WO2016070439A1 - Method, system and device for intelligently selecting medicine - Google Patents

Abstract

A method, system and device for intelligently selecting medicine, the method comprising: establishing a multi-dimensional attribute item dictionary (101); extracting medicine usage factor information (102); processing the medicine usage factor information according to the multi-dimensional attribute item dictionary (103); extracting related factor information of medicine used for a patient (104); according to the multi-dimensional attribute item dictionary, processing the related factor information of medicine used for the patient (105); conducting intelligent medicine selection matching and comparison on each attribute item information in the medicine usage factor information and the related factor information of medicine used for the patient (106); and generating an intelligent medicine selection list (107). The method, system and device for intelligently selecting medicine utilizes information technology to analyze and process a large amount of medicine usage data, and provides an intelligent medicine selection method.

Description

Method, system and device for intelligent drug selection Technical field

The invention relates to the technical field of intelligent drug information processing, in particular to a method and system for intelligent drug selection.

Background technique

A drug is a substance used to prevent, treat, or diagnose a person's disease, purposefully regulate a person's physiology, and specify an indication or function, usage, and dosage. Choosing the right medicine and the correct dosage are important issues related to the health and safety of patients.

The selection of suitable drugs and dosages involves a variety of factors and a large number of medical and pharmaceutical data. It is difficult to obtain all the key data of patients and can not be comprehensively obtained by doctors or patients when they choose drugs by existing methods. The complex relationship between the analysis of drugs easily leads to the loss of key information, which brings hidden dangers to patients' health and safety.

The method and system are aimed at safe, effective and economical medicine, and are comprehensively analyzed based on various dimensions such as patients, diseases, medicines, etc., and are suitable for doctors' prescriptions or formulating medication plans, drugstore pharmacists/store clerk recommended drugs, and patients independently selecting OTC ( Over The Counter) A pharmaceutical intelligent system that assists in the selection of drugs and usage in various application scenarios such as pharmaceuticals.

Summary of the invention

The invention provides a method, system and device for intelligent drug selection.

A method for intelligent drug selection, characterized in that the method comprises:

Create a dictionary of multi-dimensional attribute items;

Extracting drug use element information;

Processing the drug use element information according to the multi-dimensional attribute item dictionary;

Extracting information about the relevant elements of the patient's medication;

Processing the drug related factor information according to the multi-dimensional attribute item dictionary;

The intelligent drug selection matching is performed by comparing the information of the drug use element with the information of each attribute item in the information related to the drug use of the patient;

Generate a smart drug selection list;

Generate a smart usage usage plan.

Preferably, the multi-dimensional attribute item dictionary is established according to the medical or pharmaceutical attribute structure of the medication information and the definition of each attribute.

Preferably, the multi-dimensional attribute item dictionary is used to provide a standard dictionary related to various medical or pharmaceutical attributes in the drug use information and the patient medication information.

Preferably, the multi-dimensional attribute item dictionary is used to provide the drug source usage information and the drug information of the patient, and the different sources of the medical or pharmaceutical attributes are associated with the standard dictionary.

Preferably, the multi-dimensional attribute item dictionary splits the drug use information into the minimum attribute item according to different medical or pharmaceutical attributes, and saves the logical relationship between the attribute items, and the data of each minimum attribute item is Standard medical or pharmaceutical attribute item dictionary library association.

Preferably, the medical attribute items involved in the multi-dimensional attribute item dictionary include at least: a population-related attribute of the patient, a specific attribute of the patient, a disease-related attribute of the patient, a symptom-related attribute of the patient, a related history attribute of the patient, At least one dimension of the patient's operation-related attributes, the patient's personal life history-related attributes, the patient's physiological state-related attributes, and the patient's examination-related attributes.

Preferably, the pharmacy attribute items involved in the multi-dimensional attribute item dictionary include at least: a related attribute of the drug purpose, a related attribute of the drug component, a related attribute of the drug specification package, a related attribute of the drug indication, a related attribute of the drug usage and dosage, Relevant attributes of drug administration routes, related attributes of drug contraindications, related attributes of adverse drug reactions, related attributes of drug precautions, related attributes of patient allergy history, related attributes of patient medication history, relevant attributes of drug administration routes of patients, At least one of the dimensions of the patient's medication-related gene properties, and the like.

Preferably, the intelligent drug selection list is generated by the selection of the drug.

Preferably, the method further comprises excluding the unsuitable drug by a single auditing dimension of the drug contraindication, the drug allergy and the like, and generating a smart drug selection list.

Preferably, the method further comprises generating an intelligent drug selection list by including drug interactions, repeated medications, and the like to exclude unsuitable drugs from all of the patient's reform review dimensions of the drug.

Preferably, the method further comprises performing a medical insurance review on the smart drug selection list.

Preferably, the method further comprises generating a smart drug selection list by personalized screening.

Preferably, the method further comprises generating usage and usage recommendation information.

Preferably, the information on the use of the medicine is extracted, and the information of the relevant medical/pharmaceutical attribute elements of the indications, the usage and dosage conditions, and the contraindications of the medication are extracted for each medicine use information.

Preferably, the drug use information is derived from at least one of a drug instruction manual, a pharmacopoeia, a national formulary, a treatment/drug guide, an expert consensus, and medication regulations at various levels of medical institutions.

Preferably, the patient medication related information is extracted for extracting actual information about the relevant attribute elements of the patient medication.

Preferably, the source of the patient medication information is at least one of a doctor's prescription, a treatment plan, a medication plan, a medical record, a medical record, a medical record, an examination result, a patient self-reported symptom, and a patient's self-selection drug.

Preferably, the way to generate a matching comparison result is,

The age element of an indication for this drug matches the age element in the patient's medication information:

The match between the indication of the drug and the patient's medication information for the patient is:

Patient Pa, whether the result of using this drug Med is:

Among them, a patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym) There are both history (his), family disease (fam), allergic history (ale), and other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).

Preferably, the smart drug selection list is excluded by the drug single-item review dimension, the smart drug selection list is further excluded by the drug reforming review dimension, the medical insurance list is selected for the smart drug selection list, and the personalized insurance screening is performed. The order in which the smart drug selection list is generated can be adjusted according to the usage.

Preferably, the method can be used to assist at least one of a doctor's prescription, a pharmacist formulating a medication regimen, a smart recommendation drug for a patient's self-selected drug (OTC), and a pharmacy smart service for usage and dosage.

A system for intelligent drug selection, characterized in that the system comprises:

a drug use element information extracting unit for extracting drug use element information;

a multi-dimensional attribute item dictionary unit for providing a multi-dimensional attribute item dictionary;

The multi-dimensional processing unit of the medicine use element information processes the medicine use element information according to the multi-dimensional attribute item dictionary unit;

The patient medication related element information extraction unit is configured to extract information about the patient medication related elements;

The multi-dimensional processing unit for patient medication related element information processes the information related to the patient medication according to the multi-dimensional attribute item dictionary unit;

The intelligent drug selection matching unit compares the drug use element information with the information of each attribute item in the patient drug related element information for intelligent drug selection and matching;

Intelligent drug selection unit to generate a smart drug selection list;

The intelligent usage and usage unit generates a smart usage and usage plan.

