. The test results obtained after the test are as follows:
the weight values for each field are shown in the following table:
the first threshold is 99 and the second threshold is 49.
The first field combination is shown in the following table:
the second field combination is shown in the following table:
and g, constructing a matching combined knowledge base according to the test result.
The invention also provides a patient main index data generation system, which comprises: the system comprises a registration module, a verification module, a matching module, a merging module, a newly-built module and a manual module.
The registration module is used for acquiring registration data of the patient. The verification module is used for verifying whether the registration data is in compliance or not, and activating the matching module if the registration data is in compliance. The matching module is used for performing similarity matching query in the main index database according to the registration data, activating the merging module if a query result meets an automatic merging condition, activating the newly-built module if the query result meets an automatic newly-built condition, and activating the manual module if the query result meets a manual processing condition. The merging module is used for merging the registration data and the corresponding patient index data and covering the difference part of the registration data with the corresponding part of the patient index data. And the newly-built module is used for creating the registration data into new patient index data and storing the new patient index data into the main index database. The manual module is used for providing a manual processing interface.
Wherein, the matching module further comprises: a first match submodule and a second match submodule.
The first matching submodule is used for taking the first field combination as a query condition, judging whether consistent main index data exists in the main index database, if so, meeting an automatic merging condition, and otherwise, activating the second matching submodule; the first field combination is a combination of all fields of a minimum number of which the sum of the weight values exceeds a first threshold, and the weight value, the first threshold and the first field combination are preset in the matching combination knowledge base.
The second matching sub-module is used for judging whether consistent main index data exists in the main index database or not by taking the second field combination as a query condition, if so, the manual processing condition is met, and otherwise, the automatic new-building condition is met; the second field combination is a combination of all fields with minimum number, wherein the sum of the weighted values exceeds a second threshold value but does not exceed the first threshold value, and the second threshold value and the second field combination are preset in the matching combination knowledge base.
The matched combined knowledge base is constructed through a knowledge base system, and the knowledge base system comprises: the device comprises an acquisition module, a calculation module, a setting module, a statistic module, a test module and a construction module.
The acquisition module is used for acquiring patient data. The calculation module is used for checking the correctness of each field in the patient data and calculating the correctness of each field. The setting module is used for setting the weight value, the first threshold and the second threshold of each field according to the accuracy of each field. The statistic module is used for counting the first field combination and the second field combination. The testing module is used for performing matching test by using the patient data to obtain a testing result, and the testing result comprises a weight value, a first threshold value, a second threshold value, a first field combination and a second field combination of each field. And the construction module is used for constructing a matching combined knowledge base according to the test result.
The invention also provides a patient main index data generation device which comprises a processor and a memory, wherein the memory stores a computer program, and the processor realizes the steps of the method when executing the computer program.
The invention is not described in detail, but is well known to those skilled in the art.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method for generating patient primary index data, comprising: the method comprises the following steps:
step 1, acquiring registration data of a patient;
step 2, verifying whether the registered data is in compliance, and turning to step 3 if the registered data is in compliance;
step 3, performing similarity matching query in a main index library according to the registration data, turning to step 4 if a query result meets an automatic merging condition, turning to step 5 if an automatic newly-built condition is met, and turning to step 6 if a manual processing condition is met;
step 4, combining the registration data with corresponding patient index data, and covering the difference part of the registration data with the part corresponding to the patient index data;
step 5, establishing the registration data as new patient index data and storing the new patient index data in a main index database;
and 6, providing a manual processing interface.
2. The method of claim 1, wherein the patient primary index data generation method comprises: the step 2 comprises the following steps:
if the mandatory item in the registration data is a null value, judging that the mandatory item is not in compliance, generating a record and notifying a data source party;
if the data type of the necessary item in the registered data has an error type, judging that the data is not in compliance, and if other fields have error types, clearing, recording the operation and retaining the original data, and allowing the subsequent steps to be carried out;
if the identity card number in the registration data is not compliant, judging that the identity card number is not compliant, generating a record and notifying a data source party;
and clearing the mobile phone number in the registration data if the mobile phone number is not verified, recording the operation, retaining the original data and allowing the subsequent steps to be carried out.
3. The method of claim 1, wherein the patient primary index data generation method comprises: the step 3 comprises the following steps:
step 31, taking the first field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting an automatic merging condition, otherwise, turning to step 32; the first field combination is the combination of all fields with the minimum number of weighted values exceeding a first threshold, and the weighted values, the first threshold and the first field combination are preset in a matching combination knowledge base;
step 32, taking the second field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting a manual processing condition, otherwise, meeting an automatic new condition; the second field combination is a combination of all fields with a minimum number of weighted values exceeding a second threshold value but not exceeding the first threshold value, and the second threshold value and the second field combination are preset in a matching combination knowledge base.
