CN116805524A - Cloud platform-based pharmacist medication suggestion method, system and storage medium - Google Patents
Cloud platform-based pharmacist medication suggestion method, system and storage medium Download PDFInfo
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- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H70/00—ICT specially adapted for the handling or processing of medical references
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Abstract
The invention discloses a cloud platform-based drug recommendation method, a cloud platform-based drug recommendation system and a cloud platform-based drug recommendation storage medium, belongs to the field of patient drug recommendation intelligence, and solves the problems that in the prior art, the working efficiency of drug recommendation of a traditional Chinese drug is low, and the drug recommendation is safe due to the fact that a drug administrator cannot quickly know the characteristics of each drug: the medicine description information base is manufactured and stored in the cloud platform server; the client is connected with the cloud platform server to be matched with the medicine description information base, and is connected with the hospital information system to be matched with the diagnosis and treatment information of the patient; the patient makes a doctor visit in the hospital to store the information of the doctor visit in a hospital information system; the pharmacist uses the client prescription information to match the medicine instruction information base to extract the medicine corresponding information in the hospital, forms an electronic written medication suggestion, sends the electronic written medication suggestion to the patient mobile equipment end through the cloud platform server, guides the accurate safety of data, and work efficiency is high, and is mainly used for pharmacist to use.
Description
Technical Field
The invention relates to the field of intelligent drug recommendation of pharmacists for patients, in particular to a cloud platform-based drug recommendation method, a cloud platform-based drug recommendation system and a cloud platform-based storage device.
Background
Chinese patent publication No.: CN113593669a, patent name: intelligent medication recommendation method, system and device solve the technical problems: the medicine inquiry function can only inquire according to the medicine name or specific keywords, the inquiry process is completely based on the experience and memory of doctors, and in such a large-scale medicine library, the doctors can hardly record the medicine information such as the medicine name, the medicine effect, the dosage and the like of each medicine, and the doctors select medicines by adopting the method of inquiring according to the medicine name or the keywords, so that the medicine opening efficiency is low, and the pertinence and the accuracy of the medicine opening are also difficult to ensure; the industry generally has the defect of insufficient medical practitioner personnel, and the medical practitioner has limited knowledge storage, so that comprehensive suggestions are difficult to provide for users in combination with medication. It is inevitable to produce improper recommended medicines and the like. The description is specialized for adverse reaction and tabu sometimes, and a general user cannot intuitively and clearly know the meaning of the description, so that the situation of wrong administration of the medicine by the user can be caused; the technical scheme is as follows: establishing a corresponding relation among medicines, diseases and symptoms through an artificial intelligent model; wherein the artificial intelligence model comprises a first model, a second model and a third model; the corresponding relation comprises a first relation, a second relation and a third relation; extracting symptom keywords and medicine name keywords in the medicine instruction book, and establishing a first relation between the medicine and the symptoms through the first model; extracting a disease keyword and the drug name keyword in the drug specification, and establishing a second relation between the drug and the disease through the second model; extracting the symptom keywords and the disease keywords in symptom descriptions, and establishing a third relation between the disease and the symptoms through the third model; generating recommended medication conditions according to the first relationship, the second relationship and the third relationship; acquiring current symptom information, influence medication information and historical medication purchasing information of a current user, and determining recommended medication information of the current user according to the current symptom information, the influence medication information, the historical medication purchasing information and the recommended medication condition.
The second rule of prescription management method is that the registered medical practitioner and medical assistant doctor (doctor) issue the prescription for the patient in the diagnosis and treatment activities, and the medical professional technician (pharmacist for short) who obtains the qualification of the medical professional technical job checks, prepares and checks the prescription as the medical document of the patient's medication certificate. The prescription includes a medical order for administration to the medical facility.
The thirty-first rule of the prescription management method is that a person with the qualification of the professional technical job above the pharmacist is responsible for prescription auditing, evaluation, checking, dispensing and safe medication guidance; the pharmacy engages in prescription preparation work.
