A COPD big data management platform and construction method thereof

Abstract

The present invention discloses a COPD big data management platform and a construction method thereof, and belongs to the field of chronic disease health management. The present invention constructs a Chinese and Western medicine standard medical health database and a Chinese and Western medicine characteristic prevention and treatment technology database by effectively integrating multi-source data, realizes data standardization, eliminates data redundancy, and improves data quality. The Chinese and Western medicine standard medical health database, the Chinese and Western medicine characteristic prevention and treatment technology database, and a dedicated medical system interface are integrated to establish a COPD big data center, laying a foundation for subsequent data analysis, mining, and application, making the health and medical data of COPD patients more reliable and easy to analyze, thereby providing more valuable support for Chinese and Western medicine clinical decision-making and health management, and medical workers can also obtain the required information faster and make more accurate diagnosis and treatment decisions. In addition, the present invention also establishes an auxiliary engine that can help medical staff and patients better obtain information and feedback.

Description

Technical Field

[0001] The present invention belongs to the field of chronic disease health management, and in particular relates to a chronic obstructive pulmonary disease big data management platform and a construction method thereof. Background Art

[0002] Chronic obstructive pulmonary disease (COPD) has the characteristics of "four highs" of high prevalence, high disability rate, high mortality rate and high disease burden. The main reason is that COPD people lack effective management and scientific guidance, which leads to repeated attacks and continuous aggravation of the disease. How to effectively prevent and control the progression of COPD, reduce mortality and improve the quality of life are still difficult and hot issues to be overcome in the medical community. At present, the management of COPD patients has problems such as unsatisfactory community electronic health record filing, serious information islands, and lack of intelligent risk factor evaluation methods. How to more reasonably and efficiently integrate the "Internet +" concept and technology with the three functions of COPD management monitoring, evaluation and intervention, create a comprehensive COPD management platform, optimize the management process, and provide patients with better quality and more convenient services is a development trend.

[0003] Some management systems for COPD have also been disclosed in the prior art. For example, patent publication number CN115458190A proposes a community-oriented chronic obstructive pulmonary disease early screening and intervention system, which mainly connects community doctors and respiratory specialists with a respiratory disease data management platform through the mobile Internet; patent publication number CN111681725A discloses a COPD prevention and treatment management method and system, which monitors the vital signs of COPD patients, determines the health status of COPD patients based on personal files, treatment information and vital signs information, and then formulates prevention and treatment strategies based on the health status, thereby achieving individualized management of COPD.

[0004] However, in the process of building the above-mentioned system, due to the current clinical medical data such as diagnostic data, surgical data, medication data, test data, vital sign data, and data extracted from electronic medical records, the definitions and names of data items (fields) are ambiguous, the value range codes are not unified, the information model and resource content lack a unified description and expression, and there are incomplete data, duplicate data, erroneous data, and data in irregular formats in Chinese and English, and abbreviations for data names. This has led to many non-standard and non-uniform problems in the collection of basic data for hospitals and community populations, which has also had a great impact on the construction of the COPD management platform. Moreover, there is no COPD management platform with the characteristics of traditional Chinese medicine in the above-mentioned systems. Summary of the invention

[0005] In view of the above problems, the present invention proposes a COPD big data management platform and a construction method thereof. The specific technical solutions are as follows:

[0006] The present invention proposes a method for constructing a COPD big data management platform, comprising the following steps:

[0007] Establish a standard medical and health database for COPD using traditional Chinese and Western medicine and a database of traditional Chinese and Western medicine-specific prevention and treatment technologies for COPD;

[0008] Integrate the traditional Chinese and Western medicine standard medical health database, the traditional Chinese and Western medicine characteristic prevention and treatment technology database and the dedicated medical system to establish a COPD big data center;

[0009] Establishing an auxiliary engine in the prevention and treatment of COPD based on the COPD big data center;

[0010] Based on the COPD big data center and auxiliary engine, determine the disease development pattern and trend of the patient and provide optional treatment plans; the treatment plans include traditional Chinese medicine management plans and integrated traditional Chinese and Western medicine treatment plans;

[0011] A COPD big data management platform is constructed based on the COPD big data center and auxiliary engine.