4. A method of generating patient master index data according to claim 3, wherein: the matching combined knowledge base is constructed by the following steps:
step a, collecting patient data;
b, checking the correctness of each field in the patient data, and calculating the correctness of each field;
step c, setting a weight value, a first threshold value and a second threshold value of each field according to the accuracy of each field;
step d, counting the first field combination and the second field combination; the first field combination is a combination of all fields with a minimum number that the sum of the weight values exceeds a first threshold, and the second field combination is a combination of all fields with a minimum number that the sum of the weight values exceeds a second threshold but does not exceed the first threshold;
step e, carrying out matching test by using the patient data to obtain a test result, wherein the test result comprises a weight value, a first threshold value, a second threshold value, a first field combination and a second field combination of each field;
and f, constructing a matching combined knowledge base according to the test result.
5. A method of generating patient master index data according to claim 4, wherein: the step e comprises the following steps:
e1, performing similarity matching on the patient data and the patient index data in a main index database one by one, and determining an input mode according to a matching result;
step e2, checking whether the patient index data in the main index database after passing the step e1 is reasonable, if so, turning to the step e3, otherwise, turning to the step c;
and e3, judging whether the testing times reach preset times, if so, outputting a testing result and turning to the step f, otherwise, turning to the step a.
6. The method of claim 5, wherein: the e1 comprises the following steps:
step e11, using the first field combination as a query condition to query whether consistent main index data exists in a main index database, if so, turning to the step e13, otherwise, turning to the step e2;
step e12, using the second field combination as a query condition to query whether consistent main index data exists in a main index database, if so, turning to the step e14, otherwise, turning to the step e15;
step e13, inputting the patient data into a main index database in an automatic merging mode;
step e14, inputting the patient data into a main index database in a manual input mode; the manual mode is manual combination or manual new construction;
and e15, inputting the patient data into the main index database by adopting an automatic new establishment mode.
7. A patient primary index data generation system, characterized by: the method comprises the following steps:
the registration module is used for acquiring registration data of the patient;
the verification module is used for verifying whether the registration data is in compliance or not, and activating the matching module if the registration data is in compliance;
the matching module is used for performing similarity matching query in the main index library according to the registration data, activating the merging module if a query result meets an automatic merging condition, activating the newly-built module if the query result meets an automatic newly-built condition, and activating the manual module if the query result meets a manual processing condition;
a merging module, configured to merge the registration data with corresponding patient index data, and overlay a difference portion of the registration data with a portion corresponding to the patient index data;
the newly-built module is used for creating the registration data into new patient index data and storing the new patient index data into a main index database;
and the manual module is used for providing a manual processing interface.
8. A patient master index data generation system according to claim 7, wherein: the matching module includes:
the first matching submodule is used for taking the first field combination as a query condition, judging whether consistent main index data exists in a main index database, if so, meeting an automatic merging condition, and otherwise, activating a second matching submodule; the first field combination is the combination of all fields with the minimum number that the sum of the weight values exceeds a first threshold value, and the weight value, the first threshold value and the first field combination are preset in a matching combination knowledge base;
the second matching sub-module is used for taking the second field combination as a query condition, judging whether consistent main index data exists in the main index database, if so, meeting manual processing conditions, and otherwise, meeting automatic new conditions; the second field combination is a combination of all fields with a minimum number of weighted values exceeding a second threshold value but not exceeding the first threshold value, and the second threshold value and the second field combination are preset in a matching combination knowledge base.
9. A patient master index data generation system according to claim 7, wherein: the matching combined knowledge base is constructed by a knowledge base system, and the knowledge base system comprises:
an acquisition module for acquiring patient data;
the calculation module is used for checking the correctness of each field in the patient data and calculating the correctness of each field;
the setting module is used for setting the weight value, the first threshold and the second threshold of each field according to the accuracy of each field;
the statistical module is used for counting the first field combination and the second field combination;
the testing module is used for performing matching test by using the patient data to obtain a testing result, and the testing result comprises a weight value, a first threshold value, a second threshold value, a first field combination and a second field combination of each field;
and the construction module is used for constructing a matching combined knowledge base according to the test result.
10. A patient primary index data generation apparatus, characterized in that: comprising a processor and a memory, said memory storing a computer program, said processor realizing the steps of the method as claimed in claim 1 when executing the computer program.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117851411A (en) * | 2024-03-05 | 2024-04-09 | 北方健康医疗大数据科技有限公司 | Patient main index generation method and system |
| CN117851411B (en) * | 2024-03-05 | 2024-05-10 | 北方健康医疗大数据科技有限公司 | Patient main index generation method and system |
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