Children asthma whole-course management and medication monitoring method based on intelligent APP

Abstract

The invention relates to the technical field of medical treatment, in particular to a child asthma whole-course management and medication monitoring method based on an intelligent APP, and the method comprises the following steps: collecting the medication record, C-ACT score, lung function data, acute attack event record and other multi-dimensional data of a child patient through the intelligent APP; an LSTM (Long Short-Term Memory) network algorithm is utilized to predict the acute attack risk in the future 30 days, and corresponding early warning and intervention measures are taken according to risk classification (low risk, medium risk and high risk). In combination with remote intervention of a medical care team and a specialized nurse, the intelligent APP provides personalized health guidance and treatment adjustment suggestions, and intelligent and personalized management of children asthma is realized. The dynamic health report generated each month helps doctors to optimize long-term treatment strategies, follow-up visit frequency or medicine dosage is adjusted according to change of the state of illness of the child patient, the treatment effect of the child patient is ensured, the doctors adjust the treatment scheme according to real-time data, acute attack of the child patient is avoided, and the treatment effect is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a method for comprehensive management and medication monitoring of childhood asthma based on a smart APP. Background Art

[0002] Asthma is a heterogeneous disease characterized by chronic airway inflammation and airway hyperresponsiveness (AHR). Its primary clinical manifestations are recurrent episodes of wheezing, coughing, shortness of breath, and chest tightness. It is particularly prevalent among children. Acute asthma exacerbations in children are often caused by multiple factors, including poor medication adherence, environmental factors (such as allergen exposure), and fluctuations in lung function. Timely monitoring and intervention are crucial for effective asthma control.

[0003] However, while existing asthma management methods can assist with treatment through data collection and real-time monitoring, many technical bottlenecks remain in predicting the risk of acute asthma exacerbations and implementing personalized interventions. Existing technologies primarily rely on physician experience and regular health checkups, lacking dynamic predictions and precise early warning mechanisms tailored to individual children's conditions. Furthermore, existing methods often fail to fully integrate a child's historical health data (such as medication records, symptom feedback, and lung function data), resulting in inaccurate and in-time predictions of acute exacerbation risk. This prevents many children from receiving timely intervention before an attack, increasing the risk of an acute exacerbation. Summary of the Invention

[0004] The present invention provides a method for the comprehensive management and medication monitoring of childhood asthma based on a smart APP.

[0005] The smart app-based method for managing and monitoring childhood asthma throughout the entire process includes the following steps: S1, Establishment and synchronization of electronic health records for the first visit: The patient's personal information and medical history, lung function test data, and initial diagnosis results are entered into the smart app to generate an electronic health record containing a unique identifier. The electronic health record is synchronized to the cloud server in real time for sharing by multiple teams; S2, Follow-up data integration and plan adjustment: During follow-up visits, historical data in the electronic health record (including the patient's personal information and medical history, pulmonary function test data, and initial diagnosis results) is called up. Combined with newly collected pulmonary function test results, medication records, and C-ACT scores, a comprehensive assessment report is generated. Based on the report, the doctor and the parents adjust the treatment plan, update the electronic health record, and synchronize it to the app. S3, real-time medication monitoring and symptom feedback after discharge: The smart app connects to the medication management device to record medication data in real time, including medication time, dosage, and correct operation. Parents submit symptom scores and acute exacerbation events daily through the smart app, which are automatically synchronized to the electronic health record. S4, remote multi-team collaborative intervention: The medical team monitors medication data and symptom feedback in real time through the smart app backend, sending personalized reminders to children who are not taking medication on time or whose condition is poorly controlled. Specialized nurses use the app's video module to guide drug inhalation techniques and provide health education content based on symptom feedback. S5, health report generation and management optimization: C-ACT scores in electronic health records are summarized monthly, and medication data and lung function indicators are summarized every three months to generate dynamic health reports. Doctors use these reports to optimize long-term management strategies and adjust follow-up frequency or medication dosage. S6, Intelligent Risk Prediction and Warning: Use historical data to train machine learning models to predict the risk of acute asthma attacks in the next 30 days, push warning information to high-risk children through the APP, and trigger a priority follow-up mechanism.