[0012] Furthermore, the establishment of a standard medical health database for COPD using traditional Chinese and Western medicine includes the following steps:

[0013] Obtain the diagnosis and treatment data and monitoring data of COPD patients to form a basic database;

[0014] Obtain COPD-related terms and establish a standard medical terminology database for COPD in both traditional Chinese and Western medicine according to the International Classification of Diseases;

[0015] Acquire the clinical vocabulary used in the treatment and rehabilitation of COPD and establish a synonym database of COPD in both Chinese and Western medicine;

[0016] The basic database is processed based on the traditional Chinese and Western medicine COPD standard medical terminology library and the traditional Chinese and Western medicine COPD synonym library to obtain the traditional Chinese and Western medicine COPD standard medical health database.

[0017] Furthermore, processing the basic database to obtain a standard medical health database of traditional Chinese and Western medicine for COPD includes the following steps:

[0018] Extracting raw data from different sources to form a basic database, and performing desensitization processing on the raw data in the basic database;

[0019] Clean the desensitized data to remove or correct incomplete, erroneous and irregularly formatted data to obtain correct and standardized data;

[0020] Deduplication processing is performed on duplicate data in the correct standard data to obtain a patient information database and store it in the COPD big data center;

[0021] The patient information database, COPD standard medical terminology database, and COPD synonym database are matched to form a COPD standard medical health database of traditional Chinese and Western medicine.

[0022] Furthermore, the original data includes electronic health record data, electronic medical record data, public health data, disease control data and personal vital sign monitoring data.

[0023] Furthermore, establishing a database of traditional Chinese and Western medicine prevention and treatment technologies for COPD includes the following steps:

[0024] Integrate TCM treatment methods, drug formulas, and TCM data during the treatment process for COPD;

[0025] Integrate Western medicine data on COPD treatment methods, drugs, and treatment processes;

[0026] Based on the integration of traditional Chinese medicine data and Western medicine data, a database of traditional Chinese and Western medicine prevention and treatment technologies is generated using big data and machine learning algorithms.

[0027] Furthermore, the dedicated medical system includes HIS, EMR, LIS and PACS.

[0028] Furthermore, the auxiliary engine includes an auxiliary medical AI engine, a COPD medical AI engine and a voice AI engine.

[0029] Furthermore, the auxiliary engine for establishing the COPD prevention and treatment process based on the COPD big data center includes the following steps:

[0030] Analyze the outpatient case data of COPD Big Data Center and use artificial intelligence technology to generate an auxiliary medical AI engine;

[0031] Analyze the medical imaging data and clinical information of the COPD big data center and use artificial intelligence technology to generate a COPD medical AI engine;

[0032] The patient rehabilitation data and personal vital sign monitoring data in the COPD big data center are analyzed, and artificial intelligence technology is used to generate a voice AI engine.

[0033] Furthermore, the auxiliary medical AI engine is used to form an outpatient medical record generation system, filter out conversations that are not related to the condition, automatically capture and structure key consultation information, and generate standard medical records that meet medical record writing specifications;

[0034] The COPD medical AI engine is used to conduct comprehensive analysis of patients’ medical imaging data and clinical information to diagnose the disease at an early stage;

[0035] The voice AI engine is used to obtain the patient's voice-reported health status and provide health management suggestions and voice reminders after analysis.

[0036] Furthermore, determining the disease development pattern and trend of the patient based on the COPD big data center and the auxiliary engine and providing optional treatment plans includes the following steps:

[0037] Constructing a patient portrait based on the patient information database stored in the COPD Big Data Center and performing risk assessment based on the patient portrait, wherein the patient information includes the patient's physiological, genetic, living environment and behavioral factors;

[0038] Using the patient portrait and auxiliary engine to establish an AI disease prediction model and a disease development trend prediction model;

[0039] Based on the results of the risk assessment, the disease development trend prediction model and the AI ​​disease prediction model, the patient's disease development pattern is predicted and optional treatment plans are generated.

