CN117524408A - AI-based intravenous administration configuration checking system and use method thereof - Google Patents
AI-based intravenous administration configuration checking system and use method thereof Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000001990 intravenous administration Methods 0.000 title claims abstract description 12
- 239000003814 drug Substances 0.000 claims abstract description 126
- 229940079593 drug Drugs 0.000 claims abstract description 31
- 239000003086 colorant Substances 0.000 claims abstract description 6
- 210000001503 joint Anatomy 0.000 claims abstract description 4
- 230000009471 action Effects 0.000 claims description 15
- 238000012795 verification Methods 0.000 claims description 12
- 230000007613 environmental effect Effects 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 9
- 238000012549 training Methods 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 claims description 6
- 238000005192 partition Methods 0.000 claims description 6
- 238000001802 infusion Methods 0.000 claims description 5
- 230000006399 behavior Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 claims description 4
- 229930182555 Penicillin Natural products 0.000 claims description 3
- JGSARLDLIJGVTE-MBNYWOFBSA-N Penicillin G Chemical compound N([C@H]1[C@H]2SC([C@@H](N2C1=O)C(O)=O)(C)C)C(=O)CC1=CC=CC=C1 JGSARLDLIJGVTE-MBNYWOFBSA-N 0.000 claims description 3
- 230000005856 abnormality Effects 0.000 claims description 3
- 239000003708 ampul Substances 0.000 claims description 3
- 238000001514 detection method Methods 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 3
- 238000002372 labelling Methods 0.000 claims description 3
- 238000003058 natural language processing Methods 0.000 claims description 3
- 229940049954 penicillin Drugs 0.000 claims description 3
- 230000000284 resting effect Effects 0.000 claims description 3
- 238000009423 ventilation Methods 0.000 claims description 3
- 238000011161 development Methods 0.000 abstract description 5
- 239000002552 dosage form Substances 0.000 abstract description 3
- 241000282412 Homo Species 0.000 description 3
- 206010013710 Drug interaction Diseases 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000001647 drug administration Methods 0.000 description 1
- 229940126534 drug product Drugs 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000005802 health problem Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000002483 medication Methods 0.000 description 1
- 239000000825 pharmaceutical preparation Substances 0.000 description 1
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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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses an AI-based intravenous drug configuration checking system and a using method thereof, which belong to the field of drug dispensing, can improve the accuracy and efficiency of drug configuration, provide real-time feedback and guidance, have strong adaptability, save human resources, adapt to future development demands, and have important practical value and wide application prospect. The system mainly comprises an information database, wherein the information database comprises a medicine information database and an environment information storage database; the medicine information database is continuously updated through the internal database of the butt joint medical unit, or is self-built, the environment information storage database is used for storing article information appearing in the three-dimensional space of the operation area of the configuration table, and the medicine information database stores medicine names, specifications, dosage forms, usage and appearance shapes, and has representative characteristics such as colors, shapes and internal characteristics. The invention is mainly used for checking during manual dispensing.
Description
Technical Field
The invention relates to the field of medicine dispensing, in particular to an AI-based intravenous medicine configuration checking system and a use method thereof.
Background
In the medical field, configuring patients for intravenous administration is a common and important procedure. However, there are potential safety issues in this process, such as incorrect drug product configuration, where one drug is configured as another drug; dose configuration errors, incomplete amounts of drug configured in full amounts resulting in overdose; an irregular operational behavior results in a hospital feel event. These problems can lead to health problems for the patient and even life threatening. In the traditional intravenous drug configuration process, manual verification is mainly performed by depending on the professional skills and responsibility of medical staff, however, the efficiency and the accuracy of the mode are required to be improved. Although automatic equipment such as intravenous drug administration configuration robots and the like is present, manual configuration cannot be completely replaced, because of the following points:
1. complicated medical conditions: in the medical field, the situation is often complex and special. The robot may not understand nuances and special needs in certain situations, and humans may perform personalized medicine configurations according to the patient's specific situation.
2. Responsibility problem of medical accidents: during the dispensing process, if any errors occur, the robot may not be able to interpret or explain the cause of the errors. Whereas humans can clearly interpret and assume responsibility.
3. Maintenance and repair of robots: although dispensing robots can be efficient, there are problems such as failure and damage to the robot that can cause it to function improperly, requiring repair and maintenance by human technicians.
Such as a venous dispensing machine with publication number CN115744774a, which lacks a re-check contrast module, cannot be found in time for the case of incorrect dispensing, and is easy to cause accidents.
Thus, while dispensing robots may improve the efficiency and accuracy of dispensing, in some specific situations, manual configuration by humans is still required.
Disclosure of Invention
The invention aims to provide an AI-based intravenous drug configuration checking system and a use method thereof, which can improve the accuracy and efficiency of drug configuration, provide real-time feedback and guidance, have strong adaptability, save human resources, adapt to future development demands, and have important practical value and wide application prospect.
