CN111667896A - Transnasal high-flow humidification oxygen therapy remote management platform based on expert treatment mode - Google Patents
Transnasal high-flow humidification oxygen therapy remote management platform based on expert treatment mode Download PDFInfo
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Abstract
The invention discloses a transnasal high-flow humidified oxygen therapy remote management platform based on an expert treatment mode, which comprises a data acquisition module, a data storage and processing module, a monitoring module, an expert auxiliary treatment system, a cloud server and a remote platform management system, wherein the data acquisition module is used for acquiring a plurality of data; the data collector is used for collecting the symptom data of the patient, the treatment parameter data and the data indexes of the epidemiological data of the related diseases; the data storage and processing module is used for storing the acquired data and carrying out normalization processing to form an HFNC expert database; the monitoring module is used for remotely acquiring data of the terminal; the expert assistant treatment system is used for formulating an individual expert treatment scheme and transmitting the scheme to the terminal for real-time treatment; the cloud server is used for storing the treated patient data to the cloud end; the remote platform management system establishes a monitoring and management mode for long-period HFNC treatment. The invention can remotely manage and provide clinical data support, and establish a monitoring and management mode of long-period HFNC treatment.
Description
Technical Field
The invention belongs to the technical field of medical equipment, and particularly relates to a transnasal high-flow humidification oxygen therapy remote management platform based on an expert treatment mode.
Background
Respiratory failure is a clinical syndrome of a series of physiological and metabolic disorders caused by severe impairment of the function of pulmonary ventilation and/or ventilation due to various causes, so that effective gas exchange cannot be carried out, resulting in hypoxia with (or without) carbon dioxide retention. The patient can cause dyspnea and tachypnea, even psychoneurosis and the like, and the patient can also have gastrointestinal hemorrhage when suffering from pulmonary encephalopathy, so that great pain is brought to the patient, and the life is directly harmed when the patient is serious.
The nasal High-flow nasal oxygen therapy (HFNC) is a novel oxygen therapy method of directly delivering air-oxygen mixed High-flow gas with a certain oxygen concentration to a patient through a nasal obstruction catheter without sealing, and as a form of noninvasive respiratory support, the nasal High-flow oxygen therapy (HFNC) can rapidly improve oxygenation, is a main medical treatment method for solving respiratory failure at home and abroad at present, and has been used for various clinical treatments. However, at present, research and development of HFNC equipment at home and abroad are in a starting stage, and obvious defects exist in the technology, which are mainly expressed as follows: 1) the intelligent technology is lacked, the individual difference of patients cannot be well adapted, the curative effect is influenced, and the application and the popularization in the basic level and family standard are not facilitated; 2) the degree of digitization is not enough, equipment data and patient vital sign data cannot be collected remotely, and large-scale and long-period oxygen therapy management cannot be realized by utilizing the Internet of things.
Therefore, how to provide a remote management platform for nasal high-flow humidified oxygen therapy based on an expert treatment mode is a problem to be solved urgently by those skilled in the art.
Disclosure of Invention
In view of the above, the invention provides a transnasal high-flow humidification oxygen therapy remote management platform based on an expert therapy mode, which can stably and reliably transmit data to a cloud, establish an electronic health file of a patient, provide clinical data support for remote management, establish a monitoring and management mode of long-period HFNC therapy, and provide scientific management and personalized guidance for the patient.
In order to achieve the purpose, the invention adopts the following technical scheme:
a transnasal high flow humidified oxygen therapy remote management platform based on expert treatment mode, comprising: a data acquisition module, a data storage and processing module, a monitoring module, an expert auxiliary treatment system, a cloud server and a remote platform management system, wherein,
the data acquisition unit acquires data indexes of representative symptom data, treatment parameter data and related disease epidemiological data of the respiratory failure patient;
the data storage and processing module is used for storing the data acquired by the data acquisition device, performing statistical analysis on the stored data, and performing normalization processing to form an HFNC (high frequency network control) expert database;
the monitoring module is used for remotely acquiring data of the terminal;
the expert-assisted treatment system formulates an individualized expert treatment scheme based on the HFNC expert database and the data of the terminal, and transmits the scheme to the terminal for real-time treatment;
the cloud server is used for storing the treated patient data to a cloud end;
the remote platform management system analyzes and monitors the patient data stored in the cloud by using a deep learning technology, and establishes a monitoring and management mode of long-period HFNC treatment.
