[go: up one dir, main page]

WO2025095574A1 - Dispositif et procédé pour fournir un service de recommandation de médicament sur la base d'une consultation - Google Patents

Dispositif et procédé pour fournir un service de recommandation de médicament sur la base d'une consultation Download PDF

Info

Publication number
WO2025095574A1
WO2025095574A1 PCT/KR2024/016803 KR2024016803W WO2025095574A1 WO 2025095574 A1 WO2025095574 A1 WO 2025095574A1 KR 2024016803 W KR2024016803 W KR 2024016803W WO 2025095574 A1 WO2025095574 A1 WO 2025095574A1
Authority
WO
WIPO (PCT)
Prior art keywords
customer
consultation
terminal
pharmacist
medicine
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/KR2024/016803
Other languages
English (en)
Korean (ko)
Inventor
김병주
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Charmacist Corp
Original Assignee
Charmacist Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Charmacist Corp filed Critical Charmacist Corp
Publication of WO2025095574A1 publication Critical patent/WO2025095574A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/14—Payment architectures specially adapted for billing systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/20—Point-of-sale [POS] network systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/20—ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Definitions

  • the present disclosure relates to a device and method for providing a pharmaceutical recommendation service based on consultation.
  • General medicine consultation is one of the main services provided by pharmacies. Customers can conveniently use general medicine consultation at pharmacies when they are in a situation where it is difficult to go to the hospital or have mild symptoms that are judged not to require treatment. From a national and social perspective, general medicine consultation can reduce the burden of national medical expenses and is meaningful as an easily accessible service.
  • Pharmacists providing consultation services must collect a lot of information to provide high-quality general medicine services. First, they must collect a large amount of up-to-date evidence-based health information necessary for consultation. Second, they must understand the customer's underlying disease, existing medications, and reactions to medications. They also need regulatory information such as approvals or sales suspensions.
  • the purpose of the embodiment disclosed in the present disclosure is to provide a device and method for providing a medicine recommendation service based on consultation.
  • a device for providing a medicine recommendation service based on consultation includes a communication unit, a memory storing at least one process for providing a service for recommending a product based on consultation with a customer, and a processor performing an operation according to the process, wherein the processor sequentially provides a plurality of questions for checking detailed symptoms of a disease of a customer through a first UI (User Interface) output to a pharmacist's terminal, and recommends a type of medicine for improving the disease based on responses to each of the plurality of questions received from the pharmacist terminal through the first UI, and requests payment for a product selected by the pharmacist terminal from among a plurality of products corresponding to the type of medicine to a pharmacy payment system server.
  • UI User Interface
  • the remaining questions excluding the first question, are provided with different content depending on the response to the previous question, and the number of previously recommended drug types may change each time a response to the remaining questions is received.
  • the processor may recommend the first type of medicine and the second type of medicine together through the first UI.
  • the processor provides the customer's consultation history to the pharmacist terminal so that the consultation is conducted based on the consultation history, and the customer's consultation history can be accumulated and stored as consultation results from different pharmacies so that it can be shared among pharmacists using the service.
  • the processor when a solution provision request is received from the pharmacist terminal, the processor provides the solution to the pharmacist terminal, and the solution may include information on the selected product, instructions for use of the selected product, and a lifestyle guide.
  • the solution may be delivered to the customer's terminal based on the customer's information stored in the customer DB, and if the customer is a new customer, the solution may be delivered to the customer's terminal based on the customer's information entered by the pharmacist through the pharmacist terminal.
  • the processor can recommend at least one hospital based on the consultation content and the customer's location up to the time the request is received.
  • the processor when it receives a consultation request from the customer's terminal, it can sequentially provide a plurality of questions for checking detailed symptoms of the customer's disease through a second UI output to the customer terminal, and recommend a type of medicine for improving the disease based on the response to each of the plurality of questions received from the customer terminal.
  • the processor when the processor receives information about a product held by the customer from the customer terminal, it determines whether there is a product corresponding to the recommended type of pharmaceutical among the products held by the customer, and if there is a product corresponding to the recommended type of pharmaceutical among the products held by the customer, it can provide a user guide for the product to the customer terminal.
  • a method for providing a medicine recommendation service based on consultation according to another aspect of the present disclosure for achieving the above-described technical task may include a step of sequentially providing a plurality of questions for checking detailed symptoms of a customer's disease through a first UI (User Interface) output on a pharmacist's terminal, a step of recommending a type of medicine for improving the disease based on responses to each of the plurality of questions received from the pharmacist terminal through the first UI, and a step of requesting payment for a product selected by the pharmacist terminal from among a plurality of products corresponding to the type of medicine to a pharmacy payment system server.
  • UI User Interface
  • a computer program stored in a computer-readable recording medium for executing a method for implementing the present disclosure may be further provided.
  • a computer-readable recording medium recording a computer program for executing a method for implementing the present disclosure may be further provided.
  • customers can receive counseling services through the app and quickly identify their illness without having to visit a pharmacy.
  • FIG. 1 is a schematic diagram illustrating a system for providing a drug recommendation service based on consultation according to an embodiment of the present disclosure.
  • FIG. 2 is a block diagram of a device for providing a medicine recommendation service based on consultation according to an embodiment of the present disclosure.
  • FIG. 3 is a flowchart of a method for providing a pharmaceutical recommendation service through a pharmacist platform according to an embodiment of the present disclosure.
  • FIGS. 4 to 10 are drawings for explaining a UI (User Interface) provided to a pharmacist terminal for conducting consultation through a pharmacist platform according to one embodiment of the present disclosure.
  • UI User Interface
  • FIG. 11 is a diagram illustrating an algorithm for sequentially providing multiple questions about a customer's condition according to one embodiment of the present disclosure.
  • FIG. 12 is a flowchart of a method for providing a pharmaceutical recommendation service through a customer platform according to an embodiment of the present disclosure.
  • the present disclosure does not describe all elements of the embodiments, and general contents in the technical field to which the present disclosure belongs or overlapping contents between the embodiments are omitted.
  • the terms 'part, module, member, block' used in the specification can be implemented by software or hardware, and according to the embodiments, a plurality of 'parts, modules, members, blocks' may be implemented as a single component, or a single 'part, module, member, block' may include a plurality of components.
  • a part is said to be "connected" to another part, this includes not only cases where it is directly connected but also cases where it is indirectly connected, and the indirect connection includes connection via a wireless communication network.
  • first, second, etc. are used to distinguish one component from another, and the components are not limited by the aforementioned terms.
  • Singular expressions include plural expressions unless the context clearly indicates otherwise. Identifiers for each step are used for convenience of explanation and do not describe the order of each step. Each step may be performed in a different order than stated unless the context clearly indicates a specific order.
  • a device includes all kinds of devices that can perform computational processing and provide results to a user.
  • a device according to the present disclosure may include all of a computer, a server device, and a portable terminal, or may be in the form of any one of them.
