33 results about "Patient flow" patented technology

The invention discloses an AI-based medical and health care integrated data management method and system and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the data preprocessing and data standardization of collected multi-source medical and health care data, and obtaining a standardized medical data set; performing classification and semantic annotation on the data of the standardized medical data set by using a preset medical ontology, and constructing a structured medical knowledge graph; performing virtual mapping based on the structured medical knowledge graph by adopting a digital twinborn model to form a virtual medical twinborn body; based on the virtual medical twins, combining real-time monitoring data and historical patient flow data, through multi-dimensional feature extraction and pension mode recognition, dynamically optimizing and presetting a personalized medical scheme and a resource scheduling strategy, and outputting a medical care service optimization scheme; generating a target service list in combination with the analyzed doctor-patient dialogue text, and distributing the target service list to a preset pension service cooperation terminal; the method has the effect of improving the real-time performance and the accuracy of the old people medical care service strategy.

The invention provides a medical hospital guide robot scheduling method based on dynamic path planning. The method comprises the following steps: acquiring hospital guide information of a patient to be diagnosed; determining a task priority of the hospital guide information based on the hospital guide information; based on the task priority of the to-be-diagnosed patient, determining a target hospital guide robot, performing path planning processing through a preset reinforcement learning algorithm, and determining a walking path of the target hospital guide robot; and based on the walking route, controlling the target hospital guide robot to guide the to-be-diagnosed patient to the target consulting room. The hospital guide robot resource can be reasonably scheduled according to the task emergency degree, the surrounding environment information is sensed in real time through the reinforcement learning algorithm, the path is planned, the patient is guided to the destination, and the hospital guide efficiency is improved; the problems that according to an existing hospital guide robot, hospital guide robot resources cannot be reasonably dispatched according to the patient flow and the task emergency degree, surrounding environment information cannot be accurately sensed, and consequently path planning is inaccurate, and hospital guide efficiency is low are solved.

The invention relates to the technical field of medical resource management, in particular to a pediatric outpatient service resource intelligent scheduling and patient flow prediction management system which comprises a data acquisition module, a flow prediction module, a resource scheduling module, a scheduling optimization module and a feedback correction module. Historical patient flow data, doctor scheduling data, consulting room availability data and patient reservation data are collected in real time, a patient flow prediction result generated by the flow prediction module is combined, data support is provided for resource scheduling, the resource scheduling module generates a preliminary scheduling scheme according to the prediction result and actual data, and the preliminary scheduling scheme is used for resource scheduling. And a scheduling scheme is optimized through a simulated annealing algorithm, and the resource utilization rate is improved. And the feedback correction module monitors patient flow and resource use conditions in real time, and adjusts a scheduling scheme in time to cope with emergencies and expected changes. According to the invention, the scheduling scheme can be dynamically adjusted under different demand fluctuations, the high efficiency and flexibility of resource allocation are ensured, and the service quality of hospitals is improved.

The invention relates to the technical field of medical management informatization, in particular to a visual multi-dimensional patient flow adjustment system and method, and the system comprises a patient sensing module, an intelligent analysis gateway, an adjustment strategy generation module, a resource dynamic scheduling engine, and a visual positioning platform. Wherein the patient sensing module is used for collecting basic information, doctor seeing states, department resource use conditions and environment data of patients in all areas of a hospital; the intelligent analysis gateway is used for fusing and processing data and predicting the patient flow risk through the gating circulation unit; the adjustment strategy generation module is used for carrying out treatment priority fine classification on the patients and generating a personalized flow adjustment strategy; the resource dynamic scheduling engine is used for performing accurate scheduling through an intelligent allocation algorithm according to the adjustment strategy; the visual positioning platform is used for calibrating patient positions and rendering a hospital-wide patient distribution thermodynamic diagram and a resource occupancy rate in real time. Therefore, the problems of long waiting time, unreasonable resource allocation, single management strategy and the like in the prior art are solved.

Provided herein are computerized system and method for full patient flow management through an emergency department process, integrating multi-agents LLM. The system and method utilize a plurality of LLM-based agents configured to perform one or more of: extract relevant medical information and generate a summarized medical history; interactively questioning the subject regarding its medical history and regarding the main complaint(s); provide recommendations regarding various medical examinations; process the summarized medical history and the results of the recommended medical examination(s) and; provide further summary, recommendations or instructions, regarding diagnosis and a decision regarding discharge or admission of the subject.