[0006] Optionally, the S1 includes: S11, Child Information Collection: The smart app provides parents with an input interface, allowing them to fill in their child's basic information, including name, gender, date of birth, contact information, and address, and upload their child's relevant medical history, including past medical history, allergy history, and family medical history; S12, pulmonary function test data collection: connect the smart app to the pulmonary function test equipment to automatically collect the child's pulmonary function test data, including vital capacity, respiratory rate and airflow, and enter the pulmonary function test data into the smart app; S13, input of initial diagnosis results: The doctor logs into the system through the smart app and inputs the child's initial diagnosis results, including the severity of asthma, control status, and associated symptoms. The doctor then conducts a comprehensive assessment based on the child's relevant medical history, lung function test data, and clinical symptoms. S14, Generate Electronic Health Records: Generate the child's electronic health record based on the child's basic information, relevant medical history, pulmonary function test data, and initial diagnosis results, and assign a unique identifier to each record to facilitate subsequent data tracking and management; S15, electronic health records are synchronized to the cloud: the generated electronic health records are automatically synchronized to the cloud server through the smart APP to ensure real-time update and storage of data; S16, multi-team sharing and access rights management: The cloud server sets different access rights based on different team roles (such as doctors, nurses, and parents).

[0007] S17, electronic health record storage backup: The cloud server regularly performs storage backup of electronic health records and sets up a data recovery mechanism to ensure that historical data can be quickly restored in the event of a system failure to avoid data loss.

[0008] Optionally, the S2 includes: S21, follow-up information collection: During follow-up visits, the smart app provides parents and doctors with an input interface to collect and enter the child's latest lung function test results, medication records, and C-ACT scores; S22, call historical data: The smart APP automatically calls the child’s electronic health record from the cloud server and extracts historical data.

[0009] S23, Data Integration and Analysis: Data fusion algorithms are used to integrate historical and new data (including the patient's latest pulmonary function test results, medication records, and C-ACT scores). Combined with a rule engine, this allows analysis of the patient's condition and comprehensive assessment of pulmonary function status, medication compliance, and asthma control. S24, generate comprehensive evaluation report: automatically generate a comprehensive evaluation report based on the results of integration and analysis.

[0010] S25, Report sharing and discussion: The comprehensive assessment report is pushed to the parents’ and doctors’ interfaces in real time through the smart APP. Doctors and parents review the report content together and discuss it.

[0011] S26, Adjust treatment plan: Based on the results of the comprehensive assessment report, the doctor and parents will discuss and decide whether the treatment plan needs to be adjusted.

[0012] S27, Update electronic health records: The adjusted treatment plan and related decision information will be automatically updated to the child's electronic health record and synchronized to the cloud server; S28, synchronize data to APP: The updated electronic health record information is synchronized to the smart APP in real time, so that parents and doctors can access and track the latest treatment plan of the child at any time.

[0013] Optionally, the S3 includes: S31, smart APP connected to medication management device: wirelessly connect to medication management device (such as smart inhaler and medication meter) via smart APP; S32, recording medication time and dosage: The medication management device automatically records the specific medication time and dosage each time medication is taken, and uploads the medication time and dosage to the electronic health record through the smart APP; S33, check operation correctness: The smart app automatically checks the correctness of the drug inhalation operation. If the operation is not standardized (such as incorrect inhalation, insufficient drug dosage or inhaler malfunction), the app will send a reminder to the parent and suggest to perform the correct inhalation operation again; S34, Parents submit symptom scores: After each medication, parents submit their child's symptom scores through the smart app, including the severity of symptoms such as coughing, wheezing, and dyspnea. The symptom scores use pre-set scoring standards, such as the C-ACT rating scale or other pediatric asthma scoring systems. Parents fill in the symptom scores based on their child's actual experience and ensure timely submission. S35, Record acute attacks: Parents record any acute asthma attacks through the smart app and fill in relevant details, including the time of the attack, the severity of the symptoms, and whether emergency treatment was provided.