  • the computer may include, for example, a notebook, desktop, laptop, tablet PC, slate PC, etc. equipped with a web browser.
  • the above server device is a server that processes information by communicating with an external device, and may include an application server, a computing server, a database server, a file server, a game server, a mail server, a proxy server, and a web server.
  • the above portable terminal may include, for example, all kinds of handheld-based wireless communication devices such as PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (Wideband Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminals, smart phones, tablets, etc., and wearable devices such as watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted-devices (HMDs).
  • PCS Personal Communication System
  • GSM Global System for Mobile communications
  • PDC Personal Digital Cellular
  • PHS Personal Handyphone System
  • PDA Personal Digital Assistant
  • IMT International Mobile Telecommunication
  • CDMA Code Division Multiple Access
  • W-CDMA Wideband Code Division Multiple Access
  • WiBro Wireless Broadband Internet
  • the function related to artificial intelligence is operated through a processor and a memory.
  • the processor may be composed of one or more processors.
  • one or more processors may be a general-purpose processor such as a CPU, an AP, a DSP (Digital Signal Processor), a graphics-only processor such as a GPU, a VPU (Vision Processing Unit), or an artificial intelligence-only processor such as an NPU.
  • One or more processors control to process input data according to a predefined operation rule or artificial intelligence model stored in a memory.
  • the artificial intelligence-only processor may be designed with a hardware structure specialized for processing a specific artificial intelligence model.
  • the predefined operation rules or artificial intelligence models are characterized by being created through learning.
  • being created through learning means that the basic artificial intelligence model is learned by using a plurality of learning data by a learning algorithm, thereby creating a predefined operation rules or artificial intelligence model set to perform a desired characteristic (or purpose).
  • Such learning may be performed in the device itself on which the artificial intelligence according to the present disclosure is performed, or may be performed through a separate server and/or system.
  • Examples of the learning algorithm include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.
  • the artificial intelligence model may be composed of a plurality of neural network layers.
  • Each of the plurality of neural network layers has a plurality of weight values, and performs a neural network operation through an operation between the operation result of the previous layer and the plurality of weights.
  • the plurality of weights of the plurality of neural network layers may be optimized by the learning result of the artificial intelligence model. For example, the plurality of weights may be updated so that a loss value or a cost value obtained from the artificial intelligence model is reduced or minimized during the learning process.
  • the artificial neural network may include a deep neural network (DNN), and examples thereof include, but are not limited to, a convolutional neural network (CNN), a deep neural network (DNN), a recurrent neural network (RNN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), or a deep Q-network.
  • DNN deep neural network
  • the processor can create a neural network, train (or learn) a neural network, perform computations based on received input data, and generate information signals based on the results of the computations, or retrain the neural network.
  • Neural networks include CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), perceptron, multilayer perceptron, FF (Feed Forward), RBF (Radial Basis Network), DFF (Deep Feed Forward), LSTM (Long Short Term Memory), GRU (Gated Recurrent Unit), AE (Auto Encoder), VAE (Variational Auto) Encoder), DAE (Denoising Auto Encoder), SAE (Sparse Auto Encoder), MC (Markov Chain), HN (Hopfield Network), BM (Boltzmann Machine), RBM (Restricted Boltzmann Machine), DBN (Depp Belief Network), DCN (Deep Convolutional Network), DN (Deconvolutional Network), DCIGN (Deep Convolutional Inverse Graphics Network), Generative Adversarial Network (GAN), Liquid State Machine (LSM), Extreme Learning Machine (ELM), It will be understood by those skilled in the art that any neural network may
  • the processor may be configured to perform a CNN (Convolution Neural Network) such as GoogleNet, AlexNet, VGG Network, R-CNN (Region with Convolution Neural Network), RPN (Region Proposal Network), RNN (Recurrent Neural Network), S-DNN (Stacking-based deep Neural Network), S-SDNN (State-Space Dynamic Neural Network), Deconvolution Network, DBN (Deep Belief Network), RBM (Restrcted Boltzman Machine), Fully Convolutional Network, LSTM (Long Short-Term Memory) Network, Classification Network, Generative Modeling, eXplainable AI, Continual AI, Representation Learning, AI for Material Design, BERT, SP-BERT, MRC/QA for natural language processing, Text Analysis, Dialog System, GPT-3, GPT-4, Visual Analytics for vision processing, Visual Understanding, Video Synthesis, ResNet for data intelligence, Anomaly Detection, Prediction, Time-Series Forecasting,
  • CNN Convolution Neural Network
  • CNN
  • ‘product’ may include, but is not limited to, general pharmaceuticals, quasi-drugs, health functional foods, medical devices, etc.
  • 'first UI' refers to an app screen displayed on the screen of the pharmacist terminal (20) when the pharmacist consults with a customer who has visited the pharmacy.
  • the 'first UI' can be switched to various screens depending on the consultation content (pharmacist's selection and customer's response).
  • 'second UI' refers to an app screen displayed on the screen of a customer terminal (30) when a customer conducts a consultation on his/her own without visiting a pharmacy.
  • the 'second UI' can be switched to various screens depending on the consultation content (customer response).
  • FIG. 1 is a schematic diagram illustrating a system for providing a drug recommendation service based on consultation according to an embodiment of the present disclosure.
  • a system for providing a pharmaceutical recommendation service based on consultation according to one embodiment may include a service server (10), a pharmacist terminal (20), and a customer terminal (30).
  • the system may include fewer or more components than the components illustrated in FIG. 1.
  • a system uses a pharmaceutical recommendation service provided by a service server (10) to enable a medical professional user (e.g., a pharmacist) to recommend a product to a customer visiting a medical institution (e.g., a pharmacy), or to enable a non-medical professional user to receive a recommendation for a product he or she needs without visiting a medical institution (e.g., a pharmacy).
  • a medical professional user e.g., a pharmacist
  • recommend a product to a customer visiting a medical institution (e.g., a pharmacy)
  • a non-medical professional user to receive a recommendation for a product he or she needs without visiting a medical institution (e.g., a pharmacy).
  • the service server (10) may be a server managed by a company that provides a drug recommendation service to medical users and non-medical users through a service platform.
  • the service server (10) can configure a service platform for medical users and a service platform for non-medical users differently and provide services to each.
  • the service server (10) can store and manage information and data generated when medical personnel and non-medical personnel use the service.
  • the pharmacist terminal (20) may be a terminal used by a medical professional (hereinafter, pharmacist) working at a medical institution (hereinafter, pharmacy).
  • the pharmacist terminal (20) may be a tablet (a device provided to a pharmacist by the pharmacy), a kiosk, a PC installed in a pharmacy, or a mobile phone carried by a pharmacist, and may include, but is not limited to, a processor such as a control unit, a photographing means such as a camera, an input/output means including a touch screen, and may include all electronic devices including a communication function.
  • a processor such as a control unit
  • a photographing means such as a camera
  • an input/output means including a touch screen and may include all electronic devices including a communication function.
  • Pharmacists can install a service application on their pharmacist terminal (20) and use the service by signing up and logging in.
  • a pharmacist can start a consultation with a customer who has visited the pharmacy after logging into the service application using the pharmacist terminal (20). Specifically, if the customer has visited before, the customer can start a consultation by logging into the service application and entering the customer's information (e.g., name, contact information). If the customer is visiting for the first time, the customer can start a consultation right away without entering the customer's information after logging into the service application.
  • the customer's information e.g., name, contact information
  • the consultation may begin without the customer entering any information.
  • the customer information may be entered first and then the consultation may begin.