Thirty-third rule of prescription management method, pharmacist should adjust prescription drug according to operation rules: carefully checking the prescription, accurately preparing the medicine, correctly writing a medicine bag or pasting a label, noting the name and the medicine name of a patient, the usage and the dosage, and packaging; when delivering medicines to patients, medication delivery and instruction are carried out according to the medicine instruction book or prescription usage, including usage, dosage, notice and the like of each medicine.
According to the background art, the disclosed patent technical content is to establish a connection with disease symptom keywords according to drug keywords, so that a doctor can conveniently prescribe the prescription, and the doctor cannot effectively avoid the prescription risk when prescribing the prescription because only the keyword suggestions are provided; according to prescription management method, pharmacists need to audit the prescriptions and make drug delivery and instruction work, and because the medicines are large in quantity, the pharmacists cannot memorize the instruction content of each medicine and make effective instruction, so that the pharmacists cannot effectively audit the prescriptions which are obtained by doctors according to the technical scheme of the patent, and effectively give out the effective drug delivery and instruction of patients, and write a medicine bag and label of the pharmacists and work and indicate drug information, the working amount is large, and the practical implementation of drug advice work is not facilitated.
Disclosure of Invention
The invention aims to provide a cloud platform-based drug recommendation method, a cloud platform-based drug recommendation system and a cloud platform-based storage medium, which solve the problems that in the prior art, the work efficiency of drug recommendation by a traditional Chinese medicine is low, and the drug recommendation is safe due to the fact that a drug administrator cannot quickly know the characteristics of each drug: the characteristic of each medicine can be quickly known by pharmacists according to the prescription, and medication suggestions can be quickly given, so that the medicine is real and safe.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the drug administration suggestion method based on the cloud platform comprises the following steps: s1: the medicine description information base is manufactured and stored in the cloud platform server; s2: the client is connected with the cloud platform server to be matched with the medicine description information base, S3, the client is connected with a hospital information system to be matched with diagnosis and treatment information of patients; s4: the patient makes a doctor visit in the hospital to store the information of the doctor visit in a hospital information system; s5: a pharmacist uses a client to inquire personal information, treatment information, prescription information and allergy history of a patient in a hospital, and matches the prescription information of the client with a medicine description information base to extract medicine corresponding information, so that an electronic written medication suggestion is formed and sent to a mobile equipment end of the patient through a cloud platform server; s1, the drug description information library is manufactured, and paper information of drug description on the market is collected through a client; the input mode is as follows: scanning the paper-based medicine instruction book into an electronic-based medicine instruction book, and uploading the electronic-based medicine instruction book to a medicine instruction information base through a client; extracting basic information, indications, usage, notes, incompatibility, interaction and adverse reaction of a medicine instruction through a client, classifying and uploading the basic information, indications, usage, notes, incompatibility and interaction and adverse reaction to a medicine instruction information base; step S1 further includes: and the client extracts the original information according to the classified original information to carry out medication suggestion summarization and labeling, and uploads a medicine description information base for reintroducing the client to be matched with the prescription information of the patient.
The medicine recommendation system based on the cloud platform comprises a prescription set module, wherein the prescription set module comprises a unit for scanning and uploading paper medicine specifications, and the uploading unit classifies information in the uploaded medicine specifications according to basic information of medicines, classifying information of the medicines, indications, usage, notes, incompatibility, interaction and adverse reactions of the medicines and uploads the medicine pictures; the prescription module further comprises an extraction unit, wherein the extraction unit extracts usage amount original data and notice original data of the classification information, and summarizes and marks the original data to form a contrast chart, and the contrast chart is stored in the cloud platform server; further comprises: the medication advice module comprises an importing unit, the medication advice module is connected with a hospital information system, personal information, treatment information, prescription information and allergy Shi Dao of a patient in a hospital are imported through the importing unit, and a pharmacist inquires about the information of the patient through the medication advice module; the medication advice module comprises a matching unit, wherein the matching unit is used for a pharmacist to open a patient prescription, and the drug advice module is imported by matching the drug summary labeling information stored by the cloud platform server according to the drug information on the corresponding prescription and forms a medication advice list with the patient prescription information on the medication module; the medication advice note labeling comprises: drug name information, usage amount, start time, end time, medication advice, department, physician, pharmacist information; the medication suggestion module further comprises a storage unit, wherein the storage unit prints or stores the medication suggestion list in a cloud platform server, and sends the medication suggestion list to a patient mobile device through the cloud platform server.