The invention is realized by the following technical scheme:
an AI-based intravenous administration configuration verification system comprising
The information database comprises a medicine information database and an environment information storage database; the medicine information database is continuously updated through the internal database of the butt joint medical unit, or is self-built, the environment information storage database is used for storing article information appearing in the three-dimensional space of the operation area of the configuration table, and the medicine information database stores medicine names, specifications, dosage forms, usage and appearance shapes and has representative characteristics such as colors, shapes and internal characteristics;
the image recognition module monitors elements such as large transfusion and transfusion patches, medicine labels and the like in the medicine configuration process in real time through computer vision, and recognizes information such as names, doses, specifications and the like of medicines;
the semantic analysis module is used for analyzing the text information on the medicine label by utilizing a natural language processing technology, confirming key information such as medicine names, usage, contraindications and the like, and comparing the key information with medicine information in a database;
the data comparison module is used for comparing the medicine information acquired in real time with the pre-established standard medicine information and verifying the accuracy and compliance of the medicine;
the abnormality detection module is used for identifying potential errors or abnormal conditions in the drug configuration, such as dose exceeding, drug interaction and the like, based on historical data and model training; identifying whether the operating environment and the operating behavior are normative;
the early warning module emits lights with different colors, gives an alarm and prevents the error configuration from proceeding;
and the feedback and learning module is used for recording information of each medicine configuration, including successful configuration and abnormal conditions, manually correcting the identification error conditions and continuously improving the accuracy of the model and the stability of the system.
Further, also comprises
The medicine partition module is a grid plate, the height of the grid plate is lower than that of large transfusion, each group of medicines can be partitioned without shielding medicine information, and the medicine information acquisition identification degree is increased;
and the medicine lighting module is used for lighting the medicine information for the lighting lamp group, so that the table top is shadowless, and the medicine information acquisition identification degree is increased.
A method of using an AI-based iv administration configuration verification system, using the AI-based iv administration configuration verification system, comprising the steps of:
s1: setting an image recognition module at a designated position of a configuration table, assembling a medicine partition module on the table surface, arranging medicines and large transfusion in groups, enabling configuration personnel to perform characteristic instruction actions, starting an illumination module after the characteristic instruction actions are recognized, and enabling a system to perform an instruction of collecting environmental information;
s2: setting an early warning module at a designated position of the configuration platform, and evaluating the environment of the configuration platform;
s3: in the configuration process, recognizing that the body of an operator exceeds the specified range of the configuration table, and prompting by turning on an orange lamp;
s4: after the medicine is configured, the staff puts the ampoule or the penicillin bottle after the suction at a designated position, makes characteristic instruction action, starts a data comparison module after the action is identified, analyzes and judges whether the configured medicine information is configured accurately, if the configured medicine information is checked correctly, a green light prompt is turned on, and if the configured medicine information is checked incorrectly, a yellow light prompt is turned on for manual check;
s5: and generating big configuration information data by collecting configuration data of multiple rounds, and continuously training and optimizing the system by using a feedback and learning module to serve as a basis for iterative updating of a later-stage system.
Further, in step S1, the environmental information refers to all the article information appearing in the stereoscopic space of the operation area of the configuration console, including appearance, shape, number, stored in the environmental information database, and the form is not limited to images, texts, etc.; the instruction action includes a human resting state.
Further, in step S1, the designated position of the placement stage is a position at which the panorama of the placement stage can be captured without affecting laminar ventilation, and is different from one placement stage to another.
Further, in step S2, the infusion paste information is a two-dimensional code or text on the index label, the two-dimensional code is identified by using the medical system own medicine database, and the label text is identified by using the self-built medicine database.
Further, in step S2, it is identified that the number of large infusion bags exceeds the upper limit set by the system, and if non-drug configuration related articles appear in the image, a blue light is turned on for prompting; the acquired transfusion labeling information is matched with the medicine database, the acquired medicine image information is compared with the database information, a green light prompt is turned on when the information is consistent, and a red light prompt is turned on when the information is inconsistent; after identifying that the drug dosage is different from the conventional dosage in the drug database, the yellow light is turned on to prompt the operator to check the prescription again.
Further, in step S4-step S5, the data comparison module and the feedback and learning module are based on the data obtained after the acquisition of a large amount of data and training.
Compared with the prior art, the invention has the beneficial effects that:
1. the accuracy and efficiency of medicine configuration are improved: by using the AI technology to automatically check, the medicine mismatching caused by human errors can be greatly reduced, and meanwhile, the checking efficiency can be improved.
2. Providing real-time feedback and guidance: the early warning module can provide real-time feedback information to inform medical staff of the correctness of the medicine configuration; if foreign matters exist in the configuration environment or the operation method is wrong, the early warning module can prompt the staff to correct and take measures in time.