  • a pharmacist can edit products held in the pharmacy after logging into the service application using a pharmacist terminal (20). Specifically, the held products can be added, deleted, or modified.
  • a pharmacist can log into the service application using a pharmacist terminal (20) and check the details of consultations he or she has conducted (or conducted by other pharmacists in the pharmacy).
  • a pharmacist can use a pharmacist terminal (20) to check the details of consultations conducted at the pharmacy for a specific period (e.g., one month).
  • a pharmacist can input information about a specific customer using a pharmacist terminal (20) and search for details of consultations conducted at his/her pharmacy or at other pharmacies for the customer, the patient's medication history, and information about medications prescribed to the customer. Specifically, a pharmacist can use the pharmacist terminal (20) to check medications prescribed to a specific customer at other medical institutions and check interactions with general medicines.
  • pharmacies and pharmacists are explained as pharmacies and pharmacists, but are not limited thereto, and medical institutions and medical personnel can be applied in various ways, such as hospitals, public health centers, doctors, and public health workers.
  • the customer terminal (30) may be a terminal used by a non-medical person.
  • the non-medical person may be a customer visiting a pharmacy, or a service user who wishes to proceed with consultation through the service platform on his/her own without visiting a pharmacy.
  • the service user can install the service application on his/her terminal (customer terminal) (30) and use the service by signing up and logging in.
  • Non-medical service users can log in to the service application and begin consultation by entering their information (e.g. name, contact information, symptoms, etc.).
  • information e.g. name, contact information, symptoms, etc.
  • the customer terminal may be applied with an information processing means such as a computer, and may include a processor such as a control unit, a photographing means such as a camera, an input/output means including a touch screen, and may mean any device including a communication function.
  • a processor such as a control unit
  • a photographing means such as a camera
  • an input/output means including a touch screen
  • any device such as a smartphone, tablet, PDA, laptop, or desktop may be applied.
  • Fig. 2 is a block diagram of a pharmaceutical recommendation service providing device (hereinafter, “pharmaceutical recommendation service providing device”) (100) based on consultation according to an embodiment of the present disclosure.
  • the pharmaceutical recommendation service providing device (100) to be described with reference to Fig. 2 may be the service server (10) described with reference to Fig. 1 above.
  • the drug recommendation service providing device (100) may include a communication unit (110), a memory (120), and a processor (130). However, in some embodiments, the drug recommendation service providing device (100) may include fewer or more components than the components illustrated in FIG. 2.
  • the communication unit (110) may include one or more modules that enable wireless or wired communication between the pharmaceutical recommendation service providing device (100) and a pharmacist terminal (20), between the pharmaceutical recommendation service providing device (100) and a customer terminal (30), between the pharmaceutical recommendation service providing device (100) and an external server (not shown), between the pharmaceutical recommendation service providing device (100) and an external device (not shown), and between the pharmaceutical recommendation service providing device (100) and a communication network.
  • a pharmacist terminal (20) between the pharmaceutical recommendation service providing device (100) and a customer terminal (30), between the pharmaceutical recommendation service providing device (100) and an external server (not shown), between the pharmaceutical recommendation service providing device (100) and an external device (not shown), and between the pharmaceutical recommendation service providing device (100) and a communication network.
  • a wired communication module e.g., a wireless communication module
  • a short-range communication module e.g., a short-range communication module
  • a location information module e.g., a location information module.
  • the external device may be, but is not limited to, a payment device (POS device) installed in a pharmacy.
  • POS device a payment device
  • the external server may be, but is not limited to, a pharmacy server, a payment server, or a database server.
  • the communication network may use various types of communication networks, for example, wireless communication methods such as WLAN (Wireless LAN), Wi-Fi, Wibro, WiMAX, and HSDPA (High Speed Downlink Packet Access), or wired communication methods such as Ethernet, xDSL (ADSL, VDSL), HFC (Hybrid Fiber Coax), FTTC (Fiber to The Curb), and FTTH (Fiber To The Home) may be used.
  • wireless communication methods such as WLAN (Wireless LAN), Wi-Fi, Wibro, WiMAX, and HSDPA (High Speed Downlink Packet Access)
  • wired communication methods such as Ethernet, xDSL (ADSL, VDSL), HFC (Hybrid Fiber Coax), FTTC (Fiber to The Curb), and FTTH (Fiber To The Home) may be used.
  • the communication network is not limited to the communication methods presented above, and may include all other forms of communication methods that are widely known or will be developed in the future in addition to the above-described communication methods.
  • the wired communication module may include various wired communication modules such as a Local Area Network (LAN) module, a Wide Area Network (WAN) module, or a Value Added Network (VAN) module, as well as various cable communication modules such as a Universal Serial Bus (USB), a High Definition Multimedia Interface (HDMI), a Digital Visual Interface (DVI), RS-232 (recommended standard232), power line communication, or plain old telephone service (POTS).
  • LAN Local Area Network
  • WAN Wide Area Network
  • VAN Value Added Network
  • USB Universal Serial Bus
  • HDMI High Definition Multimedia Interface
  • DVI Digital Visual Interface
  • RS-232 recommended standard232
  • POTS plain old telephone service
  • the wireless communication module may include, in addition to a WiFi module and a Wireless Broadband module, a wireless communication module that supports various wireless communication methods such as GSM (global System for Mobile Communication), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), UMTS (universal mobile telecommunications system), TDMA (Time Division Multiple Access), LTE (Long Term Evolution), 4G, 5G, and 6G.
  • GSM Global System for Mobile Communication
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • UMTS universalal mobile telecommunications system
  • TDMA Time Division Multiple Access
  • LTE Long Term Evolution
  • the short-range communication module is for short-range communication and can support short-range communication using at least one of BluetoothTM, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus) technologies.
  • RFID Radio Frequency Identification
  • IrDA Infrared Data Association
  • UWB Ultra Wideband
  • ZigBee Ultra Wideband
  • NFC Near Field Communication
  • Wi-Fi Wireless-Fidelity
  • Wi-Fi Direct Wireless USB (Wireless Universal Serial Bus) technologies.
  • the memory (120) may store at least one process for providing a service of recommending a product based on consultation with a customer.
  • the memory (120) can store data supporting various functions of the drug recommendation service providing device (100) and a program for the operation of the processor (130), can store input/output data (e.g., music files, still images, moving images, etc.), and can store a plurality of application programs (or applications) run by the drug recommendation service providing device (100), data for the operation of the drug recommendation service providing device (100), and commands. At least some of these application programs can be downloaded from an external server via wireless communication.
  • the memory (120) may include at least one type of storage medium among a flash memory type, a hard disk type, an SSD (Solid State Disk type), an SDD (Silicon Disk Drive type), a multimedia card micro type, a card type memory (for example, an SD or XD memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk.
  • the memory (120) may be a database that is separate from the drug recommendation service providing device (100) but is connected by wire or wirelessly.
  • the processor (130) can perform the above-described operation using a memory that stores data on an algorithm for controlling the operation of components within the pharmaceutical recommendation service providing device (100) or a program that reproduces the algorithm, and the data stored in the memory.
  • the memory (120) and the processor (130) can be implemented as separate chips.
  • the memory (120) and the processor (130) can be implemented as a single chip.
  • processor (13) can control one or more of the components discussed above in combination to implement various embodiments according to the present disclosure described in FIGS. 3 to 11 below on the pharmaceutical recommendation service providing device (100).
  • FIG. 3 is a flowchart of a method for providing a pharmaceutical recommendation service through a pharmaceutical platform according to an embodiment of the present disclosure.