A computer device comprising a memory having a computer program stored thereon, and a processor, which when executing the computer program, implements the method system of the invention.
A storage medium storing a computer program which, when executed by a processor, implements the method system of the invention.
The beneficial effects are that: the invention is different from the prior art in that
Drawings
Fig. 1: a flow chart of a method of suggesting medication for the present invention;
fig. 2: a workflow chart for a prescription module of the system of the invention;
fig. 3: a workflow diagram of a medication suggestion module for the system of the invention;
fig. 4: an operation interface schematic diagram is suggested for the medication of the invention;
fig. 5: an interface schematic is derived for the medication proposal sheet of the invention.
Description of the embodiments
The invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1-5, the cloud platform-based pharmacist medication recommendation method comprises the following steps:
s1: the medicine description information base is manufactured and stored in the cloud platform server;
s2: the client is connected with the cloud platform server to be matched with the medicine description information base, and the client initiates a connection request: the client initiates a connection request according to the address (such as an IP address or a domain name) of the cloud server; the request is sent to the cloud server using a specific transmission protocol (e.g., HTTP, HTTPS, TCP, etc.); the cloud server accepts and responds to the connection request: the cloud server receives a connection request of the client and processes the connection request according to a contracted protocol; the server verifies the identity of the client, allocates resources and the like; and (3) data exchange: the connection establishment is successful, and data exchange is carried out between the client and the cloud server; operations including sending request, receiving response, transmitting data, etc., the transmission protocol is HTTP, webSocket; connection termination: the connection may be terminated actively by the client or the server, or may be interrupted by a network interruption or the like.
S3, the client is connected with a hospital information system to match diagnosis and treatment information of a patient; using the APIs provided by HIS: the HIS system provides APIs (application program interfaces) that allow developers to use to enable communication with the HIS system; sending a request to the HIS system and acquiring data or performing an operation by using an API provided by the HIS system; using standard protocols: some HIS systems may support standard protocols, such as HL7 (Health Level Seven) protocol; HL7 is a standard protocol for transmitting and exchanging data in the medical field. The HIS system supports an HL7 protocol, a developer can write codes according to protocol specifications, and data exchange is carried out between the HIS system and the HL7 protocol; database connection: the data of the HIS system is stored in a database, and the database connection is used for interacting with the HIS system; the developer uses the database related API or driver to connect to the database of the HIS system to execute SQL query, insert, update or delete operations; network integration: the HIS system allows other systems to be integrated with the HIS system through a network, and uses a network integration technology; and establishing network connection with the HIS system and communicating by using a specific protocol to realize data transmission and interaction.
The following are examples of formulas related to some of the algorithms mentioned in API implementations: authentication and authorization algorithm:
OAuth 2.0 authentication procedure: OAuth uses token exchange to verify user identity and authorize access to protected resources. The authentication process involves a series of steps including generating an authorization code, exchanging an access token, etc. Specific algorithm steps may be referred to the OAuth 2.0 specification.
Data compression algorithm gzip compression algorithm: gzip is a commonly used data compression algorithm. The compression formula is as follows: [ \text { { compacteddata } = \text { { { gzip. Compact } (\text { { originalData }) ], a plurality of entities are incorporated in the package, and the package is assembled to form a package
Encryption algorithm AES (Advanced Encryption Standard) algorithm: AES is a symmetric encryption algorithm that uses the same key for both encryption and decryption operations. The encryption and decryption formulas are as follows: [ \text { { encryptedData } { aes } (\text { { playintextdata }, \text { { key }) [ \text { { decryptedData } ] = \text { { aes. DecryptedData } }, { text { encryptedData }, text { { key } ].