The invention discloses an emergency operation visual management method and device based on digital twinning, and relates to the technical field of digital twinning. The method comprises the following steps: constructing a three-dimensional twinborn scene corresponding to a physical emergency treatment space, and establishing a virtual mapping model; collecting multi-source heterogeneous data in real time; identifying a patient flow thermodynamic diagram and a resource usage rate based on a data-driven model update; identifying a homogeneous index according to the thermodynamic diagram and predicting a patient flow; a limit scheduling scheme and a reception flow are formed by combining the resource utilization rate and prediction sequence simulation scheduling; and visualizing the result and synchronizing a manager to remind. The technical problem that existing emergency treatment management depends on static data and artificial experience and cannot perform real-time perception, prediction and global optimization on dynamically changing patient flow and resource bottlenecks is solved, real-time dynamic visual management of emergency treatment operation is realized through the digital twinning technology, a patient flow thermodynamic diagram and the emergency treatment resource utilization rate are accurately identified, and the emergency treatment efficiency is improved. And the accuracy and timeliness of emergency operation management are improved.

A system and method generate synthetic data simulating patient flow in a hospital for a simulation to provide hospital operations analytics. The method includes populating a hospital configuration file by specifying hospital parameters to provide data specific to the hospital and simulation criteria; populating arrival configuration files by specifying arrival parameters for arrival modules, where each arrival module includes corresponding constraints, and is configured to generate a base waveform to capture corresponding arrival patterns or a schedule; generating a patient trajectory for each arrival module based on the base waveform or the schedule, and the data specific to the hospital from the hospital configuration file; integrating the patient trajectories to provide an integrated patient trajectory including synthetic data specific to the patient flow in the hospital; and applying the integrated patient trajectory to an analytics algorithm to enable realistic situational simulations for enabling staff planning, resource allocation, and / or simulated remediation strategies.

The invention relates to a big data analysis method based on a hospital human resource digital intelligence simulation model, and belongs to the technical field of data analysis. The method comprises the following steps: acquiring doctor mastering skill data and doctor attendance data through a hospital human resource digital intelligent simulation model; obtaining doctor information preprocessing data through a data preprocessing model according to the doctor mastering skill data and the doctor attendance data; historical patient flow data and historical online reservation data are obtained, and patient flow prediction data are obtained through the patient flow prediction model according to the historical patient flow data and the historical online reservation data; according to the scheduling demand, the department demand and the doctor information preprocessing data, a scheduling constraint set is obtained through logic formula conversion; and obtaining a balanced scheduling result through a balanced scheduling model according to the scheduling constraint set, the patient flow prediction data and the doctor information preprocessing data. And big data analysis based on the hospital human resource digital intelligence simulation model is realized.

The invention provides a hospital outpatient service and emergency treatment resource allocation management method, and relates to the technical field of hospital resource allocation. The method comprises the steps that a first information set of an emergency department is collected in real time, when patient flow data reaches a first threshold value, resource allocation strategy optimization is triggered, and emergency resource requirements in a future preset time period are predicted; an initial population containing N initial allocation schemes is generated, each allocation scheme code is a binary chromosome, a chromosome coding region is divided into an emergency treatment resource section and a common resource section, and a genetic algorithm is adopted to perform iterative optimization on the initial population to obtain an optimized resource allocation strategy; according to the method, through emergency treatment resource segment gene lock protection in the genetic algorithm, consulting room and equipment gene variation is allowed, physicians are dynamically supplemented, reservation of emergency treatment resources is ensured, meanwhile, common outpatient service resources are flexibly adjusted according to needs, resource conflicts are avoided, the dynamic response efficiency of the emergency treatment resources is improved, and a priority guarantee mechanism is provided.

