21 results about "Referral" patented technology

The invention relates to the technical field of intelligent medical treatment, and discloses a three-level medical network intelligent referral method and equipment, and the method comprises the steps: collecting patient diagnosis and treatment information and medical institution resource information, and converting the information into structured data in a unified format; inputting the structured data into a preset referral decision model, carrying out correlation analysis on the illness condition severity feature of the patient and the medical institution reception capability feature, and generating a referral necessity evaluation result; when the referral necessity evaluation result indicates that referral is needed, performing comprehensive scoring on candidate receiving mechanisms in the structured data based on a multi-dimensional matching rule, screening out a target receiving mechanism according to a scoring result, and generating a referral suggestion scheme; and analyzing the referral suggestion scheme to construct a referral execution instruction, planning a transfer path in response to the referral execution instruction, and locking medical resources of the target receiving mechanism by using an intelligent contract mechanism to obtain a referral result. The referral efficiency of the medical network is improved.

A method of using data markers in a health insurance entity claims database to assist in tracking episodes of care (EOCs) to assist in generating referrals of medical specialists to a referring user, comprises providing an interface enabling a referring user to request a medical procedure for a patient and for making a referral of a medical specialist to assist with the medical procedure; identifying medical specialists; accessing a health insurance entity claims database storing historical claims associated with the same medical procedure; evaluating the historical claims to retrospectively estimate historical EOCs; using a respective data marker in the health insurance entity claims database to uniquely mark each retrospectively estimated historical EOC; using predictive analytics to generate an expected EOC for each medical specialist; generating an expected cost and a list of candidate medical specialists therefrom; receiving a selection; generating and using a particular data marker to mark an actual claim for the particular medical procedure and actual claims for the actual subsequent medical events to track the actual EOC in the health insurance entity claims database.

1. The name of the design product: emergency rescue breathing machine. 2. The use of the design product: the design product is used to provide continuous and stable mechanical ventilation support during patient transfer, ensuring the respiratory safety of patients in multiple scenarios such as pre-hospital emergency, in-hospital transfer, and long-distance referral. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

To provide an information processing system etc. for doctors etc. to more efficiently generate letters of referral to other medical institutions. [Solution] According to one aspect of the present invention, an information processing system is provided, which includes at least one processor, and the processor is configured to execute the following steps by reading a program: in an acquisition step, medical institution information regarding the medical institution that is the user and diagnostic information of a specific patient diagnosed at the medical institution are acquired, the diagnostic information is managed for each patient and includes at least first date information regarding the date the diagnosis was made; and in a first output step, written data for referring the specific patient to another medical institution different from the user is output based on the diagnostic information and at least one reference information, and the written data has medical institution information pre-filled in and uses at least one of the first date information.

A dental triage and clinical risk assessment system (100), the system (100) comprising: a first user device (102) configured to receive patient-related dental information for remote dental assessment; a first user interface (104) within the first user device (102) that is configured to guide the patient's interaction by presenting structured symptom questionnaires, image acquisition instructions, and status notifications; a communication network (110) that is connected to the first user device (102) and configured to securely transmit patient-related dental information and control signals; a processing unit (112) connected to the first user device (102) via the communication network (110) and configured to perform automated dental triage and clinical risk assessment through coordinated data analysis decision logic and routing operations, wherein the processing unit (112) comprises: a data acquisition module (114) configured to receive patient-related dental information from the first user device (102); a data preprocessing module (116) configured to validate, normalize and structure the received dental information for analytical processing; a triage intelligence module (124) configured to analyze the structured dental information to generate a quantified urgency score and risk classification level using combined analytical logic; a decision support module (130) configured to assign the urgency score and risk classification level to a recommended dental care pathway; a nursing navigation module (134) configured to generate routing instructions corresponding to emergency referrals, scheduled consultations, teleconsultations or automated guidance; a learning and analysis module (144) configured to update internal analytical parameters based on confirmed clinical results; a storage unit (154) connected to the processing unit (112) and configured to store patient data, analytical results, priority points, routing decisions and result feedback for continuous system operation; a second user device (158), connected to the processing unit (112) via the communication network (110) and configured to receive triage outputs and recommendations for care pathways; and a second user interface (160) in the second user device (158), configured to display risk indicators, urgency points, patient data summaries and override controls for interaction with the clinician.

