WO2023029511A1 - Procédé et appareil d'inspection intelligente pour un médicament sur ordonnance médicale en ligne, et dispositif ainsi que support de stockage - Google Patents

Procédé et appareil d'inspection intelligente pour un médicament sur ordonnance médicale en ligne, et dispositif ainsi que support de stockage Download PDF

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WO2023029511A1
WO2023029511A1 PCT/CN2022/087816 CN2022087816W WO2023029511A1 WO 2023029511 A1 WO2023029511 A1 WO 2023029511A1 CN 2022087816 W CN2022087816 W CN 2022087816W WO 2023029511 A1 WO2023029511 A1 WO 2023029511A1
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prescription
information
drug
patient
detected
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PCT/CN2022/087816
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English (en)
Chinese (zh)
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侯永帅
吴汉
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康键信息技术（深圳）有限公司
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Publication of WO2023029511A1 publication Critical patent/WO2023029511A1/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/02—Knowledge representation; Symbolic representation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • 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

Definitions

  • the present application relates to the field of artificial intelligence technology, and in particular to an online medical prescription drug intelligent inspection method, device, electronic equipment and computer-readable storage medium.
  • the inspection method of prescription medication in the online medical scene is manual inspection, and when the pharmacy doctor checks the prescription, he pays more attention to the drug matching in the prescription. Due to the lack of understanding of the specific situation of the patient, he rarely checks the drug and the Matching of patient condition. Therefore, the accuracy rate of the prescription drug inspection method in the current online medical scene is low.
  • An online medical prescription drug intelligent inspection method provided by this application includes:
  • a decision result of the prescription to be detected is judged according to the score of the prescription to be detected and a preset threshold.
  • the present application also provides an online medical prescription drug intelligent inspection device, which includes:
  • the information extraction module is used to obtain the prescription to be detected and patient consultation information, and query the preset drug knowledge base according to the prescription to be detected to obtain the medication conditions of the prescription to be detected;
  • a text matching module configured to use a preset text matching model to calculate the matching score of the medication condition and the patient's medical inquiry information, and judge whether the prescription to be detected is consistent with the patient's medical inquiry information through the matching score conflict;
  • the prescription drug name value prediction module is used to predict the prescription of the patient's consultation information by using the intelligent detection model of the prescription drug that is pre-trained and completed when the prescription to be detected does not conflict with the patient's consultation information, and obtains Predict the score of each drug name in the prescription;
  • the comprehensive scoring module is used to calculate the score of the prescription to be detected by using the score of each drug name in the predicted prescription;
  • a decision-making module configured to judge the decision-making result of the prescription to be detected according to the score of the prescription to be detected and a preset threshold.
  • the present application also provides an electronic device, the electronic device comprising:
  • a memory storing at least one instruction
  • the processor executes the instructions stored in the memory to realize the following online medical prescription drug intelligent inspection method:
  • a decision result of the prescription to be detected is judged according to the score of the prescription to be detected and a preset threshold.
  • the present application also provides a computer-readable storage medium, wherein at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is executed by a processor in an electronic device to realize online medical prescription drug intelligence as described below Inspection Method:
  • a decision result of the prescription to be detected is judged according to the score of the prescription to be detected and a preset threshold.
  • FIG. 1 is a schematic flow diagram of an online medical prescription drug intelligent inspection method provided by an embodiment of the present application
  • Fig. 2 is a schematic diagram of a detailed implementation process of one of the steps in the online medical prescription drug intelligent inspection method shown in Fig. 1;
  • Fig. 3 is a detailed implementation flow diagram of one of the steps in the online medical prescription drug intelligent inspection method shown in Fig. 1;
  • Fig. 4 is a functional block diagram of an online medical prescription drug intelligent inspection device provided by an embodiment of the present application.
  • Fig. 5 is a schematic structural diagram of an electronic device implementing the online medical prescription intelligent inspection method provided by an embodiment of the present application.
  • An embodiment of the present application provides an online medical prescription drug intelligent inspection method.
  • the execution subject of the online medical prescription drug intelligent inspection method includes but is not limited to at least one of electronic devices such as a server end and a terminal that can be configured to execute the method provided by the embodiment of the present application.
  • the online medical prescription drug intelligent inspection method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a block chain platform.
  • the server can be an independent server, or provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (ContentDeliveryNetwork , CDN), and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms.
  • the online medical prescription drug intelligent inspection method includes:
  • the detection prescription is a prescription issued by a doctor in the online medical system, including the drug name, usage, dosage, etc.
  • the patient consultation information is the patient consultation information in the online medical system, including gender, age, pregnancy status, breastfeeding status, medication status, contraindications, allergy history, consultation content, diagnosis results, etc.
  • the preset drug knowledge base is a drug knowledge base checked and checked by doctors, including prescription database, age drug database, contraindication drug database, allergy history drug database, drug efficacy conflict database, etc.
  • the prescription database includes efficacy information of medicines and the like.
  • the medication conditions refer to the drug use conditions, including but not limited to applicable age, contraindication information, and allergy information.
  • said S1 includes:
  • the contraindication information and the allergy information are obtained in combination.
  • a drug is suitable for age information: no age limit; contraindication information: use with caution for infants, those with impaired liver and kidney function, use with caution for late-gestation puerpera, breast-feeding Contraindicated for women; allergy information: It is contraindicated for those who are allergic to penicillin or other penicillin-like drugs.
  • contraindication information use with caution for infants, those with impaired liver and kidney function, use with caution for late-gestation puerpera, breast-feeding Contraindicated for women
