CN112786206A - Data processing method and system for information standardization of medical institution - Google Patents
Data processing method and system for information standardization of medical institution Download PDFInfo
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Abstract
The scheme acquires service data to be matched of a medical institution and constructs a source dictionary; importing the target value domain dictionary into a cache, and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key; determining service data which are completely matched with the target value domain dictionary in the source dictionary, and storing the contrast relation; comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity, and storing the comparison relation; and realizing the standardization processing of the medical institution data according to the obtained comparison relationship.
Description
Technical Field
The disclosure belongs to the technical field of medical information, and particularly relates to a data processing method and system for information standardization of medical institutions.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In order to implement the national strategy of 'internet + medical health', each committee encourages hospitals at all levels to strengthen informatization and digitization construction, and firstly, interconnection and intercommunication of information systems in the hospitals, such as an integration platform, are achieved; and the other is interconnection and intercommunication among medical institutions in the region, such as a hospital. An important item in interconnection and interworking is standardization, and an important part is to complete comparison of value ranges so as to complete standard docking.
The inventor finds that in the current medical data interconnection process, the comparison mode mainly used is that each source value range is compared with all target value ranges in a traversing mode, the character strings with the highest similarity are taken for comparison display, and a comparison relation table of value range codes is formed by one-to-one comparison, so that the corresponding relation between the source value range and the target value range is determined for subsequent use. For the data volume of the value domain dictionary, the number of the data volume can exceed tens of thousands or even hundreds of thousands, the speed of circulating is extremely low, the time consumption is long, the response speed is low, the user experience is poor, and the matching efficiency is low; meanwhile, the matching result may not be the most correct matching degree in the aspect of service and is easy to deviate due to simple field string similarity matching, namely, the similarity of some character strings is higher and the actual meanings are different; however, to identify such problems, the requirements on the medical service level of the operator are high, the matching efficiency is low, and errors are prone to occur.
Disclosure of Invention
In order to solve the above problems, the present disclosure provides a data processing method and system for information standardization of a medical institution.
According to a first aspect of embodiments of the present disclosure, there is provided a data processing method for medical institution information standardization, including:
acquiring service data to be matched of a medical institution and constructing a source dictionary;
importing the target value domain dictionary into a cache, and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key;
determining service data which are completely matched with the target value domain dictionary in the source dictionary, and storing the contrast relation;
comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity, and storing the comparison relation;
and realizing the standardization processing of the medical institution data according to the obtained comparison relationship.
Further, the specific step of storing the data in the target value domain dictionary through the tree structure is as follows:
initializing a root node by default;
calculating the service criticality of the data in the target value domain dictionary and sequencing the data from large to small;
selecting a preset amount of data in the front of the sequence as a second-level node;
and storing the nodes according to the sequence of the service criticality which is reduced in sequence, and storing the target value domain data in a cache according to a tree structure.
Furthermore, the business criticality is determined by an expert evaluation method, the number of information contained in the business data and the importance degree of the contained information are scored, and the sum of the scores of the business data and the information is calculated to serve as a value of the business criticality.
Further, the service data completely matched with the target value domain dictionary in the source dictionary is determined, the processing process of the service data is directly compared with the target value domain dictionary stored in the database, and the data completely matched with the target value domain dictionary in the source dictionary is determined;
or
And comparing the data with the target value range dictionary in the cache to determine the completely matched data in the source dictionary and the target value range dictionary.
Furthermore, the business data which cannot be completely matched is compared with target value range data stored in a tree structure in a cache one by one, the matching result with the highest similarity is displayed, in consideration of the situation that the matching result with the highest similarity has mismatching, an operator is additionally provided for manually comparing the displayed matching result and checking the result, and the confirmed comparison relation is stored.
Further, in order to coordinate the relationship between the accuracy of the matching result and the matching efficiency, the manual comparison and the result check are controlled by setting a similarity threshold, and the manual comparison and the result check are performed only when the highest similarity of the matching result is lower than the similarity threshold.
Further, the business data includes names of departments of organizations, names of medical resources, and names of medical services.
According to a second aspect of the embodiments of the present disclosure, there is provided a data processing system for medical institution information standardization, comprising:
the data acquisition module is used for acquiring service data to be matched of the medical institution and constructing a source dictionary;
the target value domain dictionary storage module is used for leading the target value domain dictionary into a cache and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key;
the complete matching module is used for determining the service data which is completely matched with the target value domain dictionary in the source dictionary and storing the contrast relation;
the incomplete matching module is used for comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity and storing the comparison relation;
and the standardization processing module is used for realizing the standardization processing of the medical institution data according to the acquired contrast relationship.
According to a third aspect of the embodiments of the present disclosure, there is provided an electronic device, comprising a memory, a processor and a computer program stored in the memory for execution, wherein the processor implements the data processing method for information standardization of a medical institution when executing the program.
According to a fourth aspect of the embodiments of the present disclosure, there is provided a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the data processing method for medical institution information standardization.
