Artificial intelligence-based accompanying person and patient matching system
By using an AI-based system to match caregivers with patients, precise matching and efficient dispatch of care services have been achieved. This has solved the problems of application gaps and difficulty in ensuring quality in existing systems for care services, and improved user experience and service efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-17
- Publication Date
- 2026-03-31
AI Technical Summary
The existing order-grabbing and dispatching system cannot meet the personalized needs of the caregiving service sector. It suffers from poor matching accuracy, difficulty in guaranteeing service quality, and a lack of intelligent matching capabilities.
An AI-based matching system is adopted, which uses user terminals, caregiver terminals, cloud servers and AI matching modules to achieve accurate matching of patient needs and caregiver service capabilities. A multi-dimensional qualification review and capability evaluation system is constructed, and a two-way interactive mechanism of order grabbing and order dispatch is adopted.
It improves the accuracy of matching caregiving services, ensures service quality, increases dispatch efficiency, reduces the incidence of service disputes, supports multi-dimensional order inquiries, and meets the needs of patients' families for handling matters on their behalf.
Smart Images
Figure CN121768612A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of medical service technology, specifically referring to an artificial intelligence-based matching system for caregivers and patients. Background Technology
[0002] In the healthcare service landscape, patients' demand for companions and caregivers is increasing, especially among elderly patients, patients with mobility issues, and patients seeking medical treatment in other locations. Companionship services can effectively improve the efficiency and experience of medical care. However, the current matching model for companionship services has many pain points: patients' families often rely on introductions from acquaintances or "try their luck" at the hospital to find companions, which not only limits the range of choices but also makes it difficult to verify the qualifications, skills, and experience of companions, resulting in significant uncertainty in service quality; while some offline intermediaries provide matching services, they suffer from problems such as information asymmetry, opaque pricing, and low dispatch efficiency, and are unable to dynamically adjust the matching plan according to the patient's real-time medical needs.
[0003] Existing order-grabbing and dispatching systems are primarily used in the instant delivery sector, such as ride-hailing and food delivery. Their core focus is on "capacity" to address location-based transportation or travel needs, prioritizing fulfillment efficiency. The entire service process is controlled and managed by the capacity provider. This system's design logic is only suitable for scenarios with short service cycles and standardized service content. However, caregiving services are characterized by flexible fulfillment cycles (from a few hours of accompanying a patient to months of long-term caregiving), personalized service content (requiring consideration of the patient's condition, medical procedures, and personal habits), and strict service qualification requirements. Existing order-grabbing and dispatching systems cannot meet these needs, leaving their application in the caregiving service sector largely unexplored.
[0004] Although some medical-related systems have begun to try managing caregiver services, they mostly focus on the simple display of caregiver information and lack intelligent matching capabilities based on multi-dimensional data. They cannot achieve accurate matching between patients' needs and caregivers' service capabilities, nor have they formed an efficient order-grabbing and dispatching collaboration mechanism, making it difficult to meet the matching needs of large-scale and standardized caregiver services. Summary of the Invention
[0005] To address the application gaps in existing order-grabbing and dispatching systems in the field of caregiving services, as well as the problems of low efficiency, poor matching accuracy, and difficulty in guaranteeing service quality in traditional caregiving matching models, this invention provides an artificial intelligence-based matching system for caregivers and patients. Through AI intelligent analysis and a two-way interactive order-grabbing and dispatching mechanism, it achieves accurate and efficient matching between patient needs and caregiver service capabilities.
[0006] To achieve the above functions, the technical solution adopted by the present invention is as follows: a matching system for caregivers and patients based on artificial intelligence, including a user terminal, a caregiver terminal, a cloud server and an artificial intelligence matching module, wherein the user terminal, the caregiver terminal, the cloud server and the artificial intelligence matching module are connected by a signal; The user terminal includes a user registration unit, an order generation unit, a payment unit, and an order query unit, used to collect user and patient information, generate caregiver orders, complete fee settlement, and query order status; The companion terminal includes a companion registration unit, a service setting unit, an order interaction unit, and a service feedback unit, which are used to collect companion personnel qualification information, set service scope, receive order pushes, and provide feedback service information. The cloud server includes an order management module, a qualification review module, and a data storage module, which are used to manage order status, verify the qualifications of caregivers, and store system data. The AI matching module is embedded in the cloud server and includes a demand analysis submodule, a capability profiling submodule, and a matching decision submodule. It is used to analyze user needs, build a capability model of caregivers, and calculate matching priorities to provide a basis for order push.