The utility model provides a blood glucose detection sampling device which comprises a blood purification tube and an artery end sampling point arranged on the blood purification tube in a communicated mode, a limiting piece is detachably installed on the top of the artery end sampling point, a rubber plug is embedded in the limiting piece, a blood storage piece is arranged on the rubber plug, and a blood outlet is formed in the blood storage piece. The blood suction pipe is used for sucking blood in the blood purification pipe. According to the blood purification device, blood of a patient flows in the blood purification tube to achieve blood circulation, then the liquid storage bag is squeezed, gas in the liquid storage bag is discharged through the capillary needle, the interior of the liquid storage bag is in a negative pressure state, then the capillary needle penetrates through the rubber plug, the blood in the blood purification tube flows into the liquid storage bag through the capillary needle, and the blood is purified. According to the blood sampling device, temporary storage is achieved, the purpose of blood sampling is achieved at the moment, the mode does not need to additionally conduct needle insertion on the arms of a patient, harm to the patient is reduced, the purpose of continuous multiple times of sampling can be achieved, multiple times of detection can be conducted on the patient more efficiently, and the data accuracy is improved.

Cataract surgery is in recent years more and more augmented and supported by the application of laser cuts in the eye tissue. Such laser systems are separate units from the phacoemulsification system units that are usually used for cataract extraction. The laser systems require the patient to be positioned under the laser unit and then being moved under the surgical microscope next to the phacoemulsification unit. The here described invention relates to systems combining several aspects of the laser system and the phacoemulsification system. In particular, this invention relates to combining at least some parts of the control system and the housing for both systems and thereby minimizing and optimizing setup time, operating room footprint, patient flow and cost. Furthermore the here disclosed invention relates to integrating the laser system under the surgical microscope and thereby significantly reducing the surgery setup and complexity.

The invention relates to the technical field of medical informatization and intelligent management, in particular to a medical oncology daytime chemotherapy center patient whole-process intelligent scheduling and safety management method which comprises the steps of admission sign-in and dynamic scheduling, nursing task intelligent decomposition and pushing, drug flow and patient flow double-closed-loop safety checking and infusion process intelligent monitoring and early warning. The admission sign-in and dynamic scheduling specifically comprises the steps that after the patient actually arrives at sign-in, the system dynamically adjusts and locks an optimal execution path according to the real-time resource occupation condition, generates a personal exclusive all-day electronic treatment navigation timeline for the patient, pushes the timeline to a patient mobile terminal and updates the timeline in real time. According to the technical scheme provided by the invention, full-process and multi-resource collaborative optimization and closed-loop safety management of daytime chemotherapy patients are realized, the running efficiency of a daytime chemotherapy center can be remarkably improved, the medical error risk is reduced, the medical experience of the patients is improved, and data support is provided for fine management and continuous improvement.

The invention relates to the technical field of big data analysis, and discloses a big data analysis-based outpatient service payment medical insurance data monitoring analysis management system, which comprises a data acquisition module for acquiring outpatient service medical insurance settlement data before and after hierarchical diagnosis and treatment of all medical insurance fixed-point medical institutions in a target area; and the data analysis module is used for acquiring sub-data change amplitudes of the patient flow direction data, the cost benefit data and the disease matching degree data before and after the implementation of the hierarchical diagnosis and treatment in the same target area according to the outpatient medical insurance settlement data before and after the implementation of the hierarchical diagnosis and treatment, and constructing a change amplitude data set. The method comprises the steps of obtaining outpatient medical insurance settlement data before and after hierarchical diagnosis and treatment of a medical insurance fixed-point medical institution in a target area, obtaining a change amplitude data set and a difference value data set according to the outpatient medical insurance settlement data, completing correction, and performing comprehensive evaluation according to the corrected data to obtain a hierarchical diagnosis and treatment effectiveness evaluation result.

The present invention provides a method, apparatus, device, and storage medium for predicting the number of hospital outpatient visits based on two-step regression. The method comprises: step S1: constructing a two-step regression-based prediction model for the number of hospital outpatient visits; and step S2: using the above-described prediction model to predict the number of hospital outpatient visits over a future period. The present invention utilizes a regression model with time series error to predict patient flow, capable of predicting patient flow over relatively long periods of time with reasonable accuracy. It performs well for time series data with strong regularity, facilitating management arrangements such as hospital shift scheduling.