[0014] Optionally, the S3 further includes: S36, Data synchronization to electronic health records: Through the smart app, all medication data, symptom scores and acute exacerbation events will be automatically synchronized to the cloud server and updated to the child's electronic health record; S37, Data Storage and Backup: All recorded medication data, symptom scores, and acute episodes are encrypted and stored in a cloud server, and data backup is performed regularly; S38, Real-time Monitoring and Feedback: The smart app monitors medication records, symptom scores, and acute episodes in real time. If a child's symptoms worsen or medication compliance issues are detected, it will automatically alert parents and doctors and recommend appropriate intervention measures. S39, Data aggregation and report generation: Based on daily recorded medication data, symptom scores and acute attack events, dynamic health reports are generated regularly.

[0015] Optionally, the S4 includes: S41, the medical team monitors medication data and symptom feedback in real time: The medical team obtains and monitors the children's medication data, symptom scores and acute attacks in real time through the smart APP background.

[0016] S42, personalized reminder push: Based on real-time monitoring data, the medical team pushes personalized reminders to parents through the smart APP background.

[0017] S43, video guidance by specialist nurses: If it is detected that the child has made an error in drug inhalation operation (such as improper operation of the inhaler, insufficient drug dosage, etc.), the specialist nurse will provide remote guidance through the video module of the smart APP. Parents can communicate with the specialist nurse through video calls. The specialist nurse will guide parents on the correct use of the inhaler or drug management device based on the specific situation of the child.

[0018] S44, Symptom feedback analysis and health education: The medical team analyzes the changes in the child's condition and evaluates the effectiveness of symptom control based on the symptom scores and acute attack event records submitted by the parents.

[0019] S45, personalized health guidance push: The medical team pushes personalized health guidance content through the smart APP based on the individual condition and treatment effect of the child.

[0020] S46, real-time feedback and adjustment: The smart APP collects parents' feedback on health education content in real time, such as whether they understand it and whether they have implemented the suggestions. If parents do not adjust or operate according to the health suggestions in time, they will be reminded again and relevant content will be pushed to ensure that parents can correctly implement the treatment plan.

[0021] S47, Multi-Team Collaboration and Information Sharing: The medical team, specialist nurses, and doctors share the child's health data and treatment progress via a smart app, ensuring that each team can develop and adjust treatment plans based on the child's latest condition. After each intervention, all relevant data (such as symptom changes, medication use, and health education feedback) is synchronized in real time to the electronic health record for reference and use by all team members.

[0022] Optionally, the S5 includes: S51, Data Aggregation and Integration: Automatically aggregate key health data from electronic health records monthly; S52, generating a dynamic health report: generating a dynamic health report based on the summarized key health data; S53, Health report review and diagnosis: The doctor views the generated dynamic health report through the smart app and reviews the data in the report; S54, Optimize long-term management strategies: Based on the dynamic health report, the doctor will optimize the long-term management strategy for the child.

[0023] S55, Adjustment of follow-up frequency or drug dosage: Based on the evaluation results of the health report, the doctor adjusts the follow-up frequency or drug dosage of the child; S56, Update electronic health records: The adjusted follow-up frequency and medication dosage information will be updated in real time to the child's electronic health record and synchronized to the cloud server; S57, report push and parent notification: After the doctor adjusts the treatment plan, the smart APP will push the dynamic health report and adjusted treatment plan to the parent side, so that parents can timely understand the health status of the child and changes in the treatment plan.

[0024] Optionally, the S6 includes: S61, historical data collection and preprocessing: collecting historical data of children from electronic health records through smart APP; S62, model training: A prediction model was constructed using the long short-term memory network algorithm to predict the risk of acute asthma attacks within the next 30 days; S63, Risk Assessment and Grading: Utilizing a trained prediction model, based on the patient's real-time data (including medication records, C-ACT scores, lung function indicators, acute exacerbation event records, and symptom feedback), the patient's risk of acute asthma exacerbation within the next 30 days is predicted. The patient's risk of acute exacerbation is then assessed and graded into low, moderate, and high risk categories. S64, high-risk warning information push: For children assessed as high-risk, warning information will be pushed through the smart APP; S65, priority follow-up mechanism triggered: Based on the risk assessment results, the priority follow-up mechanism is triggered. For high-risk children, doctors or medical teams are arranged to conduct priority follow-up to ensure further health monitoring and intervention during the warning period.

