Digital management system for valvular heart disease

Abstract

The invention discloses a heart valvular disease digital management system, which relates to the technical field of medical data management, and is characterized in that a data acquisition module comprises an automatic acquisition unit and a multi-channel input unit; the storage management module comprises a data storage unit and a data management unit; the monitoring and early warning module comprises a data analysis unit and a health early warning unit; the data visualization module comprises a chart display unit, a dynamic interaction unit and a report generation unit; the health assistant module comprises a personalized management unit, a follow-up visit management unit, a health activity evaluation unit, an intelligent reasoning unit and a family member unit. The system has an early risk perception and hospital-family linkage valvular heart disease full-process digital health management mode, can improve the active health management ability of patients, controls disease risk factors, effectively restrains the risk of cardiovascular diseases, and improves the overall quality and efficiency of medical services.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data management, and more specifically, to a digital management system for heart valve disease. Background Art

[0002] In recent years, the number of patients with valvular heart disease has increased significantly worldwide. There are currently 12 million patients with valvular heart disease, and nearly 1 million people die from it every year. Although my country's medical level is developing rapidly, valvular heart disease in my country still has the status of "one high and three lows", namely high incidence, low early diagnosis rate, low treatment rate, and low follow-up management rate. ① High incidence: With the aging of the population and changes in lifestyle, the incidence of valvular heart disease is increasing. Especially among the elderly, valvular degenerative lesions (such as calcification and stenosis of the aortic valve and mitral valve) are becoming more and more common, resulting in an increase in the number of patients with valvular heart disease year by year. According to epidemiological surveys, the incidence of valvular heart disease in my country is 2.5%-3.2%. Based on the total population, there are more than 4 million patients with valvular heart disease. Among them, the incidence of valvular heart disease in the elderly over 75 years old is as high as 13.3%. ② Low early diagnosis rate: Valvular heart disease may not have obvious symptoms in the early stage, or the symptoms are atypical, which is easy to be ignored or misdiagnosed. Many patients are not diagnosed until the disease progresses to a more serious stage, missing the best time for treatment. ③ Low treatment rate: Although modern medical technology can provide a variety of effective treatments for valvular heart disease (such as valve repair and replacement surgery, transcatheter valve replacement, etc.), many patients fail to receive standardized treatment in a timely manner due to uneven distribution of medical resources, economic conditions and patients' lack of understanding of the disease. ④ Low follow-up management rate: After receiving treatment, patients with valvular heart disease need long-term follow-up and management to monitor changes in their condition and adjust treatment plans.

[0003] However, many patients lack systematic follow-up management, which leads to recurrence or deterioration of the disease, affecting treatment outcomes and quality of life. In addition, out-of-hospital management and early intervention of valvular heart disease is still an important and underdeveloped area in the cardiovascular field. Especially in the application of mobile health management technology, although it has broad potential, there are still many challenges and gaps in actual operation and widespread application.

[0004] Therefore, the present invention aims to provide a digital management system for heart valve disease to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a digital management system for valvular heart disease. The present invention has an early risk perception and hospital-family linkage valvular heart disease full-process digital health management model, which can enhance patients' proactive health management capabilities, control disease risk factors and effectively curb the risk of cardiovascular disease, and improve the overall quality and efficiency of medical services.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: A digital management system for heart valve disease, including a data acquisition module, a storage management module, a monitoring and early warning module, a data visualization module and a health assistant module;

[0007] The data collection module includes an automatic collection unit and a multi-channel input unit; the automatic collection unit is used to automatically extract the patient's medical history data from the electronic medical record system, and the multi-channel input unit is used to be compatible with multiple data input methods to obtain the patient's medical history data;

[0008] The storage management module includes a data storage unit and a data management unit; the data storage unit is used to obtain the medical history data of the patient in the data acquisition module and store them in categories; the data management unit is used for unified management of patient data;

[0009] The monitoring and early warning module includes a data analysis unit and a health early warning unit; the data analysis unit is used to analyze the patient's health data and convert it into a specific health index; the health early warning unit has a built-in multi-level early warning mechanism for automatically generating early warning signals according to different risk levels;