Provided herein are computerized system and method for full patient flow management through an emergency department process, integrating multi-agents LLM. The system and method utilize a plurality of LLM-based agents configured to perform one or more of: extract relevant medical information and generate a summarized medical history; interactively questioning the subject regarding its medical history and regarding the main complaint(s); provide recommendations regarding various medical examinations; process the summarized medical history and the results of the recommended medical examination(s) and; provide further summary, recommendations or instructions, regarding diagnosis and a decision regarding discharge or admission of the subject.

A medical fluid treatment system includes a source of purified water; at least one concentrate for mixing with the water from the source to form a treatment fluid; a disposable set including a pumping portion, a concentrate line in fluid communication with the concentrate source and the pumping portion, and a patient line in fluid communication with the pumping portion, the patient line including a filter having a membrane configured to filter the treatment fluid, the filter configured such that (i) fresh treatment fluid flowing from the pumping portion towards a patient flows through the membrane and (ii) used treatment fluid flowing through the filter from the patient to the pumping portion bypasses the membrane; and a medical fluid delivery machine including a pump actuator operable with the pumping portion of the disposable set.

To provide a blood purification device that can reduce the installation space required for the device in a space where multiple patients are treated. [Solution] The blood purification device 1A comprises a housing 10, a first blood purifier 21, a second blood purifier 22, a first blood pump 31, and a second blood pump 32. The housing 10 has a first side wall 11 and a second side wall 12. The first blood purifier 21 is incorporated into a first blood circuit through which the blood of a first patient flows. The second blood purifier 22 is incorporated into a second blood circuit through which the blood of a second patient flows. The first blood pump 31 is connected to the first blood circuit. The second blood pump 32 is connected to the second blood circuit. The first blood purifier 21 and the first blood pump 31 are provided on the first side wall 11. The second blood purifier 22 and the second blood pump 32 are provided on the second side wall 12.

The invention discloses an outpatient service intelligent scheduling method and system based on patient flow prediction, and relates to the technical field of data processing, and the method comprises the steps: obtaining a first time interval and a second time interval, obtaining a first historical time sequence and a second historical time sequence, obtaining a first average patient flow, and obtaining a second average patient flow; acquiring a prediction time point, acquiring initial demand intensity corresponding to the prediction time point based on the first intensity model, the prediction time point, the first historical time sequence and the first average patient flow, and acquiring fluctuation demand intensity corresponding to the prediction time point based on the second intensity model, the prediction time point, the second historical time sequence and the second average patient flow, obtaining basic demand strength; obtaining a constraint factor based on the limitation model and the prediction time point, and obtaining target demand intensity according to the constraint factor and the basic demand intensity; and completing corresponding outpatient scheduling at the prediction time point according to the target demand intensity. The method has the advantages of being accurate in prediction, safe, stable and self-adaptive.

The present invention relates to a device for optimizing a patient flow for maximizing patient convenience and enabling efficient operation of a hospital. To this end, the present invention provides a device for optimizing a patient flow, comprising: a first module that confirms that a patient has visited a hospital when a trigger device installed in the hospital and a patient terminal interact; a second module that provides guidance to the patient terminal to a next destination in the hospital, including an examination room and a testing room, on the basis of a treatment schedule for the patient whose visit has been confirmed by the first module; and a third module that the changes the patient flow and transmits same to the second module when a preset treatment schedule or patient flow changes according to a doctor's orders in the hospital.

Devices for monitoring cancerous cells in blood of a patient that are preloaded with a marker and a magnetic agent and removing them are provided. The device comprises a tray onto which blood withdrawn from the patient flows before returned to the patient; a magnet placed at a distance from the tray so that the blood on the tray is within a magnetic field of the magnet and the cancerous cells that are preloaded with the magnetic agent are forced to move from the blood on the tray towards the magnet. A detector configured to detect the marker in the cancerous cells in the blood on the tray is provided as well and a filter that is placed between the tray and the magnet so as to capture the cancerous cells that are forced to move towards the magnet and remove them from the blood of the patient.