Preferably, the multi-dimensional attribute item dictionary unit is established according to the medical or pharmaceutical attribute structure of the medication information and the definition of each attribute.

Preferably, the multi-dimensional attribute item dictionary unit is configured to provide a standard dictionary related to various medical or pharmaceutical attributes in the drug use information and the patient medication information.

Preferably, the multi-dimensional attribute item dictionary unit is configured to provide a drug dictionary use information and a drug dictionary information, and different medical source or drug attribute different origins from the standard dictionary.

Preferably, the multi-dimensional attribute item dictionary unit splits the drug use information into the minimum attribute item according to different medical or pharmaceutical attributes, and simultaneously saves the logical relationship between the attribute items, and records the data of each minimum attribute item. Associated with a standard medical or pharmaceutical attribute item dictionary library.

Preferably, the medical attribute items involved in the multi-dimensional attribute item dictionary include at least: a population-related attribute of the patient, a specific attribute of the patient, a disease-related attribute of the patient, a symptom-related attribute of the patient, a related history attribute of the patient, At least one dimension of the patient's operation-related attributes, the patient's personal life history-related attributes, the patient's physiological state-related attributes, and the patient's examination-related attributes.

Preferably, the pharmacy attribute items involved in the multi-dimensional attribute item dictionary include at least: a related attribute of the drug purpose, a related attribute of the drug component, a related attribute of the drug specification package, a related attribute of the drug indication, a related attribute of the drug usage and dosage, Relevant attributes of drug administration routes, related attributes of drug contraindications, related attributes of adverse drug reactions, related attributes of drug precautions, related attributes of patient allergy history, related attributes of patient medication history, relevant attributes of drug administration routes of patients, At least one of the dimensions of the patient's medication-related gene properties, and the like.

Preferably, the intelligent drug selection list is generated by the selection of the drug.

Preferably, the system further comprises an intelligent drug selection unit for eliminating unsuitable drugs by a single review dimension of drugs such as drug contraindications and drug allergy.

Preferably, the system further comprises an intelligent drug selection unit that covers all of the patient's re-inspection dimensions of the drug by drug interaction, re-use, and the like.

Preferably, the system further comprises a medical insurance review unit.

Preferably, the system further comprises a personalized screening intelligent drug selection unit.

Preferably, the system further comprises a usage and dosage recommendation unit.

Preferably, the medicine use element information extracting unit is configured to extract information about the indications, the usage and dosage conditions, and the medical/pharmacy attribute elements of the medication contraindications for each medicine use information.

Preferably, the drug use information is derived from at least one of a drug instruction manual, a pharmacopoeia, a national formulary, a treatment/drug guide, an expert consensus, and medication regulations at various levels of medical institutions.

Preferably, the patient medication related information extracting unit is configured to extract actual information of related attribute elements when the patient takes medication.

Preferably, the source of the patient medication information is at least one of a doctor's prescription, a treatment plan, a medication plan, a medical record, a medical record, a medical record, an examination result, a patient self-reported symptom, and a patient's self-selection drug.

Preferably, the way to generate a matching comparison result is,

The age element of an indication for this drug matches the age element in the patient's medication information:

The match between the indication of the drug and the patient's medication information for the patient is:

Patient Pa, whether the result of using this drug Med is:

Among them, a patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym) There are both history (his), family disease (fam), allergic history (ale), and other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i ,ag,gen,spe,sym,his,fam,ale, Oth)).

Preferably, the intelligent drug selection unit that excludes unsuitable drugs through the single item review dimension, the intelligent drug selection unit that further excludes inappropriate drugs through the drug reforming review dimension, the medical insurance review unit, and the personalized screening intelligent drug selection unit are successively The order can be adjusted according to the order.

Preferably, the system can be used to assist at least one of a doctor's prescription, a pharmacist formulating a medication regimen, a smart recommendation drug for a patient's self-selected drug (OTC), and a pharmaceutical intelligent system for usage and dosage.

An intelligent drug selection device, characterized in that the device comprises:

a drug use element information extraction module for extracting drug use element information;

a multi-dimensional attribute item dictionary module for providing a multi-dimensional attribute item dictionary;

The multi-dimensional processing module of the drug use element information processes the drug use element information according to the multi-dimensional attribute item dictionary module;

The patient medication related element information extraction module is used for extracting information about the relevant elements of the patient medication;

The multi-dimensional processing module for patient medication related element information processes the information related to the patient medication according to the multi-dimensional attribute item dictionary module;

The intelligent drug selection matching comparison module compares the drug use element information with the information of each attribute item in the patient drug related element information for intelligent drug selection and matching;

Intelligent drug selection module to generate a smart drug selection list;

Preferably, the multi-dimensional attribute item dictionary module is established according to the medical or pharmaceutical attribute structure of the medication information and the definition of each attribute.

Preferably, the multi-dimensional attribute item dictionary module is configured to provide a standard dictionary related to various medical or pharmaceutical attributes in the drug use information and the patient medication information.

Preferably, the multi-dimensional attribute item dictionary module is configured to provide a drug dictionary using the drug source information and the patient medication information in different medical or pharmaceutical attributes from different sources and a standard dictionary.

Preferably, the multi-dimensional attribute item dictionary module splits the drug use information into the minimum attribute item according to different medical or pharmaceutical attributes, and simultaneously saves the logical relationship between the attribute items, and records the data of each minimum attribute item. Associated with a standard medical or pharmaceutical attribute item dictionary library.

Preferably, the medical attribute items involved in the multi-dimensional attribute item dictionary module include at least: a population-related attribute of the patient, a specific attribute of the patient, a disease-related attribute of the patient, a symptom-related attribute of the patient, and a related history attribute of the patient. At least one dimension of the patient's operation-related attributes, the patient's personal life history-related attributes, the patient's physiological state-related attributes, and the patient's examination-related attributes.

Preferably, the pharmacy attribute items involved in the multi-dimensional attribute item dictionary module include at least: relevant attributes of the drug purpose, related attributes of the drug component, relevant attributes of the drug specification package, related attributes of the drug indication, and related attributes of the drug usage and dosage. Relevant attributes of drug administration routes, related attributes of drug contraindications, related attributes of adverse drug reactions, related attributes of drug precautions, related attributes of patient allergy history, related attributes of patient medication history, and related attributes of drug administration routes of patients At least one of the dimensions of the drug-related gene properties of the patient.

Preferably, the intelligent drug selection list is generated by the selection of the drug.

Preferably, the device further comprises a module for generating an intelligent drug selection list by excluding unsuitable drugs through a single auditing dimension of drugs such as drug contraindications and drug allergy.

Preferably, the device further comprises a module for generating an intelligent drug selection list by using a drug interaction, a repeated drug, or the like to cover all of the patient's re-inspection dimensions of the drug in use.

Preferably, the device further comprises a medical insurance review module.

Preferably, the device further comprises a personalized screening intelligent drug selection module.

Preferably, the device further comprises a usage and dosage recommendation module.

Preferably, the medicine use element information extraction module is configured to extract information about the indications, the usage and dosage conditions, and the medical/pharmacy attribute elements of the medication contraindications for each medicine use information.

