347 results about "Patient stay" patented technology

The invention relates to a method and system of physician economic performance evaluation in which the relative medical difficulty associated with patients admitted by a particular physician is determined and, given that measurement, judgments made concerning the relative amount of inpatient resources that the physician required. Also, one application of the present invention relates to a method for gainsharing of physician services using a surplus allocation methodology for rewarding physicians in relation to their performance. An incentive pool is determined from previous patient claims and payments made to physicians in advance, such as in a base year. Best practice norms are established for a plurality of classified diagnosis groups. In one embodiment of the present invention, the classified diagnosis related groups are adjusted for severity of illness to compensate for actual clinical challenges faced by individual physicians. The best practice norms can be used in the surplus allocation method for determining physician performance. The incentive is established proportional to the relationship between a physician's individual performance and the best practice norm.

The invention provides a tray organizer apparatus for safely organizing routine expendable medical supplies for in hospital patients disclosing a plurality of variants in the form of a non power embodiment of a surface tray with shaped recesses for retaining medical supplies and power embodiments with 110 ac volt supply with a multiplicity of 110 volt outlet and a plurality of USB ports, Firewire port, and other devices such tiltable LED illuminated mirrors.The tray organizer is formed of injection molded plastic, folded sheet metal or other equal structures and incorporates a peripheral upstanding rim connected to a lower planar surface from which a number of recessed openings are formed with enclosed bottom surfaces to retain expendable supplies in a variety of shapes.

The invention discloses a novel epidemic prevention detection channel which comprises an inlet gate machine, a temperature detection door, a temperature detection gate machine, a human body disinfection box, a mask pick-up machine and a release gate machine. The inlet gate machine, the temperature detection door, the temperature detection gate machine, the human body disinfection box, the mask pick-up machine and the release gate machine are sequentially connected from front to back. The temperature detection gate machine comprises a first temperature detection gate machine and a manual passage gate machine, the temperature detection door is provided with a camera electrically connected with the temperature detection door, the camera is used for shooting the face of a patient, and the manual passage gate machine is provided with a display screen in communication connection with the camera. Through the arrangement of the temperature detection door, the workload of medical personnel formeasuring the body temperature of patients can be reduced, medical personnel only needs to recheck the patients with abnormal temperature at the manual passage gate machine, the quarantine efficiencyis effectively improved, the efficiency of the patients entering a hospital is improved, and the spread of viruses caused by the fact that a large number of the patients stay at the doorway of the hospital is avoided.

The present invention is a novel method of generating and representing the status of various physiological parameters that are monitored for patients during hospitalization. The system of present invention allows healthcare providers to easily view, at a glance, the status or trend of a patient or a plurality of patients as well as any changes in the parameter values.

An embodiment in accordance with the present invention provides a method of forecasting a demand for a particular hospital unit. The method can be executed by programming the steps into a computer readable medium. One step includes logging a total number of beds in the particular hospital unit and available nursing slots to determine a capacity for the particular hospital unit. The method also includes analyzing data for patients scheduled to stay in the particular hospital unit data to predict stochastic arrivals in order to estimate a total inflow. A length of stay of a patient in the particular hospital unit is predicted using a survival analysis based on physician orders to estimate a total outflow. Additionally, the method includes executing an algorithm designed to use the capacity, total inflow, and total outflow to determine the demand for the particular hospital unit.

A system links a standardized coded diagnosis associated with a medication order with information in a pharmacy information system to supplement medication utilization data. A pharmacy user interface system includes a user interface processor for providing data representing at least one display image supporting user entry of a coded diagnosis identifier for association with an order identifier identifying a medication order record indicating an order for a particular medication to be administered to a particular patient during an inpatient stay in a medical facility. A repository stores information associating multiple order identifiers and associated multiple coded diagnosis identifiers A utilization processor uses the stored repository information and processing data associating multiple order identifiers and associated multiple coded diagnosis identifiers to determine utilization information indicating usage characteristics of a particular medication for treatment of a condition indicated by a particular coded diagnosis.