The utility model discloses a drainage bag, which belongs to the technical field of drainage bags and comprises a drainage bag for storing urine of a patient, a catheter and a filter device, the catheter is communicated at an inlet of the drainage bag through the filter device, and the head end of the catheter is connected with a position to be treated of the patient. The filtering device is located at the inlet of the drainage bag and has the function of filtering urine impurities in the catheter; when a patient wears the child-mother drainage bag for treatment, urine and fine tissues of the patient flow into the child-mother drainage bag through the catheter to be stored, the tissues can be blocked through the filtering device in the process of flowing into the child-mother drainage bag, and under the condition that a large amount of tissues are accumulated, the urine and the fine tissues can be filtered through the filtering device. Only the filtering device needs to be replaced, the treatment effect of a patient is not affected, the pain of the patient is avoided, meanwhile, the cost is low, operation is convenient, the workload of medical workers is greatly reduced, and therefore wide use is facilitated.

The present application provides a hospital outpatient and emergency resource allocation management method, which relates to the technical field of hospital resource allocation; the method comprises: real-time collection of a first information set of the emergency department, triggering resource allocation strategy optimization when patient flow data reaches a first threshold, and predicting emergency resource demand within a preset time period in the future; generating an initial population comprising N initial allocation schemes, each allocation scheme being encoded as a binary chromosome, the chromosome coding region being divided into an emergency resource segment and a general resource segment, and iteratively optimizing the initial population using a genetic algorithm to obtain an optimized resource allocation strategy; the method ensures that emergency resources are reserved while general outpatient resources are flexibly adjusted as needed to avoid resource conflicts through genetic lock protection of the emergency resource segment in the genetic algorithm, allowing genetic variation of clinics and equipment, and dynamically supplementing physicians. This method not only improves the dynamic response efficiency of emergency resources, but also has a priority guarantee mechanism.

Cataract surgery is in recent years more and more augmented and supported by the application of laser cuts in the eye tissue. Such laser systems are separate units from the phacoemulsification system units that are usually used for cataract extraction. The laser systems require the patient to be positioned under the laser unit and then being moved under the surgical microscope next to the phacoemulsification unit. The here described invention relates to systems combining several aspects of the laser system and the phacoemulsification system. In particular, this invention relates to combining at least some parts of the control system and the housing for both systems and thereby minimizing and optimizing setup time, operating room footprint, patient flow and cost. Furthermore the here disclosed invention relates to integrating the laser system under the surgical microscope and thereby significantly reducing the surgery setup and complexity.

A computerized medical services system that includes at least one processor for obtaining identification of the patient and obtaining registration for a visit via the at least one processor, wherein the at least one input device registers healthcare services that include laboratory services, radiology services, outpatient services, inpatient services, immunization services, emergency, and pharmacy services and then determine diagnosis and treatment throughout a patient visit, with artificial intelligence analyzes the diagnosis and treatment information and generates warnings, errors, corrective actions correlated with treatment protocols and documentation. In addition to patient flow, immunizations, laboratory information, work shifts, attendance, dynamic forms, security sign-in and sign-out, tasks, telehealth hubs, pharmaceutical vending machines, medical gas, payroll, immunizations, loans, time, attendance, human resources, contracts, recruitment, air conditioning, and the entire supply chain process are also electronically managed.

The utility model relates to the technical field of exudate absorption auxiliary devices, in particular to a nasal cavity postoperative exudate absorption device. According to the technical scheme, the non-woven fabric comprises non-woven fabric and further comprises a sealing part fixedly installed at the bottom of the non-woven fabric, a bonding layer is arranged on the sealing part, a plurality of telescopic belts are arranged on the bonding layer, and an absorption belt is installed on the sealing part and located above the bonding layer in a replaceable mode. Blood flowing into the upper lip is absorbed through the absorption belt, the postoperative bleeding amount of the nasal cavity can be observed according to the number of the products and the absorption degree of each piece in the application process, the exuded blood can be effectively prevented from flowing to the face, and the situation that a patient flows to a bed unit and pollutes personal clothes when sleeping or resting in bed is prevented. Through the arrangement of the telescopic band, the situation that a large gap is formed between the absorption band and the lip due to the fact that the bonding layer and the lip loosen can be effectively prevented, and then the absorption stability of the absorption band on blood oozing from the upper lip is guaranteed.