[0007] Furthermore, the requirement parsing submodule allows users to directly input requirement tags, or uses natural language processing technology to perform semantic analysis on user requirements, extract keywords, and map them into standard requirement tags; the capability profiling submodule constructs a multi-dimensional capability evaluation system that includes qualification level, service history, user evaluation, and hospital department matching degree.
[0008] Furthermore, the matching decision submodule uses rule matching or recommendation algorithms to calculate the matching degree between the user's demand vector and the caregiver's ability matrix, and combines other factors of the caregiver to correct the matching result, generating a TopN matching priority list.
[0009] Furthermore, the user registration unit supports the input of medical information for the user and others, and the order generation unit includes a hospital list selection module, a medical appointment time calibration module, and a special needs label module. The special needs label module presets standardized labels such as "wheelchair requirement", "language requirement", and "elderly patient" as well as a custom text input interface.
[0010] Furthermore, the caregiver registration unit requires registration via mobile phone number or WeChat authorization, and the qualification verification module requires uploading identity information, professional qualification certificate and health certificate. The certificate information can be extracted through OCR recognition technology and compared with a third-party authoritative database for verification. Only after the verification is passed can the caregiver obtain the right to accept orders.
[0011] Furthermore, the service settings unit supports adding multiple target hospitals, setting service time periods by time, and setting dispatch acceptance permissions.
[0012] Furthermore, the order interaction unit adopts a message push or timed retrieval mechanism, and the order grabbing operation can be set with a countdown; when the system dispatches an order, it sends an order dispatch notification to the caregiver who ranks first and has the order dispatch permission based on the matching priority list.
[0013] Furthermore, the payment unit integrates a third-party payment interface, which can process payment settlements for orders and allow caregivers to tip. The order query unit displays the order status, caregiver information, and service trajectory in real time. After the service is completed, it provides a user evaluation portal, and the evaluation data is synchronously updated to the caregiver's competency profile.
[0014] The beneficial effects achieved by adopting the above-described solution in this invention are as follows: 1. By using an AI-driven multi-dimensional matching mechanism, the system solves the problem of matching the uncertainty of the fulfillment cycle and content of care services, greatly improves the accuracy of matching, and fills the application gap of the existing order grabbing and dispatching system in the field of care services. 2. Establish a standardized system for verifying the qualifications and evaluating the abilities of caregivers, making caregiver information transparent, solving the pain points of difficulty in verifying qualifications and tracing service quality in the traditional model, and reducing the incidence of service disputes; 3. Adopting a two-way interactive mode of "order grabbing and order dispatching" not only ensures the service autonomy of caregivers, but also improves the efficiency of order dispatching through AI matching priority, and significantly shortens the average order acceptance time; 4. Supports order placement on behalf of patients and multi-dimensional order inquiry to meet the needs of patients' families and improve user experience. At the same time, it forms a service optimization loop through data accumulation and continuously improves matching accuracy. Attached Figure Description
[0015] Figure 1 This is a block diagram of the overall architecture of an artificial intelligence-based matching system for caregivers and patients. Detailed Implementation
[0016] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0017] The present invention discloses an artificial intelligence-based matching system for caregivers and patients, comprising a user terminal, a caregiver terminal, a cloud server, and an artificial intelligence matching module, all of which are connected via network communication.
[0018] User terminal: For user use, supporting Android, iOS, HarmonyOS, Web, and mini-program platforms, integrating a user registration unit, order generation unit, payment unit, and order query unit; the user registration unit is used to collect user identity information and frequently visited patient information; the order generation unit is used to obtain the medical information input by the user, including the hospital, department, and time of visit, the type of caregiving needs, and special service requirements, and generate a tagged caregiving order; the payment unit is used to receive user payment instructions and complete service fee settlement; the order query unit is used to display the order status in real time.
[0019] Companion Terminal: For use by companions and caregivers, supporting Android, iOS, HarmonyOS, Web, and mini-program platforms. It integrates a companion registration unit, a service settings unit, an order interaction unit, and a service feedback unit. The companion registration unit collects the companion's identity information, qualification certificates, and service history, and uploads them to the cloud server for record-keeping. The service settings unit allows companions to set their service scope, available service time periods, and order acceptance permissions. The order interaction unit displays companion orders that match the service settings, provides an order confirmation entry, and order notification reception functions. The service feedback unit records service process information for user evaluation and reference.