[0025] Optionally, the S62 specifically includes: S621, Data Preparation: Collect historical data of children from electronic health records and divide the historical data into training and validation sets in chronological order; S622, Model Construction and Training: Use the long short-term memory network algorithm to build a prediction model and train the prediction model with the training set data; S623, Risk prediction and grading: After training is completed, the prediction model predicts the risk of acute asthma attacks in the next 30 days based on the input data and grades the risk of children.

[0026] Beneficial effects of the present invention: This invention uses a smart app to implement multi-team collaborative intervention. Through real-time monitoring by the medical team and specialist nurses, combined with intelligent reminders, video guidance, and health education, it provides precise remote intervention. The medical team can promptly send personalized reminders and intervention measures based on the child's medication use and symptom changes. Video guidance can also be used to help parents correct drug inhalation procedures and ensure the correct use of medications. This intelligent remote management method not only improves treatment compliance, but also effectively reduces acute attacks in children, reducing the pressure on hospitals.

[0027] This invention helps doctors better track changes in their children's conditions by regularly generating dynamic health reports that summarize key information such as medication data, C-ACT scores, and lung function indicators. This allows doctors to optimize long-term management strategies, adjust follow-up frequency and medication dosage, and ensure personalized and precise treatment plans. The health reports provide detailed analysis of disease changes and treatment adjustment recommendations. Parents can also access the reports at any time through the smart app to understand their children's health status, further enhancing parental involvement and treatment compliance.

[0028] This study, using a prediction model trained on a long-short-term memory network, can predict the risk of acute asthma exacerbations in children within the next 30 days. By combining multi-dimensional data such as medication records, C-ACT scores, lung function indicators, and acute exacerbation event records, the prediction model captures dependencies within time series, providing personalized risk predictions for each child. This approach allows doctors to adjust treatment plans based on real-time data, preventing acute exacerbations and significantly improving treatment outcomes. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the present invention or 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 only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 Schematic diagram of a method flow in an embodiment of the present invention; Figure 2 Schematic diagram of the S4 process of an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0032] It should be noted that references in the specification to "one embodiment," "an embodiment," "exemplary embodiments," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not necessarily every embodiment will include such specific features, structures, or characteristics. Furthermore, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0033] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0034] like Figure 1-Figure 2 As shown in the figure, the method for the comprehensive management and medication monitoring of childhood asthma based on the smart app includes the following steps: S1, Establishment and synchronization of electronic health records for the first visit: The patient's personal information and medical history, lung function test data, and initial diagnosis results are entered into the smart app to generate an electronic health record containing a unique identifier. The electronic health record is synchronized to the cloud server in real time for sharing by multiple teams; S2, Follow-up data integration and plan adjustment: During follow-up visits, historical data in the electronic health record (including the patient's personal information and medical history, pulmonary function test data, and initial diagnosis results) is called up. Combined with newly collected pulmonary function test results, medication records, and C-ACT scores, a comprehensive assessment report is generated. Based on the report, the doctor and the parents adjust the treatment plan, update the electronic health record, and synchronize it to the app. S3, real-time medication monitoring and symptom feedback after discharge: The smart app connects to the medication management device to record medication data in real time, including medication time, dosage, and correct operation. Parents submit symptom scores and acute exacerbation events daily through the smart app, which are automatically synchronized to the electronic health record. S4, remote multi-team collaborative intervention: The medical team monitors medication data and symptom feedback in real time through the smart app backend, sending personalized reminders to children who are not taking medication on time or whose condition is poorly controlled. Specialized nurses use the app's video module to guide drug inhalation techniques and provide health education content based on symptom feedback. S5, health report generation and management optimization: C-ACT scores in electronic health records are summarized monthly, and medication data and lung function indicators are summarized every three months to generate dynamic health reports. Doctors use these reports to optimize long-term management strategies and adjust follow-up frequency or medication dosage. S6, Intelligent Risk Prediction and Warning: Use historical data to train machine learning models to predict the risk of acute asthma attacks in the next 30 days, push warning information to high-risk children through the APP, and trigger a priority follow-up mechanism.