Compared with the prior art, the beneficial effect of this disclosure is:
according to the scheme disclosed by the invention, the target value range data is put into a cache in advance, so that the interaction of the database is reduced, and the query efficiency is improved; when traversing value range matching, the traversal times are less, the time consumption for matching a certain number of source dictionary value ranges can be reduced to one half or even one tenth of the original time, the matching response is fast, and the value range comparison efficiency is improved. When the matching cannot be completed and needs to be selected from a plurality of value range options with higher similarity, the requirement on value range comparison implementing personnel is reduced and the matching accuracy is improved according to the tree structure of the importance of the matching field.
Advantages of additional aspects of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
FIG. 1 is a schematic diagram of a tree structure of target value range dictionary data according to a first embodiment of the present disclosure;
fig. 2 is a flowchart of a data processing method according to a first embodiment of the disclosure.
Detailed Description
The present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The first embodiment is as follows:
the embodiment aims to provide a data processing method for information standardization of a medical institution.
A data processing method for medical institution information standardization, comprising:
acquiring service data to be matched of a medical institution and constructing a source dictionary;
importing the target value domain dictionary into a cache, and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key;
determining service data which are completely matched with the target value domain dictionary in the source dictionary, and storing the contrast relation;
comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity, and storing the comparison relation;
and realizing the standardization processing of the medical institution data according to the obtained comparison relationship.
The business data comprises department names, medical resource names and medical service names of organizations.
Furthermore, the business criticality is determined by an expert evaluation method, the number of information contained in the business data and the importance degree of the contained information are scored, and the sum of the scores of the business data and the information is calculated to serve as a value of the business criticality; specifically, the judgment of the main technician in advance mainly includes two aspects, namely, the amount of information contained, such as comparison of the operation value range, "operation name" includes more information than "operation level," and the information contained in "operation level" is insufficient as a key condition for judgment, so that the "operation name" is more critical. The second is the importance of the contained information, such as drug value range contrast, different dosage forms can be judged as different value ranges, the number of the types of the dosage forms is less, the retrieval times in the tree structure can be reduced, and the business key of the dosage forms is higher.
Specifically, for ease of understanding, the schemes described in the present disclosure are described in detail below by specific examples:
(1) in value range matching, the target value range dictionary is a standard set, data basically cannot change, and the target value range dictionary is imported by a program and is placed into a cache. When a simple match request is generated, the database is no longer accessed to query the target dictionary, but is fetched in cache for traversal. Therefore, the interaction times with the database can be reduced, the pressure of the database is relieved, and the response speed of the system is improved, so that the efficiency of value range matching is improved.
(2) When a target value domain is placed into a cache, an original dictionary list is converted into a tree structure to be stored, a root node is initialized by default, a field with high business criticality is selected as a second-level node, if the content of the field is totally divided into 3 types, if the medicine dosage form is divided into tablets, injection and capsules, 3 second-level nodes exist under the root node, then the business criticality of the nodes is sequentially reduced, the leaf nodes on the last layer are the lowest business criticality, and original target value domain data are formed into a tree structure in the cache according to the importance.
(3) The matching is carried out through complete matching, namely, automatic matching is carried out on all matching items which are 100% identical, a cache is not needed in the matching process, matching can be achieved through comparison in a database (the matching can also be carried out with a target value domain dictionary in the cache, and data which are completely matched with the target value domain dictionary in a source dictionary are determined), the comparison relation can be stored after the comparison is finished, the operation is relevant to the improvement degree of the matching work efficiency and the quality of dictionary data, the complete matching items are firstly picked out, and the matching efficiency can be obviously improved for most value domain comparison work.
(4) And (3) matching value ranges which cannot be completely matched in batches, comparing each piece of the source dictionary with the tree-shaped data in the cache, such as matching 200 pieces at one time, starting to compare the two-level nodes of the tree-shaped data in the cache during comparison, entering a node branch of a tablet if the medicine dosage form of the source field data is the tablet, sequentially comparing the two nodes downwards, displaying the final matching result with the highest similarity, and facilitating comparison and result confirmation by an implementer. The method can greatly reduce the traversal times when the single source table dictionary is matched, does not need to traverse all the target standard sets every time, and greatly shortens the matching response time.
Further, in order to coordinate the relationship between the accuracy of the matching result and the matching efficiency, the manual comparison and the result check are controlled by setting a similarity threshold, and the manual comparison and the result check are performed only when the highest similarity of the matching result is lower than the similarity threshold.
(5) If the nodes which cannot be completely matched appear due to the data quality, the tree node with the highest similarity can be selected by default to be executed downwards, and the pull-down box search and selection can also be implemented to trigger the matching query.
Further, the solution of the present disclosure fully considers the following problems, and gives a corresponding solution to the problems:
(1) the target value domain dictionary is large in data volume, few data is thousands of data, most data is hundreds of thousands of data, the original full-scale circulation traversal comparison is very time-consuming, when in matching, an operator is always in a waiting response state, and the matching efficiency is low.
According to the scheme, the target value range data are analyzed in advance by adopting the tree structure, the traversal comparison times are greatly reduced, the response is quick, and the value range matching efficiency is improved.