To provide information useful for executing the reverse introduction of a patient while preventing the deterioration of the management conditions of a hospital.SOLUTION: An information processor acquires patient information on patients receiving medical care in a target hospital and hospital management information on the management of the target hospital (step S1). An information processor extracts candidates of patients to be reversely introduced to hospitals other than a target hospital within a prescribed period on the basis of patient information and hospital management information (step S5). The information processor updates patient information and hospital management information on the assumption that the extracted patient candidates are reversely introduced (step S7). The information processor predicts a management indicator showing the management situation of the target hospital after a prescribed period based on the updated patient information and hospital management information (step S8).SELECTED DRAWING: Figure 5

The present application relates to the field of medical informatization and emergency medical technology, and particularly relates to an emergency cross-hospital data intercommunication method and system. The method collects core data, performs timestamp marking and terminal identification binding, and generates an initial collection data set; processes the initial collection data set to form an EDXP data packet; in response to a cross-hospital referral event, desensitizes, compresses and encrypts the EDXP data packet, and transmits the EDXP data packet to a target receiving terminal after attaching a data integrity check code; after the target receiving terminal receives the data, performs data integrity verification, analyzes and extracts the data, and completes cross-hospital referral data intercommunication. The EDXP data packet of the present application has a three-layer structure design of'mandatory fields + optional fields + disease-specific extension fields', encapsulates only structured data necessary for emergency treatment classified by disease, eliminates redundant data, and solves the problems of existing transmission redundancy inefficiency and complex heterogeneous system docking.

Techniques for using machine learning models to create and present medical orders for patients are disclosed. These techniques facilitate the identification, selection, and fulfillment of an order, e.g., prescription or treatment, in response to updates to patient data for the patient, e.g., reporting of test results, receipt of messages or referrals, and addition of discussions. The system monitors, in real time, updates to the patient data. The patient data may be part of an EHR. When the system determines that content of an update satisfies a trigger for generating an order, the system applies a machine learning model to the patient data to determine an order corresponding to the patient data. The machine learning model generates the order for the patient and presents the order to medical professionals for review.

Methods and systems for AI-based robotic automation for persuasive referrals are provided. In a novel aspect, a robotic persuasive referral is generated based on a potential customer product-service P_PS matrix, which is generated based on predictive analysis using a DNN model and dynamically obtained feedback. In one embodiment, the DNN model is trained using customer personal profiles for associated product and service PS revenue for each customer dataset. In one embodiment, the predictive analysis uses a decision tree classifier. In one embodiment, a computer system detects one or more predefined trigger events including feedback information for the robotic persuasive referral and one or more predefined life event, updates the P_PS matrix and the robotic persuasive referral accordingly. In one embodiment, the feedback information is sentiment analysis of responses from potential customers. In another embodiment, proximate cause, frequency, and page view analysis are performed based on one or more detected life events.

The application relates to the technical field of medical management, in particular to an intelligent management system for medical remote referral and consultation based on the Internet. The system comprises a center and a collaborative end dynamic management module, a personalized consultation path generation module, a multi-center collaborative task scheduling module, a business whole-process data aggregation module and a management decision and performance optimization module. The system can receive and verify the registration information of different medical institutions, dynamically allocate the center end or the collaborative end role identity, and generate multi-dimensional role identity configuration data of the medical institutions; receive a remote consultation request, dynamically generate a personalized case information collection module and a standardized examination and inspection material submission list; after receiving the consultation application data packet, the system performs optimal scheduling and distribution and deep correlation analysis and pattern mining on the multi-center collaborative consultation task, generates a multi-dimensional management decision support report, and updates the operation according to the driving. The application can effectively improve the management efficiency and service quality of remote medical collaboration.