[0035] S1 includes: S11, Child Information Collection: The smart app provides parents with an input interface, allowing them to fill in their child's basic information, including name, gender, date of birth, contact information, and address, and upload their child's relevant medical history, including past medical history, allergy history, and family medical history; S12, pulmonary function test data collection: connect the smart app to the pulmonary function test equipment to automatically collect the child's pulmonary function test data, including vital capacity, respiratory rate and airflow, and enter the pulmonary function test data into the smart app; S13, input of initial diagnosis results: The doctor logs into the system through the smart app and inputs the child's initial diagnosis results, including the severity of asthma, control status, and associated symptoms. The doctor then conducts a comprehensive assessment based on the child's relevant medical history, lung function test data, and clinical symptoms. S14, Generate Electronic Health Records: Generate the child's electronic health record based on the child's basic information, relevant medical history, pulmonary function test data, and initial diagnosis results, and assign a unique identifier to each record to facilitate subsequent data tracking and management; S15, electronic health records synchronization to the cloud: the generated electronic health records are automatically synchronized to the cloud server through the smart app to ensure real-time update and storage of data. The synchronization process uses encrypted transmission to ensure data security and ensure that electronic health records can be shared among multiple teams; S16, Multi-Team Sharing and Access Management: The cloud server sets different access permissions based on team roles (e.g., doctors, nurses, parents), ensuring that relevant team members can view and edit information in the electronic health record according to their permissions. The permission management system includes read, edit, and update permissions to ensure data security and privacy.

[0036] S17, electronic health record storage backup: The cloud server regularly performs storage backup of electronic health records and sets up a data recovery mechanism to ensure that historical data can be quickly restored in the event of a system failure to avoid data loss.

[0037] S2 includes: S21, Follow-up Information Collection: During follow-up visits, the smart app provides parents and doctors with an input interface to collect and enter the child's latest lung function test results, medication records, and C-ACT scores. This information includes recent vital capacity, peak expiratory flow, medication status, dosage, frequency, and correct operation. The C-ACT (Children's Asthma Control Test) score is also recorded as a reference for assessing asthma control. S22, call historical data: The smart APP automatically calls the child's electronic health record from the cloud server and extracts historical data, including historical medical history, previous lung function test data and initial diagnosis results, to provide a data basis for comprehensive evaluation.

[0038] S23, Data Integration and Analysis: Data fusion algorithms are used to integrate historical and new data (including the patient's latest pulmonary function test results, medication records, and C-ACT scores). Combined with a rule engine, this allows analysis of the patient's condition and comprehensive assessment of pulmonary function status, medication compliance, and asthma control. Rule Engine Example: (1) Analysis rules for lung function status: Rule 1: If the latest vital capacity is lower than the preset normal range (e.g., 80% predicted value), lung function is determined to be limited, triggering a treatment adjustment recommendation; Rule 2: If the latest maximum expiratory flow rate decreases by more than 20% compared with the previous measurement, it indicates that the condition has worsened, prompting increased follow-up frequency or adjustment of treatment plan; (2) Medication compliance analysis rules: Rule 1: If medication records show missed doses more than three times per week, medication adherence is considered poor, and parents are advised to reassess medication habits; Rule 2: If medication dosage and frequency deviate from the recommended regimen (e.g., medication is not taken on time or the recommended dose is not taken), prompt the physician to review medication adherence; (3) C-ACT scoring analysis rules: Rule 1: If the C-ACT score is greater than 19, asthma is well controlled and no changes are needed in the treatment plan; Rule 2: If the C-ACT score is less than 15, it indicates poor control and the doctor is advised to adjust the treatment plan and increase the frequency of follow-up; (4) Comprehensive treatment adjustment rules: Rule 1: If lung function declines, the C-ACT score is low, and medication compliance is poor, comprehensive consideration should be given to strengthening the treatment plan, including adjusting drug doses, adding additional drug types, or introducing new therapies; Rule 2: If lung function improves, C-ACT scores are normal, and medication adherence is good, maintain the current treatment regimen; S24, Generate Comprehensive Assessment Report: Automatically generate a comprehensive assessment report based on the results of integration and analysis. The report includes the following contents: The child's current lung function status and comparison with historical data; The child's medication status, whether there is any missed medication or poor medication compliance; C-ACT scores and the control they reflect; Based on the evaluation results, improvement suggestions are automatically given (such as adjusting drug dosage, modifying treatment plan or increasing follow-up frequency).

