77 results about "Inpatient stay" patented technology

Disclosed embodiments include a telemedicine communication system designed to make possible “virtual” patient visits by approved visitors such as the spouse, family, and friends of the hospitalized patient having the appropriate digital certificate and visitation/communication permissions. According to one embodiment, the system enables relatives to visit hospitalized patients using audiovisual communication modalities selected according to the severity and health status of the patient. Additionally, the system provides functionality to enable approved relatives to follow the health status of the patient according to their permissions.

The invention discloses a method and device for establishing a model for early risk assessment of tachycardia events. According to the method, through easily-obtained continuous monitoring vital signsand electronic health record information, real-time assessment and early warning of the tachycardia event risk of an inpatient are realized by utilizing advanced artificial intelligence deep learningand unsupervised learning methods; therefore, doctors are assisted in treating and intervening patients as soon as possible, and the workload of medical workers is reduced. The device mainly comprises the following execution steps: 1) a data set construction module; 2) a data processing module; and 3) a model construction and evaluation module. Through verification of different scene data sets, the method has high prediction performance, can be used to predict the occurrence of tachycardia events 0-6 hoursearlier only based on clinically easily obtained information, and is suitable for different scenes and medical resource configuration mechanisms.

The invention belongs to the technical field of medical insurance supervisory, and particularly relates to a medical insurance in-hospital supervisory system. The medical insurance in-hospital supervisory system is composed of a supervisory center platform, a hospital terminal application platform and in-hospital patient individual terminals. The supervisory center platform is a data and service center of the whole system, the hospital terminal application platform is arranged at a medical insurance appointed hospital, and the in-hospital patient individual terminals are wearable devices and are worn by in-hospital patients, so that the formed medical insurance in-hospital supervisory system is connected through the internet, and data and information are transmitted in real time. The medical insurance in-hospital supervisory system can perform real-time supervision on appointed hospital and patient in-hospital illegal behaviors, the problems that some appointed hospitals receive and cure insured patients illegal, the in-hospital patient number or frequency is increased virtually, and medical insurance pooling funds are extracted are solved, and the medical insurance pooling funds are prevented from being lost.

The invention provides a diabetes blood glucose prediction system and method based on CNN and model fusion. The system comprises a blood glucose management module, an inpatient management module, an intelligent user side and a terminal monitoring module. The blood glucose management module is connected with the intelligent user side through the network server; the blood glucose management module comprises a data input unit, a data processing unit, a data output unit, a reminding unit and a data display unit; the data input unit is connected with the hospitalized patient management module and the intelligent user side; the data output unit is connected with the intelligent user side, the reminding unit and the data display unit; the data input unit, the data processing unit and the data output unit are electrically connected; the intelligent user side comprises a warning error correction module, an information input module and a service module; and the terminal monitoring module is connected with the intelligent user side through the wireless transmission module. Multi-directional monitoring is achieved, harm of hyperglycemia or hypoglycemia to a patient is reduced, and accurate nursing is achieved.

A multifunctional intelligent medical care and patient interaction system comprises a user terminal, a background system, a positioning device and a cloud server which are interconnected through a communication network; the user terminal comprises intelligent portable equipment bound with a user and/or a monitoring instrument matched with a patient's sickbed; the intelligent portable equipment is a wearing equipment unit bound with a user, and the background system analyzes and manages information data from the user terminal, opens corresponding user permissions for different user terminals, and processes navigation and interaction requirements of the user; and the positioning equipment is interconnected with the background system and tracks the movement and positioning information of the corresponding wearing user. The system not only can monitor various physiological parameters of critical patients in real time to prevent accidents, but also can realize position linkage interaction between common hospitalized patients and medical care, and has positive practical significance.

