CN111986750B - Structural detection method for electronic medical record template - Google Patents
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Abstract
The embodiment of the invention relates to a method for detecting the structuring of an electronic medical record template, which comprises the following steps: acquiring electronic medical record template data and an electronic medical record basic data set; carrying out structured data detection marking processing on information element data of the electronic medical record template data by using basic data of the electronic medical record basic data set; calculating to obtain the percentage of the structured information elements, and extracting an unstructured information element data list; and when the percentage of the structured information elements is not less than the threshold value of the percentage of the structured information elements, the structural detection return state of the electronic medical record template is successful in execution, and the structural detection return data of the electronic medical record template is generated by the total number of the structured data, the percentage of the structured information elements and the unstructured information element data list. According to the embodiment of the invention, through structural detection of the electronic medical record template, workers do not need to rework after the electronic medical record is written, so that the working difficulty is reduced, and the working efficiency is improved.
Description
Technical Field
The invention relates to the technical field of data information processing, in particular to a method for detecting the structuring of an electronic medical record template.
Background
The electronic medical record system (Electronic Medical Record System, EMRS) is one of the core information systems of the medical institutions, each medical institution uses the EMRS to select information elements related to the detection diagnosis and treatment process to establish a corresponding electronic medical record template, and the corresponding electronic medical record writing is completed based on the electronic medical record template. The information elements of the electronic medical record are shared in each department in the same medical institution, so that the internal working efficiency can be improved, and the medical experience of a patient can be improved; sharing is realized in different medical institutions, so that the medical expense of patients can be reduced, and the diagnosis and treatment efficiency of the patients can be improved. In actual operation, in order to ensure the integrity of the shared information element, the structured detection of the written electronic medical record is required according to the basic data set of the electronic medical record agreed between departments or institutions.
The current structured detection method is that after a medical institution worker completes the setting of an electronic medical record template and the filling of the electronic medical record, the electronic medical record is subjected to structured detection according to an electronic medical record basic data set, and when the fact that information elements are missing in the electronic medical record is found, the worker is required to reset the electronic medical record template and refill electronic medical record information, so that the information input difficulty of the worker can be increased, and the working efficiency of the worker is reduced.
Disclosure of Invention
The invention aims at overcoming the defects of the prior art and provides a structured detection method for an electronic medical record template, a computer program product and a computer readable storage medium, wherein by carrying out structured detection on the electronic medical record template, workers do not need to carry out repeated work due to the structured detection after writing the electronic medical record, so that the information input difficulty of the workers is reduced, and the working efficiency of the workers is improved; and outputting the percentage of the structured information elements which are in line with the electronic medical record basic data set and the unstructured information element data list which is beyond the electronic medical record basic data set after the detection is successful, and further refining the structured detection result.
To achieve the above object, a first aspect of an embodiment of the present invention provides a method for detecting a structure of an electronic medical record template, where the method includes:
acquiring electronic medical record template data; the electronic medical record template data comprises a plurality of information element data;
acquiring an electronic medical record basic data set corresponding to the electronic medical record template data; the electronic medical record basic data set comprises a plurality of basic data;
carrying out structured data detection marking processing on the information element data by using the basic data to obtain a plurality of marked information element data marked as structured data;
counting the quantity of the basic data included in the electronic medical record basic data set to generate a total quantity of the basic data; counting the number of the marking information element data included in the electronic medical record template data to generate the total structured data;
generating a structured information element percentage according to the ratio of the total structured data to the total basic data;
extracting all the information element data which are not marked as the structured data from the electronic medical record template data to form an unstructured information element data list;
when the percentage of the structuring information elements is not smaller than the threshold value of the structuring percentage, the structuring detection return state of the electronic medical record template is successful in execution; and generating the structured detection return data of the electronic medical record template by the total structured data, the structured information element percentage and the unstructured information element data list.
Preferably, the performing structured data detection marking processing on the information element data by using the basic data to obtain a plurality of marked information element data marked as structured data specifically includes:
sequentially acquiring the information element data of the electronic medical record template data as current information element data;
and sequentially using the basic data of the electronic medical record basic data set to compare the current information element data, when the basic data for comparison is matched with the current information element data, using the information element data corresponding to the current information element data as the marking information element data, and marking the marking information element data as the structured data.
Preferably, when the structured information element percentage is less than the structured percentage threshold; the structural detection return state of the electronic medical record template is failure execution; and generating the structured detection return data of the electronic medical record template by the total structured data and the structured information element percentage.
A second aspect of an embodiment of the present invention provides a computer program product comprising computer program code which, when executed by a computer, causes the computer to perform the method of the first aspect described above.