Preferably, the drug use information is derived from at least one of a drug instruction manual, a pharmacopoeia, a national formulary, a treatment/drug guide, an expert consensus, and medication regulations at various levels of medical institutions.

Preferably, the patient medication related information extraction module is configured to extract actual information of related attribute elements when the patient takes medication.

Preferably, the source of the patient medication information is at least one of a doctor's prescription, a treatment plan, a medication plan, a medical record, a medical record, a medical record, an examination result, a patient self-reported symptom, and a patient's self-selection drug.

Preferably, the way to generate a matching comparison result is:

The age element of an indication for this drug matches the age element in the patient's medication information:

The match between the indication of the drug and the patient's medication information for the patient is:

Patient Pa, whether the result of using this drug Med is:

Among them, a patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym) There are both history (his), family disease (fam), allergic history (ale), and other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).

Preferably, the single-audit dimension excludes the unsuitable drug intelligent drug selection module, the re-inspection dimension excludes the unsuitable drug intelligent drug selection module, the medical insurance review module, and the personalized screening intelligent drug selection module. The order can be adjusted according to the order.

Preferably, the device can be used to assist at least one of a doctor's prescription, a pharmacist's medication plan, a smart recommendation drug for the patient's self-selected drug (OTC), and a pharmacy service for usage.

Preferably, the device includes, but is not limited to, a medical institution doctor workstation, a pharmacist workstation, a pharmacy pharmacist workstation, a clerk workstation, a patient self-service terminal, and the patient can access an internet device (computer, smart TV, mobile computer, smart phone, smart watch) Wait).

DRAWINGS

Figure 1 shows a schematic structural view of a system according to the present invention;

2 is a flow chart showing a method of intelligent drug selection according to the present invention;

3 is a flow chart showing a method for eliminating inappropriate drugs according to the single item review dimension according to the present invention;

4 is a flow chart showing a method for excluding an unsuitable drug according to the drug reforming review dimension of the present invention;

5 is a flow chart showing a method for performing medical insurance review on an intelligent drug selection list according to the present invention;

Figure 6 is a flow chart showing the method of personalized screening according to the present invention;

Figure 7 is a flow chart showing the method of usage and dosage recommendation according to the present invention;

Figure 8 is a diagram showing the functional structure of an intelligent drug selection system according to the present invention;

Figure 9 is a diagram showing the functional structure of a single item review dimension to exclude an inappropriate drug system according to the present invention;

Figure 10 is a diagram showing the functional structure of the drug reforming review dimension according to the present invention for eliminating an inappropriate drug system;

11 is a diagram showing the functional structure of a medical insurance review system for an intelligent drug selection list according to the present invention;

Figure 12 is a diagram showing the functional structure of a personalized screening system in accordance with the present invention;

Figure 13 is a diagram showing the functional structure of the usage and dosage recommendation system according to the present invention;

detailed description

The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Fig. 1 shows a system configuration diagram of the present invention. Among them, the workstation is connected to the server through the public network or the internal network of the medical institution and the retail pharmacy. The workstation includes a physician workstation, a pharmacist workstation, a clerk workstation, a patient self-service terminal, and the like. The workstation may be at least one of a PC terminal, a mobile terminal, a wearable device, and the like. The network architecture of the workstation and server can be either a C/S architecture or a B/S architecture.

2 is a schematic diagram showing the workflow of an intelligent drug selection method according to an embodiment of the present invention.

In step 101, a multi-dimensional attribute item dictionary is established.

A multi-dimensional attribute item dictionary for providing a standard dictionary related to various medical or pharmaceutical attributes in drug use information and patient medication information, and a relationship between different source synonyms and a standard dictionary, and is based on medical or pharmaceutical attribute information for drug use information. A structured standard database built with multi-dimensional splits.

Drug use information comes from drug instructions, pharmacopoeia, national formulary, treatment/drug guidelines, expert consensus, and medication regulations at all levels of medical institutions. This information can be divided into a variety of information types such as drug indications, usage and dosage conditions, and medication contraindications.

Drug indication information refers to all information about the conditions applicable to the drug. The same drug may need to be applied according to different usage and dosage under different conditions, so the applicable conditions of the drug usage and use refer to the different conditions applicable to different usage and dosage of the same drug. Medication contraindications, that is, regular medication contraindications, refer to all information on the conditions under which drugs are contraindicated. Information on drug indications, applicable conditions for drug usage and dosage, and sources of drug contraindications include: drug instructions, national formulary, national pharmacopoeia, clinical guidelines, medication guidelines, clinical consensus, medical institution in-house pharmacy, and related literature.

Information on drug indications, usage and dosage, and contraindications for medication contain a large amount of data of different medical or pharmaceutical properties, and these data are separated into minimum attribute items according to their different medical or pharmaceutical properties, and each attribute item is saved. Between the logical relationship, and the data of each minimum attribute item is associated with the standard medical or pharmaceutical attribute item dictionary library, the structuring of the medical indications, the usage and dosage conditions, and the medical or pharmaceutical attribute information corresponding to the drug contraindications can be generated. A standard database that builds a dictionary of multi-dimensional attribute items.

Take the indication information of aspirin enteric-coated tablets as an example:

The indications for indications for aspirin enteric-coated tablets are: prevention of deep vein thrombosis and pulmonary embolism after major surgery; reduction of cardiovascular risk factors (family history of coronary heart disease, diabetes, dyslipidemia, hypertension, obesity, smoking history, age greater than 50) The age of the person) the risk of myocardial infarction.

The indications for the drug in the multi-dimensional attribute item dictionary include:

Attribute item	Property description	Corresponding attribute dictionary
			Type of action	prevention	prevention
operating	Major surgery	Major surgery
			Type of action	Reduce the risk of ...	reduce risk
Family history	Family history of coronary heart disease	Family history of coronary heart disease
			diagnosis	diabetes	diabetes
diagnosis	Dyslipidemia	Hyperlipidemia
			diagnosis	hypertension	hypertension
Special population	obesity	Obese people
			Special population	History of smoking	Smoking history
Age group	Those older than 50 years old	>50

Take the condition information of the usage and dosage of atenolol tablets as an example:

Atenolol tablets commonly used in adults: start each time 6.25 ~ 12.5mg, twice a day, as needed and tolerance to gradually increase to 50 ~ 200mg. In the case of renal dysfunction, the creatinine clearance rate is less than 15ml / (min.1.73m [sup] 2 [/sup]), 25mg daily; 15 ~ 35ml / (min.1.73m [sup] 2 [/sup]) , up to 50mg per day. Or follow the doctor's advice.

Child dosage: for children should start from a small dose of 0.25 ~ 0.5mg / kg, twice a day. Pay attention to monitoring heart rate and blood pressure.

Older medications: The required dose can be reduced, especially in patients with impaired renal function.

The records applicable to the usage of atenolol tablets in the multi-dimensional attribute item dictionary include:

Take the taboo information of omeprazole enteric-coated capsules as an example:

Omeprazole enteric-coated capsules are contraindicated in those who are allergic to the drug, those with severe renal insufficiency, and infants.