[0040] In the second aspect, the present invention proposes a COPD big data management platform constructed using the above method.

[0041] Furthermore, the service objects of the COPD big data management platform include patients, community workers and medical staff;

[0042] The patient registers on the first operation terminal, fills in identity information and medical condition information, and obtains application services. The above information is synchronized to the second operation terminal;

[0043] Medical staff enter the COPD big data platform through the second operating terminal to obtain the identity information and disease information synchronized with the first operating terminal and the electronic health records established with the assistance of community personnel, and manage and intervene in patients. Medical staff can also conduct research projects through the COPD big data center. For example, they can classify the data and conduct special research on the classified data.

[0044] Furthermore, the application services include COPD monitoring, risk factor evaluation, COPD intervention and health benefit assessment.

[0045] Beneficial effects of the present invention:

[0046] The present invention realizes standardized data processing, eliminates data redundancy, and improves data quality by effectively integrating multi-source data. Then, the standard medical health database, the Chinese and Western medicine characteristic prevention and treatment technology database, and the dedicated medical system interface are integrated to establish a COPD big data center, laying the foundation for subsequent data analysis, mining, and application, making the health and medical data of COPD patients more reliable and easy to analyze, thereby providing more valuable support for Chinese and Western medicine clinical decision-making and health management, and medical workers can also obtain the required information faster and make more accurate diagnosis and treatment decisions. In addition, the present invention also establishes an auxiliary engine to help medical staff and patients better obtain information and feedback. The COPD big data platform with Chinese medicine characteristics constructed by the present invention through the above method provides patients with corresponding Chinese medicine characteristic technical guidance and management based on the evaluation of the patient's constitution and Chinese medicine syndrome, thereby promoting the patient's recovery.

[0047] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A flowchart of a method for constructing a COPD big data management platform proposed in an embodiment of the present invention is shown;

[0050] Figure 2 A schematic diagram showing the formation of a research topic library in an embodiment of the present invention is shown;

[0051] Figure 3 A schematic diagram of the health record information of a patient proposed in an embodiment of the present invention is shown;

[0052] Figure 4 A schematic diagram of a process for processing raw data proposed in an embodiment of the present invention is shown;

[0053] Figure 5 A schematic diagram of a COPD big data management platform constructed in an embodiment of the present invention is shown;

[0054] Figure 6 A schematic diagram of the operation interface of the first operation terminal in an embodiment of the present invention is shown;

[0055] Figure 7 A schematic diagram of an operation interface of a second operation terminal in an embodiment of the present invention is shown;

[0056] Figure 8 A schematic diagram showing the relationship between the patient operation terminal and the medical staff operation terminal in an embodiment of the present invention is shown;

[0057] Fig. 9 A schematic diagram of a family-community-hospital three-level prevention and control system proposed in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] In another embodiment of the present invention, a method for constructing a COPD big data management platform is proposed. Figure 1 As shown, the following steps are included:

[0060] S1: Establish a standard medical and health database of traditional Chinese and Western medicine for COPD and a database of traditional Chinese and Western medicine prevention and treatment technologies for COPD;

[0061] S2: Integrate the traditional Chinese and Western medicine standard medical health database, the traditional Chinese and Western medicine characteristic prevention and treatment technology database and the dedicated medical system to establish a COPD big data center;

[0062] S3: Establishing an auxiliary engine in the prevention and treatment of COPD based on the COPD big data center;

[0063] S4: Based on the COPD big data center and the auxiliary engine, determine the disease development pattern and trend of the patient and provide optional treatment plans; the treatment plans include a TCM management plan and a combination of TCM and Western medicine treatment plans;

[0064] S5: Construct a COPD big data management platform based on the COPD big data center and auxiliary engine.