The invention discloses a machine learning-fused cross-department referral recommendation system. The system comprises an information acquisition module, an information classification module, a medical entity recognition module and a referral scheme generation module which are connected in sequence, the information acquisition module is used for acquiring treatment information of a to-be-referred patient; the information classification module is used for classifying and re-concluding the treatment information of the to-be-referred patient by using rule matching and a TextCNN model to obtain the classified treatment information of the to-be-referred patient; the medical entity identification module is used for extracting an initial medical entity in the treatment information of the classified patient to be referred, and identifying a final medical entity in the information by using MedBERT-wwm and BiLSTM-CRF models; and the referral scheme generation module is used for inputting the final medical entity into the referral recommendation model to obtain an optimal referral scheme. According to the invention, the reasonability and accuracy of medical resource configuration are improved, and the efficiency and quality of diagnosis and treatment are greatly improved.

The application discloses an admission assessment form automatic generation system based on an AI large model, relates to the technical field of admission assessment form generation, and has the technical scheme that after a user inputs information through a voice input mode, a voice file is generated; the voice file is transmitted to a voice recognition model for processing and is converted into initial text; the initial text is transmitted to a large language model, and a target title and an answer specification requirement corresponding to the target title are matched from a knowledge base in association with the content of the initial text; the large language model generates formatted answer content according to the target title, the answer specification requirement and the understanding of the initial text and fills the target form; and rule data of a target medical institution and instance data related to a specific patient are acquired, wherein the rule data comprises department diagnosis and treatment data, clinical path variation adaptation data and patient cross-department referral association data; and the effect is that the admission assessment form is more targeted and applicable.

The invention belongs to the technical field of medical health and intelligent medical treatment, and particularly relates to a chest stuffiness prevention and treatment and health integrated medical linkage intelligent pivot, which is characterized in that firstly, synchronous acquisition and intelligent differentiation of traditional and western medicine indexes are realized through an upgraded portable terminal, then high-risk group layering and risk trend pre-judgment are completed through an AI model, and then a personalized prevention scheme is generated; on the basis, the upgraded portable terminal is used for synchronously collecting traditional Chinese and western medicine indexes and intelligent syndrome differentiation, and the AI model is combined for layering risks, pre-judging trends and triggering early warning and referral treatment, so that the screening accuracy is improved, the difficulty of traditional Chinese medicine syndrome differentiation is overcome, and screening leakage of high-risk groups is reduced.

The invention relates to the technical field of medical informatization and emergency medicine, in particular to an emergency cross-hospital data intercommunication method and system. The method comprises the following steps: acquiring core data, marking a timestamp and binding a terminal identifier, and generating an initial acquisition data set; processing the initial acquisition data set to form an EDXP data packet; in response to a cross-hospital referral event, desensitizing, compressing and encrypting the EDXP data packet, carrying a data integrity check code, and transmitting the EDXP data packet to a target receiving terminal; after the target receiving terminal receives the data, data integrity verification is completed, the data is analyzed and extracted, and cross-hospital referral data intercommunication is completed. The EDXP data packet is of a three-layer structure design of'necessary fields + selectable fields + disease type exclusive extension fields', only structured data which is classified according to disease types and necessary for emergency treatment is packaged, redundant data is kicked out, and the problems that existing transmission redundancy is low in efficiency and heterogeneous system butt joint is tedious are solved.

An automatic fax document processing method is disclosed which receives one or more fax documents on an online healthcare platform from a plurality of sources, including, but not limited to, insurance companies, and one more medical service providers. The received fax documents are classified using integrated programmatic and specially guided and constrained artificial intelligence based on predefined categories, including authorization, denial, referral, payment, and miscellaneous. The relevant information from the classified fax documents is extracted using machine learning techniques and based on the extracted information an action is triggered. A final document is generated that is approved and saved by the expert user.