The invention relates to an intelligent information capturing and evaluating method and system for trauma severity of a traumatic inpatient. The method comprises the following steps of: extracting scoring related information for scoring trauma severity from medical record information; comparing the extracted scoring related information with a trauma severity scoring standard to form trauma severity scores; through medical record analysis, obtaining text content thereof, and analyzing the trauma severity scoring standard to obtain a trauma part name and a trauma condition name; performing searching and positioning through trauma part keywords and trauma condition name keywords to obtain a statement for describing a trauma as a trauma instance of a medical record, performing calculating to obtain k trauma description samples most similar to the trauma instance by utilizing a word vector and a KNN algorithm, and taking a trauma severity score corresponding to most of the trauma description samples as the trauma severity score of the trauma description instance, thereby achieving automatic scoring. The system includes a processor for score calculation and a program memory and a data memory.

A nurse call system that enables a call for a nurse from anywhere in a hospital ward while a patient carries a mobile phone is provided. The nurse call system includes a plurality of patient mobile phones 10 are carried by hospitalized patients and connected to a controller 8 via a base station 12 as with nurse mobile phones 9, and each patient mobile phone 10 has a hospital room ID and a nurse call slave device ID registered therein for recognizing a bed location of the patient carrying the patient mobile phone 10, thus enabling a nurse call operation for transmitting a call signal with the hospital room ID and the slave device ID added thereto, to the nurse call master device 7 and at least one of the nurse mobile phones 9, through a predetermined operation.

The invention provides a statistical method and device for infection cases of an I-type incision operation part and a storage medium, and aims to solve the problem that in the prior art, the infectioncases of the I-type incision operation site of an inpatient is hard to count in the statistical time period. According to the method, the infection cases of the I-type incision operation part in thestatistical time is screened out by utilizing information including the hospitalization process information A, infection information H, surgical information G, selected surgical infection site, statistical time, permission department information, selected surgical department, selected surgical name, selected surgical classification, selected surgeon, selected anesthesia mode, selected surgical duration, selected ASA score, selected healing level, selected surgical part, selected NNIS score, selected period selection emergency treatment, selected operating room and selected surgical frequency.Thus, the infection cases of the I-type incision operation part of the patient subjected to the operation in the statistical time period can be conveniently and accurately counted.

The invention provides a statistical method and device for the number of newly infected inpatients and a storage medium, and aims to solve the problem that in the prior art, statistics of the number of the newly infected inpatients is troublesome in a statistical time period. The invention provides a statistical method for the number of newly infected inpatients. The statistical method comprises the following steps: obtaining statistical time, selection of a corresponding department, authority department information, hospitalizing process information, transfer records, infection information and operation information; a step of acquiring the confirmed infection information H (a) _ Y, a step of acquiring infection information H (g) _ Y of non-surgical site infection, a step of acquiring infection information H (g) _ Y of surgical site infection, and a step of merging the infection information H (g) _ Y and the infection information H (b1) _ Y to obtain infection diagnosis information H (h); and counting the number of patients whose output results are not empty. According to the invention, the number of newly infected inpatients can be accurately counted within the statistical period,and the data of the number of newly infected inpatients can be conveniently obtained.

The invention discloses a re-admission risk and hospitalization time risk assessment model based on data driving. In the first stage, the re-admission prediction model is used for carrying out classification prediction on whether a case is avoidable admission or inevitable re-admission; and in the second stage, for patients capable of avoiding admission, the model takes intervention measures to prevent the patients from entering the hospital again, so that the hospital cost can be effectively reduced. For inevitable hospitalized patients, a hospitalization time prediction model is provided topredict the hospitalization time of the inevitable hospitalization patients so as to improve the scheduling and management of medical resources; the risk factors of re-admission and LOS of the patientare determined, the diagnosis efficiency of doctors is improved, and the satisfaction degree of the patient is improved; a clinical database of a patient is perfected, so that the medical service level and efficiency of a hospital are improved, more accurate re-admission prediction is provided, and meanwhile, the method has important significance for guiding practice.