A third aspect of the embodiments of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the instructions of the method of the first aspect.
According to the electronic medical record template structured detection method, the computer program product and the computer readable storage medium, the structured detection is carried out on the electronic medical record template, so that workers do not need to carry out repeated work due to the structured detection after the electronic medical record is written, the information input difficulty of the workers is reduced, and the working efficiency of the workers is improved; and after the detection is successful, outputting the percentage of the structured information elements which are in line with the electronic medical record basic data set and the unstructured information element data list which is beyond the electronic medical record basic data set, and further refining the structured detection result.
Drawings
Fig. 1 is a schematic diagram of a method for detecting the structuring of an electronic medical record template according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
After a worker finishes setting an electronic medical record template through an EMRS (or other medical information system) or related equipment, the electronic medical record template structural detection method provided by the embodiment of the invention can be used for carrying out structural detection on the electronic medical record template: and obtaining the set electronic medical record template data, marking the information element data of the template data by using the basic data of the electronic medical record basic data set corresponding to the electronic medical record template data, counting the structured information element percentage of the template, and finally returning the corresponding electronic medical record template structured detection return state and the corresponding electronic medical record template structured detection return data according to the threshold range of the structured information element percentage. Then, the EMRS (or other medical information system) or related devices perform further processing operations (such as display of prompt information of success/failure of detection, display of structured data information, etc.) according to the structured detection return state of the electronic medical record template.
Or, when a worker performs structural detection on an electronic medical record (an electronic medical record stored locally or a shared electronic medical record obtained from other information systems) obtained by an EMRS (or other medical information systems) or related equipment, the structural detection method for an electronic medical record template provided by the embodiment of the invention may also be used for performing structural detection: before the step 1, obtaining corresponding electronic medical record template data by determining medical record template information of the electronic medical record; and starting from the step 1, carrying out structured data marking on the information element data of the electronic medical record template data by using the basic data of the electronic medical record basic data set corresponding to the electronic medical record template data, counting the structured information element percentage of the structured data, and finally returning the corresponding electronic medical record template structured detection return state and the corresponding electronic medical record template structured detection return data according to the threshold range of the structured information element percentage. Then, the EMRS (or other medical information system) or related devices perform further processing operations (such as display of prompt information of success/failure of detection, display of structured data information, etc.) according to the structured detection return state of the electronic medical record template.
As shown in fig. 1, which is a schematic diagram of a method for detecting the structuring of an electronic medical record template according to an embodiment of the present invention, the method mainly includes the following steps:
step 1, acquiring electronic medical record template data;
wherein the electronic medical record template data comprises a plurality of information element data.
Specifically, after a worker finishes setting an electronic medical record template through an EMRS (or other medical information systems) or related equipment, reading the set electronic medical record template from a storage medium of the EMRS (or other medical information systems) or related equipment to obtain electronic medical record template data; for example, the electronic medical record template after completion of setting is specifically "transfer record template", the specific information element data included in the electronic medical record template data obtained in step 1 is shown in table one, where the electronic medical record template data of "transfer record template" includes 8 information element data: document identification, service object identification, demographic information collection (including name, gender, age, etc.), health service organization, health server, records of diagnosis and treatment process, allergic medicine history and special area epidemic history.
In particular, when a worker performs structural detection on an electronic medical record (a local electronic medical record or a shared electronic medical record obtained from other information systems) obtained by an EMRS (or other medical information systems) or related equipment, a corresponding electronic medical record template is obtained by determining medical record template information of the electronic medical record, and then corresponding electronic medical record template data is obtained. For example, the obtained electronic medical record is specifically shown in the table two of the Zhang Sanzhuan Hospital record, and because the medical record template information of the Zhang Sanzhuan Hospital record is specifically shown in the table two of the transfer record template, the electronic medical record template data obtained according to the electronic medical record of the table two and the specific information element data included in the electronic medical record template data are also shown in the table one.
List one
Watch II
Step 2, acquiring an electronic medical record basic data set corresponding to the electronic medical record template data;
the electronic medical record basic data set comprises a plurality of basic data.
Specifically, an electronic medical record base data set corresponding to the electronic medical record template data is obtained from a storage medium of an EMRS (or other medical information system) or related equipment.
The electronic medical record basic data set corresponding to the electronic medical record template data is a set of shared information element data appointed in advance when the electronic medical record information element data is shared among different departments or different medical institutions in the same medical institution, the data sets are distinguished according to the classification of the electronic medical record template, and each type of electronic medical record template data has the corresponding electronic medical record basic data set.