Preferably, the terminal comprises a vital sign detector and a high-flow humidified oxygen therapy apparatus.
Preferably, the vital sign detector acquires patient vital sign data including pulse oxygen saturation, heart rate, and respiratory rate.
Preferably, the data of the flow humidification oxygen therapy apparatus comprises flow, oxygen concentration, temperature and humidity, pressure, alarm, fault, working time and environment data.
Preferably, the remote platform management system comprises a core processor and a human-computer interaction interface, and the human-computer interaction interface is electrically connected with the core processor.
Preferably, the method for analyzing the cloud-based patient treatment data by using the deep learning technology comprises the following steps:
1) collecting vital sign data of a patient;
2) establishing a dynamic change model of each parameter based on the acquired data; establishing an evolution process of the disease condition by utilizing a deep learning algorithm and the disease condition reflected under each parameter;
3) establishing an illness state evolution model and a medical effect evaluation model through long-time acquisition, processing and analysis, comparing the illness state evolution model established according to the vital sign data of the patient with an HFNC (high frequency network control) expert database, finding out an abnormal value, and evaluating the health state according to the change trend and the abnormal degree of the abnormal value.
Preferably, after the treated patient data are stored to the cloud server through the cloud server, the patient data are stored to the cloud server, and then the patient electronic health record is established, so that clinical data support is provided for remote management.
The invention has the beneficial effects that:
the invention can improve the accuracy and convenience of treatment, and solve the problems that the use of HFNC of different medical institutions and families in China is not standard, convenient and quick, and the treatment effect is influenced; the method and the system realize stable and reliable data transmission to the cloud, establish the electronic health file of the patient, provide clinical data support for remote management, establish a monitoring and management mode of long-period HFNC treatment, and provide scientific management and personalized guidance for the patient.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a remote management platform for nasal high flow humidified oxygen therapy based on expert therapy mode, comprising: a data acquisition module, a data storage and processing module, a monitoring module, an expert auxiliary treatment system, a cloud server and a remote platform management system, wherein,
the data acquisition unit is used for acquiring data indexes of representative symptom data, treatment parameter data and related disease epidemiological data of the respiratory failure patient;
the data storage and processing module is used for storing the data acquired by the data acquisition unit, performing statistical analysis on the stored data, and performing normalization processing to form an HFNC (high frequency network control) expert database;
the monitoring module is used for remotely acquiring data of the terminal;
the expert assistant treatment system is used for formulating an individual expert treatment scheme based on the HFNC expert database and the data of the terminal and transmitting the scheme to the terminal for real-time treatment;
the cloud server is used for storing the treated patient data to the cloud end;
the remote platform management system analyzes and monitors the patient data stored in the cloud by utilizing a deep learning technology, and establishes a monitoring and management mode of long-period HFNC treatment.
The terminal includes vital sign detector and high flow humidification oxygen therapy appearance. The vital sign detector obtains the vital sign data of the patient, including pulse oxygen saturation, oxygen partial pressure and oxygenation fingerNumber, pH, CO2Partial pressure, respiratory rate, heart rate, blood pressure, and the like. The data of the flow humidification oxygen therapy therapeutic apparatus comprises flow, oxygen concentration, temperature and humidity, pressure, alarm, fault, working time, environmental data and the like.
The remote platform management system comprises a core processor and a human-computer interaction interface, wherein the human-computer interaction interface is electrically connected with the core processor. The core processor is used for analyzing and processing the patient data stored in the cloud, and the human-computer interaction interface is used for inputting parameters and displaying real-time monitoring data.