This invention discloses a visualized IoT integrated management platform, comprising a device and data acquisition layer, a network and protocol conversion layer, a data processing layer, and a visualization application layer. By leveraging IoT technology, this invention connects patient flow, doctor flow, material flow, and information flow, enabling real-time perception and transparent management of hospital operational status. Through a built-in intelligent analysis engine, it not only achieves post-event statistics but also provides in-process early warning and pre-event prediction, such as early detection of emerging epidemics and prediction of resource bottlenecks. It transforms complex multi-source data into intuitive graphics, charts, and 3D models, significantly reducing management complexity and improving decision-making efficiency.

The invention relates to the technical field of medical valves, in particular to an anti-backflow urine bag multi-stage sealing valve set structure. The anti-backflow urine bag comprises a sealing piece which is inserted into the top of a urine bag body in a sealed mode, the sealing piece comprises a limiting frame, and an anti-backflow structure is slidably connected into the limiting frame; the limiting frame is of a hollow structure, and the upper portion of the limiting frame is provided with a liquid inlet channel used for liquid inlet. After broken and small stones of a urethra and kidney stone patient flow into the liquid inlet channel along with urine, most of the stones penetrate through the liquid passing hole and flow into the urine bag body, but a small part of the stones still stay at the top of the plugging seat and are located on the outer side of the plugging seat, and after the patient completes urination, the small part of the stones are separated from the liquid passing hole. The scraping plate slides from the edge to the center from the top of the plugging seat, so that stones staying at the top of the plugging seat are scraped to the position near the outer wall of the pressure-bearing seat, the situation that the space between the top of the plugging seat and the side wall of the scraping plate cannot be completely sealed due to the stones is avoided, and the effect of preventing urine backflow is achieved.

The invention discloses an emergency equipment dynamic scheduling method based on demand prediction, and the method comprises the following steps: a), real-time data collection: continuously obtaining the information of a patient flow, a disease type structure, an illness condition grade, a traffic condition, weather, holidays and festivals and emergencies through an HIS, an RIS, a PACS, a pre-hospital 120 vehicle-mounted terminal, a wearable vital sign monitoring device and a public event API in a hospital, and carrying out the real-time data collection of the patient flow, the disease type structure, the illness condition grade, the traffic condition, the weather, the holidays and the emergencies; forming multi-source heterogeneous original data; b) a data preprocessing and feature engineering step: performing missing value interpolation, abnormal value elimination, time synchronization and normalization processing on the original data, and constructing spatio-temporal features, event features, periodic features, disease-device matching features and potential conflict features to form standard training samples; the invention relates to the technical field of intelligent medical treatment and first-aid resource optimization, in particular to an emergency treatment first-aid equipment dynamic scheduling method based on demand prediction.

The invention relates to a medical building BIM (Building Information Modeling) modeling method, which adopts a multi-resolution modeling technology, constructs BIM models with different precision levels according to the requirements of different medical functional areas, ensures that the models can accurately guide construction and equipment installation, and reduces the workload of on-site modification and reworking. A patient flow, a logistics flow and an information flow of a medical building are simulated and optimized through an AI algorithm and big data analysis, so that the patient flow is smoother, the waiting time of a patient is shortened, and the working process of medical staff is optimized; through a multi-specialty collaborative design tool of a cloud platform, real-time sharing and collaborative editing of multi-specialty data are realized, design contradictions among different specialties are found and solved, and the cost hyper-branched risk caused by a collaborative problem is reduced; through the intelligent operation and maintenance management system developed by combining the Internet of Things technology and the BIM model, real-time monitoring and intelligent management of equipment in a medical building are realized, the operation and maintenance efficiency is improved, the operation and maintenance cost is reduced, and meanwhile, the safety and stability of a medical environment are ensured.

Examples of the disclosure include a method of operating a patient-discharge-optimization system to improve medical outcomes, the method comprising: accessing, from memory and / or storage, historical patient flow information including a plurality of timestamped events for each of a plurality of patients; converting, by the discharge-optimization system, the historical patient flow information into standardized flow information having a standardized format defined by a plurality of standardized parameters; generating, by the discharge-optimization system, a plurality of models, each model indicating an effect of modifying at least one parameter of the standardized parameters for each of the patients; deriving, by the discharge-optimization system and based on the models, an optimal discharge histogram for one or more days; forecasting, based on the historical patient flow information, an anticipated future number of discharges for the day(s); deriving an optimal patient discharge timetable for the day(s); and providing the optimal patient discharge timetable to users.