3. The adaptability is strong: the information database can be continuously updated by machine learning algorithms to accommodate new medications and medical knowledge.
4. Human resources are saved: the artificial intelligence check replaces the manual check, so that the human resource cost is reduced.
5. Adapt to the future development demand: the design of the system is prospective, can adapt to the development and change of future medicines and medical knowledge, and meets the future medical demands.
In summary, the invention can improve the accuracy and efficiency of drug configuration, provide real-time feedback and guidance, has strong adaptability, saves human resources, adapts to future development demands, and has important practical value and wide application prospect.
Drawings
FIG. 1 is a schematic diagram of the structure of the present invention;
fig. 2 is a flow chart of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
As shown in fig. 1 to 2, embodiment 1, an AI-based intravenous administration configuration verification system includes
The information database comprises a medicine information database and an environment information storage database; the medicine information database is continuously updated through the internal database of the butt joint medical unit, or is self-built, the environment information storage database is used for storing article information appearing in the three-dimensional space of the operation area of the configuration table, and the medicine information database stores medicine names, specifications, dosage forms, usage and appearance shapes and has representative characteristics such as colors, shapes and internal characteristics;
the image recognition module monitors elements such as large transfusion and transfusion patches, medicine labels and the like in the medicine configuration process in real time through computer vision, and recognizes information such as names, doses, specifications and the like of medicines;
the semantic analysis module is used for analyzing the text information on the medicine label by utilizing a natural language processing technology, confirming key information such as medicine names, usage, contraindications and the like, and comparing the key information with medicine information in a database;
the data comparison module is used for comparing the medicine information acquired in real time with the pre-established standard medicine information and verifying the accuracy and compliance of the medicine;
the abnormality detection module is used for identifying potential errors or abnormal conditions in the drug configuration, such as dose exceeding, drug interaction and the like, based on historical data and model training; identifying whether the operating environment and the operating behavior are normative;
the early warning module emits lights with different colors, gives an alarm and prevents the error configuration from proceeding;
the feedback and learning module records information of each medicine configuration, including successful configuration and abnormal conditions, and manually corrects the identification error conditions for continuously improving the accuracy of the model and the stability of the system;
the medicine partition module is a grid plate, the height of the grid plate is lower than that of large transfusion, each group of medicines can be partitioned without shielding medicine information, and the medicine information acquisition identification degree is increased;
and the medicine lighting module is used for lighting the medicine information for the lighting lamp group, so that the table top is shadowless, and the medicine information acquisition identification degree is increased.
Embodiment 2, a method for using the AI-based iv configuration check system described in embodiment 1, includes the steps of:
s1: setting an image recognition module at a designated position of a configuration table, assembling a medicine partition module on the table surface, arranging medicines and large transfusion in groups, enabling configuration personnel to perform characteristic instruction actions, starting an illumination module after the characteristic instruction actions are recognized, and enabling a system to perform an instruction of collecting environmental information;
s2: setting an early warning module at a designated position of the configuration platform, and evaluating the environment of the configuration platform;
s3: in the configuration process, recognizing that the body of an operator exceeds the specified range of the configuration table, and prompting by turning on an orange lamp;
s4: after the medicine is configured, the staff puts the ampoule or the penicillin bottle after the suction at a designated position, makes characteristic instruction action, starts a data comparison module after the action is identified, analyzes and judges whether the configured medicine information is configured accurately, if the configured medicine information is checked correctly, a green light prompt is turned on, and if the configured medicine information is checked incorrectly, a yellow light prompt is turned on for manual check;
s5: and generating big configuration information data by collecting configuration data of multiple rounds, and continuously training and optimizing the system by using a feedback and learning module to serve as a basis for iterative updating of a later-stage system.
In the embodiment 3, an AI-based intravenous administration configuration checking system is used, in the step S1, the environmental information refers to all the article information appearing in the stereoscopic space of the operation area of the configuration console, including the appearance, shape, number, and the like, stored in the environmental information database, and the form is not limited to the image, text, and the like; the instruction actions include a human resting state; in step S1, the designated position of the placement stage is a position that does not affect laminar ventilation and can capture the panorama of the placement stage, which varies from placement stage to placement stage; in step S2, the infusion paste information is a two-dimensional code or text on the index sign, the two-dimensional code is identified by using the medical system own medicine database, and the label text is identified by using the self-built medicine database; in the step S2, recognizing that the number of large transfusion placing bags exceeds the upper limit set by the system, and lighting a blue light prompt when related non-medicine configuration articles appear in the image in the step S2; the acquired transfusion labeling information is matched with the medicine database, the acquired medicine image information is compared with the database information, a green light prompt is turned on when the information is consistent, and a red light prompt is turned on when the information is inconsistent; after recognizing that the dosage of the medicine is different from the conventional dosage in the medicine database, the yellow light is turned on to prompt an operator to check the prescription again; in steps S4 to S5, the data comparison module and the feedback and learning module are the same as those of example 2, except that the data obtained by collecting a large amount of data and training are used.