  • the method of FIG. 3 may be performed by the pharmaceutical recommendation service providing device (100) disclosed in FIG. 2, but is not limited thereto and may also be performed by the service server (10) disclosed in FIG. 1.
  • FIGS. 4 to 10 are drawings for explaining a UI (User Interface) provided to a pharmacist terminal for conducting consultation through a pharmacist platform according to one embodiment of the present disclosure.
  • UI User Interface
  • FIG. 11 is a diagram illustrating an algorithm for sequentially providing multiple questions about a customer's condition according to one embodiment of the present disclosure.
  • the processor (130) of the pharmaceutical recommendation service providing device (100) can sequentially provide multiple questions for detailed symptom confirmation of the customer's disease through the first UI (User Interface) output to the pharmacist terminal (20) (S310).
  • first UI User Interface
  • the processor (130) of the pharmaceutical recommendation service providing device (100) can recommend a type of pharmaceutical for improving the disease based on the response to each of the plurality of questions received from the pharmacist terminal (20) through the first UI (S320).
  • consultation can begin after the customer's information is entered into the pharmacist terminal (20).
  • the processor (13) receives the customer's information from the pharmacist terminal (20), it can provide the customer's consultation history so that consultation can be conducted based on the consultation history.
  • the customer's consultation history is accumulated and saved as a result of consultations at different pharmacies, and can be shared among pharmacists using the drug recommendation service through the service platform. That is, if one customer has been to multiple pharmacies using the drug recommendation service in the past and received consultations, the contents of each consultation can be accumulated and saved within the platform, and provided as a list to the pharmacist terminal (20) currently conducting the consultation.
  • the customer information may be received by the pharmacist receiving the customer's voice message and entering it into the pharmacist terminal (20) on behalf of the customer, or may be received by the customer directly entering it into the pharmacist terminal (20).
  • the customer information may be, but is not limited to, the customer's contact information or name.
  • the pharmacist terminal (20) may display a first UI including the customer's name, contact information, age, gender, and consultation history list.
  • the processor (130) may cause the consultation to proceed based on the selected consultation history.
  • the processor (130) can sequentially provide multiple questions to the pharmacist terminal (20) to improve a disease identified from the selected consultation history.
  • the processor (130) may recommend the same medicine as the selected consultation history (because it was effective in improving the disease).
  • the processor (130) may recommend a different medicine from the selected consultation history (because it was not effective in improving the condition).
  • the processor (130) can determine whether the customer is satisfied with the product through the customer's evaluation of the product purchased in the last consultation, and determine whether to recommend the same type of medicine or a different type of medicine based on the satisfaction level.
  • the processor (130) can recommend other products by taking into consideration not only the selected consultation history but also the customer's age, gender, underlying disease, prescription history, and product purchase history.
  • the processor (130) can start a new consultation for an existing customer in the same way as conducting a consultation for a new customer. A detailed description of this is the same as the description of the consultation method for a new customer described below.
  • the processor (130) can initialize all information except customer information.
  • the pharmacist can start consultation right away without entering the customer's information (e.g., contact information) into the pharmacist terminal (20).
  • customer's information e.g., contact information
  • the first UI includes a customer information input area (51), whereby name, contact information, age, and gender can be input from a pharmacist or customer.
  • name, contact information, age, and gender can be input from a pharmacist or customer.
  • the name and contact information are sensitive information, only age and gender, which are information helpful in predicting disease, may be input.
  • the processor (13) can display a first UI including a human body diagram (61) and a detailed part selection area (62) for confirming the part of the symptom on the pharmacist terminal (20).
  • 'head' may be selected in the human body diagram (61), and if the customer answers that he/she feels pain mainly in the forehead of the head, 'forehead' may be selected in the detailed body part selection area (62).
  • a modal window may be launched to identify at least one aspect of the symptom.
  • the symptom pattern can be selected as 'rash and dry skin' (71) based on the customer's response.
  • the processor (130) can predict the customer's disease based on this response. That is, the processor (130) can suggest a possible disease by considering the customer's symptom site, symptom pattern, gender, age, etc.
  • the processor (130) may provide a list of the customer's diseases (72) based on the response that the customer's symptoms mainly appear on the head, especially the forehead, and that the symptoms appear in the form of rash and dry skin.
  • the pharmacist may select at least one disease from the list of diseases (72) and then select (touch or click) a selection completion button (73).
  • the pharmacist may select a disease by searching for the disease name or disease area in the search box without selecting the customer's symptom area.
  • the processor (130) switches to the product recommendation screen when the recommended medicine and consultation method inquiry button (81) is selected (touched or clicked).
  • the disease selected in Fig. 8 can be deleted. For example, among atopic dermatitis and contact dermatitis, contact dermatitis can be deleted.
  • the processor (130) can recommend a medicine suitable for a disease by asking multiple questions about the selected disease. If there are multiple selected diseases, multiple questions about each disease are provided, and a medicine suitable for each disease can be recommended based on the response to each question.
  • the processor (130) can sequentially provide multiple questions for symptom confirmation, one by one, based on the customer's response to each question. Specifically, a question matching the input customer information can be read from a DB (a DB that constructs symptom-related questions as a flow chart) and displayed on the screen, and the next question matching the response to the displayed question can be read from the DB and displayed on the screen.
  • a DB a DB that constructs symptom-related questions as a flow chart
  • multiple questions are asked to identify detailed symptoms for the selected disease, and may include questions to identify the intensity and pattern of symptoms felt by the customer, factors causing and aggravating the symptoms, and the time of onset.
  • Multiple-choice questions consist of questions that can be answered with either yes or no, and the content of the next question can be determined based on the answer to the previous question.
  • the remaining questions can be provided with different content depending on the response to the previous question. For example, if the answer to the first question is 'yes', question A can be provided as the second question, and if the answer to the first question is 'no', question B can be provided as the second question.
  • the first question can be fixed as the question that needs to be confirmed most urgently for the disease.
  • the number of previously recommended drug types may change each time a response is received to any of the questions other than the first question among multiple questions.
  • a medicine that matches the customer's symptoms is deduced or added. For example, if there are 10 types of medicines recommended when a response to the first question is received, the types of medicines recommended when a response to the second question is received may be 7 or 12. Or, unlike the method in which the types of recommended medicines change each time a question is received, when a response to a question is completed, a method may be provided in which medicines matching all symptoms are recommended.
  • the processor (130) can display a first UI including an area (91) in which multiple questions about the disease are provided and an area (92) that recommends a type of medicine for improving the disease on the pharmacist terminal (20).
  • Questions are sequentially provided one by one in the question area (91), and the type of medicine can be provided in the medicine recommendation area (92) according to the response to each question.
  • the drug recommendation area (92) only one type of drug may be recommended for disease improvement, but if the academic evidence grades of the drugs to be taken for disease improvement are determined to be different, multiple types may be classified according to the academic evidence grades and multiple drugs may be recommended for each type.