The method for analyzing the cloud patient treatment data by utilizing the deep learning technology comprises the following steps:
1) collecting vital sign data of a patient;
2) establishing a dynamic change model of each parameter based on the acquired data; establishing an evolution process of the disease condition by utilizing a deep learning algorithm and the disease condition reflected under each parameter;
3) establishing an illness state evolution model and a medical effect evaluation model through long-time acquisition, processing and analysis, comparing the illness state evolution model established according to the vital sign data of the patient with an HFNC (high frequency network control) expert database, finding out an abnormal value, and evaluating the health state according to the change trend and the abnormal degree of the abnormal value.
In another embodiment, after the patient data after treatment is stored in the cloud server through the cloud server, the patient data is stored in the cloud server, and then an electronic health record of the patient is established, so that clinical data support is provided for remote management.
The invention can improve the accuracy and convenience of treatment, and solve the problems that the use of HFNC of different medical institutions and families in China is not standard, convenient and quick, and the treatment effect is influenced; according to the HFNC clinical research conclusion, by combining typical symptoms such as acute and chronic respiratory failure and the like, an HFNC expert database and an expert auxiliary treatment system are developed, an HFNC treatment scheme is optimized, the treatment accuracy and convenience are improved, and the HFNC intelligent clinical application is realized; aiming at remote management defects, a nasal high-flow humidification oxygen therapy remote management platform based on the Internet of things is provided, vital sign data of basic medical institutions and family HFNC equipment and patients are remotely acquired, the data are stably and reliably transmitted to the cloud, electronic health files of the patients are built, and clinical data support is provided for remote management; the cloud patient treatment data are analyzed by adopting a deep learning technology, the disease treatment condition of the patient is comprehensively evaluated, an individualized and reasonable comprehensive treatment path is provided for the patient based on an evaluation result, intelligent applications such as basic medical institutions and family remote monitoring, data review, abnormity alarm and the like are formed, a monitoring and management mode of long-period HFNC treatment is realized, and scientific management and personalized guidance are provided for the patient.
The working process of the invention is as follows:
(1) the data acquisition unit acquires data indexes such as representative symptom data of the respiratory failure patient, treatment parameter data, related disease epidemiological data and the like.
(2) The data storage and processing module stores the data indexes, performs statistical analysis and normalization processing to form an HFNC expert database so as to optimize the treatment scheme.
(3) And developing a remote platform management system based on the Internet of things by using a distributed cloud storage technology and a data filtering and analyzing technology.
(4) Based on the technology of the internet of things, basic medical institutions and family HFNC equipment (flow, oxygen concentration, temperature, humidity, pressure, alarm, fault, working time, environmental data and the like) and patient vital sign (pulse oxygen saturation, heart rate, respiratory rate and the like) data are remotely acquired.
(5) And forming a personalized expert treatment scheme according to the HFNC expert database and the remote patient data, and transmitting the scheme to the terminal for real-time treatment.
(6) The data of the patient after the collection and treatment is transmitted to the cloud stably and reliably by adopting a dynamic data receiving and transmitting strategy and an anti-interference technology, the parameters of the treatment scheme are adjusted in real time according to the data feedback condition, and an electronic treatment file of the patient is established.
(7) The method for analyzing the cloud patient treatment data by using the deep learning technology comprises the following steps: 1) collecting vital sign (pulse oxygen saturation, heart rate, respiratory rate, etc.) data of a patient; 2) establishing a dynamic change model of each parameter based on the acquired data; establishing an evolution process of the disease condition by utilizing a deep learning algorithm and the disease condition reflected under each parameter; 3) an illness state evolution model and a medical effect evaluation model are established through long-time acquisition, processing and analysis, the evolution model established according to the vital sign data (pulse oxygen saturation, heart rate, respiratory rate and the like) of a patient is compared with an expert knowledge base established by utilizing the vital sign of a healthy person, an abnormal value is found out, and the health state is evaluated according to the change trend and the abnormal degree of the abnormal value. Comprehensively evaluating the disease treatment condition of the patient, providing a personalized and reasonable comprehensive treatment path for the patient based on the evaluation result, and early warning, recording and supervising the corresponding management activities of the patient.
