CN117037985A - Pre-hospital emergency medical record quality control system based on artificial intelligence - Google Patents
Pre-hospital emergency medical record quality control system based on artificial intelligence Download PDFInfo
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- 238000011156 evaluation Methods 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 11
- 238000013441 quality evaluation Methods 0.000 claims description 11
- 238000012544 monitoring process Methods 0.000 claims description 8
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- 238000003058 natural language processing Methods 0.000 claims description 4
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- 238000001303 quality assessment method Methods 0.000 claims description 2
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F40/10—Text processing
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- G06F40/174—Form filling; Merging
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Abstract
The invention relates to the technical field of medical record quality control. The invention relates to an artificial intelligence pre-hospital emergency medical record quality control system. The system comprises an emergency filling unit, a filling correction unit and a medical record scoring unit; the emergency filling unit is used for connecting with a command and dispatch management end of a hospital through artificial intelligence, acquiring emergency tasks sent by the command and dispatch management end, formulating pre-hospital emergency medical records according to the emergency tasks, and sending to an emergency doctor for filling, so as to acquire filled emergency medical records; the emergency filling unit is used for making corresponding pre-hospital emergency medical records for each emergency task, so that the medical records are prevented from overlapping, or the medical records are inconsistent with the emergency patient information, and the filling correction unit and the medical record scoring unit are used for filling auxiliary for filling the pre-hospital emergency medical records for emergency doctors, so that the emergency doctors can complete the filling of the pre-hospital emergency medical records on time.
Description
Technical Field
The invention relates to the technical field of medical record quality control, in particular to an artificial intelligence pre-hospital emergency medical record quality control system.
Background
The pre-hospital emergency medical record is a medical record form filled when a patient is first-aid in an emergency scene, but when an emergency doctor fills, the doctor fills a disease duration possibly to have filling errors due to emergency treatment, meanwhile, the emergency doctor needs to carry out emergency work on the patient when the patient is dangerous when the pre-hospital emergency medical record is filled, the doctor is not in the way of checking the filling process, the medical record at the moment is uploaded to a system with lower use quality, and the quality control system based on the pre-hospital emergency medical record is proposed in view of the fact.
Disclosure of Invention
The invention aims to provide an artificial intelligence pre-hospital emergency medical record quality control system to solve the problems in the background technology.
In order to achieve the above purpose, the system for controlling the quality of emergency medical records based on artificial intelligence pre-hospital emergency medical records comprises an emergency filling unit, a filling correction unit and a medical record scoring unit;
the emergency filling unit is used for connecting with a command and dispatch management end of a hospital through artificial intelligence, acquiring emergency tasks sent by the command and dispatch management end, preparing pre-hospital emergency medical records according to the emergency tasks, and sending to an emergency doctor for filling to acquire filled emergency medical records;
the filling correction unit is used for recording the filling actual time of the emergency doctor, comparing the actual time with a preset filling standard time, and sending a refill prompt to the emergency doctor according to the comparison result to obtain a correct medical record;
the medical record scoring unit is used for establishing medical record quality evaluation standards, and scoring the emergency medical record filled by the emergency filling unit and the correct medical record acquired by the filling correction unit in combination with the medical record quality evaluation standards.
As a further improvement of the technical scheme, the emergency filling unit connects the artificial intelligence with the command and dispatch management end of the hospital through the network information interface, the artificial intelligence monitors the emergency task sent by the command and dispatch management end and receives task information in real time, wherein the task information comprises task type, emergency degree and patient information.
As a further improvement of the technical scheme, the emergency filling unit is used for making a pre-hospital emergency medical record according to the emergency task when the emergency task is acquired, signing the pre-hospital emergency medical record for the emergency task, and then sending the generated pre-hospital emergency medical record to an emergency doctor for filling to acquire the emergency medical record.
As a further improvement of the technical scheme, the filling correction unit monitors the process of filling the emergency medical records before the emergency doctor fills the hospital through screen recording software, records the actual time of filling the emergency medical records by the doctor through the recording software in real time.