Records of contraindications for omeprazole enteric-coated capsules in the multi-dimensional attribute item dictionary include:

Attribute item	Property description	Corresponding attribute dictionary
			allergies	This product	Omeprazole
diagnosis	Severe renal insufficiency	Severe renal insufficiency
			Age group	Infant	<3

The multi-dimensional medical attribute items involved in the multi-dimensional attribute item dictionary include at least: a population-related attribute of the patient, for example, age, gender, weight, height, body surface area, ethnicity, marital status, etc.; specific characteristics of the patient's particular population, for example, Pregnancy, pregnancy, lactation, menopause, etc.; disease-related attributes of the patient, for example, morbidity, course of disease, cause of illness, location of disease, diagnosis, symptoms, test results, physiological indicators, accompanying diseases, sequelae, etc.; History-related attributes, such as family history, disease history, chronic disease history, history of infectious disease, history of vaccination, history of surgical trauma, history of blood transfusion, etc.; patient-related attributes, such as surgery, examination operations, assisted operations, etc.; Life history related attributes, such as birthplaces and long-term residence, lifestyle habits, hobbies such as tobacco/wine/food/drugs, possible health damage from occupational and working conditions, etc. The medical attribute items involved in the multi-dimensional attribute item dictionary include at least the patient's population-related attributes, the patient's special population-related attributes, the patient's disease-related attributes, the patient's past medical history-related attributes, the patient's operational-related attributes, and the patient's personal life history. At least one of the related attributes, etc.

The multi-dimensional pharmacy attribute items involved in the multi-dimensional attribute item dictionary include at least: related attributes of the purpose of the medication, for example, treatment, prevention, examination, diagnosis, etc.; related attributes of the patient's allergy history, for example, history of drug allergy, history of food allergy, allergens Etc.; related properties of the patient's medication history, for example, using special drugs, taking drugs, adverse drug reactions, etc.; relevant attributes of the route of administration of the patient, for example, oral, topical, injection, inhalation, etc.; . The pharmacy attribute items involved in the multi-dimensional attribute item dictionary include at least one of the attributes related to the purpose of the medication, the attributes related to the history of the patient's allergy, the attributes related to the history of the medication of the patient, the relevant attributes of the administration route of the patient, and the genetic properties of the patient medication. Dimensions.

In step 102, drug use element information is extracted. The information on the use of drugs mainly includes information on the indications, the conditions of use and dosage, and the relevant medical or pharmaceutical attribute elements of each drug use information. Drug use information comes from drug instructions, pharmacopoeia, national formulary, treatment/drug guidelines, expert consensus, and medication regulations at all levels of medical institutions.

Step 103: Process the medicine use element information according to the multi-dimensional attribute item dictionary.

Multi-dimensional processing is performed by searching the multi-dimensional attribute item dictionary according to the split information. According to the multi-dimensional attribute item dictionary, different diagnostic names of the same disease in different hospitals can be treated differently, for example, Alzheimer's disease and Alzheimer's disease are treated differently; different dosage forms and specifications of the same medicine can also be processed by different names. The merchandise, which in turn improves the accuracy of the association match.

In step 104, patient medication related element information is extracted. The actual information used to extract the relevant attribute elements of the patient's medication. For example, it includes information such as the patient's gender, age, past medical history, disease name, and illness, and in particular, the necessary information in the drug use information of the drug used by the patient. The source of patient medication information is the doctor's prescription, treatment plan, medication plan, medical record, medical record, drug record, test result, patient's self-reported symptoms, and patient's self-selected drugs.

Step 105: Process the patient medication related element information according to the multi-dimensional attribute item dictionary. Find the attribute item dictionary based on the split information and perform multi-dimensional processing.

In step 106, the intelligent drug selection matches the alignment.

The specific matching comparison formula is described as follows:

A patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym), both History disease (his), family disease (fam), allergic history (ale), other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).

The age element of an indication for this drug matches the age element in the patient's medication information:

The match between the indication of the drug and the patient's medication information for the patient is:

Patient Pa, whether the result of using this drug Med is:

Step 107: Generate an intelligent drug selection list by selecting the drug selection. Drugs that meet the matching rules enter the list of drugs to be selected for the indications.

According to another embodiment of the present invention, referring to FIG. 3, the workflow further includes step 108.

In step 108, the single item review dimension excludes an unsuitable drug to generate a smart drug selection list. The single-item audit information that is unsuitable for use, such as drug contraindications and sensitizing components, is selected and compared with the patient drug information database data, and the system automatically excludes drugs that are unsuitable for use, and further generates a list of recommended drugs. For patients with incomplete medication information, the system prompts the key information to be confirmed by the doctor, pharmacist, clerk and patient, or the patient confirms it and then excludes it.

According to another embodiment of the present invention, the workflow further includes step 109 with reference to FIG.

In step 109, the drug re-inspection dimension excludes an unsuitable drug-generating smart drug selection list. Extracting drug review and drug review information such as drug interaction and repeated drug use in the recommended list after screening, and comparing with the drug history or drug in the patient information database, automatically excluding the existence of interaction, repeated drug use, etc. The drug used further generates a list of recommended drugs. For patients with incomplete medication information, the key information is confirmed by the doctor, pharmacist, clerk and patient, or confirmed by the patient, and then excluded.

According to another embodiment of the present invention, the workflow further includes step 110 with reference to FIG.

Step 110: Perform a medical insurance review on the smart drug selection list. According to the patient's medical insurance and patient medical insurance regulations, the system automatically reviews the medical insurance payment of the recommended drugs, and submits the drugs that need to be paid by the patient to the patient for selection, thereby further generating a list of recommended drugs.

According to another embodiment of the present invention, the workflow further includes step 111 with reference to FIG.

Step 111: Generate a smart drug selection list by personalized screening. According to the needs of the treatment plan or the patient's requirements for other parameters of the selected drug (such as dosage form, medication cycle, frequency of drug use, mouthfeel, brand of drug manufacturer, user evaluation, price, carrying, storage, etc.), by doctor, pharmacist, clerk or patient After selecting the screening elements by yourself (OTC drugs), the list of recommended drugs is automatically filtered to obtain a list of recommended drugs, which are selected by doctors, pharmacists or clerk, and patients (purchasing OTC drugs).

Those skilled in the art can know that 108, 109, 110, 111 in the above steps can adjust their sequence as needed.

According to another embodiment of the present invention, the workflow further includes step 112 with reference to FIG.

Step 112: Generate usage and usage recommendation information. According to the usage and dosage information of the finally selected drugs, the information obtained or confirmed in the previous steps is automatically compared, and the appropriate usage and dosage are recommended to facilitate the confirmation by the doctor, the pharmacist or the clerk, and the patient (purchasing the OTC drug).

FIG. 8 is a schematic diagram showing the functional structure of an intelligent medicine selection system according to an embodiment of the present invention. The system includes a medicine use element information extraction unit 201, a multi-dimensional attribute item dictionary unit 202, and a medicine use element information multi-dimensional processing unit 203. The patient medication related element information extraction unit 204, the patient medication related element information multidimensional processing unit 205, the intelligent drug selection matching unit 206, and the indication intelligent selection unit 207.