[0065] In step S1, establishing a standard medical health database for COPD includes the following steps:

[0066] S1.1: Obtain the diagnosis and treatment data and monitoring data of COPD patients to form a basic database;

[0067] S1.2: Obtain COPD-related terms and establish a standard medical terminology database for COPD in both traditional Chinese and Western medicine according to the International Classification of Diseases;

[0068] In an exemplary embodiment of the present invention, COPD can be used as a theme, and domestic and international terminology resources for related diseases can be collected through organizing industry experts, consulting the Internet, literature books, clinical documents and other channels; referring to the International Classification of Diseases Standard Code ICD-10, the International Medical Ontology SNOMED-CT, UMLS, etc., by developing a collaborative standard medical terminology system to create a living environment, and organizing experts to participate, a standard medical terminology system for COPD can be established, and it will be continuously enriched and improved in the later application process;

[0069] S1.3: Obtain the vocabulary used in clinical writing during COPD treatment and rehabilitation, and establish a synonym database of COPD in both traditional Chinese and Western medicine;

[0070] In an exemplary embodiment of the present invention, a synonym map related to COPD is established from different types of vocabulary such as diagnosis, symptoms, tests, examinations, units, and drugs, and non-standard expressions in clinical writing are standardized; whether the doctor writes standard vocabulary or non-standard vocabulary, it can be converted through the platform to achieve full utilization of data. Due to the different expressions of data standard terms generated by hospitals and communities in the actual diagnosis and treatment process, there may be dozens or hundreds of clinical diagnosis original words corresponding to the same hospital. This data can only be fully utilized after being standardized by the disease diagnosis data model.

[0071] S1.4: Based on the COPD standard medical terminology library and COPD synonym library, the basic database is standardized to obtain a COPD Chinese and Western medicine standard medical health database, specifically including the following steps:

[0072] S1.4.1: Extract raw data from different sources to form a basic database, and perform desensitization on the raw data in the basic database;

[0073] Among them, the original data includes electronic health record data, electronic medical record data, public health data, disease control data and personal vital sign monitoring data; desensitization processing refers to the de-identification of patient privacy, and sensitive data is transformed through desensitization rules. The new data obtained still retains the source data characteristics, business data logic, and data relevance.

[0074] In an exemplary embodiment of the present invention, Figure 2As shown, ETL data exchange tools can be used to extract original data from HIS (hospital information system), EMR (electronic medical record), LIS (laboratory information system), and PACS (medical imaging archive and communication system) to obtain a high-quality clinical database. The data in the high-quality clinical database is subjected to patient privacy de-identification, intelligent screening of enrolled patients, dynamic form data collection, and data statistical analysis to form a research topic library for medical staff to conduct research topics as needed.

[0075] The electronic health record data is the patient's health record information. Each patient's electronic health record consists of dynamic data and static data, such as Figure 3 As shown, the static data (i.e., the static (relative) data in the figure) includes basic information, examination results, diagnosis records, and medication history, etc.; dynamic data includes the physical signs and condition change data obtained by patient self-monitoring and regular follow-up by community workers. Based on the real-time progress and effectiveness of the patient's physical recovery, flexible selection and customization of personalized follow-up strategies can be made to ensure the accuracy and timeliness of medical care. Electronic medical record data is the patient's medical data, including the patient's medical history, diagnosis, treatment plan, medication records, surgical records, etc.; public health data is data from the public health system, including regional infectious disease prevalence, vaccination coverage, environmental health factors, etc.; disease control data is data from the Centers for Disease Control; personal physical sign monitoring data comes from the physical sign data of patients' self-monitoring or regular monitoring by community workers, including real-time monitoring data of daily blood pressure, blood sugar, heart rate and other physiological indicators.

[0076] The present invention does not impose any specific restrictions on the manner of comparing and merging data. For example, duplicate records can be detected by comparing whether the data attribute values ​​of the records are the same, and equal records can be merged into one record or duplicate records can be deleted.

[0077] S1.4.2: Clean the desensitized data to remove or correct incomplete, erroneous and irregular data to obtain correct and standardized data, such as Figure 4 As shown;

[0078] It should be noted that the method of data cleaning in the present invention is not specifically limited. For example, missing values ​​can be processed by interpolation, deletion or manual filling; erroneous values ​​can be detected and corrected by statistical analysis, rule checking or comparison with external data.