[0010] The data visualization module includes a chart display unit, a dynamic interaction unit and a report generation unit; the chart display unit is used to compare and analyze health data of different dimensions, and intuitively display the changes of key health indicators through different chart types; the dynamic interaction unit is used to realize the dynamic interaction function of data display, and customize the detailed data of different time periods or specific health indicators; the report generation unit is used to automatically generate personalized health reports;

[0011] The health assistant module includes a personalized management unit, a follow-up management unit, a health activity assessment unit, an intelligent reasoning unit and a family member unit; the personalized management unit is used to create a detailed health record for the patient, record all diagnosis and treatment and health management information, and realize personalized health management; the follow-up management unit is used to set up a follow-up reminder function, and notify the patient through WeChat to conduct regular review and follow-up to ensure the continuity of disease monitoring; the health activity assessment unit is used to conduct a comprehensive assessment of the health-related activities input by the user, and analyze the factors affecting overall health by monitoring the changing trajectory of the health index within a specific period; the intelligent reasoning unit is used to perform mathematical operations and reasoning on the patient's health data to realize applications such as query answering, personalized recommendations and disease prediction; the family member unit is used to design a system that allows family members to register and participate in the patient's health management.

[0012] The present invention is further configured as follows: the storage management module is specifically a storage and computing platform built using cloud computing technology, which realizes seamless data sharing and intercommunication between hospitals and homes, undertakes big data storage and computing tasks through a server cluster, and ensures the security, real-time and stability of the data; at the same time, it supports large-scale data processing and analysis, so that the system can process massive health data from different sources, and improve data utilization and the accuracy of diagnosis and treatment decisions.

[0013] By adopting the above technical solution,

[0014] The present invention is further configured as follows: the automatic collection unit automatically extracts the patient's medical history, laboratory test reports and imaging examination results through natural language processing and image recognition technology, thereby reducing the time and errors of manual input and realizing efficient digitization and information integration of electronic medical records.

[0015] The present invention is further configured such that: the multi-channel input unit is also compatible with manual entry, voice input and scanning recognition input methods to ensure the comprehensiveness and accuracy of case information.

[0016] The present invention is further configured as follows: the data analysis unit adopts machine learning and AI algorithms to analyze patient health data in real time and generate a health index to quantify the patient's overall health level. At the same time, through deep learning and pattern recognition technology, it identifies and analyzes the potential combined risk factors of each patient to provide a personalized health risk overview.

[0017] The present invention is further configured as follows: the data visualization module specifically adopts advanced data visualization technology to convert complex health data into easy-to-understand charts and dashboards, supports dynamic interactive functions, and users can customize the viewing of data through operations such as clicking and zooming. This multimodal display and interactive design enhances the efficiency of patients and doctors in understanding health data.

[0018] The present invention is further configured as follows: the health activity assessment unit conducts a comprehensive assessment of the health-related activities input by the user, monitors the changing trajectory of the health index within a specific period, integrates the environmental information around the patient, and analyzes the impact of various activities on overall health. The assessment results will be presented in a quantitative form and integrated in a measurement table of the effectiveness of each activity, helping users understand which activities have a positive impact on health and which activities may have a negative impact, thereby guiding them to adjust their daily behaviors and optimize health management strategies.

[0019] The present invention is further configured as follows: the intelligent reasoning unit is used to perform mathematical operations and reasoning on the patient's health data, and realize applications such as query answering, personalized recommendations and disease prediction through semantic understanding and graph reasoning technology; at the same time, based on the user's health records and dynamic data, combined with the user's preferences and health needs, it infers potential health risks and proposes preventive measures, and recommends personalized health activities and diet plans.