For example, the electronic medical record basic data set corresponding to the "transfer record template" acquired from the storage medium of the EMRS (or other medical information system) or the related devices is specifically "transfer basic data set", as shown in table three; wherein, the transfer basic data set comprises 6 basic data (shared information element data): document identification, service object identification, demographic information collection (including name, gender, age, etc.), health service institutions, health servers, and records of medical procedures.
Watch III
Step 3, carrying out structured data detection marking processing on the information element data by using the basic data to obtain a plurality of marked information element data marked as structured data;
the method specifically comprises the following steps: sequentially acquiring information element data of the electronic medical record template data as current information element data;
and sequentially using the basic data of the electronic medical record basic data set, comparing the current information element data, and when the basic data for comparison is matched with the current information element data, taking the information element data corresponding to the current information element data as marked information element data and marking the marked information element data as structured data.
The method for detecting the information element data in the electronic medical record template data sequentially checks whether each information element data is included in the electronic medical record basic data set, and if so, the information element data is described as structured data and is regarded as marked information element data. Structured data herein refers to data that conforms to the shared data structure of an electronic medical record.
For example, the electronic medical record template data is shown in a first table, the electronic medical record basic data set is shown in a third table, and the structured data in the electronic medical record template data marks the result, as shown in a fourth table; the information element data 1-6 are respectively matched with the basic data 1-6 in the electronic medical record basic data set, so that the information element data are marked as structured data; the information element data 7 and 8 do not find matches in the underlying data in the electronic medical record underlying data set and are therefore not marked as structured data. Finally, 6 pieces of flag information element data (information element data 1 to 6) are obtained.
Table four
Step 4, counting the quantity of the basic data included in the electronic medical record basic data set, and generating the total quantity of the basic data; and counting the number of the marking information element data included in the electronic medical record template data to generate the total structured data.
The total structured data is the total information element data which accords with the corresponding electronic medical record basic data set in the acquired electronic medical record template data.
For example, the electronic medical record template data is shown in table one, the electronic medical record basic data set is shown in table three, the structured data marks in the electronic medical record template data are shown in table four, and then the total number of the basic data is 6, and the total number of the structured data is 6.
And 5, generating the structured information element percentage according to the ratio of the total structured data to the total basic data.
Specifically, the structured information element percentage= (structured data total/base data total) ×100%.
For example, the electronic medical record template data is shown in table one, the electronic medical record basic data set is shown in table three, the structured data marks in the electronic medical record template data are shown in table four, the total number of the basic data is 6, and the total number of the structured data is 6, so that the percentage of the structured information elements is= (6/6) ×100% = 100%. The electronic medical record template data comprises basic data for sharing, which are required in all electronic medical record basic data sets.
And 6, extracting all the information element data which are not marked as structured data from the electronic medical record template data to form an unstructured information element data list.
For example, if the electronic medical record template data is shown in table one, the electronic medical record basic data set is shown in table three, and the structured data marks in the electronic medical record template data are shown in table four, the unstructured information element data list specifically includes two information element data: allergic medication history and history of specific regional disease, as shown in table five.
TABLE five
And 7, judging whether the structured information element percentage is smaller than a structured percentage threshold, switching to the step 8 when the structured information element percentage is not smaller than the structured percentage threshold, and switching to the step 9 when the structured information element percentage is smaller than the structured percentage threshold.
Here, the structuring percentage threshold is a basic threshold used for judging whether the structuring detection is successful, when the structuring information element percentage is not less than the structuring percentage threshold, it is indicated that the electronic medical record template data meets the requirement, and the electronic medical record written based on the electronic medical record template data can be provided for sharing information receivers (EMRS or other information systems or related devices of other departments or different institutions in the same institution) for medical information sharing, and the next step should be transferred to the process flow of executing the structuring detection success in step 8; conversely, when the percentage of the structured information elements is lower than the threshold of the percentage of the structured information elements, it is indicated that the total number of the information element data available for sharing the electronic medical record in the currently detected electronic medical record template data is too low, which may cause that the sharing information receiver (the EMRS or other information systems or related devices of other departments or different institutions in the same institution) cannot extract enough information element data from the electronic medical record written based on the electronic medical record template data for diagnosis and treatment, and the next step should go to step 9 to execute the processing flow of the failure of the structured detection.