  • allergy information It is contraindicated for those who are allergic to penicillin or other penicillin-like drugs.
  • Before taking the drug ask the patient whether there is any allergy history. For those who have not used penicillin for 24 hours, an intradermal sensitivity test should be done. If the test result is positive, it should be contraindicated , Those who are allergic to penicillin or other penicillin drugs, those with allergic diseases and allergic states are prohibited.
  • a preset text matching model may be used to calculate the matching score between the medication condition and the patient's medical inquiry information.
  • the text matching model includes a convolutional representation layer, a similarity matching layer, and a fully connected layer, wherein the convolutional representation layer can process the text information to obtain a vector representation of the text information; wherein the similarity matching The layer can perform outer product on the text to be matched to obtain a similarity matrix; wherein the fully connected layer can obtain a matching score by normalizing a two-dimensional vector through softmax.
  • the S2 includes:
  • the attention weight is used to improve the matching accuracy of the medication condition and the corresponding patient inquiry information, thereby improving the inspection accuracy of the prescription to be inspected.
  • the embodiment of the present application judges whether the prescription to be detected conflicts with the patient inquiry information by comparing a preset threshold with the matching score.
  • the prescription to be tested when the matching score is less than the preset threshold, and the prescription to be tested conflicts with the corresponding patient consultation information, the decision result of the prescription to be tested is given, and the prescription to be tested is sent to fail prompt information.
  • the medication conditions include: those who are allergic to penicillin or other penicillin-like drugs are prohibited, and the patient inquiry information includes: if the patient is allergic to penicillin, then a prompt message will be sent that the prescription to be tested fails.
  • the prescription to be tested does not conflict with the patient’s consultation information, for example: the medication condition includes allergy to penicillin or other penicillin-like drugs It is prohibited for those who are breast-feeding, and the patient’s consultation information includes: no allergic drug, male, indicating that the medication condition matches the patient’s consultation information.
  • the preset prescription drug intelligent detection model includes a BERT model, an encoder, and a CNN model
  • the BERT model is a large-scale pre-trained language model based on a bidirectional Transformer, which has powerful language representation capabilities and The feature extraction capability can extract and match the features of each word in the text
  • the CNN model is a deep neural network model consisting of multiple convolutional layers.
  • the training process of the prescribed drug intelligent detection model completed by the preset training in S5 includes:
  • the predicted prescription drug name and the doctor-approved prescription drug name are word-segmented and vectorized respectively to obtain the predicted prescription drug name vector and the doctor-approved prescription drug name vector;
  • a loss value between the predicted prescription drug name and the doctor-approved prescription drug name is calculated according to the predicted prescription drug name vector and the doctor-approved prescription drug name vector.
  • the predicted prescription drug name vector in the embodiment of the present application can be expressed as: (x 1 , x 2 ,..., x n ), and the doctor’s approved prescription drug name vector can be expressed as: (y 1 , y 2 , ...,y n ).
  • the following cross-entropy loss function is used to calculate the loss value L(x, y) between the predicted prescription drug name and the prescription drug name approved by the doctor:
  • N represents the total number of vectors of the predicted prescription drug name
  • l n represents the difference value between the nth vector in the predicted prescription drug name and the nth vector of the prescription drug name approved by the doctor
  • x n represents the Predict the nth vector value of the prescription drug name
  • y n represents the nth vector value of the prescription drug name approved by the doctor
  • t represents the number of iterations in the training process.
  • the loss value adjusts the parameters of the prescription drug intelligent detection model to obtain the trained prescription drug intelligent detection model, including:
  • an optimization algorithm is used to optimize the parameters of the prescription drug intelligent detection model
  • the Adadelta optimization algorithm when the loss value of the loss function is greater than the preset loss threshold, the Adadelta optimization algorithm is used to optimize the parameters of the prescription drug intelligent detection model, and the Adadelta optimization algorithm can adaptively adjust the prescription drug intelligent detection model training process
  • the learning rate in the middle makes the prescription drug intelligent model more accurate and improves the accuracy of predicting the prescription drug name.
  • the prescription score to be detected is calculated according to a preset weighting function, for example: the drug names of the predicted prescription are: drug x 1 , drug x 2 , drug x 3 , drug x 4 , the drug x 1 , drug x 2 ,
  • the matching scores of medicine x 3 and medicine x 4 are respectively: X 1 , X 2 , X 3 , and X 4
  • the names of the prescribed medicines to be tested are: medicine x 1 and medicine x 2 respectively;
  • the preset function formula is :
  • S represents the score value of the prescription to be detected
  • Xi represents the drug name value of the drug name of the prescription drug to be detected is the same as the predicted prescription drug name; i is the number of Xi .
  • the decision result includes: the result of the prescription to be tested passing, the result of the prescription to be tested failing, the result of the prescription to be tested to be confirmed; wherein the prescription to be tested is to be confirmed
  • the result indicates that the prescription to be tested needs to be further confirmed manually, and a reminder message that the prescription to be tested needs to be further confirmed is sent to the doctor.
  • the application of this application queries the preset drug knowledge base through the information of the prescription drug to be detected, obtains the medication condition of the prescription drug information to be detected, and judges whether the medication condition conflicts with the patient's consultation information, and if so If there is a conflict, the prescription to be detected will not pass. If there is no conflict, the patient’s consultation information will be predicted by the pre-trained intelligent detection model of prescription medication, and the scores of each drug in the predicted prescription will be obtained. The value of the prescription to be tested is scored, and the prescription to be tested is judged to pass, fail or to be confirmed according to the score of the prescription to be tested, so as to improve the accuracy of prescription drug inspection in the online medical system.
  • FIG. 4 it is a functional block diagram of an online medical prescription drug intelligent inspection device provided by an embodiment of the present application.
  • the online medical prescription drug intelligent inspection device 100 described in this application can be installed in an electronic device.