(8) And providing an individualized and rationalized comprehensive treatment path for the patient based on the evaluation result, early warning, recording and supervising the patient to perform corresponding management activities, forming intelligent applications of basic medical institutions and family remote monitoring, data review, abnormity alarm and the like, establishing a monitoring and management mode of long-period HFNC treatment, and providing long-term scientific management and individualized guidance for the patient.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A transnasal high-flow humidified oxygen therapy remote management platform based on an expert treatment mode is characterized by comprising: a data acquisition module, a data storage and processing module, a monitoring module, an expert auxiliary treatment system, a cloud server and a remote platform management system, wherein,
the data acquisition unit acquires data indexes of representative symptom data, treatment parameter data and related disease epidemiological data of the respiratory failure patient;
the data storage and processing module is used for storing the data acquired by the data acquisition device, performing statistical analysis on the stored data, and performing normalization processing to form an HFNC (high frequency network control) expert database;
the monitoring module is used for remotely acquiring data of the terminal;
the expert-assisted treatment system formulates an individualized expert treatment scheme based on the HFNC expert database and the data of the terminal, and transmits the scheme to the terminal for real-time treatment;
the cloud server is used for storing the treated patient data to a cloud end;
the remote platform management system analyzes and monitors the patient data stored in the cloud by using a deep learning technology, and establishes a monitoring and management mode of long-period HFNC treatment.
2. The remote management platform for transnasal high-flow humidified oxygen therapy based on expert treatment mode of claim 1, wherein the terminal comprises a vital sign detector and a high-flow humidified oxygen therapy apparatus.
3. The remote management platform for nasal high flow humidified oxygen therapy based on expert therapy mode of claim 2, wherein the vital sign detector obtains patient vital sign data including pulse oxygen saturation, heart rate and respiratory rate.
4. The remote management platform for nasal high flow humidified oxygen therapy based on expert therapy mode of claim 2, wherein the data of the flow humidified oxygen therapy apparatus comprises flow, oxygen concentration, temperature and humidity, pressure, alarm, fault, working time and environmental data.
5. The remote management platform for transnasal high flow humidified oxygen therapy based on expert treatment mode of claim 1, wherein the remote platform management system comprises a core processor and a human-machine interface electrically connected to the core processor.
6. The remote management platform for transnasal high flow humidified oxygen therapy based on expert treatment mode of claim 1, wherein the method for analyzing the treatment data of the cloud-end patient by using deep learning technology comprises:
1) collecting vital sign data of a patient;
2) establishing a dynamic change model of each parameter based on the acquired data; establishing an evolution process of the disease condition by utilizing a deep learning algorithm and the disease condition reflected under each parameter;
3) establishing an illness state evolution model and a medical effect evaluation model through long-time acquisition, processing and analysis, comparing the illness state evolution model established according to the vital sign data of the patient with an HFNC (high frequency network control) expert database, finding out an abnormal value, and evaluating the health state according to the change trend and the abnormal degree of the abnormal value.
7. The remote management platform for the transnasal high-flow humidified oxygen therapy based on the expert treatment mode of claim 1, wherein the patient data after treatment is stored to the cloud server through the cloud server, and after the patient data is stored to the cloud server, an electronic health file of the patient is built to provide clinical data support for remote management.
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Cited By (4)
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| CN113244492A (en) * | 2021-07-02 | 2021-08-13 | 湖南比扬医疗科技有限公司 | Oxygen supply adjusting method and device and HFNC (high frequency vapor deposition) equipment |
| CN114864068A (en) * | 2022-03-24 | 2022-08-05 | 中国人民解放军总医院第一医学中心 | Method and system for evaluating nasal high-flow humidification therapeutic apparatus and computer storage medium |
| CN117976125A (en) * | 2024-04-02 | 2024-05-03 | 山东拓庄医疗科技有限公司 | Medical equipment management system and method based on data analysis |
| CN117976125B (en) * | 2024-04-02 | 2024-06-04 | 山东拓庄医疗科技有限公司 | Medical equipment management system and method based on data analysis |
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