For example, the electronic medical record template data is shown in table one, the electronic medical record basic data set is shown in table three, the percentage of the structured information elements obtained through the steps 1 to 6 is 100%, the threshold of the structured percentage is 90%, if the percentage of the structured information elements is greater than the threshold of the structured percentage, the step 8 should be shifted to; for another example, the electronic medical record template data is shown in a sixth table, the electronic medical record basic data set is shown in a third table, and the percentages of the structured information elements obtained through the steps 1 to 6 are as follows: (2/6) 100% ≡33.33%, where the structuring percentage threshold is 90%, the structuring information element percentage is smaller than the structuring percentage threshold, and go to step 9.
TABLE six
Step 8, the structural detection of the electronic medical record template returns to the state that the execution is successful; generating the structured detection return data of the electronic medical record template by the total structured data, the structured information element percentage and the unstructured information element data list; turning to step 10.
Here, the percentage of the structured information element is greater than or equal to the threshold of the structured percentage, which indicates that the electronic medical record template data meets the requirements. The structured detection return status of the electronic medical record template should be set to be executed successfully for status feedback to the EMRS (or other medical information system) or related devices invoking the method; the total structured data, the percentage of structured information elements and the list of unstructured information elements should be combined into structured test return data of the electronic medical record template for feedback of test refinement data to the EMRS (or other medical information system) or related devices invoking the method.
Step 9, the structural detection return state of the electronic medical record template is the execution failure; generating the structured detection return data of the electronic medical record template according to the total structured data and the percentage of the structured information elements; turning to step 10.
Here, the percentage of the structured information elements is less than the threshold of the structured percentage, which indicates that the electronic medical record template data does not meet the requirements. The structured detection return status of the electronic medical record template should be set to be an execution failure for status feedback to the EMRS (or other medical information system) or related devices that invoke the method; the total number of structured data and the percentage of structured information elements should be combined into the electronic medical record template structured test return data for test refinement data feedback to the EMRS (or other medical information system) or related devices invoking the method.
And 10, carrying out data return processing on the electronic medical record template structured detection return state and the electronic medical record template structured detection return data.
The method is a processing procedure for carrying out state feedback on the electronic medical record template structural detection return state and data to the EMRS (or other medical information systems) or related equipment which call the method.
After receiving the detection return state of the electronic medical record template structure, which is concretely successful in execution, the EMRS (or other medical information systems) or related equipment can feed back detection success information to the staff and further allow the staff to create a corresponding electronic medical record through the template; meanwhile, visual prompt information such as graphics, tables and the like can be further made to staff according to the total number of the structured data and the percentage of the structured information elements, and richer personalized medical information element data can be obtained according to the unstructured information element data list.
After receiving the structural detection return state of the electronic medical record template, which is specifically the execution failure, the EMRS (or other medical information system) or related equipment can feed back detection failure information to the staff, and further does not allow the staff to create a corresponding electronic medical record through the template; meanwhile, visual prompt information such as a graph, a table and the like can be further made to staff according to the total structured data and the percentage of structured information elements.
It should be noted that, the present embodiment further provides a computer readable storage medium, where instructions are stored, when the instructions are executed on a computer, to cause the computer to perform the steps and the processing procedures of the method provided by the embodiment of the present invention.
The embodiment of the present invention also provides a computer program product, which includes a computer program, where the computer program is stored in a storage medium, and at least one processor may read the computer program from the storage medium, where the at least one processor performs the steps and processes of the method provided by the embodiment of the present invention.
According to the electronic medical record template structured detection method, the computer program product and the computer readable storage medium, the structured detection is carried out on the electronic medical record template, so that workers do not need to carry out repeated work due to the structured detection after writing the electronic medical record, the information input difficulty is reduced, and the working efficiency is improved; and outputting the percentage of the structured information elements which are in line with the electronic medical record basic data set and the unstructured information element data list which is beyond the electronic medical record basic data set after the detection is successful, so that the structured detection result is further refined.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of function in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. 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 invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (4)
1. The method for detecting the structuring of the electronic medical record template is characterized by comprising the following steps:
acquiring electronic medical record template data; the electronic medical record template data comprises a plurality of information element data;
acquiring an electronic medical record basic data set corresponding to the electronic medical record template data; the electronic medical record basic data set comprises a plurality of basic data;
carrying out structured data detection marking processing on the information element data by using the basic data to obtain a plurality of marked information element data marked as structured data;
counting the quantity of the basic data included in the electronic medical record basic data set to generate a total quantity of the basic data; counting the number of the marking information element data included in the electronic medical record template data to generate the total structured data;
generating a structured information element percentage according to the ratio of the total structured data to the total basic data;
extracting all the information element data which are not marked as the structured data from the electronic medical record template data to form an unstructured information element data list;
when the percentage of the structuring information elements is not smaller than the threshold value of the structuring percentage, the structuring detection return state of the electronic medical record template is successful in execution; and generating the structured detection return data of the electronic medical record template by the total structured data, the structured information element percentage and the unstructured information element data list.