Drug use element information extracting unit 201. It is used to extract the information of the relevant medical or pharmaceutical attribute elements of indications, usage and dosage conditions, and medication contraindications in each medicine use information. Drug use information comes from drug instructions, pharmacopoeia, national formulary, treatment/drug guidelines, expert consensus, and medication regulations at all levels of medical institutions.

The multi-dimensional attribute item dictionary unit 202 is configured to provide each of the drug use information and the patient medication information. Standard dictionaries involving medical or pharmaceutical attributes and associations between different sources of different names and standard dictionaries. Information on drug indications, usage and dosage, and contraindications for medication contain a large amount of data of different medical or pharmaceutical properties, and these data are separated into minimum attribute items according to their different medical or pharmaceutical properties, and each attribute item is saved. Between the logical relationship, and the data of each minimum attribute item is associated with the standard medical or pharmaceutical attribute item dictionary library, the structuring of the medical indications, the usage and dosage conditions, and the medical or pharmaceutical attribute information corresponding to the drug contraindications can be generated. A standard database that builds a multidimensional attribute item dictionary unit.

The medicine use element information multi-dimensional processing unit 203 is configured to perform multi-dimensional processing on the split attribute information of the medicine according to the multi-dimensional attribute item dictionary. According to the multi-dimensional attribute item dictionary unit, different diagnostic names of the same disease in different hospitals can also be treated differently, for example, Alzheimer's disease and Alzheimer's disease are treated differently; different dosage forms of the same medicine can also be processed by different names. And the specification of the product, which in turn improves the accuracy of the association match.

The patient medication related element information extracting unit 204 is configured to extract actual information of related attribute elements at the time of patient medication. For example, it includes information such as the patient's gender, age, past medical history, disease name, and illness, and in particular, the necessary information in the drug use information of the drug used by the patient. The source of patient medication information is the doctor's prescription, treatment plan, medication plan, medical record, medical record, drug record, test result, patient's self-reported symptoms, and patient's self-selected drugs.

The patient medication related element information multi-dimensional processing unit 205 performs multi-dimensional processing on the related information according to the multi-dimensional attribute item dictionary. Find the attribute item dictionary based on the split information and perform multi-dimensional processing.

The intelligent drug selection matching unit 206. The following shows a way to generate an association match.

The specific matching comparison formula is described as follows:

A patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym), both History disease (his), family disease (fam), allergic history (ale), other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).

The age element of an indication for this drug matches the age element in the patient's medication information:

The match between the indication of the drug and the patient's medication information for the patient is:

Patient Pa, whether the result of using this drug Med is:

The indication intelligent medicine selection unit 207 generates an intelligent drug selection list through the indication selection medicine. Drugs that meet the matching rules enter the list of drugs to be selected for the indications.

In accordance with another embodiment of the present invention, referring to FIG. 9, the workflow further includes a drug single item review dimension exclusion of the unsuitable drug smart drug selection unit 208.

The drug single item review dimension excludes the unsuitable drug smart drug selection unit 208. The single-item audit information that is unsuitable for use, such as drug contraindications and sensitizing components, is selected and compared with the patient drug information database data, and the system automatically excludes drugs that are unsuitable for use, and further generates a list of recommended drugs. For patients with incomplete medication information, the system prompts the key information to be confirmed by the doctor, pharmacist, clerk and patient, or the patient confirms it and then excludes it.

According to another embodiment of the present invention, the workflow further includes a drug reforming review dimension exclusion of the unsuitable drug smart drug selection unit 209 with reference to FIG.

The unsuitable drug intelligent drug selection unit 209 is dynamically excluded, and the reorganization review excludes the unsuitable drug generation intelligent drug selection list. Extracting drug review and drug review information such as drug interaction and repeated drug use in the recommended list after screening, and comparing with the drug history or drug in the patient information database, automatically excluding the existence of interaction, repeated drug use, etc. The drug used further generates a list of recommended drugs. For patients with incomplete medication information, the key information is confirmed by the doctor, pharmacist, clerk and patient, or confirmed by the patient, and then excluded.

According to another embodiment of the present invention, the workflow further includes a medical insurance review unit 210 with reference to FIG.

The medical insurance review unit 210 performs a medical insurance review on the smart drug selection list. According to the patient's medical insurance and patient medical insurance regulations, the system automatically reviews the medical insurance payment of the recommended drugs, and submits the drugs that need to be paid by the patient to the patient for selection, thereby further generating a list of recommended drugs.

According to another embodiment of the present invention, the workflow further includes personalizing the screening smart selection unit 211 with reference to FIG.

The intelligent screening drug selection unit 211 is personalized to generate an intelligent drug selection list through personalized screening. According to the needs of the treatment plan or the patient's requirements for other parameters of the selected drug (such as dosage form, medication cycle, frequency of drug use, mouthfeel, brand of drug manufacturer, user evaluation, price, carrying, storage, etc.), by doctor, pharmacist, clerk or patient After selecting the screening elements by yourself (OTC drugs), the list of recommended drugs is automatically filtered to obtain a list of recommended drugs, which are selected by doctors, pharmacists or clerk, and patients (purchasing OTC drugs).

Those skilled in the art can know that the above 208 units, 209 units, 210 units, and 211 units can be adjusted according to their needs.

According to another embodiment of the present invention, the workflow further includes a usage usage recommendation unit 212 with reference to FIG.

The usage and dosage recommendation unit 212 generates usage and usage recommendation information. According to the usage and dosage information of the finally selected drugs, the information obtained or confirmed in the previous steps is automatically compared, and the appropriate usage and dosage are recommended to facilitate the confirmation by the doctor, the pharmacist or the clerk, and the patient (purchasing the OTC drug).

The invention further provides an intelligent drug selection device, which comprises a drug use element information extraction module, a multi-dimensional attribute item dictionary module, a drug use element information multi-dimensional processing module, a patient medication related element information extraction module, and a patient medication related element. Information multi-dimensional processing module, intelligent drug selection matching module, indication intelligent drug selection module.

The medicine use element information extraction module is used for extracting information about the indications, the usage and dosage conditions, and the medical or pharmaceutical attribute elements of the medication contraindications for each medicine use information. Drug use information comes from drug instructions, pharmacopoeia, national formulary, treatment/drug guidelines, expert consensus, and medication regulations at all levels of medical institutions.

The multi-dimensional attribute item dictionary module is configured to provide a standard dictionary related to various medical or pharmaceutical attributes in the drug use information and the patient medication information, and a relationship between the different source synonyms and the standard dictionary. Information on drug indications, usage and dosage, and contraindications for medication contain a large amount of data of different medical or pharmaceutical properties, and these data are separated into minimum attribute items according to their different medical or pharmaceutical properties, and each attribute item is saved. Between the logical relationship, and the data of each minimum attribute item is associated with the standard medical or pharmaceutical attribute item dictionary library, the structuring of the medical indications, the usage and dosage conditions, and the medical or pharmaceutical attribute information corresponding to the drug contraindications can be generated. Standard database, establish a multi-dimensional attribute item dictionary module.

The multi-dimensional processing module of the medicine use element information is used for multi-dimensional processing of the separated attribute information of the medicine according to the multi-dimensional attribute item dictionary. According to the multi-dimensional attribute item dictionary module, different diagnostic names of the same disease in different hospitals can also be treated differently, for example, Alzheimer's disease and Alzheimer's disease are treated differently; different dosage forms of the same drug can also be processed by different names. And the specification of the product, which in turn improves the accuracy of the association match.