  • the processor (130) determines that the academic evidence grades for multiple types of medicines that need to be taken to improve a disease are divided into first and second levels, the processor (130) can recommend the first type of medicine and the second type of medicine together through the first UI.
  • the first recommended product area (92-1) and the second recommended product area (92-2) can be divided to provide different types of pharmaceutical products.
  • the first recommendation product area (92-1) can display a list of the first type of drugs with the first-ranked academic evidence grade among multiple drugs that need to be taken to improve a disease
  • the second recommendation product area (92-2) can display a list of the second type of drugs with the second-ranked academic evidence grade among multiple drugs that need to be taken to improve a disease.
  • the pharmacist can select any number of drugs from any type of the first type of drug list and the second type of drug list.
  • the question algorithm for recommending drugs will be described in detail with reference to FIG. 11 below.
  • the processor (13) may recommend medicine based on the customer's underlying disease and allergy information.
  • the underlying disease and allergy information may already be displayed in the underlying disease information and allergy information area (93) in the case of an existing customer, and in the case of a new customer, the pharmacist may confirm the information from the customer and enter it in the underlying disease information and allergy information area (93).
  • the processor (13) may recommend a medicine based on the customer's medication history information.
  • the medication history information may be checked through the medication history inquiry button (93), and if the customer is a new customer, no information may be provided even if the medication history inquiry button (93) is pressed.
  • the medication history inquiry button (93) may be pressed, a response regarding the medication history may be received from the customer, and a product may be recommended based on this.
  • the processor (130) can recommend a medicine for each predicted disease. Referring to FIG. 9, the processor (130) can recommend a medicine for atopic dermatitis and a medicine for contact dermatitis, respectively.
  • the processor (130) can display a first UI including a list of multiple products for a type of medicine recommended for a disease on the pharmacist terminal (20).
  • the processor (130) can extract only products corresponding to the classification criteria from among multiple products according to the classification criteria received from the pharmacist terminal (20), and sort the extracted products according to the preset sorting criteria.
  • the classification criteria are criteria for filtering some of the multiple products related to the recommended medicine. Since the products held by the pharmacy for a specific medicine may be diverse, and furthermore, the products distributed may be even more diverse, only some are extracted according to the classification criteria.
  • the classification criteria are products held by a pharmacy
  • products related to medicines that are not held by the pharmacy may be filtered out and disappear from the list.
  • the sorting criterion is a criterion for determining the exposure order of products extracted based on the classification criterion, and may be at least one of product inventory, product margin rate, degree of relevance to the customer's underlying disease, and pharmacist custom.
  • At least one of the product inventory and the product margin rate can be set as the sorting criteria, and when not linked, at least one of the degree of relevance to the customer's underlying disease and the pharmacist's custom can be set as the sorting criteria.
  • the extracted products could be sorted in order of high inventory within the pharmacy. Or, the extracted products could be sorted in order of high margins. Or, the extracted products could be sorted in order of low association with the customer's underlying condition.
  • the processor (130) can extract only products available at the pharmacy where the pharmacist works.
  • the processor (130) can extract only products corresponding to external dexpanthenol.
  • multiple classification criteria can be selected in the classification criteria selection area (101) illustrated in FIG. 10. For example, if 'Show only pharmacy-available products' and 'External dexpanthenol' are selected, the processor (130) can extract only products corresponding to external dexpanthenol and available at pharmacies.
  • no classification criteria may be selected in the classification criteria selection area (101) illustrated in FIG. 10.
  • products can be sorted only by sorting criteria without applying classification criteria.
  • the processor (130) may sort products extracted by applying classification criteria or multiple products to which classification criteria are not applied in order of high margin rates according to a margin rate-based sorting request (102) received from the pharmacist terminal (20).
  • a margin rate-based sorting request (102) received from the pharmacist terminal (20).
  • margin rate-based sorting (102) is illustrated, but other sorting criteria may also be displayed in the UI, and criteria may be applied according to the pharmacist's selection.
  • the processor (130) can request input of a sales price to the pharmacist terminal (20) and register the input sales price as the sales price of the corresponding product.
  • the processor (130) can add the product to the pharmacy's stock products. After the product is added as a stock product, the sales registration can be performed.
  • the processor (130) can include the product in the selected product list at the bottom of the screen.
  • the processor (130) can delete the corresponding product from the list.
  • the processor (130) can switch to the screen of FIG. 9.
  • the total price for the selected product may be displayed at the bottom of the screen of Fig. 9. According to an embodiment, if a change in quantity for the selected product is requested from the pharmacist terminal (20), the total price may be changed based on the changed quantity.
  • the processor (130) When the processor (130) receives a product selection completion button (96) from the pharmacist terminal (20), it confirms at least one selected product as the final recommended product for improving the customer's symptoms.
  • the processor (130) may store the customer's consultation history.
  • the processor (130) of the pharmaceutical recommendation service providing device (100) can request payment for a product selected by the pharmacist terminal (20) among multiple products corresponding to a pharmaceutical type to the pharmacy's payment system server (same as POS deletion, hereinafter) (S330).
  • the processor (130) may provide payment information for the selected product (final recommended product) to the payment system server so that payment for the selected product may be made through a payment device installed in the pharmacy.
  • the processor (130) may receive information about the other products from the pharmacy payment system server and add them to the customer's purchase information, and may add the consultation results including the purchase information to the customer's consultation history.
  • the pharmacist uses the payment system device to pay for additional purchase products along with the final recommended product, and the processor (130) receives purchase information about the additional purchase products from the pharmacy payment system server and adds it to the consultation history of the customer. This information can be used as reference information for pharmacists conducting other consultations in the future.
  • the processor (130) can provide a solution to the pharmacist terminal (20).
  • the solution may include information about the selected product (i.e., the product purchased by the customer), how-to instructions for using the selected product (i.e., the product purchased by the customer), and a lifestyle guide.
  • the product usage and lifestyle guide can be generated based on the customer's response to the symptoms.
  • the product usage and lifestyle while using the product can be customized to the customer based on the customer's symptoms.
  • the solution can be delivered to the customer's terminal based on the customer's information stored in the customer DB.
  • the solution can be transmitted to the customer's terminal (30) based on the customer's information entered by the pharmacist through the pharmacist terminal (20).
  • the new customer's information (contact information) obtained in this way is stored in the customer DB so that consultation can be conducted as an existing customer when visiting the pharmacy in the future.
  • the processor (130) can recommend at least one hospital based on the consultation content conducted up to the time the request was received, customer information (age, gender), and the customer's location.
  • a hospital referral can be requested through the customer terminal (20) so that the customer can quickly receive hospital treatment.
  • the processor (130) determines the department based on the consultation content and customer information (age, gender), and extracts a list of hospitals with the department among hospitals within a preset distance based on the customer's location and provides the list to the customer terminal (20).