2. The method for detecting the structuring of an electronic medical record template according to claim 1, wherein the step of performing structured data detection marking processing on the information element data by using the base data to obtain a plurality of marked information element data marked as structured data specifically comprises the steps of:
sequentially acquiring the information element data of the electronic medical record template data as current information element data;
and sequentially using the basic data of the electronic medical record basic data set to compare the current information element data, when the basic data for comparison is matched with the current information element data, using the information element data corresponding to the current information element data as the marking information element data, and marking the marking information element data as the structured data.
3. The electronic medical record template structured detection method of claim 1, wherein when the structured information element percentage is less than the structured percentage threshold;
the structural detection return state of the electronic medical record template is failure execution; and generating the structured detection return data of the electronic medical record template by the total structured data and the structured information element percentage.
4. A computer readable storage medium storing computer instructions which, when executed by a computer, cause the computer to perform the instructions of the method of any one of claims 1-3.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106383853A (en) * | 2016-08-30 | 2017-02-08 | 刘勇 | Realization method and system for electronic medical record post-structuring and auxiliary diagnosis |
| CN106682397A (en) * | 2016-12-09 | 2017-05-17 | 江西中科九峰智慧医疗科技有限公司 | Knowledge-based electronic medical record quality control method |
| CN107229831A (en) * | 2017-06-08 | 2017-10-03 | 成都深泉科技有限公司 | Electronic health record generation method, apparatus and system |
| JP2018077630A (en) * | 2016-11-08 | 2018-05-17 | キヤノン株式会社 | Structured data preparation device, control method thereof and computer program |
| CN110020660A (en) * | 2017-12-06 | 2019-07-16 | 埃森哲环球解决方案有限公司 | Use the integrity assessment of the unstructured process of artificial intelligence (AI) technology |
| CN110362829A (en) * | 2019-07-16 | 2019-10-22 | 北京百度网讯科技有限公司 | Method for evaluating quality, device and the equipment of structured patient record data |
| CN110504009A (en) * | 2018-05-16 | 2019-11-26 | 北京理工大学 | A kind of method of electronic health record structuring |
| CN110720101A (en) * | 2017-10-23 | 2020-01-21 | 谷歌有限责任公司 | Validating structured data |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11113418B2 (en) * | 2018-11-30 | 2021-09-07 | International Business Machines Corporation | De-identification of electronic medical records for continuous data development |
-
2020
- 2020-07-27 CN CN202010732488.2A patent/CN111986750B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106383853A (en) * | 2016-08-30 | 2017-02-08 | 刘勇 | Realization method and system for electronic medical record post-structuring and auxiliary diagnosis |
| JP2018077630A (en) * | 2016-11-08 | 2018-05-17 | キヤノン株式会社 | Structured data preparation device, control method thereof and computer program |
| CN106682397A (en) * | 2016-12-09 | 2017-05-17 | 江西中科九峰智慧医疗科技有限公司 | Knowledge-based electronic medical record quality control method |
| CN107229831A (en) * | 2017-06-08 | 2017-10-03 | 成都深泉科技有限公司 | Electronic health record generation method, apparatus and system |
| CN110720101A (en) * | 2017-10-23 | 2020-01-21 | 谷歌有限责任公司 | Validating structured data |
| CN110020660A (en) * | 2017-12-06 | 2019-07-16 | 埃森哲环球解决方案有限公司 | Use the integrity assessment of the unstructured process of artificial intelligence (AI) technology |
| CN110504009A (en) * | 2018-05-16 | 2019-11-26 | 北京理工大学 | A kind of method of electronic health record structuring |
| CN110362829A (en) * | 2019-07-16 | 2019-10-22 | 北京百度网讯科技有限公司 | Method for evaluating quality, device and the equipment of structured patient record data |
Non-Patent Citations (3)
| Title |
|---|
| Named_Entity_Recognition_in_Chinese_Electronic_Medical_Records_Based_on_ALBERT-IDCNN-CRF;Gongzheng Tang，等;《2022 IEEE the 8th International Conference on Computer and Communications》;第1753-1757页 * |
| 基于电子住院病历的临床决策支持***的设计与应用;张慧娟;《中国医疗管理科学》;第6卷(第6期);第10-14页 * |
| 结构化电子病历的设计与应用;张波;《技术应用》;第74-75页 * |
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