This invention is for a catheter apparatus that greatly reduces microbial infections resulting from catheterization of dialysis, semi-mobile, or hospitalized patients. The apparatus applies light in the ultraviolet and near ultraviolet band to multiple catheter lumens for both detection and inactivation of biofilm microorganisms. It uses real-time automated techniques for the selection of wavelength, power level and exposure time regimes that are used for irradiating the biofilm in vivo. Artificial intelligence is incorporated to adjust the UV irradiation regimes to maximize the microorganism inactivation efficacy while minimizing the destruction of keratinocytes. The biofilm inactivation efficacy of this infection resistant catheter apparatus is at least 99%. The apparatus allows for minimal deviation from conventional catheter insertion procedures and can remain in vivo for long periods of time without the risk of microorganism contamination.

The invention relates to application of a two-dimensional code lock in the medical treatment aspect. An application procedure includes the steps that a patient or an old man wears an intelligent bracelet on one hand, the intelligent bracelet can monitor the health condition of a wearer and send the health condition to a medical data center, when the patient or the old man goes to a hospital or a nursing home to see a doctor, online inquiring can be conducted through the intelligent bracelet, offline interrogation is then conducted, online examination and payment are carried out, examination is carried out, a report generated after examination will be sent to a diagnostician and the intelligent bracelet of the patient or the old man through the medical data center, the patient or the old man can obtain a two-dimension code key through the intelligent bracelet if the patient or the old man needs to be hospitalized, and the corresponding two-dimensional code lock is opened accordingly; meanwhile, corresponding expenses for medicine can be paid on line to the medical data center through the intelligent bracelet, and the medicine can be quickly fetched under the arrangement of the hospital. The two-dimensional code lock has the advantages that use convenience is achieved, management efficiency is high, and ward dwelling diagnosis and arrangement efficiency is high.

The invention discloses a refrigeration storage and disinfection refrigerator with inpatient identity recognition function. The refrigeration storage and disinfection refrigerator comprises a box bodyand a storage cabinet, a disinfection device is arranged in one side of the box body; the cleanness of stored objects taken by inpatients is ensured; cross infection is avoided; a box door is arranged at the outer end of each grid of a grid bracket; one end of each box door is connected with one end of the corresponding grid through a hinge; an inner wall is arranged at the inner end of each gridof the grid bracket; each grid, a corresponding box door and a corresponding inner wall are adopted to form an independent storage box; each patient has a storage box belonging to the patient, so that the stored articles of each patient is protected from being mixed with stored articles of other people; an intelligent cabinet lock is arranged at the outer end of the grid bracket; after hospitalization, if a patient has an article needing to be refrigerated, the patient can input information such as face information, hospitalization number and fingerprint of the patient, identity recognition can be conducted when the patient takes and places the stored articles every time, medical accidents caused by taking wrong drugs are avoided, each patient can only take out the stored article of the patient, and meanwhile the workload of medical staff is reduced.

The invention discloses a hospital expense prediction method and device based on a knowledge graph, and computer equipment, relates to the technical field of artificial intelligence, and can solve the technical problems of large prediction workload and low accuracy of an existing hospital expense prediction mode. The method comprises the following steps: acquiring a medical knowledge graph, and carrying out representation learning on the medical knowledge graph by utilizing a graph embedding algorithm to obtain a node representation vector of each knowledge graph node; generating a first feature vector of the sample hospital patient about historical medical data according to the node representation vector, and training a hospital expense prediction model by using the first feature vector and historical expense data in the historical medical data; and obtaining target diagnosis data of the target patient in the first time period, generating a second feature vector of the target diagnosis data according to the node representation vector, inputting the second feature vector into the trained hospital expense prediction model, and obtaining a hospital expense prediction result of the target patient in the second time period.

The invention provides a method, system and device for counting the number of hospitalized people in a department and a storage medium, and aims to solve the problem that in the prior art, counting ofthe number of hospitalized people in the department is troublesome within the counting time. The method for counting the number of hospitalized people in a department comprises the following steps: acquiring statistical time, selection information of the corresponding department, authority department information and transfer records of patients, and filtering out the transfer records of which thein-department time is not within the statistical time range; filtering transfer records of non-authority departments; filtering the transfer records which do not reach the corresponding department; judging whether the transfer record of the patient in the corresponding department is empty or not; and counting the number of patients whose output results are not empty. According to the invention, by obtaining the statistical time, the selection information of the corresponding department, the authority department information and the transfer record of patients, whether each hospitalized patientchecks in the selected department within the statistical time is judged, and statistics is carried out, so that the number of hospitalized patients in the department within the statistical time can be accurately counted.