As a further improvement of the technical scheme, the filling correction unit further comprises an automatic submitting unit, wherein the automatic submitting unit is used for monitoring the process of filling the pre-hospital emergency medical records by a doctor, and when the rest time exceeds three minutes, the filled emergency medical records are automatically submitted to a hospital.
As a further improvement of the technical scheme, the filling correction unit comprises a standard time preset module and a refilling reminding module;
the standard time presetting module is used for carrying out filling simulation according to pre-hospital emergency medical records formulated by the emergency filling unit, and acquiring the shortest standard time after filling;
the refill reminding module is used for comparing the difference values according to the standard time acquired by the standard time presetting module and the actual time recorded by the filling correction unit, if the comparison result is positive, the refill reminding is not sent out, otherwise, if the comparison result is negative, the refill reminding is sent out to the emergency doctor, and the emergency doctor is reminded to refill a correct medical record after the emergency.
As a further improvement of the technical scheme, the filling correction unit further comprises an automatic input module, wherein the automatic input module is used for monitoring voice data of an emergency site, automatically converting the voice record of the emergency site into a text form by utilizing voice recognition and natural language processing technology, extracting key information and automatically recording emergency medical records before admission.
As a further improvement of the technical scheme, the medical record scoring unit establishes medical record quality evaluation standards according to pre-hospital emergency electronic medical record scoring standards and pre-hospital emergency electronic medical record manual quality check scoring standards.
As a further improvement of the technical scheme, the medical record scoring unit comprises a medical record evaluation module, wherein the medical record evaluation module is used for extracting error data of the correct medical record obtained by the emergency medical record and the refilling reminding module, and putting the error data into a medical record quality evaluation standard for score evaluation so as to obtain the score of the emergency medical record.
Compared with the prior art, the invention has the beneficial effects that:
in the pre-hospital emergency medical record quality control system based on the artificial intelligence, corresponding pre-hospital emergency medical records are formulated for each emergency task through the emergency filling unit, overlapping of medical records is avoided, or the medical records are inconsistent with emergency patient information, filling assistance is carried out on filling of pre-hospital emergency medical records to emergency doctors through the filling correction unit and the medical record scoring unit, the problem of business performance of the emergency doctors is rapidly determined through the medical record scoring unit after the emergency doctors complete filling on time, a solution is formulated, measures are taken, evaluation measures are taken, adjustment is carried out according to requirements, the business performance level is finally improved, and the purposes of improving the pre-hospital emergency medical quality level and normalizing pre-hospital emergency medical behaviors are achieved.
Drawings
Fig. 1 is a schematic diagram of the overall structure of the present invention.
The meaning of each reference sign in the figure is:
10. an emergency filling unit; 20. filling in a correction unit; 30. and a medical record scoring unit.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Example 1
Referring to fig. 1, the present embodiment is directed to providing an emergency medical record quality control system based on artificial intelligence, which includes an emergency filling unit 10, a filling correction unit 20, and a medical record scoring unit 30;
the emergency filling unit 10 is used for connecting with a command and dispatch management end of a hospital through artificial intelligence to acquire an emergency task sent by the command and dispatch management end;
the emergency filling unit 10 connects the artificial intelligence with the command and dispatch management end of the hospital through the network information interface, the artificial intelligence monitors the emergency task sent by the command and dispatch management end, and receives task information in real time, including task type, emergency degree and patient information. The method comprises the following steps:
and (3) system connection: the connection and communication between the artificial intelligent system and the command scheduling management end can be ensured, and the data transmission can be performed through a network interface or an API;
receiving a task: the artificial intelligent system monitors the emergency task sent by the command dispatching management end and receives task information in real time, wherein the task information comprises task type, emergency degree, patient information and the like;
task analysis: the artificial intelligence system analyzes and processes the received tasks, and extracts key information in the tasks, such as task places, task time, patient conditions and the like.