The invention discloses a re-hospitalization risk predicting method based on a deep learning hybrid model. The method comprises the following steps of 1, collecting a data set which comprises a patient personal characteristic and an outer environment characteristic; 2, performing characteristic grouping and preprocessing, dividing the characteristics to static characteristics and time sequence characteristics; 3, mining the time sequence characteristics, performing statistics analysis on the time sequence characteristics, and establishing an LDA model and a bidirectional LSTM model; 4, performing characteristic splicing, fusing the static characteristics and the time sequence characteristics after characteristic engineering processing, and using the fused characteristic as input of a CNN model; and 5, establishing the CNN model for predicting the patient re-hospitalization risk. The method is based on a deep learning algorithm. Researching and analysis are performed on patient health medical big data and the outer environment, thereby establishing the re-hospitalization risk predicting model, facilitating reasonable medical resource arrangement by a medical organization, supplyingbetter medical service to the patient, and improving efficiency and accuracy in performing re-hospitalization risk identification of a participant by an insurance organization.

The invention provides a method for recording and transmitting an electronic medical record file. The method comprises the following steps of: firstly, arranging more than one recording units, wherein each of the recording units comprises a computer host, a keyboard or a handwriting board and a network interface; arranging at least one main server which is connected with the recording units through network transmission cables; and arranging a standardized recording module in the computer host of each recording unit, wherein the standardized recording module comprises a medical record model; the medical record format of the medical record model comprises a medical record sheet editor; and the medical record model comprises 100 models of branch hospitalized medical records in medicinal hospitals and covers branches set in large and extra-large hospitals. The method for recording and transmitting the electronic medical record file can be applicable to electronic recording, transmission and final management of the medical records of small, middle-sized and large hospitals.

The invention relates to an APP-based novel coronavirus pneumonia screening and evaluating system. The system comprises a personal registration module, a mobile terminal, a home FECWBY symptomatic screening module, an outpatient C-BCEU examination result evaluating module, a PCR definite diagnosis module and a hospitalization CROPB early warning module. Through the system, a common user can carryout novel coronavirus pneumonia home FECWBY symptomatic screening and outpatient C-BCEU examination result evaluation; a suspected case or a user with a high infection risk is prompted to the system;PCR definite diagnosis and examination and hospitalization CROPB early warning are completed through intelligent prompt; according to the scheme of the system, a common user can effectively and quickly screen the novel coronavirus pneumonia at home; an outpatient doctor-seeing user can perform examination result evaluation and a patient is intelligently guided to see a doctor, safety early warningis set, unnecessary outgoing exposure and contact history during an epidemic situation period is reduced, cross infection is avoided, protection on privacy of a patient is enhanced, and patients areeffectively and accurately guided to see doctors.

The invention discloses a hospital management early warning system based on the face recognition technology, and the system comprises a nurse station information processing platform which is used forcollecting patient information, carrying out the modeling according to a face image, and extracting a corresponding face feature; a portrait big data platform which comprises a database used for storing patient information and face information; and an inpatient area monitoring fortification platform which is used for collecting faces of patients entering and exiting the inpatient area and controlling the patients to enter and exit the inpatient area according to the database. The hospital management early warning method based on the face recognition technology comprises the steps: inputting aface image of a patient, and extracting the corresponding face features; integrating and storing the patient data; collecting faces of patients entering and exiting the inpatient area, and comparing the faces with the database to control the patients to enter and exit the inpatient area. The face recognition technology is applied to ward management, so inpatients can be effectively controlled to carry out early warning when going out and going out in advance, the problem that medical workers are insufficient in manpower can be effectively solved, the internal operation efficiency of hospitalscan be greatly improved, and the manpower and material resources are saved.

An automated healthcare integration system generally includes a plurality of residential stations, a clinician station, a data library, and may include emergency response stations. Each residential station includes a residential controller with analytical logic such as artificial intelligence, biometric devices interfaced to the residential controller, a user interface, and a communication interface for communication with the data library and the clinician station. The clinician station includes a clinician server, user interfaces, and a communication interface for communicating with the data library and the residential stations. Data derived from the biometric devices is communicated to and aggregated in the data library. Clinicians can retrieve such data for analysis to determine courses of treatment of the patients. Biometric and / or environmental sensor data indicating a life threatening situation of a patient can cause an alert to be issued to the emergency response station to assist such a patient.