[0079] S1.4.3: Use data deduplication technology to process the duplicate data in the correct standard number to obtain a patient information database and store it in the COPD big data center, such as Figure 4 As shown;

[0080] It should be noted that data deduplication technology includes but is not limited to hash-based deduplication technology, text similarity-based deduplication technology, machine learning-based deduplication technology, and distributed deduplication algorithm.

[0081] S1.4.4: Match the patient information database, COPD standard medical terminology database, and COPD synonym database to form a COPD standard medical health database of traditional Chinese and Western medicine.

[0082] In an exemplary embodiment of the present invention, a SAGE (Standard-Based Sharable Active Guideline Environment) medical knowledge model is constructed using the Protégé ontology tool. The SAGE medical knowledge model is then automatically converted into a series of rules that meet the requirements of computer reasoning through a rule generator. The SAGE model is then converted into an expression method of CLIPS (C Language Integrated Production System). Through programming, the automatic conversion of the SAGE medical knowledge model to CLIPS (C Language Integrated Production System) is achieved, so that medical knowledge can be automatically reasoned in the CLIPS reasoning engine and converted into rules.

[0083] In step S1, establishing a database of traditional Chinese and western medicine prevention and treatment technologies for chronic obstructive pulmonary disease includes the following steps:

[0084] Integrate TCM treatment methods, drug formulas, and TCM data during the treatment process for COPD;

[0085] Integrate Western medicine data on COPD treatment methods, drugs, and treatment processes;

[0086] Based on the integrated traditional Chinese medicine data and Western medicine data, a database of traditional Chinese and Western medicine prevention and treatment technologies is generated using big data and machine learning algorithms. The database includes traditional Chinese medicine treatment plans, Western medicine treatment plans, and traditional Chinese and Western medicine combined treatment plans.

[0087] The establishment of a standard medical and health database of traditional Chinese and Western medicine for COPD and a database of traditional Chinese and Western medicine prevention and treatment technologies can achieve continuity and systematic management of COPD disease. It can also provide opinions on TCM diagnosis and medication through auxiliary engines or data analysis, and use big data technology to analyze treatment effects and changes in patients' quality of life. The personalized treatment recommendation algorithm based on patient data and TCM theory can provide patients with customized treatment plans and health guidance with TCM characteristics (such as health teas, winter disease treatment in summer, nutritional intervention, etc.).

[0088] In an exemplary embodiment of the present invention, in step S2, expert consensus / guideline definition data elements, intelligent HIS / EMR / LIS / PACS interfaces, dedicated equipment interfaces, academic literature knowledge bases, cloud computing and big data support platforms, data security management systems, etc. can be integrated to form a COPD big data center. In the specific implementation process, expert consensus and guidelines can be converted into data elements to ensure data consistency and comparability. The interface integration technology of intelligent HIS, EMR, LIS, PACS and other systems can achieve seamless docking and circulation of data and ensure accurate collection and real-time transmission of equipment data.

[0089] In an exemplary embodiment of the present invention, the COPD big data center may also set corresponding rules such as data encryption, access control and privacy protection to ensure the secure management and application of data.

[0090] In an exemplary embodiment of the present invention, establishing an auxiliary engine in the COPD prevention and treatment process based on the COPD big data center in step S3 includes the following steps:

[0091] S3.1: Analyze the outpatient case data of COPD Big Data Center and use artificial intelligence technology to generate an auxiliary medical AI engine;

[0092] Specifically, the auxiliary medical AI engine improves the efficiency and accuracy of medical diagnosis, treatment and management by using artificial intelligence technology. It is used to form an outpatient medical record generation system, filter out conversations that are not related to the condition, automatically capture and structure key consultation information, and generate standard medical records that meet medical record writing specifications. Or it can be used for patient health management and remote medical consultation; through wearable devices and other IoT technologies, it collects patient health data, conducts real-time analysis and early warning, and provides patients with personalized health guidance and intervention measures. It helps doctors to understand the patient's health status in a timely manner, provide timely medical intervention and consulting services, and reduce the risk of patients seeking medical treatment due to worsening conditions.