  • the online medical prescription drug intelligent inspection device 100 may include: an information extraction module 101 , a text matching module 102 , a prescription drug name value prediction module 103 , a comprehensive scoring module 104 , and a decision-making module 105 .
  • the module described in this application can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of the electronic device and can complete fixed functions, and are stored in the memory of the electronic device.
  • each module/unit is as follows:
  • the information extraction module 101 is used to obtain the prescription to be detected and patient consultation information, and query the preset drug knowledge base according to the prescription to be detected to obtain the medication conditions of the prescription to be detected;
  • the text matching module 102 is configured to use a preset text matching model to calculate the matching score of the medication condition and the patient consultation information, and judge whether the prescription to be detected matches the patient consultation information through the matching score. conflict of information;
  • the prescription drug name value prediction module 103 is used to predict the prescription of the patient's consultation information by using the intelligent detection model of the prescription drug that has been pre-trained and completed when the prescription to be detected does not conflict with the patient's consultation information, Get the score of each drug name in the predicted prescription;
  • the comprehensive scoring module 104 is used to calculate the score of the prescription to be tested by using the score of each drug name in the predicted prescription;
  • the decision module 105 is configured to judge the decision result of the prescription to be detected according to the score of the prescription to be detected and a preset threshold.
  • each module in the online medical prescription drug intelligent inspection device 100 described in the embodiment of the present application adopts the same technical means as the online medical prescription drug intelligent inspection method described in the flowchart in the above-mentioned drawings when used, And can produce the same technical effect, and will not repeat them here.
  • FIG. 5 it is a schematic structural diagram of an electronic device implementing an online medical prescription drug intelligent inspection method provided by an embodiment of the present application.
  • the electronic device 1 may include a processor 10, a memory 11 and a bus, and may also include a computer program stored in the memory 11 and operable on the processor 10, such as an online medical prescription drug intelligent inspection program.
  • the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card type memory (for example: SD or DX memory, etc.), magnetic memory, magnetic disk, Optical discs, etc., the computer-readable storage medium may be non-volatile or volatile.
  • the storage 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1 .
  • the memory 11 can also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk equipped on the electronic device 1, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, flash memory card (FlashCard), etc.
  • the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device.
  • the memory 11 can not only be used to store application software and various data installed in the electronic device 1, such as codes of an online medical prescription drug intelligent inspection program, etc., but also can be used to temporarily store data that has been output or will be output.
  • the processor 10 may be composed of integrated circuits, for example, may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same function or different functions, including one or more A combination of central processing unit (Central Processing unit, CPU), microprocessor, digital processing chip, graphics processor and various control chips, etc.
  • the processor 10 is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, and runs or executes programs or modules stored in the memory 11 (such as online medical Prescription drug intelligent inspection program, etc.), and call the data stored in the memory 11 to execute various functions of the electronic device 1 and process data.
  • the bus may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (EISA for short) bus or the like.
  • PCI peripheral component interconnect
  • EISA extended industry standard architecture
  • the bus can be divided into address bus, data bus, control bus and so on.
  • the bus is configured to realize connection and communication between the memory 11 and at least one processor 10 and the like.
  • FIG. 5 only shows an electronic device with components. Those skilled in the art can understand that the structure shown in FIG. 5 does not constitute a limitation to the electronic device 1, and may include fewer or more components, or combinations of certain components, or different arrangements of components.
  • the electronic device 1 can also include a power supply (such as a battery) for supplying power to various components.
  • the power supply can be logically connected to the at least one processor 10 through a power management device, so that the power supply can be controlled by power management.
  • the device implements functions such as charge management, discharge management, and power consumption management.
  • the power supply may also include one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.
  • the electronic device 1 may also include various sensors, bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.
  • the electronic device 1 may also include a network interface.
  • the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which are usually used in the electronic device 1 Establish a communication connection with other electronic devices.
  • the electronic device 1 may further include a user interface, which may be a display (Display) or an input unit (such as a keyboard (Keyboard)).
  • the user interface may also be a standard wired interface or a wireless interface.
  • the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, Organic Light Emitting Diode) touch device, and the like.
  • the display may also be appropriately called a display screen or a display unit, and is used for displaying information processed in the electronic device 1 and for displaying a visualized user interface.
  • the online medical prescription drug intelligent inspection program stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can realize:
  • a decision result of the prescription to be detected is judged according to the score of the prescription to be detected and a preset threshold.
  • the integrated modules/units of the electronic device 1 are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the computer-readable storage medium may be volatile or non-volatile.
  • the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory) ).
  • the present application also provides a computer-readable storage medium, the readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, it can realize:
  • a decision result of the prescription to be detected is judged according to the score of the prescription to be detected and a preset threshold.
  • modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional module in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software function modules.
  • Blockchain essentially a decentralized database, is a series of data blocks associated with each other using cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify its Validity of information (anti-counterfeiting) and generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.
  • AI artificial intelligence
  • the embodiments of the present application may acquire and process relevant data based on artificial intelligence technology.
  • artificial intelligence is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