The data format conversion algorithm is JSON to XML: this is an example JSON-to-XML algorithm: [ _text { { { xmlData } = \text { { { JSON2XML } (\text { { jsonData } ]) XML-to-JSON: this is an example XML-to-JSON algorithm: [ \text { { jsonData } = \text { { { xml2json } (\text { { xmlData }) ]
Data verification algorithms regular expression matching is used to verify whether text meets a particular pattern, e.g., using regular expressions to verify email addresses: [ text { { isValidEmail } = \text { { { regex. Match } (\text { { email }, \text { { email pattern } ], text }
S4: the patient makes a doctor visit in the hospital to store the treatment information in the hospital information system, which is the original function realization of each hospital his system;
s5: the medical chef uses the client to inquire personal information, treatment information, prescription information and allergy history of the patient in the hospital, and extracts corresponding information of the medicine by matching prescription information of the client with the medicine description information base, so as to form an electronic written medicine suggestion, the electronic written medicine suggestion is sent to the mobile equipment end of the patient through the cloud platform server, the cloud platform server sets up, the client application can select files and a target path sent to the cloud platform server, and the files are transmitted to the cloud platform server: and transmitting the file selected on the hospital client to a designated path in the cloud platform server by establishing connection with the cloud platform server. Using a file transfer protocol, such as HTTP or FTP; after receiving the file, the cloud platform server stores the file in a designated path, and processes storage, organization and maintenance of the file; and the cloud platform server sends the requested file to the patient mobile equipment end. The transfer of files may be implemented using a specific Application Program Interface (API) or protocol, such as HTTP download.
S1, the drug description information library is manufactured, and paper information of drug description on the market is collected through a client; the input mode is as follows: scanning the paper-based medicine instruction book into an electronic-based medicine instruction book, and uploading the electronic-based medicine instruction book to a medicine instruction information base through a client; basic information, indications, usage, notes, incompatibility, interaction and adverse reactions of the drug instruction are extracted through a client, and the drug instruction information library is classified and uploaded, and the extraction and classification mode is that the information sources are real through manually copying corresponding parts of the drug instruction, so that identification errors caused by intelligent extraction are avoided, and the safety of drug recommendation is further guaranteed.
Step S1, referring to fig. 4, further includes: the client extracts the original information according to the classified original information to carry out medication suggestion summarization and labeling, and uploads a medicine description information base for reintroducing the client to be matched with the prescription information of the patient, and particularly, the client uses a network protocol (such as HTTP) to communicate with the cloud platform server so as to ensure that the client can access an API or a data interface of the cloud server; inquiring information content of the medicine: in the client, the medicine information is queried, which can be a search column or a table; when a user inputs a medicine name according to a prescription in a client or selects a medicine in a patient prescription, the client transmits a request to a cloud server to inquire information content of related medicines; the cloud server processes the query request: after receiving the query request, the cloud server processes the query request according to the requested medicine information; the server may query its database or call a related API to obtain detailed information of the drug.
2-3, the cloud platform-based pharmacist medication suggestion system comprises a prescription set module, wherein the prescription module comprises a unit for scanning and uploading paper drug specifications, and the uploading unit classifies information in the uploaded drug specifications according to basic drug information, drug classification information, indications, usage amount, notes, incompatibility, interaction and adverse reactions, uploads drug pictures and realizes specific operation through manual table operation arranged in the prescription set module; the prescription module further comprises an extraction unit, the extraction unit extracts the usage amount original data and notice original data of the classification information, and summarizes and marks the original data to form a comparison chart, the implementation mode is realized by manually operating the extraction unit according to the table setting in the unit, and the comparison chart is stored in the cloud platform server through the step S2, so that the use is convenient.