(2) Simple character string similarity contrast is relatively rough and open in matching effect, the item with the highest matching degree may have deviation from the actual business relationship, even the term "south beam northern rut" is understood, the workload of analysis and determination of an operator is large, and time is consumed and mistakes are easily made.
The scheme disclosed by the invention adopts the technical scheme that the target value domain is processed in advance, the tree graph is built from top to bottom according to the weight of the business key degree, the comparison of the key fields is ensured not to be wrong, the similar matching result set is well checked, and the error rate in the matching process is reduced.
Example two:
an object of the present embodiment is to provide a data processing system for information standardization of medical institutions.
A data processing system for medical facility information standardization, comprising:
the data acquisition module is used for acquiring service data to be matched of the medical institution and constructing a source dictionary;
the target value domain dictionary storage module is used for leading the target value domain dictionary into a cache and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key;
the complete matching module is used for determining the service data which is completely matched with the target value domain dictionary in the source dictionary and storing the contrast relation;
the incomplete matching module is used for comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity and storing the comparison relation;
and the standardization processing module is used for realizing the standardization processing of the medical institution data according to the acquired contrast relationship.
In further embodiments, there is also provided:
an electronic device comprising a memory and a processor, and computer instructions stored on the memory and executed on the processor, the computer instructions when executed by the processor performing the method of embodiment one. For brevity, no further description is provided herein.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits AS ic, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory, and may provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
A computer readable storage medium storing computer instructions which, when executed by a processor, perform the method of embodiment one.
The method in the first embodiment may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, among other storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
Those of ordinary skill in the art will appreciate that the various illustrative elements, i.e., algorithm steps, described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The data processing method and the data processing system for information standardization of the medical institution, which are provided by the embodiment, can be realized, and have wide application prospects.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.
Claims (10)
1. A data processing method for medical institution information standardization, comprising:
acquiring service data to be matched of a medical institution and constructing a source dictionary;
importing the target value domain dictionary into a cache, and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key;
determining service data which are completely matched with the target value domain dictionary in the source dictionary, and storing the contrast relation;
comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity, and storing the comparison relation;
and realizing the standardization processing of the medical institution data according to the obtained comparison relationship.
2. The data processing method for information standardization of medical institutions according to claim 1, wherein the step of storing the data in the target value range dictionary in a tree structure comprises the following specific steps:
initializing a root node by default;
calculating the service criticality of the data in the target value domain dictionary and sequencing the data from large to small;
selecting a preset amount of data in the front of the sequence as a second-level node;
and storing the nodes according to the sequence of the service criticality which is reduced in sequence, and storing the target value domain data in a cache according to a tree structure.
3. The data processing method for the information standardization of the medical institution as claimed in claim 1, wherein the business criticality is determined by an expert assessment method, and the sum of the scores of the business data containing the information and the importance degree of the contained information is calculated as the value of the business criticality.
4. The data processing method for information standardization of medical institutions according to claim 1, wherein the business data in the source dictionary which are completely matched with the business data in the target value range dictionary are determined, and the processing procedure of the business data in the source dictionary which are completely matched with the business data in the target value range dictionary is directly compared with the target value range dictionary stored in the database, so that the data in the source dictionary which are completely matched with the target value range dictionary are determined;
or
And comparing the data with the target value range dictionary in the cache to determine the completely matched data in the source dictionary and the target value range dictionary.
5. The data processing method for information standardization of medical institutions according to claim 1, wherein the business data which cannot be completely matched are compared with the target value range data stored in the tree structure in the cache one by one, the matching result with the highest similarity is displayed, and in consideration of the fact that the matching result with the highest similarity is mismatched, an operator is additionally provided to manually compare and check the displayed matching result, and the confirmed comparison relationship is stored.
6. The data processing method for medical institution information standardization of claim 5, wherein the manual alignment and result collation is controlled by setting a similarity threshold value in order to harmonize the relationship between the matching result accuracy and the matching efficiency, and the manual alignment and result collation is performed only when the highest similarity of the matching results is lower than the similarity threshold value.
7. The data processing method for medical institution information standardization of claim 1, wherein the business data includes an institution department name, a medical resource name, a medical service name.
8. A data processing system for medical facility information standardization, comprising:
the data acquisition module is used for acquiring service data to be matched of the medical institution and constructing a source dictionary;
the target value domain dictionary storage module is used for leading the target value domain dictionary into a cache and storing data in the target value domain dictionary through a tree structure; the tree structure stores nodes according to the service key, and the last layer of leaf nodes have the lowest service key;
the complete matching module is used for determining the service data which is completely matched with the target value domain dictionary in the source dictionary and storing the contrast relation;
the incomplete matching module is used for comparing the business data which cannot be completely matched with target value range data stored in a tree structure in a cache one by one, displaying a matching result with the highest similarity and storing the comparison relation;
and the standardization processing module is used for realizing the standardization processing of the medical institution data according to the acquired contrast relationship.
9. An electronic device comprising a memory, a processor and a computer program stored for execution on the memory, wherein the processor when executing the program implements a data processing method for medical institution information standardization as claimed in any of claims 1-7.
10. A non-transitory computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing a data processing method for medical institution information standardization as claimed in any one of claims 1 to 7.
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