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Abstract

La présente demande concerne le domaine technique de l'intelligence artificielle et du traitement médical numérique, et divulgue un procédé d'inspection intelligente pour un médicament sur ordonnance médicale en ligne, consistant à : interroger une base de connaissances de médicaments prédéfinie en fonction d'informations de médicament d'une ordonnance à détecter, pour obtenir des conditions de médicament des informations de médicament de l'ordonnance à détecter ; déterminer si les conditions du médicament sont en conflit avec des informations d'interrogation de patient ; si un conflit existe, déterminer que l'ordonnance à détecter ne passe pas la détection ; si aucun conflit n'existe, prédire les informations d'interrogation de patient au moyen d'un modèle de détection intelligente entraîné prédéfinie pour le médicament sur ordonnance pour obtenir des scores de tous les médicaments dans une ordonnance prédite ; noter, au moyen des scores de tous les médicaments dans l'ordonnance prédite, l'ordonnance à détecter ; et déterminer, en fonction du score de l'ordonnance à détecter, un résultat de décision de l'ordonnance à détecter. La présente demande concerne en outre un appareil d'inspection intelligente pour un médicament sur ordonnance dans un système médical en ligne, un dispositif et un support. La présente demande peut améliorer la précision de l'inspection de médicament sur ordonnance dans le système médical en ligne.
PCT/CN2022/087816 2021-08-30 2022-04-20 Procédé et appareil d'inspection intelligente pour un médicament sur ordonnance médicale en ligne, et dispositif ainsi que support de stockage WO2023029511A1 (fr)

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CN109920508A (zh) * 2018-12-28 2019-06-21 安徽省立医院 处方审核方法及系统
CN111986770A (zh) * 2020-08-31 2020-11-24 平安医疗健康管理股份有限公司 药方用药审核方法、装置、设备及存储介质
CN113674858A (zh) * 2021-08-30 2021-11-19 康键信息技术（深圳）有限公司 在线医疗处方用药智能检查方法、装置、设备及存储介质

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CN116631573A (zh) * 2023-07-25 2023-08-22 讯飞医疗科技股份有限公司 一种处方用药审核方法、装置、设备及存储介质
CN116662375A (zh) * 2023-08-02 2023-08-29 湖南远跃科技发展有限公司 一种基于his的处方数据校验方法及系统
CN116662375B (zh) * 2023-08-02 2023-10-10 湖南远跃科技发展有限公司 一种基于his的处方数据校验方法及系统
CN116936021A (zh) * 2023-09-18 2023-10-24 万链指数(青岛)信息科技有限公司 一种基于区块链的医疗电子病历信息管理方法及系统

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