As shown in fig. 2-3, further includes: the medication advice module comprises an importing unit, the medication advice module is connected with the hospital information system, the personal information, the treatment information, the prescription information and the allergy Shi Dao medication advice module of the patient in the hospital are realized through the importing unit, and a pharmacist inquires the information of the patient through the medication advice module.
As shown in fig. 3, the medication advice module includes a matching unit for a pharmacist to open a patient prescription, and to import medication advice module by matching the medication summary label information stored by the cloud platform server with the medication information on the corresponding prescription and to form a medication advice sheet with the patient prescription information on the medication module.
The algorithm involved in importing the medicine summary labeling information comprises the following steps:
text matching algorithm: in order to achieve matching of drug names, a text matching algorithm is used for measuring similarity between prescription drug names and drug names in a cloud server drug information base. Common text matching algorithms include string edit distance (e.g., levenshtein distance), jaccard similarity coefficients, cosine similarity, and the like. Relates to the formula: [ (prescriptionDrugName, databaseDrugName) = { similarity } (frac { { { text { { { len } (\text { conjugates }) } { { text { { { len } (prescriptiondrug name) +_text { len } (databasedrug name) - { text { { { len } (\text { { common characters }) } ] in this example formula, (\text { { { common characters }) represents the number of characters shared between the prescription drug name and the drug name in the database. Finding a medicine matched with the name of the prescription medicine by calculating the similarity; (\text { { prescriptiondrug name }) represents the prescription drug name; the { { { databasedrug name } } represents the drug name in the database; (\text { { len } (\text { common characters })) represents the same number of characters between the prescription drug name and the database drug name; (\text { { { len } (\text { prescriptiondrug name }) represents the number of characters of the prescription drug name; the } (\text { { { len } (\text { databasedrug name }) represents the number of characters of the database drug name.
As shown in fig. 4-5, the medication advice note includes: drug name information, usage amount, start time, end time, medication advice, department, physician, pharmacist information; the medicine name information is from prescription information of a hospital information system, the usage information is from a medicine description information base of a cloud platform server, the medicine is checked and confirmed by a pharmacist, the medicine start time and the medicine end time are checked and confirmed according to a doctor or a pharmacist, the medicine suggestion is from the medicine description information base of the cloud platform server, and the medicine suggestion list is checked by the pharmacist, so that the doctor and the pharmacist can conveniently inquire through electronic signatures.
As shown in fig. 3, the medication suggestion module further includes a storage unit, where the storage unit prints or stores the medication suggestion list on a cloud platform server, and sends the medication suggestion list to a patient mobile device through the cloud platform server, so that the patient can check the medication suggestion list conveniently.
The system operation further comprises: the memory, processor, and the like together form the main components of the computer system.
A memory: the memory is used for storing data and instructions in the computer, and comprises a main memory (such as a RAM) and an auxiliary memory (such as a hard disk or a solid state disk) for storing programs and data, and is mainly used for storing medicine specifications and uploading files of medicine pictures and storing and printing a medicine recommended sheet to be printed; the program is a series of instruction sets written in a specific order and used for telling a computer how to execute, is stored in a storage medium and is loaded into a memory for execution by a processor when needed; a processor: the processor is a core component of the computer, and is a Central Processing Unit (CPU). The method comprises the steps of executing instructions in a medication advice system program, and operating and processing data; a storage medium: the storage medium is a physical medium for storing programs and data for a long period of time, a hard disk drive, a solid state disk, an optical disk, a flash memory drive, and the like, and provides nonvolatile storage so that a computer can be restarted from a power-off, and a mass storage medium can be used for storing data for a long period of time, so that related usage data can be protected.
The present invention is not limited to the above-described embodiments, and variations that do not depart from the scope of the invention are intended to be within the scope of the invention.