Meanwhile, preparing a pre-hospital emergency medical record according to an emergency task, and sending to an emergency doctor for filling to obtain a filled emergency medical record;
the emergency filling unit 10 is configured to, when an emergency task is acquired, make a pre-hospital emergency medical record according to the emergency task, sign the pre-hospital emergency medical record for the emergency task, and send the generated pre-hospital emergency medical record to an emergency doctor for filling, so as to acquire the emergency medical record. The method comprises the following steps:
acquiring an emergency task: first-aid task information including task type, patient information, emergency degree and the like is obtained from a command scheduling management end;
and (3) medical record generation: and generating pre-hospital emergency medical records of the emergency task by utilizing a pre-designed pre-hospital emergency medical record template according to the emergency task information, wherein the pre-hospital emergency medical records comprise medical record forms and related contents. Text templates, markup language, etc. techniques may be used;
signed medical record: adding a signature of the emergency task to the generated pre-hospital emergency medical record, identifying that the medical record was generated for the emergency task;
and (5) sending medical records: the generated and signed pre-hospital emergency medical record is sent to a designated emergency doctor and can be sent by means of e-mail, instant messaging tool and the like;
the doctor fills in: after receiving the pre-hospital emergency medical records, the emergency doctor fills in relevant contents according to the actual conditions and the patient conditions. The doctor can fill in according to the classification and the form in the medical record template;
and (3) completing medical records: after completion of the filling, the emergency doctor saves the medical record and marks it as completed.
The filling correction unit 20 is used for recording the filling actual time of the emergency doctor;
the filling correction unit 20 monitors the process of filling the emergency medical records before the emergency doctor fills the hospital through the screen recording software, and records the actual time of filling the emergency medical records by the doctor through the recording software in real time.
The filling correction unit 20 further comprises an automatic submitting unit for monitoring the process of filling the emergency medical records before the hospital by the doctor, and automatically submitting the filled emergency medical records to the hospital when the rest time exceeds three minutes
Comparing the actual time with a preset filling standard time, and sending a refill prompt to an emergency doctor according to the comparison result to obtain a correct medical record;
the filling correction unit 20 includes a standard time presetting module and a refill reminding module;
the standard time presetting module is used for carrying out filling simulation according to the pre-hospital emergency medical records formulated by the emergency filling unit 10, and acquiring the shortest standard time after filling;
the refill reminding module is used for comparing the difference values according to the standard time acquired by the standard time presetting module and the actual time recorded by the filling correction unit 20, if the comparison result is positive, the refill reminding is not sent out, otherwise, if the comparison result is negative, the refill reminding is sent out to the emergency doctor, and the emergency doctor is reminded to refill a correct medical record after the emergency.
During the inquiry of the patient, the problems of one-time speaking of the patient may be more, and the doctor needs to repeatedly inquire the patient because the memory amount is too large and the doctor can not remember all the problems, so that accurate input is completed, the time for emergency treatment is wasted, the filling correction unit 20 further comprises an automatic input module, the automatic input module is used for monitoring the voice data of the emergency site, and the voice record of the emergency site is automatically converted into a text form by utilizing the voice recognition and natural language processing technology, key information is extracted, and the emergency medical record before admission is automatically recorded. Monitoring voice data: monitoring voice data of the emergency site in real time through a microphone or other recording equipment, and transmitting the voice signals to a voice recognition system;
and (3) voice recognition: the monitored speech data is converted into text form using speech recognition techniques. Open source or commercial speech recognition engines such as Google Cloud Speech-to-Text, microsoft Azure Speech-to-Text, etc. may be used;
text preprocessing: preprocessing the identified text, including removing irrelevant information such as noise, word of language, pause and the like, and reserving key content;
key information extraction: using natural language processing technology to make semantic analysis, entity identification, keyword extraction and the like on the preprocessed text, and extracting key information of emergency scene, such as illness state description, basic information of patients, doctor indication and the like;
recording the first-aid medical record before admission: and automatically filling the key information extracted from the voice data into corresponding fields in the pre-hospital emergency medical records for recording. An expression or template may be used to specify the location of the information to be filled in;
data verification and correction: and verifying and correcting the automatically recorded information to ensure accuracy and integrity. Manual auditing and automatic verification algorithms can be combined;
and (5) saving and updating medical records: after the information is input, the automatically filled pre-hospital emergency medical records are saved, and medical record information in a related system or database is updated.