The patient medication related element information extraction module is used to extract the actual information of the relevant attribute elements when the patient takes medication. For example, it includes information such as the patient's gender, age, past medical history, disease name, and illness, and in particular, the necessary information in the drug use information of the drug used by the patient. The source of patient medication information is the doctor's prescription, treatment plan, medication plan, medical record, medical record, drug record, test result, patient's self-reported symptoms, and patient's self-selected drugs.

The patient medication related element information multi-dimensional processing module performs multi-dimensional processing on the related information according to the multi-dimensional attribute item dictionary. Find the attribute item dictionary based on the split information and perform multi-dimensional processing.

Intelligent drug selection matching module. The following shows a way to generate an association match.

The specific matching comparison formula is described as follows:

A patient (Patient, referred to as Pa), whose patient medication information includes age: (age, abbreviated as ag), Gender (gen, gen), special (spe), symptom (symptom, sym), history disease (his), family disease (fam) Allergic history (referred to as ale), other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

Medi drug (Med) Med, an indication of drug use information is Med(x _i ), and the result of the split is med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).

The age element of an indication for this drug matches the age element in the patient's medication information:

The match between the indication of the drug and the patient's medication information for the patient is:

Patient Pa, whether the result of using this drug Med is:

Indications intelligent drug selection module, through the selection of drugs to generate intelligent drug selection list. Drugs that meet the matching rules enter the list of drugs to be selected for the indications.

In accordance with another embodiment of the present invention, the apparatus further includes excluding an unsuitable pharmaceutical intelligent drug selection module based on a drug individual review dimension.

The drug single-item review excludes the unsuitable drug intelligent drug selection module, extracts the static information that is unsuitable for use, such as drug contraindications and sensitizing components, and compares it with the patient drug information database data. The device automatically excludes the unsuitable use situation. The drug further generates a list of recommended drugs. For patients with incomplete medication information, the device prompts key information to be confirmed by the doctor, pharmacist, clerk and patient, or the patient confirms it and then excludes it.

In accordance with another embodiment of the present invention, the apparatus further includes a drug reforming review to exclude an unsuitable drug intelligent drug selection module.

The drug reforming review excludes the unsuitable drug intelligent drug selection module, extracts the dynamic information such as drug interaction and repeated drug use for the recommended recommendation list after screening, and compares with the drug history or the drug in the patient information database data, automatically Exclude drugs that are not suitable for use, such as interactions and repeated medications, and further generate a list of recommended drugs. For patients with incomplete medication information, the key information is confirmed by the doctor, pharmacist, clerk and patient, or confirmed by the patient, and then excluded.

According to another embodiment of the invention, the device further comprises a medical insurance review module.

The medical insurance review module conducts medical insurance review on the smart drug selection list. According to the patient's medical insurance and patient medical insurance regulations, the device automatically reviews the medical insurance payment for the recommended drugs, and submits the drugs that need to be paid by the patient to the patient for selection, thereby further generating a list of recommended drugs.

According to another embodiment of the invention, the apparatus further comprises a personalized screening intelligent drug selection module.

Personalized screening of intelligent drug selection modules to generate intelligent drug selection lists through personalized screening. According to the needs of the treatment plan or the patient's requirements for other parameters of the selected drug (such as dosage form, medication cycle, frequency of drug use, mouthfeel, brand of drug manufacturer, user evaluation, price, carrying, storage, etc.), by doctor, pharmacist, clerk or patient After selecting the screening elements by yourself (OTC drugs), the list of recommended drugs is automatically filtered to obtain a list of recommended drugs, which are selected by doctors, pharmacists or clerk, and patients (purchasing OTC drugs).

Those skilled in the art can know that the above-mentioned static exclusion unsuitable drug intelligent drug selection module, dynamic exclusion of unsuitable drug intelligent drug selection module, medical insurance examination module, and personalized screening intelligent drug selection module can be adjusted according to needs.

According to another embodiment of the invention, the apparatus further includes a usage and dosage recommendation module.

Usage and usage recommendation module, generate usage and usage recommendation information. According to the usage and dosage information of the finally selected drugs, the information obtained or confirmed in the previous steps is automatically compared, and the appropriate usage and dosage are recommended to facilitate the confirmation by the doctor, the pharmacist or the clerk, and the patient (purchasing the OTC drug).

The specific embodiments of the present invention have been described above. It is to be understood that the invention is not limited to the specific embodiments described above, and various modifications and changes may be made by those skilled in the art without departing from the scope of the invention.

Claims (61)

1. A method for intelligent drug selection, characterized in that the method comprises:

   Create a dictionary of multi-dimensional attribute items;

   Extracting drug use element information;

   Processing the drug use element information according to the multi-dimensional attribute item dictionary;

   Extracting information about the relevant elements of the patient's medication;

   Processing the drug related factor information according to the multi-dimensional attribute item dictionary;

   The intelligent drug selection matching is performed by comparing the information of the drug use element with the information of each attribute item in the information related to the drug use of the patient;

   Generate a smart drug list.
2. The intelligent drug selection method according to claim 1, characterized in that the multi-dimensional attribute item dictionary is established based on the medical or pharmaceutical attribute structure of the medication information and the definition of each attribute.
3. The intelligent drug selection method according to claim 2, characterized in that the multi-dimensional attribute item dictionary is used to provide a standard dictionary related to various medical or pharmaceutical attributes in the drug use information and the patient medication information.
4. The intelligent drug selection method according to claim 2, characterized in that the multi-dimensional attribute item dictionary is used for providing a drug dictionary use information and a drug dictionary information, and different medical source or drug attribute different origins are associated with a standard dictionary.
5. The intelligent drug selection method according to claim 2, wherein the multi-dimensional attribute item dictionary splits the drug use information into minimum attribute items according to different medical or pharmaceutical attributes, and saves the logical relationship between the attribute items. The data of each minimum attribute item is associated with a standard medical or pharmaceutical attribute item dictionary library.
6. The intelligent drug selection method according to claim 5, wherein the medical attribute items involved in the multi-dimensional attribute item dictionary include at least: a population-related attribute of the patient, a specific attribute of the patient, a disease-related attribute of the patient, and a symptom of the patient. At least one of the relevant attributes, the patient's past medical history related attributes, the patient's operational related attributes, the patient's personal life history related attributes, the patient's physiological state related attributes, the patient's examination index related attributes, and the like.
7. The intelligent drug selection method according to claim 5, wherein the pharmaceutical attribute items involved in the multi-dimensional attribute item dictionary include at least: a property related to the purpose of the drug, a related attribute of the drug component, a related attribute of the drug specification package, and a drug indication. Relevant attributes, related attributes of drug usage and dosage, related attributes of drug administration routes, related attributes of drug contraindications, related attributes of adverse drug reactions, related attributes of drug precautions, related attributes of patient allergy history, and related attributes of patient medication history At least one dimension of the drug-related route of administration, the drug-related gene attribute of the patient, and the like.
8. The intelligent drug selection method according to claim 1, characterized in that the smart drug selection list is generated by the indication drug selection.
9. The intelligent drug selection method according to claim 8, characterized in that the method further comprises generating an intelligent drug selection list by unsuitable drug by a single drug review.
10. The intelligent drug selection method according to claim 9, wherein the method further comprises excluding an unsuitable drug to generate an intelligent drug selection list by a drug reforming review.
11. The intelligent drug selection method according to claim 10, characterized in that the method further comprises performing a medical insurance review on the smart drug selection list.
12. The intelligent drug selection method according to claim 11, wherein the method further comprises Sexual screening generates a smart drug list.
13. The intelligent drug selection method according to claim 12, wherein the method further comprises generating usage amount recommendation information.
14. The intelligent drug selection method according to any one of claims 1 to 13, characterized in that the drug use information is extracted for extracting the indications, the usage and dosage conditions, and the contraindications for drug use in each drug use information. Attribute element information.
15. The intelligent drug selection method according to claim 14, wherein the drug use information is derived from at least one of a drug product specification, a pharmacopoeia, a national formulary, a treatment/drug guide, an expert consensus, and a prescription for administration of medical institutions at various levels.
16. The intelligent drug selection method according to any one of claims 1 to 13, characterized in that the patient medication related information is extracted for extracting actual information of relevant attribute elements when the patient takes the medicine.
17. The intelligent drug selection method according to claim 16, wherein the source of the patient medication information is a doctor prescription, a treatment plan, a medication plan, a medical record, a medical record, a medical record, an examination result, a patient self-reported symptom, a patient self-selection drug, and the like. At least one.
18. The intelligent drug selection method according to any one of claims 1 to 13, characterized in that the manner of generating a matching comparison result is