[0020] The cloud server serves as the core of the system's data processing and storage, including an order management module, a qualification review module, and a data storage module. The order management module receives caregiver orders generated by user terminals, marks the order status, and pushes them to eligible caregiver terminals. The qualification review module verifies the authenticity of qualification certificates uploaded by caregiver registration units, allowing them to receive orders only after verification. The data storage module stores user information, caregiver information, order data, and service evaluation data.
[0021] The AI matching module, embedded in a cloud server, includes a demand analysis submodule, a capability profiling submodule, and a matching decision submodule. The demand analysis submodule extracts key features from caregiver orders, including the hospital, department type, service duration requirements, and special demand tags, generating a user demand vector. The capability profiling submodule constructs a caregiver capability matrix based on the caregiver's qualification level, service history, historical user reviews, and real-time service status. The matching decision submodule calculates the matching degree between the user demand vector and the caregiver capability matrix using rule-based matching or recommendation algorithms, generating a matching priority list to provide a basis for order grabbing, display, and system order dispatch.
[0022] Workflow: Users register and fill in their medical information and caregiving needs through their user terminals, generating caregiving orders and submitting them to the cloud server. The order status is set to "Pending Order". The AI matching module analyzes the caregiving orders and simultaneously calls the capability profile data of caregivers that meet the conditions of address, hospital, and time period, calculates the matching degree, and generates an order push list. The cloud server sorts the caregiving orders by matching degree and pushes them to the caregiver terminals in the push list. Caregivers can view the order details through their caregiver terminals and can actively click the order grabbing entry to complete the order, or the system can send an order dispatch notification to the top-ranked caregiver who has the order dispatch permission based on the matching priority and the caregiver's order dispatch permission. After the caregiver confirms, the order is completed. After the order is successfully accepted, the status is updated to "Order Accepted", and the cloud server pushes the order acceptance notification and caregiver information to the user terminal. After the service is completed, the user completes the payment and evaluation through the user terminal, the order status is updated to "completed", and the evaluation data is synchronized to the caregiver's competency profile.
[0023] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.
Claims
1. A matching system for caregivers and patients based on artificial intelligence, characterized in that, It includes a user terminal, a caregiver terminal, a cloud server, and an AI matching module, which are connected by signals. The user terminal includes a user registration unit, an order generation unit, a payment unit, and an order query unit, used to collect user and patient information, generate caregiver orders, complete fee settlement, and query order status; The companion terminal includes a companion registration unit, a service setting unit, an order interaction unit, and a service feedback unit, which are used to collect companion personnel qualification information, set service scope, receive order pushes, and provide feedback service information. The cloud server includes an order management module, a qualification review module, and a data storage module, which are used to manage order status, verify the qualifications of caregivers, and store system data. The AI matching module is embedded in the cloud server and includes a demand analysis submodule, a capability profiling submodule, and a matching decision submodule. It is used to analyze user needs, build a capability model of caregivers, and calculate matching priorities to provide a basis for order push.
2. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The requirement parsing submodule uses natural language processing technology to perform semantic analysis on user requirements, extract keywords and map them to standard requirement tags or allow users to directly input requirement tags; the capability profiling submodule constructs a multi-dimensional capability evaluation system that includes qualification level, service history, user evaluation, and hospital department matching degree.
3. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The matching decision submodule uses rule matching or recommendation algorithms to calculate the matching degree between the user's demand vector and the caregiver's ability matrix.
4. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The user registration unit supports the entry of medical information for the user and others. The order generation unit includes a hospital list selection module, a consultation time calibration module, and a special needs label module. The special needs label module has preset standardized labels such as "wheelchair requirement", "language requirement" and "elderly patient" as well as a custom text input interface.
5. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The caregiver registration unit requires registration via mobile phone number or WeChat authorization. The qualification verification module requires uploading identity information, professional qualification certificate, and health certificate. The verification information can be extracted through OCR recognition technology and compared with a third-party authoritative database. Only after the verification is passed can the caregiver obtain the right to accept orders.
6. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The service settings unit supports adding multiple target hospitals, setting service time periods by time, and setting order acceptance permissions.
7. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The order interaction unit adopts a message push or timed retrieval mechanism, and the order grabbing operation can be set with a countdown. When the system dispatches an order, it sends an order dispatch notification to the caregiver who ranks first and has the order dispatch permission based on the matching priority list.
8. The artificial intelligence-based matching system for caregivers and patients according to claim 1, characterized in that, The payment unit integrates a third-party payment interface, which can process payment settlements for orders and allow caregivers to tip. The order query unit displays the order status, caregiver information, and service trajectory in real time. After the service is completed, it provides a user evaluation portal, and the evaluation data is synchronously updated to the caregiver's competency profile.