[0020] In summary, the present invention has the following beneficial effects:

[0021] 1. The present invention can realize cross-scenario data sharing and intercommunication. The storage management module breaks the data barriers between hospitals and families through the architecture based on cloud computing storage technology, realizes seamless sharing and intercommunication of patient health data, ensures the comprehensiveness, continuity and real-time nature of data, and improves the efficiency and effectiveness of overall health management;

[0022] 2. The present invention can monitor and enhance the early warning mechanism in real time. Many monitoring and early warning modules enable the digital management system to have real-time monitoring and early warning functions, which can timely capture and respond to abnormal changes in the patient's health status, enhance the early warning and intervention capabilities of the disease, and reduce the risk of disease progression and complications;

[0023] 3. The present invention can meet the personalized health management of patients. The personalized management unit can be customized according to the health data of patients, taking into full account the individual differences of patients such as age, gender, comorbidity and biological information, so as to enhance the effect of health management and meet the personalized needs of patients.

[0024] 4. The present invention can perform data visualization and analysis. The data visualization module can visualize and analyze multimodal data through different chart types, making it easier for doctors and patients to intuitively understand the changing trends and overall status of health data, thereby ensuring the accuracy and timeliness of diagnosis and treatment decisions;

[0025] 5. The present invention has a perfect closed-loop management system. The digital management system can perform complete closed-loop evidence chain management, forming a complete closed loop of "data-driven-evidence evaluation-management decision-update data", solving the problems of insufficient continuity and effectiveness of management and decision-making in the prior art, and can achieve dynamic optimization and continuous improvement;

[0026] 6. The digital management system of the present invention can increase patients' acceptance of professional medical knowledge. The health assistant module can consider comprehensive factors such as patients' cognitive level, daily living habits and personality, and tailor health management plans for patients to assist patients in scientific health management;

[0027] 7. The present invention also meets the requirement of involving family members in the management of patients. The family member unit can deepen the connection between patients and doctors, improve the transparency and interactivity of patient health management, and significantly improve the level and efficiency of personalized health management;

[0028] 8. The present invention can improve the efficiency of data collection. The automatic collection unit can automatically synchronize data. Through the integrated electronic medical record system, patients and medical institutions can achieve automatic data synchronization, reducing the time and operation errors of manual input. The patient's vital signs, test results, doctor's diagnosis and other information can be synchronized to the cloud platform in a timely manner to ensure the real-time and accuracy of the data;

[0029] 9. The present invention can enhance the self-management ability of patients. The digital management system will automatically send reminders to remind patients to regularly measure and record key physiological parameters such as blood pressure and heart rate, and ensure that the data is uploaded in real time. This function can effectively prevent patients from forgetting to measure and maintain the continuity of monitoring. At the same time, users can input daily health activities in the form of triples, and the system will automatically evaluate the impact of the activities on health and give specific suggestions;

[0030] 10. The present invention can combine environmental and health activity analysis. The digital management system automatically records environmental parameters such as weather, temperature, air pollution index, etc. where the patient is located, and evaluates their impact on health. At the same time, it records the patient's daily activities, evaluates the impact of daily activities, analyzes their impact on health indexes, and gives specific suggestions to assist patients in adjusting exercise intensity or methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a module structure diagram of a digital management system for heart valve disease in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following is combined with Figure 1 The present invention is described in further detail.

[0033] Embodiment: A digital management system for heart valve disease, comprising a data acquisition module, a storage management module, a monitoring and early warning module, a data visualization module and a health assistant module;

[0034] The data collection module includes an automatic collection unit and a multi-channel input unit; the automatic collection unit can automatically collect patient case information, and automatically extract the patient's medical history information from the electronic medical record system through natural language processing technology, including demographic data: name, gender, age, ethnicity, occupation, marital status, etc.; disease history: previous medical history, family medical history, personal history, etc.; onset: symptoms, onset time, duration, etc.; medication: drug name, dosage, usage, dosage, start time, end time, etc.; daily physiological data: blood pressure, heart rate, respiration, pulse, etc.; laboratory tests: blood routine, biochemistry, coagulation function, brain natriuretic peptide, troponin, and myocardial enzyme spectrum test results; imaging data: cardiac ultrasound, electrocardiogram, CT results; through advanced image recognition technology, automatically read and extract patients' laboratory test reports and imaging test results. The automatic collection unit supports medical documents in multiple formats, realizes efficient digitization and information integration of electronic medical records, and improves the utilization rate of medical data and the efficiency of diagnosis and treatment.