    The age element of an indication for this drug matches the age element in the patient's medication information:

    

    The match between the indication of the drug and the patient's medication information for the patient is:

    

    Patient Pa, whether the result of using this drug Med is:

    

    Among them, a patient (Patient, referred to as Pa), the patient medication information includes age: (age, Jane Called ag), gender (gender, referred to as gen), special population (special, referred to as spe), symptom (symptom, referred to as sym), history disease (his), family disease (family disease, referred to as fam) Allergic history (ale), other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

    Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).
19. The intelligent drug selection method according to any one of claims 1 to 13, characterized in that the smart drug selection list is generated by statically eliminating unsuitable drugs, the intelligent drug selection list is generated by dynamically excluding unsuitable drugs, and the smart drug selection list is performed. The order of medical insurance audits and the generation of intelligent drug selection lists through personalized screening can be adjusted according to the order.
20. The intelligent drug selection method according to any one of claims 1 to 13, characterized in that the method can be used for recommending drugs for doctors, formulating drug plans for pharmacists, selecting drugs for patients (OTC), assisting drug selection, and pharmacy for usage and dosage. At least one of the intelligent systems.
21. A system for intelligent drug selection, characterized in that the system comprises:

    a drug use element information extracting unit for extracting drug use element information;

    a multi-dimensional attribute item dictionary unit for providing a multi-dimensional attribute item dictionary;

    The multi-dimensional processing unit of the medicine use element information processes the medicine use element information according to the multi-dimensional attribute item dictionary unit;

    The patient medication related element information extraction unit is configured to extract information about the patient medication related elements;

    The multi-dimensional processing unit for patient medication related element information processes the information related to the patient medication according to the multi-dimensional attribute item dictionary unit;

    The intelligent drug selection matching unit compares the drug use element information with the information of each attribute item in the patient drug related element information for intelligent drug selection and matching;

    The intelligent drug selection unit generates a smart drug selection list.
22. The intelligent drug selection system according to claim 21, wherein the multi-dimensional attribute item dictionary unit is established based on a medical or pharmaceutical attribute structure of the medication information and each attribute definition.
23. The intelligent drug selection system according to claim 22, wherein the multi-dimensional attribute item dictionary unit is configured to provide a standard dictionary related to each medical or pharmaceutical attribute in the drug use information and the patient medication information.
24. The intelligent drug selection system according to claim 22, wherein the multi-dimensional attribute item dictionary unit is configured to provide a different dictionary name relationship between the medical source and the pharmaceutical drug information in the drug use information and the patient medication information.
25. The intelligent drug selection system according to claim 22, wherein the multi-dimensional attribute item dictionary unit, The drug use information is split into minimum attribute items according to different medical or pharmaceutical attributes, and the logical relationship between the attribute items is saved, and the data of each minimum attribute item is associated with the standard medical or pharmaceutical attribute item dictionary library.
26. The intelligent drug selection system according to claim 25, wherein the medical attribute items involved in the multi-dimensional attribute item dictionary include at least: a population-related attribute of the patient, a special population-related attribute of the patient, a disease-related attribute of the patient, and a symptom of the patient At least one of the relevant attributes, the patient's past medical history related attributes, the patient's operational related attributes, the patient's personal life history related attributes, the patient's physiological state related attributes, the patient's examination index related attributes, and the like.
27. The intelligent drug selection system according to claim 25, wherein the pharmacy attribute items involved in the multi-dimensional attribute item dictionary include at least: a property related to the purpose of the drug, a related attribute of the drug component, a related attribute of the drug specification package, and a drug indication. Relevant attributes, related attributes of drug usage and dosage, related attributes of drug administration routes, related attributes of drug contraindications, related attributes of adverse drug reactions, related attributes of drug precautions, related attributes of patient allergy history, and related attributes of patient medication history At least one dimension of the drug-related route of administration, the drug-related gene attribute of the patient, and the like.
28. The intelligent drug selection system according to claim 21, wherein the smart drug selection list is generated by the indication drug selection.
29. The intelligent drug selection system according to claim 28, wherein the method further comprises a drug individual review to exclude an unsuitable drug intelligent drug selection unit.
30. The intelligent drug selection system according to claim 29, wherein the method further comprises the drug reforming review to exclude the unsuitable drug intelligent drug selection unit.
31. The intelligent drug selection system of claim 30, wherein the method further comprises a medical insurance review unit.
32. The intelligent drug selection system of claim 31, wherein the method further comprises personalizing the screening of the intelligent drug selection unit.
33. The intelligent drug selection system according to claim 32, wherein the method further comprises a usage amount recommendation unit.
34. The intelligent drug selection system according to any one of claims 21 to 33, characterized in that the medicine use element information extracting unit is configured to extract an indication for each type of drug use information, an applicable condition for usage and dosage, and a related medicine for contraindications /Pharmaceutical attribute element information.
35. The intelligent drug selection system according to claim 34, wherein the drug use information is derived from at least one of a drug product specification, a pharmacopoeia, a national formulary, a treatment/drug guide, an expert consensus, and a prescription for administration of medical institutions at various levels.
36. The intelligent drug selection system according to any one of claims 21 to 33, characterized in that the patient medication-related information extraction unit is configured to extract actual information of relevant attribute elements when the patient takes medication.
37. The intelligent drug selection system according to claim 36, wherein the source of the patient medication information is a doctor prescription, a treatment plan, a medication plan, a medical record, a medical record, a medical record, an examination result, a patient self-reported symptom, a patient self-selection drug, and the like. At least one.
38. The intelligent drug selection system according to any one of claims 21 to 33, wherein the manner of generating a matching comparison result is

    The age element of an indication for this drug matches the age element in the patient's medication information:

    

    The match between the indication of the drug and the patient's medication information for the patient is:

    

    Patient Pa, whether the result of using this drug Med is:

    

    Among them, a patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym) There are both history (his), family disease (fam), allergic history (ale), and other conditions (Other, referred to as Oth). The patient's physical condition is PA (ag, gen, spe, sym, his, fam, ale, Oth).

    Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).
39. The intelligent drug selection system according to any one of claims 21 to 33, characterized in that statically selecting an unsuitable drug intelligent drug selection unit, dynamically excluding an unsuitable drug intelligent drug selection unit, a medical insurance review unit, and a personalized screening intelligent selection The order of the medicine units can be adjusted according to the order.
40. Intelligent drug selection system according to any one of claims 21-33, characterized in that the system is available At least one of the prescriptions recommended by the doctor for the prescription drug, the pharmacist formulating the medication plan, the patient's self-selected drug (OTC), the auxiliary drug selection, and the usage and dosage.
41. An intelligent drug selection device, characterized in that the device comprises:

    a drug use element information extraction module for extracting drug use element information;

    a multi-dimensional attribute item dictionary module for providing a multi-dimensional attribute item dictionary;

    The multi-dimensional processing module of the drug use element information processes the drug use element information according to the multi-dimensional attribute item dictionary module;

    The patient medication related element information extraction module is used for extracting information about the relevant elements of the patient medication;

    The multi-dimensional processing module for patient medication related element information processes the information related to the patient medication according to the multi-dimensional attribute item dictionary module;

    The intelligent drug selection matching comparison module compares the drug use element information with the information of each attribute item in the patient drug related element information for intelligent drug selection and matching;

    The intelligent drug selection module generates a smart drug selection list.
42. The intelligent drug selection device according to claim 41, wherein the multi-dimensional attribute item dictionary module is established based on a medical or pharmaceutical attribute structure of the medication information and each attribute definition.
43. The intelligent drug selection device according to claim 42, wherein the multi-dimensional attribute item dictionary module is configured to provide a standard dictionary related to various medical or pharmaceutical attributes in the drug use information and the patient medication information.
44. The intelligent drug selection device according to claim 42, wherein the multi-dimensional attribute item dictionary module is configured to provide a different dictionary name relationship between the medical source and the drug information in the drug use information and the patient medication information.
45. The intelligent drug selection device according to claim 42, wherein the multi-dimensional attribute item dictionary module splits the drug use information into the minimum attribute item according to different medical or pharmaceutical attributes, and saves the logical relationship between the attribute items. And associate the data of each minimum attribute item with the standard medical or pharmaceutical attribute item dictionary library.
46. The intelligent drug selection device according to claim 45, wherein the medical attribute items involved in the multi-dimensional attribute item dictionary include at least: a population-related attribute of the patient, a special population-related attribute of the patient, a disease-related attribute of the patient, and a symptom of the patient At least one of the relevant attributes, the patient's past medical history related attributes, the patient's operational related attributes, the patient's personal life history related attributes, the patient's physiological state related attributes, the patient's examination index related attributes, and the like.
47. The intelligent drug-selecting device according to claim 45, wherein the pharmacy attribute items involved in the multi-dimensional attribute item dictionary include at least: a property related to the purpose of the drug, a related attribute of the drug component, a related attribute of the drug specification package, and a drug indication Relevant attributes, related attributes of drug usage and dosage, related attributes of drug administration routes, related attributes of drug contraindications, related attributes of adverse drug reactions, related attributes of drug precautions, related attributes of patient allergy history, and related attributes of patient medication history At least one dimension of the drug-related route of administration, the drug-related gene attribute of the patient, and the like.
48. The intelligent drug selection device according to claim 41, wherein the smart drug selection list is generated by the indication drug selection.
49. 48. The intelligent drug selection device of claim 48, wherein the method further comprises a drug individual review to exclude an inappropriate drug intelligent drug selection module.
50. The intelligent drug selection device according to claim 49, wherein the method further comprises the drug reforming review to exclude the unsuitable drug intelligent drug selection module.
51. The intelligent drug selection device of claim 50, wherein the method further comprises a medical insurance review module.
52. The intelligent drug selection device of claim 51, wherein the method further comprises personalizing the screening of the intelligent drug selection module.
53. The intelligent drug selection device according to claim 52, wherein the method further comprises a usage amount recommendation module.
54. The intelligent drug selecting device according to any one of claims 41 to 53, wherein the drug use element information extracting module is configured to extract an indication for each drug use information, an applicable condition for usage and dosage, and a related medicine for contraindications of the drug. /Pharmaceutical attribute element information.
55. The intelligent drug selecting device according to claim 54, wherein the drug use information is derived from at least one of a drug product specification, a pharmacopoeia, a national formula set, a treatment/drug guide, an expert consensus, and a medication prescription for each level of medical institutions.
56. The intelligent drug selecting device according to any one of claims 41 to 53, wherein the patient medication related information extracting module is configured to extract actual information of related attribute elements when the patient takes medication.
57. The intelligent drug-selecting device according to claim 56, wherein the source of the patient medication information is a doctor's prescription, a treatment plan, a medication plan, a medical record, a medical record, a medical record, an examination result, a patient self-reported symptom, a patient's self-selection drug, and the like. At least one.
58. The intelligent drug selecting device according to any one of claims 41 to 53, wherein the manner of generating a matching comparison result is

    The age element of an indication for this drug matches the age element in the patient's medication information:

    

    The match between the indication of the drug and the patient's medication information for the patient is:

    

    Patient Pa, whether the result of using this drug Med is:

    

    Among them, a patient (Patient, referred to as Pa), the patient medication information includes age: (age, abbreviated as ag), gender (gender, referred to as gen), special group (special, referred to as spe), symptom (symptom, referred to as sym) There are both history (his), family disease (fam), allergic history (ale), and other conditions (Other, referred to as Oth). The patient's physical condition is Pa (ag, gen, spe, sym, his, fam, ale, Oth).

    Medi drug (Med) Med, one of the indications in the drug use information is Med(x _i ), and the result of the split is Med(x _i (ag, gen, spe, sym, his, fam, ale, Oth)).
59. The intelligent drug-selecting device according to any one of claims 41-53, characterized in that: statically eliminating unsuitable drug intelligent drug selection module, dynamically eliminating unsuitable drug intelligent drug selection module, medical insurance review module, personalized screening intelligent selection The order of the medicine modules can be adjusted according to the order.
60. The intelligent drug-selecting device according to any one of claims 41-53, wherein the device is applicable to a doctor's prescription recommending drug, a pharmacist formulating a drug-using program, an patient-selected drug (OTC), an auxiliary drug selection, and a pharmacy for usage and dosage. At least one of the smart recommendations.
61. The intelligent drug selection device according to any one of claims 41-53, including but not limited to a medical institution doctor workstation, a pharmacist workstation, a pharmacy pharmacist workstation, a clerk workstation, a patient self-service terminal, and a patient accessible Internet device (computer , smart TV, mobile computers, smart phones, smart watches, etc.).

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