Claims (8)
1. An AI-based intravenous administration configuration verification system, characterized by: comprising
The information database comprises a medicine information database and an environment information storage database; the medicine information database is continuously updated through the internal database of the butt joint medical institution or is self-built, and the environment information storage database is used for storing article information appearing in the three-dimensional space of the operation area of the configuration table;
the image recognition module monitors the large transfusion and the transfusion paste and the medicine label in the medicine configuration process in real time through computer vision and recognizes the name, the dosage and the specification of the medicine;
the semantic analysis module is used for analyzing the text information on the medicine label by utilizing a natural language processing technology, confirming the medicine name, the usage and the tabu information and comparing the medicine name, the usage and the tabu information with the medicine information in the database;
the data comparison module is used for comparing the medicine information acquired in real time with the pre-established standard medicine information and verifying the accuracy and compliance of the medicine;
the abnormality detection module is used for identifying potential errors or abnormal conditions in the drug configuration and identifying whether the operation environment and the operation behavior are standard or not based on historical data and model training;
the early warning module emits lights with different colors, gives an alarm and prevents the error configuration from proceeding;
and the feedback and learning module is used for recording information of each medicine configuration, including successful configuration and abnormal conditions, manually correcting the identification error conditions and continuously improving the accuracy of the model and the stability of the system.
2. The AI-based iv administration configuration verification system of claim 1, wherein: and also comprises
The medicine partition module is a grid plate, the height of the grid plate is lower than that of large transfusion, each group of medicines can be partitioned without shielding medicine information, and the medicine information acquisition identification degree is increased;
and the medicine lighting module is used for lighting the medicine information for the lighting lamp group, so that the table top is shadowless, and the medicine information acquisition identification degree is increased.
3. A method of using the AI-based iv configuration check system of any one of claims 1-2, comprising the steps of:
s1: setting an image recognition module at a designated position of a configuration table, assembling a medicine partition module on the table surface, arranging medicines and large transfusion in groups, enabling configuration personnel to perform characteristic instruction actions, starting an illumination module after the characteristic instruction actions are recognized, and enabling a system to perform an instruction of collecting environmental information;
s2: setting an early warning module at a designated position of the configuration platform, and evaluating the environment of the configuration platform;
s3: in the configuration process, recognizing that the body of an operator exceeds the specified range of the configuration table, and prompting by turning on an orange lamp;
s4: after the medicine is configured, the staff puts the ampoule or the penicillin bottle after the suction at a designated position, makes characteristic instruction action, starts a data comparison module after the action is identified, analyzes and judges whether the configured medicine information is configured accurately, if the configured medicine information is checked correctly, a green light prompt is turned on, and if the configured medicine information is checked incorrectly, a yellow light prompt is turned on for manual check;
s5: and generating big configuration information data by collecting configuration data of multiple rounds, and continuously training and optimizing the system by using a feedback and learning module to serve as a basis for iterative updating of a later-stage system.
4. The AI-based iv administration configuration verification system of claim 3, wherein in step S1, the environmental information is all the object information that appears in the stereoscopic space of the operation area of the configuration console, including appearance, shape, number, stored in the environmental information database in a form not limited to image, text; the instruction action includes a human resting state.
5. The method of using an AI-based iv administration configuration verification system according to claim 3, wherein the configuration table is assigned a position that does not affect laminar flow ventilation and that can capture the panorama of the configuration table in step S1, and the configuration table is different from one configuration table to another.
6. The method of using an AI-based iv administration configuration verification system according to claim 3, wherein in step S2, the infusion patch information is a two-dimensional code or text on an index label, the two-dimensional code is identified using the medical system' S own drug database, and the tag text is identified using the self-built drug database.
7. The AI-based iv administration configuration verification system of claim 3, wherein in step S2, it is recognized that the number of large infusion bags exceeds the upper limit set by the system, and a non-drug configuration related item appears in the image, and a blue light is turned on; the acquired transfusion labeling information is matched with the medicine database, the acquired medicine image information is compared with the database information, a green light prompt is turned on when the information is consistent, and a red light prompt is turned on when the information is inconsistent; after identifying that the drug dosage is different from the conventional dosage in the drug database, the yellow light is turned on to prompt the operator to check the prescription again.
8. The method of using an AI-based iv administration configuration verification system according to claim 3, wherein in steps S4 to S5, the data of the data comparison module and the feedback and learning module are based on the data obtained after a large amount of data is collected and trained.
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