[0035] The multi-channel input unit is compatible with manual entry, voice input, scanning recognition and other methods to ensure the comprehensiveness and accuracy of case information, including the use of voice input to record patient complaints and symptoms; users can enter health-related daily activity information, including all behaviors and activities that affect personal health, and each activity instance will be entered in the form of a triple (category, sub-category, intensity); its nap record includes detailed information such as nap time period, start and end time and location. Through the input information, the patient's mental health status can be evaluated: anxiety, depression, stress, etc.; happiness index: satisfaction, quality of life, etc.; drug compliance: drug intake, degree of compliance with doctor's orders, etc.; cognitive function: memory, attention, executive function, etc.; dietary structure: daily dietary composition; exercise: daily exercise form, exercise volume assessment; sleep quality: work and rest time, sleep duration, sleep quality, sleep disorders, etc. are effectively evaluated.

[0036] The storage management module includes a data storage unit and a data management unit; the data storage unit is used to obtain the patient's medical history data in the data acquisition module and classify and store it. At the same time, the data storage unit can realize seamless data sharing. By using the storage and computing platform built with cloud computing technology, seamless data sharing and intercommunication between hospitals and families can be realized, changing the traditional local data storage method. The server cluster undertakes large data storage and computing tasks to ensure the security, real-time and stability of the data; the data management unit is used for the unified management of patient data, and supports large-scale data processing and analysis, so that the digital management system can process massive health data from different sources, including electronic medical records, laboratory results, environmental data, etc., to improve data utilization and the accuracy of diagnosis and treatment decisions.

[0037] The monitoring and early warning module includes a data analysis unit and a health early warning unit. The data analysis unit uses advanced machine learning and AI algorithms to comprehensively and automatically analyze the patient's health data, monitor the patient's health status in real time, and convert it into a specific health index to quantitatively reflect the patient's overall health level. At the same time, through deep learning and pattern recognition of multi-source data, the data analysis unit can identify each patient's potential combined risk factors. These risk factors are displayed through advanced data visualization technology, including the composition and contribution ratio of each risk factor, providing an intuitive and detailed overview of health risks. The health early warning unit has a built-in multi-level early warning mechanism, which automatically generates early warning signals according to different risk levels. When an abnormal health status is detected or the risk factor exceeds the safety threshold, the system The relevant medical staff and the patient will be notified immediately, and the warning information will be notified through multiple channels (including WeChat, mobile phones, etc.) to ensure that the information is delivered in time, thereby prompting medical staff and patients to quickly take necessary medical intervention measures to prevent the condition from worsening; at the same time, the health warning unit is equipped with an automatic reminder function to regularly remind patients to measure and record key physiological parameters, including but not limited to blood pressure, heart rate, height, weight, BMI, abdominal circumference, leg circumference, hip circumference and daily steps, etc. These data will be uploaded to the system in real time to ensure the continuity and accuracy of health monitoring; the health warning unit not only improves the accuracy and efficiency of health data analysis, but also enhances the scientificity and timeliness of medical decision-making throughout the entire process of valvular heart disease, and provides solid technical support for personalized health management of valvular heart disease.

[0038] The data visualization module includes a chart display unit, a dynamic interaction unit and a report generation unit; the chart display unit includes chart display, trend curve and dashboard view functions, among which the chart function uses a variety of chart types such as bar charts, pie charts and scatter charts to compare and analyze health data of different dimensions, and intuitively display the changes in key health indicators; the trend curve function uses a time series curve to display the historical change trend of patients' health indicators (blood pressure, blood sugar, heart rate, etc.), helping doctors and patients identify fluctuations and potential problems; the dashboard view function adopts a dashboard form, integrating real-time monitoring data of multiple health indicators, providing a clear overview of the overall health status, and the dashboard is also set with warning thresholds to display in real time whether the indicators are within a safe range; the dynamic interaction unit The dynamic interactive function is used to realize data display. Users can customize the detailed data of different time periods or specific health indicators by clicking, zooming and dragging. At the same time, the dynamic interactive unit also includes multimodal integration, which can support the integration of multimodal data from different devices and data sources, such as electronic medical records, data generated by wearable devices and laboratory test results, and provide a unified visualization interface; the report generation unit automatically generates personalized health reports according to the selected time period and data type, which is convenient for doctors to make detailed diagnoses and patients to manage their health; the data visualization module significantly improves the comprehensibility and application value of health data in a comprehensive, intuitive and easy-to-use way, allowing doctors and patients to assess and make decisions on their health conditions more accurately and timely.