[0093] S3.2: Analyze the medical imaging data and clinical information of the COPD big data center and use artificial intelligence technology to generate a COPD medical AI engine;

[0094] Specifically, the medical imaging data and clinical information of patients can be comprehensively analyzed to diagnose the disease at an early stage; or personalized rehabilitation plans can be generated based on multi-dimensional data such as the patient's medical history, physiological indicators, and exercise ability, including breathing training, exercise therapy, and nutritional guidance. Through IoT technology, key health indicators of patients (such as heart rate, blood oxygen saturation, respiratory rate, etc.) can be monitored in real time and automatically analyzed and processed. When patients have their lung function tested at a community hospital, the COPD medical AI engine processes and analyzes the data in real time and gives corresponding reference suggestions to community doctors.

[0095] S3.3: Analyze the patient rehabilitation data and personal vital sign monitoring data in the COPD Big Data Center and use artificial intelligence technology to generate a voice AI engine.

[0096] Specifically, patients report their daily health status through voice, and the voice AI engine records and analyzes the data to provide health management suggestions. Voice reminds patients to take medicine on time, undergo health checks, and adjust their lifestyles. It is used to report patients' daily health status through voice, record and analyze data, and provide health management suggestions.

[0097] In one embodiment of the present invention, determining the disease development pattern and trend of the patient based on the COPD big data center and the auxiliary engine and providing optional treatment plans in step S4 includes the following steps:

[0098] S4.1: Construct a patient portrait based on the patient information database of the COPD Big Data Center, and conduct a risk assessment on the patient based on the patient portrait; the patient information includes the patient's physiological, genetic, living environment and behavioral factors; specifically includes the following steps:

[0099] Through unique identifiers such as the patient's ID and identity card number, data from different data sources are linked to identify and merge similar or identical information (such as the same indicators in multiple physical examination results);

[0100] Digital fusion technology is used to integrate structured data (such as values ​​and text in electronic medical records) and unstructured data (such as medical images and doctors' diagnosis descriptions), and natural language processing technology is used to parse text data and extract key information; natural language processing technology includes lexical analysis, syntactic analysis, semantic analysis, semantic understanding, machine translation and other methods.

[0101] Extract key features from the integrated data and quantify the key features; the key features include age, gender, medical history, medication status, and trends of changes in physiological indicators;

[0102] A health portrait model is constructed using machine learning or deep learning algorithms (such as random forests, neural networks, etc.), which takes the quantified feature data as input and outputs a patient portrait. The health portrait includes multiple dimensions, such as physical health, mental health, social adaptability, etc., and provides specific scores and explanations for each dimension to help patients and medical staff intuitively understand their health status, including health status assessment, disease risk prediction, health management recommendations, etc.

[0103] It should be noted that the present invention also sets roles and permission access to ensure that patient privacy is protected during the entire process of building the patient portrait, and uses encryption technology, access control and other means to ensure the security of data during transmission, storage and processing. The generated health portrait can also be evaluated to verify its accuracy and practicality. According to the feedback results of patients, the data collection, integration and modeling process are continuously optimized to improve the accuracy and application value of the health portrait.

[0104] S4.2: Using the patient portrait and auxiliary engine to establish an AI disease prediction model and a disease development trend prediction model;

[0105] The AI ​​disease prediction model is used to identify the risk of COPD in advance based on the patient's historical medical data and patient portraits;

[0106] The disease development trend prediction model is used to predict the disease progression of individual patients, and the prevalence trend of COPD can be predicted through multiple disease development trend prediction models. Specifically, a disease development trend prediction model can be constructed based on time series analysis and machine learning, and the analysis results can be converted into intuitive charts and reports for users to view intuitively.