The invention provides a MapReduce and big data-based statistical method and device for the number of operation cases applying antibacterial drugs; the method comprises the steps: carrying out the calculation of the number of operation cases through the parallel calculation capability of a machine under a distributed system based on a MapReduce framework; dividing millions and tens of millions of hospitalized persons, which exceed the memory and storage limitation of a server, of example times of hospital infection with multi-drug-resistant bacteria into tens of millions and hundreds of millions of small tasks, executing the small tasks on a plurality of machines at the same time, and then summarizing intermediate output results of the small tasks to generate a final result. According to the method, massive parallel calculation can be carried out on big data including million-level, ten-million-level and hundred million-level hospitalized persons according to various calibers such as provincial and municipal areas, hospital levels, hospital beds, integration and specialities, and fair and civil operation. The statistical operation case times of the application of the antibacterial drugs are high in practicability, the operation case times can be accurately counted according to user needs, and effective guidance can be provided for treatment and management of the antibacterial drugs of hospitalized patients.

The invention provides a MapReduce and big data-based operation prevention medicine case number management method and a MapReduce and big data-based operation prevention medicine case number management system. The method comprises the steps: based on a MapReduce framework, employing the parallel computing capability of a machine under a distributed system, dividing millions and tens of millions ofinpatients who are beyond the memory and storage limit of a server and are used for calculating the case frequency of infection of multi-drug-resistant bacteria in a hospital into tens of millions and billions of small tasks, simultaneously executing the small tasks on a plurality of machines, and summarizing intermediate output results of the small tasks to generate a final result. Mass parallelcomputing is performed on big data including millions, tens of millions and hundred millions of hospitalities which cannot be avoided during national-level and provincial-level network monitoring according to various calibers such as provincial and municipal areas, hospital levels, hospital beds, comprehensive and specialized departments, justice and camp; effective guidance can be provided for treatment and management of antibacterial drugs of inpatients. Meanwhile, through automatic statistics of the operation case number, the problem that manual operation case number statistics processingis complex is avoided.

The invention discloses a nutrition treatment method for clinicians. The method is realized by the clinicians through a nutrition treatment platform. A nutrition prescription generation software system is arranged in the nutrition treatment platform; the nutrition prescription generation software system realizes that the clinicians provide personalized nutrition prescriptions for patients throughhuman-computer interaction; and the nutrition treatment generation platform calculates and provides the nutrition prescriptions according to a corresponding method after acquiring required patient nutrition treatment information in real time through a hospital information management system. According to the method, hospitalized patients can obtain more reasonable nutrition treatment.

The invention discloses a curative effect and quantification system for treating cervical spondylotic radiculopathy through a three-stage syndrome differentiation traction method, relates to a curative effect and quantification system for cervical spondylotic radiculopathy, and aims to solve the problem of poor curative effect on cervical spondylotic radiculopathy in the prior art. The system comprises a data acquisition module, a data processing module and a result analysis module, wherein the data acquisition module is used for acquiring patient data and determining a patient which simultaneously meets a diagnosis standard, an incorporation standard, an exclusion standard and an elimination and falling-off standard as a CSR patient, the data processing module is used for grouping the CSRpatients acquired by the data acquisition module, selecting instruments, equipment and medicines, making a treatment scheme, setting observation items and evaluation indexes, setting curative effectstandards of the CSR patients and setting statistical analysis standards, and the result analysis module is used for analyzing the case data of the CSR hospitalized patients grouped by the data processing module. The system is applied to the field of curative effect and quantification of cervical spondylotic radiculopathy.