[0039] The health assistant module includes a personalized management unit, a follow-up management unit, a health activity assessment unit, an intelligent reasoning unit, and a family member unit; the personalized management unit creates a detailed health record for each valvular heart disease patient, records all diagnosis and treatment and health management information, and implements personalized health management. It queries the health record using a query language, uses a query engine to execute the query and returns structured results. In addition, it also supports the formulation of advanced navigation queries, and uses attribute path expressions to effectively run through the longitudinal change trajectory of health information; the personalized management unit also includes data collection and ontology design, by collecting medical knowledge and personal health data in real time from multiple sources, including but not limited to electronic medical record systems, laboratory data , environmental parameters, daily activity records, and physiological parameter measurements, convert these multi-source data into a standardized format, and ensure data consistency and interoperability by building a unified ontology. Design a personal health ontology in accordance with the Rapid Healthcare Interoperability Resource standard, and associate the data with the classes in the ontology to enhance semantic interoperability; This unit also includes data mapping and conversion, by mapping the data of electronic health records into semantic data in the Resource Description Framework format, using the W3C RDB2RDF direct mapping method, for semi-structured data (such as data generated by daily health behaviors), the Resource Description Framework Mapping Language (RML) is used for data mapping, by using the Corroborative Verification (Corroborative Verification) The unit verifies the accuracy of data in the knowledge graph using the COPAAL (Correct Fact Validation) technology. This unit includes embedding generation of the health knowledge graph. Generating embeddings from personalized health records involves converting the entities and relationships of the graph into vector representations that capture semantic information. These embeddings can be used in various applications, such as semantic similarity measurement, personalized recommendations, and disease prediction. Together, entity embeddings and relationship embeddings provide a comprehensive way to encode the semantic knowledge contained in the knowledge graph, so that various tasks that require understanding the structure and semantics of the graph can be performed. These embeddings allow efficient mathematical operations and reasoning on the graph, thereby enabling applications such as query answering, recommendation, and reasoning.

[0040] The follow-up management unit has a follow-up reminder function, which notifies patients through WeChat to conduct regular review and follow-up to ensure the continuity of disease monitoring; the health activity assessment unit system conducts a comprehensive assessment of the health-related activities entered by the user, analyzes the factors affecting overall health by monitoring the changing trajectory of the health index within a specific period, and the assessment results will be presented in a quantitative form and integrated in the effectiveness measurement table of each activity to help users understand which activities have a positive impact on health and which activities may have a negative impact, thereby guiding them to adjust their daily behaviors, optimize health management strategies, and form a complete health management closed loop; the intelligent reasoning unit is used to perform mathematical operations and reasoning on the patient's health data to achieve applications such as query answering, personalized recommendations and disease prediction. It also integrates the weather information reading function to obtain and record key environmental parameters such as the current environment's temperature, weather conditions and air pollution index. These data will be used to analyze the potential impact of environmental factors on the patient's health and provide more comprehensive health management suggestions; the family member unit allows family members to register and participate in the patient's health management, including viewing health data, receiving reminder notifications, participating in care plans, etc., to enhance the family support network.