[0107] S4.3: Based on the risk assessment results, disease development trend prediction model and AI disease prediction model, predict the patient's disease development pattern and generate optional treatment plans; the treatment plans include traditional Chinese medicine management plans and integrated Chinese and Western medicine treatment plans.

[0108] In an exemplary embodiment of the present invention, a COPD big data management platform is constructed as follows: Figure 5 As shown, it consists of a COPD big data platform, two types of service objects, and four application services;

[0109] Among them, the COPD big data platform includes a COPD big data center and an auxiliary engine. The auxiliary engine includes an auxiliary medical AI engine, a COPD medical AI engine and a voice AI engine. The function of the auxiliary engine is the same as that in the construction method and will not be described in detail here.

[0110] The second type of service objects include patients and medical staff. Patients and medical staff can access the COPD big data management platform through the first operation terminal and the second operation terminal respectively. The interface of the first operation terminal is as follows: Figure 6 As shown, the interface of the second operation terminal is as follows Figure 7 shown.

[0111] The 4 application services include COPD monitoring, risk factor assessment, COPD intervention and health benefit assessment; among them,

[0112] COPD monitoring service is used to monitor the patient's health status in real time;

[0113] Risk factor assessment is used to evaluate patients’ risk factors and provide personalized management plans;

[0114] COPD intervention is used to propose effective intervention suggestions or plans based on monitoring and evaluation results;

[0115] Health effectiveness evaluation is used to assess the health benefits of management and interventions.

[0116] Medical staff can also conduct scientific research based on the patient information database and the standard medical and health database of traditional Chinese and Western medicine for COPD.

[0117] For example, Figure 8 As shown, the first operation terminal (i.e., the patient operation terminal) is the COPD chronic disease management platform official account, and the second operation terminal (i.e., the medical staff operation terminal) is the COPD chronic disease management system. Patients can register through the COPD chronic disease management platform official account, and after filling in their identity information and condition information, they can obtain COPD-related application services through the big data management platform. The identity information and condition information are synchronized to the second operation terminal. Medical staff enter the COPD big data management platform through the community COPD chronic disease management system, manage and intervene according to the relevant information filled in by the patient, and synchronize the management and intervention service information to the first operation terminal.

[0118] Management and intervention include providing commonly used inhaled treatment drugs for COPD, popular science questions and answers about COPD, Chinese patent medicines for COPD, common syndromes and prescriptions for COPD, Chinese medicine diet therapy, and Chinese medicine teas.

[0119] It should be noted that in this process, the assistance of community workers will also be involved. For example, under the guidance of community workers, patients can register on the COPD chronic disease management platform official account, establish an electronic health record for the patient, collect baseline information (including name, age, gender, BMI, underlying diseases, etc.), grade their condition, evaluate their self-management ability and save it in the health record. Patients learn health education knowledge online and keep records of their condition regularly or when their condition changes; community workers regularly browse patient medical records, work with patients through real-time dialogue to develop personalized self-management goals and plans for them, follow up with patients regularly, push follow-up evaluation forms to patients online, re-evaluate patients' diseases and self-management conditions, and assist patients in adjusting their self-management goals and plans based on the evaluation results. For patients who have acute attacks and can no longer manage themselves, community workers refer patients to secondary and tertiary comprehensive hospitals for treatment through a two-way referral green channel, and transfer patients back to the community for continued management after their condition stabilizes. A three-level prevention and control system of family-community-hospital is established with patients (families) as the center, community health service centers as the regulatory body, and hospitals as clinical guidance, such as Fig. 9 shown.