  • the processor (130) can add the corresponding consultation content to the customer's consultation history.
  • the processor (130) can add the corresponding consultation content to the customer's consultation history.
  • the question algorithm of the present disclosure sequentially provides multiple questions to confirm detailed symptoms of a patient's (customer's) disease predicted through the symptom site and aspect of the patient's (customer's) input in the previous step.
  • questions for confirming a patient group questions for determining risk signs, questions for confirming a cause, questions for confirming a detailed condition, and questions for confirming a duration may be provided, but are not limited thereto, and various types of questions may be provided to confirm the customer's condition.
  • the processor (130) can identify a patient group through a question for patient group confirmation, and provide a question (16-1-1) for risk sign determination based on patient information.
  • the processor (130) can determine the patient's treatment plan (16-3-1) as 'visiting a specific department' or as 'visiting an emergency room' depending on the symptoms.
  • the processor (130) may provide a question (16-1-2) for cause determination.
  • the processor (130) may provide a question (16-1-3) for detailed status confirmation.
  • the processor (130) can determine the visiting department of the patient or determine a visit to the emergency room based on the symptoms.
  • the processor (130) can recommend the first type of medicines (16-2-1, 16-2-2).
  • the processor (130) may recommend the first type of drugs (16-2-1, 16-2-2).
  • the processor (130) additionally provides a question (16-1-4) for checking the duration, and if the answer to the question (16-1-4) for checking the duration is 'No', the processor (130) can additionally recommend the first type of medicine (16-2-3), and if the answer is 'Yes', the processor (130) can additionally recommend the first type of medicine (16-2-4). And the processor (130) can determine the treatment plan (16-3-2) of the patient as '1 week of observation required'.
  • the question algorithm can determine the treatment plan right away or change the questions provided next based on the patient's response, and the types of medicines recommended can also change and the treatment plan can also change.
  • the first type of medicine is recommended, as described above, both the first type of medicine and the second type of medicine can be recommended together based on the academic evidence level.
  • Questions sequentially provided through this question algorithm are displayed in the question area (91) illustrated in Fig. 9, and medicines extracted according to the answers to the questions can be displayed as a list in the medicine recommendation area (92) illustrated in Fig. 9.
  • the processor (130) can transmit the treatment plan finally determined through this question algorithm to at least one of the pharmacist terminal (20), the customer terminal (30), and an external server (e.g., a hospital server).
  • an external server e.g., a hospital server
  • a customer uses the drug recommendation service.
  • the customer described in Fig. 12 refers to a non-medical person who tries to receive a product recommendation through the service platform on his/her own without visiting a pharmacy.
  • Fig. 12 is a flowchart of a method for providing a pharmaceutical recommendation service through a customer platform according to an embodiment of the present disclosure.
  • the method of Fig. 12 may be performed by the pharmaceutical recommendation service providing device (100) disclosed in Fig. 2, but is not limited thereto and may also be performed by the service server (10) disclosed in Fig. 1.
  • the processor (130) of the pharmaceutical recommendation service providing device (100) can receive a consultation request from a customer terminal (30) (S1210).
  • the processor (130) of the pharmaceutical recommendation service providing device (100) can sequentially provide multiple questions for detailed symptom confirmation of the customer's disease through the second UI output to the customer terminal (30) (S1220).
  • the processor (130) of the pharmaceutical recommendation service providing device (100) can recommend a type of pharmaceutical for improving a disease based on responses to each of a plurality of questions received from the customer terminal (30) (S1230).
  • a patient who does not have time to visit a hospital can use his/her own terminal (30) to check his/her own symptoms and receive guidance on medications that can be taken for the corresponding symptoms.
  • the way in which customers (service users) conduct consultations on their own through the service platform may be the same as the way in which the pharmacist conducts consultations for customers (customers visiting the pharmacy) through the service platform.
  • the second UI provided to customers can be configured to be easier for non-medical customers to understand, unlike the first UI provided to pharmacists.
  • the question algorithm, terminology, and consultation method can be configured more easily according to the disease to increase customer understanding.
  • the processor (130) can extract a medicine that matches the customer's symptoms through multiple questions.
  • the processor (130) When the processor (130) receives information about a product owned by a customer from the customer terminal (30), it can determine whether the product owned by the customer can be used to improve the customer's symptoms.
  • a usage guide for the product (how to use the product, time of use, number of times, lifestyle habits when using the product, etc.) can be provided to the customer terminal (30).
  • the processor (130) analyzes the taken images and, if there is a product among the customer's products that is related to a type of medicine for improving symptoms, it can provide a user guide for the product.
  • the processor (130) can immediately provide guidance on products that can be taken among the products owned after completing responses to multiple questions (self-check questions).
  • the processor (130) can provide the customer terminal (30) with information on a pharmacy where the product related to medicine for symptom improvement can be purchased.
  • the recommended pharmacy may be a pharmacy that uses the medicine recommendation service (i.e., a medical product recommendation service affiliated store) or may be a pharmacy that does not use the medicine recommendation service.
  • the processor (130) may provide location information of a pharmacy where a product can be purchased to a customer terminal (30).
  • the location information may be provided by distinguishing between a pharmacy that uses a pharmaceutical recommendation service (i.e., a pharmaceutical product recommendation service affiliate) and a pharmacy that does not use a pharmaceutical recommendation service.
  • a pharmaceutical recommendation service i.e., a pharmaceutical product recommendation service affiliate
  • consultations conducted by the customer on his/her own can also be added to the customer's consultation history. Accordingly, when the customer visits a pharmacy based on the recommended pharmacy information, the pharmacist can input the customer's information through the service platform, check the consultation history conducted by the customer on his/her own, and proceed with product payment without a separate consultation.
  • a customer can make a pharmacy visit reservation based on the provided pharmacy information.
  • the processor (130) receives a visit reservation for a specific pharmacy from the customer terminal (30), it can provide the visit reservation information of the customer and the consultation contents that the customer has conducted on his/her own to the pharmacist terminal (20) of the specific pharmacy. Accordingly, the customer can visit the pharmacy and purchase the product immediately without a separate consultation.
  • FIGS. 3 and 12 describe the steps as being executed sequentially, this is only an example to explain the technical idea of the present embodiment, and those skilled in the art to which the present embodiment pertains may modify and apply various modifications and variations by changing the order described in FIGS. 3 and 12 or executing them in parallel without departing from the essential characteristics of the present embodiment. Therefore, FIGS. 3 and 12 are not limited to a chronological order.
  • steps described in FIG. 3 and FIG. 12 may be further divided into additional steps or combined into fewer steps, depending on the implementation example of the present disclosure.
  • some steps may be omitted as needed, and the order between the steps may be changed.
  • the disclosed embodiments may be implemented in the form of a recording medium storing instructions executable by a computer.
  • the instructions may be stored in the form of program codes, and when executed by a processor, may generate program modules to perform the operations of the disclosed embodiments.
  • the recording medium may be implemented as a computer-readable recording medium.
  • Computer-readable storage media include all types of storage media that store instructions that can be deciphered by a computer. Examples include ROM (Read Only Memory), RAM (Random Access Memory), magnetic tape, magnetic disk, flash memory, and optical data storage devices.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • magnetic tape magnetic tape
  • magnetic disk magnetic disk
  • flash memory optical data storage devices