The invention discloses a block chain unified identity authentication and cross-domain collaborative service system under smart city medical ecology, and belongs to the fields of block chain technology, privacy computing technology and medical informatization technology. According to the system, a Hyperledger Fabric alliance chain architecture is adopted, and a unified identity identification and management module, a block chain identity authentication and authorization module, a block chain data storage and security sharing module, a cross-domain collaborative service module driven by an intelligent contract and a full-process privacy protection and security audit module are constructed. Decentralized identity (DID) unified management of patients, medical staff and medical institutions is realized based on a national secret SM2 / SM3 / SM4 algorithm and a Paillier homomorphic encryption algorithm, transverse / longitudinal federated learning and a zk-SNARKs zero-knowledge proof technology are fused, and automatic collaboration of available and invisible cross-domain sharing of medical data and referral and consultation services and the like is achieved. The problems of fragmentation of identity authentication, high data sharing security risk and low collaborative service efficiency in the existing medical field are solved, and technical support is provided for medical ecological construction of a smart city.

A system is provided.SOLUTION: A system comprising: means for inputting basic information and a medical record of a patient; means for transmitting the basic information and the medical record of the patient to a server; means for analyzing received information and generating a referral letter; means for adapting the generated referral letter to a unified format and performing an error check; means for confirming and correcting the referral letter at a terminal; and means for electronically transmitting and storing a final referral letter to a medical institution.SELECTED DRAWING: Figure 1

This invention discloses a dynamic referral routing decision-making method based on barcode scanning and real-time resource awareness, specifically relating to the field of medical referral information processing, to address the problem that referral routes are susceptible to fluctuations in acceptance status. The method generates a referral event object by responding to the barcode scanning result of the patient's referral identifier, and forms a referral demand constraint set through trust and consistency verification. Then, based on the referral demand constraint set, cross-institutional resource status subscription is triggered to verify the acceptance validity of the real-time status stream returned by candidate receiving ends, obtaining a set of acceptable states with associated acceptance confidence values. A dynamic referral routing graph is constructed based on the referral demand constraint set and the set of acceptable states, feasible routes are screened, and a route priority sequence is generated. Before and during referral execution, the acceptance status of the candidate receiving ends corresponding to the target route is verified, and a referral execution instruction or an alternative referral execution instruction is generated based on the verification results.

The system according to this embodiment aims to alleviate the financial and lifestyle anxieties of the elderly. [Solution] The system according to the embodiment comprises a pension management unit, a long-term care cost planning unit, a part-time job referral unit, a housing referral unit, and a utility cost review unit. The pension management unit collects pension information. The long-term care cost planning unit predicts future long-term care costs based on the information collected by the pension management unit. The part-time job referral unit refers to part-time jobs based on the information predicted by the long-term care cost planning unit. The housing referral unit proposes housing based on the information referred by the part-time job referral unit. The utility cost review unit reviews utility costs based on the information proposed by the housing referral unit.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent triage system and method based on artificial intelligence questions and answers, and the system comprises an information collection module, a triage question module, a multi-department triage module and a triage response module which are in communication connection in sequence. The method corresponds to the system. According to the application, the patient information is accurately acquired through the information acquisition module, and the symptom information is refined through interdisciplinary dynamic questions and answers of the triage question module to generate the optimized disease information, so that the accuracy of association between the symptom and the department is improved; the multi-department triage module quantifies the distribution probability and support degree of each department to realize advanced pre-judgment of interdisciplinary collaboration; the triage response module is combined with real-time response of departments to dynamically determine main diagnosis and support departments, referral caused by misjudgment of a single department is reduced, triage efficiency is improved, the problems that interdisciplinary disease triage is difficult and cooperation is lagged are solved, medical resource configuration is optimized, and patient treatment experience and medical service quality are improved.

[Problem] To construct a network for sharing information between medical institutions and a patient or patient's family, ascertain, within this network, the present state of an illness of the patient, the degree of nursing care therefor, and a history of transfer between facilities, and to give advice related to facility selection so that appropriate medical care and nursing care can be received as necessary. Additionally, to facilitate appropriate selection of a future referral destination of a discharged patient by evaluating actual conditions of medical care and nursing care received at facilities from the viewpoint of the patient or patient's family. Furthermore, to refer an appropriate facility in consideration of the medical condition and state of nursing care to a discharged patient, as well as when a request for a referral to an in-patient facility has been received from a patient or patient's family. [Solution] Provided are: a facility registration means for registering facility names of medical institutions and care facilities; a registration means for discharged patients; and a transfer history management means for managing the history of transfer between the facilities after discharge of the patient.