Claims (10)
1. The cloud platform-based drug administration suggestion method is characterized by comprising the following steps of: the method comprises the following steps: s1: the medicine description information base is manufactured and stored in the cloud platform server; s2: the client is connected with the cloud platform server to be matched with the medicine description information base, S3, the client is connected with a hospital information system to be matched with diagnosis and treatment information of patients; s4: the patient makes a doctor visit in the hospital to store the information of the doctor visit in a hospital information system; s5: and a pharmacist uses a client to inquire personal information, treatment information, prescription information and allergy history of a patient in a hospital, and uses the client prescription information to match a medicine description information base to extract medicine corresponding information, so that an electronic written medication suggestion is formed and sent to a patient mobile device through a cloud platform server.
2. The cloud platform based pharmacist medication recommendation method as recited in claim 1, wherein: s1, the drug description information library is manufactured, and paper information of drug description on the market is collected through a client; the input mode is as follows: scanning the paper-based medicine instruction book into an electronic-based medicine instruction book, and uploading the electronic-based medicine instruction book to a medicine instruction information base through a client; basic information, indications, usage, notes, incompatibility, interaction and adverse reaction of a medicine instruction are extracted through a client, classified and uploaded to a medicine instruction information base.
3. The cloud platform based pharmacist medication recommendation method as defined in claim 2, wherein: step S1 further includes: and the client extracts the original information according to the classified original information to carry out medication suggestion summarization and labeling, and uploads a medicine description information base for reintroducing the client to be matched with the prescription information of the patient.
4. Based on cloud platform pharmacist suggestion system of using medicine, its characterized in that: the prescription set module comprises a scanning and uploading unit for scanning paper medicine specifications, wherein the uploading unit classifies information in the uploaded medicine specifications according to basic information of medicines, classification information of medicines, indications, usage amount, notes, incompatibility, interaction and adverse reaction of the medicines, and uploads medicine pictures; the prescription module further comprises an extraction unit, wherein the extraction unit extracts usage amount original data and notice original data of the classification information, and marks the original data in a summarization mode to form a comparison chart, and the comparison chart is stored in the cloud platform server.
5. The cloud platform based pharmacist medication recommendation system as recited in claim 4, wherein: further comprises: the medication advice module comprises an importing unit, the medication advice module is connected with the hospital information system, personal information, treatment information, prescription information and allergy Shi Dao of a patient in a hospital are imported through the importing unit, and a pharmacist inquires the information of the patient through the medication advice module.
6. The cloud platform based pharmacist medication recommendation system as recited in claim 5, wherein: the medication advice module comprises a matching unit, wherein the matching unit is used for enabling a pharmacist to open a patient prescription, and the drug advice module is imported by matching the drug summary labeling information stored by the cloud platform server according to the drug information on the corresponding prescription and forms a medication advice list with the patient prescription information on the medication module.
7. The cloud platform based pharmacist medication recommendation system as recited in claim 6, wherein: the medication advice note labeling comprises: drug name information, usage amount, start time, end time, medication advice, department, physician, pharmacist information.
8. The cloud platform based pharmacist medication recommendation system as in claim 7, wherein: the medication suggestion module further comprises a storage unit, wherein the storage unit prints or stores the medication suggestion list in a cloud platform server, and sends the medication suggestion list to a patient mobile device through the cloud platform server.
9. A computer device, characterized by: the computer device comprising a memory and a processor, the memory having stored thereon a computer program, the processor, when executing the computer program, implementing the method system of any of claims 1 to 8.
10. A storage medium storing a computer program which, when executed by a processor, implements the method system of any one of claims 1 to 8.
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| CN202310909315.7A CN116805524A (en) | 2023-07-24 | 2023-07-24 | Cloud platform-based pharmacist medication suggestion method, system and storage medium |
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| CN202310909315.7A CN116805524A (en) | 2023-07-24 | 2023-07-24 | Cloud platform-based pharmacist medication suggestion method, system and storage medium |
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