The medical record scoring unit 30 is used for establishing medical record quality evaluation standards;
the medical record scoring unit 30 establishes medical record quality assessment criteria based on pre-hospital emergency electronic medical record scoring criteria and pre-hospital emergency electronic medical record manual quality check scoring criteria.
The emergency medical records filled in by the emergency filling unit 10 and the correct medical records acquired by the filling correction unit 20 are scored in combination with medical record quality evaluation criteria.
The medical record scoring unit 30 comprises a medical record evaluation module, wherein the medical record evaluation module is used for extracting error data of the correct medical record acquired by the emergency medical record and refill reminding module, and putting the error data into a medical record quality evaluation standard for score evaluation, so that a scoring medical record quality evaluation standard of the emergency medical record is acquired;
extraction of emergency medical record data: extracting data to be evaluated from emergency medical record data, and performing data cleaning and arrangement to ensure the accuracy and consistency of the data;
identification of error data: and carrying out error data identification on the extracted data according to the formulated evaluation standard. For example, detecting the problems of wrongly written characters, incomplete information, conflicts and the like in the medical record;
scoring calculation of error data: each error data is scored according to scoring criteria in the evaluation criteria. The scores may be classified into different levels for indicating the degree or severity of the erroneous data;
and (5) medical record scoring calculation: and accumulating the scores of all error data to obtain the total score of the emergency medical record. The quality of the medical record can be reflected by the score, and the higher the score is, the worse the quality of the medical record is represented, and the lower the score is, the better the quality of the medical record is represented. The formula is as follows:
wherein the total score represents a maximum value of the score, for example, 100 points, (T-E)/T represents an error data ratio, represents a ratio of correct data to total data, T represents the number of correct data, E represents the number of error data, and the total score represents the maximum value of the score.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. Based on the first aid medical history quality control system before artificial intelligence hospital, its characterized in that: comprises an emergency filling unit (10), a filling correction unit (20) and a medical record scoring unit (30);
the emergency filling unit (10) is used for connecting with a command scheduling management end of a hospital through artificial intelligence, acquiring emergency tasks sent by the command scheduling management end, formulating pre-hospital emergency medical records according to the emergency tasks, and sending to an emergency doctor for filling to acquire filled emergency medical records;
the filling correction unit (20) is used for recording the filling actual time of the emergency doctor, comparing the actual time with a preset filling standard time, and sending a refilling prompt to the emergency doctor according to the comparison result to obtain a correct medical record;
the medical record scoring unit (30) is used for establishing medical record quality evaluation standards, and scoring the emergency medical record filled by the emergency filling unit (10) and the correct medical record acquired by the filling correction unit (20) by combining the medical record quality evaluation standards.
2. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the emergency filling unit (10) connects the artificial intelligence with the command and dispatch management end of the hospital through the network information interface, the artificial intelligence monitors the emergency task sent by the command and dispatch management end, and receives task information in real time, including task type, emergency degree and patient information.
3. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the emergency filling unit (10) is used for preparing a pre-hospital emergency medical record according to the emergency task when the emergency task is acquired, signing the pre-hospital emergency medical record to the emergency task, and then sending the generated pre-hospital emergency medical record to an emergency doctor for filling to acquire the emergency medical record.
4. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the filling correction unit (20) monitors the process of filling the pre-hospital emergency medical record of the emergency doctor through screen recording software, records the actual time of filling the emergency medical record of the doctor in real time through recording software.
5. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the filling correction unit (20) further comprises an automatic submitting unit for monitoring the process of filling the pre-hospital emergency medical records by the doctor, and automatically submitting the filled emergency medical records to the hospital when the rest time exceeds three minutes.
6. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the filling correction unit (20) comprises a standard time preset module and a refilling reminding module;
the standard time presetting module is used for carrying out filling simulation according to pre-hospital emergency medical records formulated by the emergency filling unit (10) to obtain the shortest standard time after filling;
the refill reminding module is used for carrying out difference comparison according to the standard time acquired by the standard time presetting module and the actual time recorded by the filling correction unit (20), if the comparison result is positive, the refill reminding is not sent out, otherwise, if the comparison result is negative, the refill reminding is sent out to the emergency doctor, and the emergency doctor is reminded to refill a correct medical record after the emergency.
7. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the filling correction unit (20) further comprises an automatic input module, wherein the automatic input module is used for monitoring voice data of an emergency site, automatically converting the voice record of the emergency site into a text form by utilizing voice recognition and natural language processing technology, extracting key information and automatically recording emergency medical records before admission.
8. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the medical record scoring unit (30) establishes medical record quality assessment criteria according to pre-hospital emergency electronic medical record scoring criteria and pre-hospital emergency electronic medical record manual quality check scoring criteria.
9. The pre-hospital emergency medical record quality control system based on artificial intelligence according to claim 1, wherein: the medical record scoring unit (30) comprises a medical record evaluation module, wherein the medical record evaluation module is used for extracting error data of the correct medical record obtained by the emergency medical record and the refill reminding module, and putting the error data into a medical record quality evaluation standard to perform score evaluation so as to obtain the score of the emergency medical record.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106295994A (en) * | 2016-08-09 | 2017-01-04 | 广州市康软信息科技有限公司 | A kind of first aid realization method and system based on emergency center's mobile terminal |
| CN108386060A (en) * | 2018-04-28 | 2018-08-10 | 中南大学湘雅医院 | Tent hospital mobile workstation system |
| CN110600095A (en) * | 2019-08-23 | 2019-12-20 | 和宇健康科技股份有限公司 | Quality control method and system for electronic medical record |
| CN111967241A (en) * | 2020-09-03 | 2020-11-20 | 卫宁健康科技集团股份有限公司 | Medical record writing quality control method and system |
| CN114613461A (en) * | 2022-03-07 | 2022-06-10 | 云知声智能科技股份有限公司 | Intelligent entry method and system for outpatient service medical record |
| WO2022174491A1 (en) * | 2021-02-19 | 2022-08-25 | 平安科技（深圳）有限公司 | Artificial intelligence-based method and apparatus for medical record quality control, computer device, and storage medium |
| CN114974541A (en) * | 2021-10-27 | 2022-08-30 | 重庆臻链汇物联网科技有限公司 | Pre-hospital medical record system based on Internet of vehicles |
| CN115512799A (en) * | 2022-10-09 | 2022-12-23 | 南京海泰医疗信息系统有限公司 | Medical record quality evaluation method and system based on clinical task closed-loop management mechanism |
-
2023
- 2023-08-10 CN CN202311004104.5A patent/CN117037985A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106295994A (en) * | 2016-08-09 | 2017-01-04 | 广州市康软信息科技有限公司 | A kind of first aid realization method and system based on emergency center's mobile terminal |
| CN108386060A (en) * | 2018-04-28 | 2018-08-10 | 中南大学湘雅医院 | Tent hospital mobile workstation system |
| CN110600095A (en) * | 2019-08-23 | 2019-12-20 | 和宇健康科技股份有限公司 | Quality control method and system for electronic medical record |
| CN111967241A (en) * | 2020-09-03 | 2020-11-20 | 卫宁健康科技集团股份有限公司 | Medical record writing quality control method and system |
| WO2022174491A1 (en) * | 2021-02-19 | 2022-08-25 | 平安科技（深圳）有限公司 | Artificial intelligence-based method and apparatus for medical record quality control, computer device, and storage medium |
| CN114974541A (en) * | 2021-10-27 | 2022-08-30 | 重庆臻链汇物联网科技有限公司 | Pre-hospital medical record system based on Internet of vehicles |
| CN114613461A (en) * | 2022-03-07 | 2022-06-10 | 云知声智能科技股份有限公司 | Intelligent entry method and system for outpatient service medical record |
| CN115512799A (en) * | 2022-10-09 | 2022-12-23 | 南京海泰医疗信息系统有限公司 | Medical record quality evaluation method and system based on clinical task closed-loop management mechanism |
Non-Patent Citations (1)
| Title |
|---|
| 李鑫 等: "急诊急救移动信息平台在院前急救工作中的应用与效果评价", 实用临床护理学杂志, vol. 3, no. 39, pages 51 - 52 * |
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