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Business, Economics & Management (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Accounting & Taxation (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Finance (AREA)
  • General Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Economics (AREA)
  • Medicinal Chemistry (AREA)
  • Development Economics (AREA)
  • Chemical & Material Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Biomedical Technology (AREA)
  • Marketing (AREA)
  • Bioethics (AREA)
  • Pharmacology & Pharmacy (AREA)
  • Toxicology (AREA)
  • Pathology (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

L'invention concerne un dispositif et un procédé pour fournir un service de recommandation de médicament sur la base d'une consultation. Le dispositif comprend : une unité de communication; une mémoire pour stocker au moins un processus pour fournir un service afin de recommander un produit sur la base d'une consultation avec un client; et un processeur pour effectuer une opération selon le processus. Le processeur : fournit séquentiellement une pluralité de questions pour vérifier des symptômes détaillés de la maladie du client par l'intermédiaire d'une première sortie d'interface utilisateur (UI) à un terminal de pharmacien; recommande un type de médicament pour soulager la maladie sur la base d'une réponse, reçue du terminal de pharmacien par l'intermédiaire de la première UI, à chaque question de la pluralité de questions; et demande un paiement à un serveur de pharmacie pour un produit sélectionné par le terminal de pharmacien parmi une pluralité de produits correspondant au type de médicament.
PCT/KR2024/016803 2023-10-31 2024-10-30 Dispositif et procédé pour fournir un service de recommandation de médicament sur la base d'une consultation Pending WO2025095574A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR10-2023-0148362 2023-10-31
KR1020230148362A KR102670755B1 (ko) 2023-10-31 2023-10-31 상담을 기반으로 한 의약품 추천 서비스 제공 장치 및 방법