[0041] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A digital management system for heart valve disease, Its characteristics are: It includes data acquisition module, storage management module, monitoring and early warning module, data visualization module and health assistant module; The data collection module includes an automatic collection unit and a multi-channel input unit; the automatic collection unit is used to automatically extract the patient's medical history data from the electronic medical record system, and the multi-channel input unit is used to be compatible with multiple data input methods to obtain the patient's medical history data; The storage management module includes a data storage unit and a data management unit; the data storage unit is used to obtain the medical history data of the patient in the data acquisition module and store them in categories; the data management unit is used for unified management of patient data; The monitoring and early warning module includes a data analysis unit and a health early warning unit; the data analysis unit is used to analyze the patient's health data and convert it into a specific health index; the health early warning unit has a built-in multi-level early warning mechanism for automatically generating early warning signals according to different risk levels; The data visualization module includes a chart display unit, a dynamic interaction unit and a report generation unit; the chart display unit is used to compare and analyze health data of different dimensions, and intuitively display the changes of key health indicators through different chart types; the dynamic interaction unit is used to realize the dynamic interaction function of data display, and customize the detailed data of different time periods or specific health indicators; the report generation unit is used to automatically generate personalized health reports; The health assistant module includes a personalized management unit, a follow-up management unit, a health activity assessment unit, an intelligent reasoning unit and a family member unit; The personalized management unit is used to create a detailed health record for the patient, record all diagnosis and treatment and health management information, and realize personalized health management; the follow-up management unit is used to set up a follow-up reminder function, and notify the patient through WeChat to conduct regular review and follow-up to ensure the continuity of disease monitoring; the health activity assessment unit is used to conduct a comprehensive assessment of the health-related activities input by the user, and analyze the factors affecting the overall health by monitoring the changing trajectory of the health index within a specific period; the intelligent reasoning unit is used to perform mathematical operations and reasoning on the patient's health data to realize applications such as query answering, personalized recommendations and disease prediction; the family member unit is used to design a system that allows family members to register and participate in the patient's health management.

2. A digital management system for heart valve disease according to claim 1, Its characteristics are: The storage management module is specifically a storage and computing platform built using cloud computing technology, which enables seamless sharing and interoperability of data between hospitals and homes, and undertakes big data storage and computing tasks through server clusters to ensure data security, real-time and stability; it also supports large-scale data processing and analysis, allowing the system to process massive health data from different sources, thereby improving data utilization and the accuracy of diagnosis and treatment decisions.

3. A digital management system for heart valve disease according to claim 1, Its characteristics are: The automatic collection unit automatically extracts the patient's medical history, laboratory test reports and imaging test results through natural language processing and image recognition technology, reducing the time and errors of manual input and achieving efficient digitization and information integration of electronic medical records.

4. A digital management system for heart valve disease according to claim 1, Its characteristics are: The multi-channel input unit is also compatible with manual entry, voice input and scanning recognition input methods to ensure the comprehensiveness and accuracy of case information.

5. A digital management system for heart valve disease according to claim 1, Its characteristics are: The data analysis unit uses machine learning and AI algorithms to analyze patient health data in real time and generate a health index to quantify the patient's overall health level. At the same time, through deep learning and pattern recognition technology, it identifies and analyzes each patient's potential combined risk factors to provide a personalized health risk overview.

6. A digital management system for heart valve disease according to claim 1, Its characteristics are: The data visualization module specifically uses advanced data visualization technology to convert complex health data into easy-to-understand charts and dashboards, and supports dynamic interactive functions. Users can customize their data viewing through operations such as clicking and zooming. This multimodal display and interactive design enhances the efficiency of patients and doctors in understanding health data.

7. A digital management system for heart valve disease according to claim 1, Its characteristics are: The health activity assessment unit conducts a comprehensive assessment of the health-related activities input by the user, by monitoring the changing trajectory of the health index within a specific period, integrating the environmental information around the patient, and analyzing the impact of various activities on overall health. The assessment results will be presented in a quantitative form and integrated into a measurement table for the effectiveness of each activity, helping users understand which activities have a positive impact on health and which activities may have a negative impact, thereby guiding them to adjust their daily behaviors and optimize health management strategies.

8. A digital management system for heart valve disease according to claim 1, Its characteristics are: The intelligent reasoning unit is used to perform mathematical operations and reasoning on the patient's health data, and realize applications such as query answering, personalized recommendations and disease prediction through semantic understanding and graph reasoning technology; at the same time, it also infers potential health risks and proposes preventive measures based on the user's health records and dynamic data, combined with user preferences and health needs, and recommends personalized health activities and diet plans.

Images