[0039] S25, Report sharing and discussion: The comprehensive assessment report is pushed to the interface of parents and doctors in real time through the smart APP. Doctors and parents review the report content together and discuss it. This discussion can be conducted through video calls, text exchanges, etc.

[0040] S26, Adjusting the treatment plan: Based on the results of the comprehensive assessment report, the doctor and parents will discuss and decide whether the treatment plan needs to be adjusted. The content of the plan adjustment includes: Changing the type or dosage of medication or adding another medication; Adjust the frequency of follow-up visits; Adopt new auxiliary treatment methods (such as physical therapy, breathing training, etc.).

[0041] S27, Update Electronic Health Record: The adjusted treatment plan and related decision information will be automatically updated to the child's electronic health record and synchronized to the cloud server. This process ensures that all treatment adjustment information is accurately archived for subsequent follow-up visits; S28, Sync data to APP: The updated electronic health record information is synced to the smart APP in real time, so that parents and doctors can access and track the latest treatment plan of the child at any time. Parents can also view the updated treatment plan in the APP and receive corresponding reminders.

[0042] S3 includes: S31, Smart App connects to medication management device: The smart app is wirelessly connected to medication management devices (such as smart inhalers and medication meters) to ensure real-time recording and synchronization of medication usage data. The medication management device automatically identifies the medication type, dosage, usage time, and whether the inhalation operation is correct, and transmits this data to the smart app in real time; S32, recording medication time and dosage: The medication management device automatically records the specific medication time and dosage each time medication is taken, and uploads the medication time and dosage to the electronic health record through the smart app. After each medication is used, the smart app generates a medication record, including the medication time stamp, dosage and device identification code, to ensure the accuracy of medication use information; S33, Checking Operation Correctness: The smart app automatically checks the correctness of the drug inhalation operation. If the operation is not standardized (such as incorrect inhalation, insufficient drug dosage, or inhaler malfunction), the app will send a reminder to the parent and suggest that the correct inhalation operation be repeated. The operation correctness check criteria include the inhaler usage technique and whether the drug is completely released. S34, Parents submit symptom scores: After each medication, parents submit their child's symptom scores through the smart app, including the severity of symptoms such as coughing, wheezing, and dyspnea. The symptom scores use pre-set scoring standards, such as the C-ACT rating scale or other pediatric asthma scoring systems. Parents fill in the symptom scores based on their child's actual experience and ensure timely submission. S35, record acute attacks: Parents use the smart app to record any acute asthma attacks and fill in relevant details, including the time of the attack, the severity of the symptoms, and whether emergency treatment was provided. Recording acute attacks helps doctors understand the fluctuations in the child's condition and adjust the treatment plan.