Publications (1)

Publication Number Publication Date
WO2025095574A1 true WO2025095574A1 (fr) 2025-05-08

Family

ID=91275487

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/KR2024/016803 Pending WO2025095574A1 (fr) 2023-10-31 2024-10-30 Dispositif et procédé pour fournir un service de recommandation de médicament sur la base d'une consultation

Country Status (2)

Country Link
KR (2) KR102670755B1 (fr)
WO (1) WO2025095574A1 (fr)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102670755B1 (ko) * 2023-10-31 2024-06-03 주식회사 참약사 상담을 기반으로 한 의약품 추천 서비스 제공 장치 및 방법
KR102811681B1 (ko) * 2024-11-21 2025-05-23 주식회사 젠피티랩 생성형 인공지능 모델 기반 약국 관련 정보 및 콘텐츠 제공 방법, 장치 및 시스템

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20150078907A (ko) * 2013-12-31 2015-07-08 (주)옵티마케어 약국 경영관리 시스템 및 그의 제어방법
KR20210094737A (ko) * 2020-01-22 2021-07-30 건국대학교 글로컬산학협력단 의약품 배달 서비스 제공 장치 및 방법
KR20220132760A (ko) * 2021-03-24 2022-10-04 주식회사 이블루 환자 및 약국관리를 위한 모바일 단말기 및 이를 구현하기 위한 프로그램이 저장된 기록매체
KR20230043628A (ko) * 2021-09-24 2023-03-31 주식회사 참약사 건강관리용 상담 시스템
KR20230064329A (ko) * 2021-11-03 2023-05-10 주식회사 메타센테라퓨틱스 고객 맞춤형 처방 정보 및 성분 제공 장치 및 방법
KR102670755B1 (ko) * 2023-10-31 2024-06-03 주식회사 참약사 상담을 기반으로 한 의약품 추천 서비스 제공 장치 및 방법

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101943217B1 (ko) 2017-08-31 2019-01-30 정혜원 의약품 식별 방법 및 이를 이용한 의약품 식별 장치

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20150078907A (ko) * 2013-12-31 2015-07-08 (주)옵티마케어 약국 경영관리 시스템 및 그의 제어방법
KR20210094737A (ko) * 2020-01-22 2021-07-30 건국대학교 글로컬산학협력단 의약품 배달 서비스 제공 장치 및 방법
KR20220132760A (ko) * 2021-03-24 2022-10-04 주식회사 이블루 환자 및 약국관리를 위한 모바일 단말기 및 이를 구현하기 위한 프로그램이 저장된 기록매체
KR20230043628A (ko) * 2021-09-24 2023-03-31 주식회사 참약사 건강관리용 상담 시스템
KR20230064329A (ko) * 2021-11-03 2023-05-10 주식회사 메타센테라퓨틱스 고객 맞춤형 처방 정보 및 성분 제공 장치 및 방법
KR102670755B1 (ko) * 2023-10-31 2024-06-03 주식회사 참약사 상담을 기반으로 한 의약품 추천 서비스 제공 장치 및 방법

Also Published As

Publication number Publication date
KR102670755B1 (ko) 2024-06-03
KR102671126B1 (ko) 2024-05-30

Similar Documents

Publication Publication Date Title
Gandhi et al. How can artificial intelligence decrease cognitive and work burden for front line practitioners?
WO2025095574A1 (fr) Dispositif et procédé pour fournir un service de recommandation de médicament sur la base d'une consultation
Cox et al. Utilizing ChatGPT-4 for providing medical information on blepharoplasties to patients
WO2020113960A1 (fr) Procédé, appareil et dispositif de délivrance de médicaments sur ordonnance partagée, et support de stockage
WO2020113959A1 (fr) Procédé, appareil et dispositif d'évaluation de niveau de dialyse d'institution médicale et support d'informations
US20230282325A1 (en) Interactive user interface and optimized health plan ranking
Meyerhoefer et al. The consequences of electronic health record adoption for physician productivity and birth outcomes
US20200279629A1 (en) System and method for gathering and analyzing human experience reports
WO2013027869A1 (fr) Procédé de fourniture d'un service de soins de santé qui fournit un rappel conscient de lui-même pour une motivation de soins de santé
Singh et al. Embryonic Machine-Deep Learning, Smart Healthcare and Privacy Deliberations in Hospital Industry: Lensing Confidentiality of Patient’s Information and Personal Data in Legal-Ethical Landscapes Projecting Futuristic Dimensions
WO2020138924A2 (fr) Système de gestion d'informations liées à l'épilepsie
WO2024039120A1 (fr) Dispositif de diagnostic portable sans face à face ayant des capteurs
Cardinale et al. Clinical pharmacist led medication reconciliation program in an Emergency Department Observation Unit
WO2025206647A1 (fr) Serveur pour le calcul d'une quantité à commander sur la base d'une consommation et d'une prédiction de la demande de produits d'un magasin sans personnel, et son procédé de commande
KR20250028225A (ko) 인공지능 기반의 훈련 태스크 조정 장치 및 이의 제어 방법
WO2024071595A1 (fr) Procédé et dispositif de détection de médicament à effets secondaires et de fourniture de médicament optimisé à l'aide de données personnalisées sur les effets secondaires
WO2024090716A1 (fr) Dispositif de soins de santé numérique basé sur l'intelligence artificielle, et procédé mis en œuvre par ordinateur associé
WO2019010266A1 (fr) Gestion de prévention de réadmissions ainsi que procédé et système associés
WO2013172490A1 (fr) Système de soins et procédé de fourniture d'un service de soins
Ramanathan et al. An Ethical Outlook on the Applications of Artificial Intelligence in Medicine and Pharmacy
WO2025095532A1 (fr) Procédé et dispositif basés sur l'intelligence artificielle pour fournir un service de diagnostic médical à l'aide d'une corrélation entre des symptômes et des maladies
KR102743128B1 (ko) 의약품 추천을 위한 상담 질문 동적 변경 시스템, 상담 질문 동적 변경 서버 및 이의 실행 방법
Happ Meeting the challenges in communication change intervention development and testing
KR102743131B1 (ko) 사용자 맞춤형 의약품 추천 시스템, 사용자 맞춤형 의약품 추천 서버 및 이의 실행 방법
Giridhar Machine Learning in Personalization

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 24886247

Country of ref document: EP

Kind code of ref document: A1