[0120] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a COPD big data management platform, characterized in that: The following steps are involved: Establish a standard medical health database of traditional Chinese and Western medicine for COPD and a database of traditional Chinese and Western medicine prevention and treatment technologies for COPD; obtain the diagnosis and treatment data and monitoring data of COPD patients to form a basic database; obtain COPD-related terms and establish a standard medical terminology database of traditional Chinese and Western medicine for COPD with reference to the International Classification of Diseases standard coding; obtain clinical writing vocabulary in the treatment and rehabilitation process of COPD and establish a synonym database of traditional Chinese and Western medicine for COPD; process the basic database based on the standard medical terminology database of traditional Chinese and Western medicine for COPD and the synonym database of traditional Chinese and Western medicine for COPD to obtain a standard medical health database of traditional Chinese and Western medicine for COPD; match the patient information database, the standard medical terminology database of COPD and the synonym database of COPD to form a standard medical health database of traditional Chinese and Western medicine for COPD; Integrate the methods, drug formulas and TCM data of COPD treatment in TCM; integrate the methods, drugs and Western medicine data of COPD treatment in Western medicine; generate a database of TCM and Western medicine prevention and treatment technologies based on the integrated TCM and Western medicine data using big data and machine learning algorithms; Integrate the traditional Chinese and Western medicine standard medical health database, the traditional Chinese and Western medicine characteristic prevention and treatment technology database and the dedicated medical system to establish a COPD big data center; An auxiliary engine in the prevention and treatment of COPD is established based on the COPD big data center; the auxiliary engine includes an auxiliary medical AI engine, a COPD medical AI engine and a voice AI engine; the outpatient case data of the COPD big data center is analyzed and the auxiliary medical AI engine is generated by artificial intelligence technology. The auxiliary medical AI engine is used to form an outpatient medical record generation system, screen out conversations irrelevant to the condition, automatically capture and structure key consultation information, and generate standard medical records that meet the medical record writing specifications; the medical imaging data and clinical information of the COPD big data center are analyzed and the COPD medical AI engine is generated by artificial intelligence technology. The COPD medical AI engine is used to comprehensively analyze the patient's medical imaging data and clinical information and make early diagnosis of the disease; the patient rehabilitation data and personal vital sign monitoring data of the COPD big data center are analyzed and the voice AI engine is generated by artificial intelligence technology. The voice AI engine is used to obtain the health status of the patient's voice report and provide health management suggestions after analysis, and make voice reminders; Determine the disease development pattern and trend of the patient based on the COPD big data center and the auxiliary engine and provide optional treatment plans, including: construct a patient portrait based on the patient information database stored in the COPD big data center and perform risk assessment based on the patient portrait; Using the patient portrait and auxiliary engine to establish an AI disease prediction model and a disease development trend prediction model; based on the risk assessment results, the disease development trend prediction model and the AI ​​disease prediction model, predict the patient's disease development pattern and generate optional treatment plans; the treatment plans include a TCM management plan and a combination of TCM and Western medicine treatment plans; A COPD big data management platform is constructed based on the COPD big data center and auxiliary engine.

2. The method for constructing a COPD big data management platform according to claim 1, characterized in that: The patient information database is constructed according to the following steps: Extracting raw data from different sources to form a basic database, and performing desensitization processing on the raw data in the basic database; Clean the desensitized data to remove or correct incomplete, erroneous and irregularly formatted data to obtain correct and standardized data; Duplicate data in the correct standard data is deduplicated to obtain a patient information database.

3. The method for constructing a COPD big data management platform according to claim 2, characterized in that: The original data includes electronic health record data, electronic medical record data, public health data, disease control data and personal vital sign monitoring data.

4. The method for constructing a COPD big data management platform according to claim 1, characterized in that: The dedicated medical systems include HIS, EMR, LIS and PACS.

5. A COPD big data management platform, characterized in that: The COPD big data management platform is constructed using the construction method of any one of claims 1-4.

6. The COPD big data management platform according to claim 5, characterized in that: The service objects of the COPD big data management platform include patients and medical staff; The patient registers at the first operation terminal, fills in identity information and medical condition information, and then obtains application services; the application services include COPD monitoring, risk factor evaluation, COPD intervention, and health benefit evaluation; Medical staff enter the COPD big data platform through the second operating terminal to obtain the identity information and disease information synchronized with the first operating terminal and the electronic health records established with the assistance of community personnel, and conduct management interventions on patients, or medical staff conduct research projects through the COPD big data center.

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