[0043] S3 also includes: S36, Data Synchronization to Electronic Health Records: Through the smart app, all medication data, symptom scores, and acute exacerbation events will be automatically synchronized to the cloud server and updated to the child's electronic health record. This synchronization process ensures real-time data update and storage, allowing all medical team members to obtain timely information on the child's health status; S37, Data Storage and Backup: All recorded medication data, symptom scores, and acute episodes are encrypted and stored in cloud servers, and data backup is performed regularly. Data backup ensures that data will not be lost in the event of a system failure and can be quickly restored; S38, Real-time Monitoring and Feedback: The smart app monitors medication records, symptom scores, and acute episodes in real time. If a child's symptoms worsen or medication compliance issues (such as missed medication or improper use) are detected, it will automatically alert parents and doctors and recommend appropriate intervention measures, such as adjusting medication dosage or increasing the frequency of follow-up visits. S39, data aggregation and report generation: Based on daily recorded medication data, symptom scores and acute attack events, dynamic health reports are generated regularly. The reports include medication compliance, symptom control and acute attack frequency, and are pushed to doctors and parents to help doctors and parents understand the health status and treatment effects of the children and provide follow-up management suggestions.

[0044] S4 includes: S41, real-time monitoring of medication data and symptom feedback by the medical team: The medical team uses the smart app backend to obtain and monitor the child's medication data, symptom scores, and acute exacerbations in real time. The medical team can view the child's medication records, symptom feedback, and whether medication is taken on time. If a child is found not to be taking medication on time or symptom control is poor, an alert will be triggered and the child will be flagged, allowing the medical team to take timely intervention measures.

[0045] S42, Personalized Reminders: Based on real-time monitoring data, the medical team sends personalized reminders to parents via the smart app. If a child misses medication, takes an insufficient dose, or uses medication improperly, the system automatically sends a notification to the parent, prompting them to readjust the medication or perform the correct procedure. Furthermore, for children with poorly controlled conditions, the system reminds parents to monitor symptom changes and seek medical attention promptly.

[0046] S43, video guidance by specialist nurses: If it is detected that the child has made an error in drug inhalation operation (such as improper operation of the inhaler, insufficient drug dosage, etc.), the specialist nurse will provide remote guidance through the video module of the smart APP. Parents will communicate with the specialist nurse through video calls. The specialist nurse will guide parents to use the inhaler or drug management device correctly according to the specific situation of the child to ensure the correct use of the drug and the correction of the inhalation technique.

[0047] S44, Symptom Feedback Analysis and Health Education: The medical team analyzes the child's condition and assesses the effectiveness of symptom control based on symptom scores and acute exacerbation records submitted by parents. If symptoms worsen or an acute exacerbation is detected, the medical team provides parents with targeted health education via a smart app. This education includes, but is not limited to, proper medication use, environmental control, and emergency response measures for acute exacerbations, helping parents better manage their child's asthma.

[0048] S45, Personalized Health Guidance Push: The medical team will push personalized health guidance content through the smart app based on the child's individual condition and treatment results. This content may include dietary advice, exercise guidance, environmental control suggestions (such as avoiding allergens), and emotional management, ensuring that children receive comprehensive support in their daily lives.

[0049] S46, real-time feedback and adjustment: The smart APP collects parents' feedback on health education content in real time, such as whether they understand it and whether they have implemented the suggestions. If parents do not adjust or operate according to the health suggestions in time, they will be reminded again and relevant content will be pushed to ensure that parents can correctly implement the treatment plan.

[0050] S47, Multi-Team Collaboration and Information Sharing: The medical team, specialist nurses, and doctors share the child's health data and treatment progress via a smart app, ensuring that each team can develop and adjust treatment plans based on the child's latest condition. After each intervention, all relevant data (such as symptom changes, medication use, and health education feedback) is synchronized in real time to the electronic health record for reference and use by all team members.

[0051] S5 includes: S51, Data Aggregation and Integration: Automatically aggregate key health data from electronic health records monthly, including medication data (drug type, dosage, duration of use, etc.), C-ACT scores (Children's Asthma Control Test scores), lung function indicators (such as vital capacity, peak expiratory flow, etc.), and records of any acute exacerbations. This data is integrated and ensured to be complete and accurate for subsequent analysis. S52, generating a dynamic health report: generating a dynamic health report based on the summarized key health data, the report including the following contents: Monthly medication compliance analysis shows whether the child is taking the medication on time and in the correct dosage, and checks the correct operation; Trend analysis of C-ACT scores shows changes in the child's asthma control and provides a comparison between historical and current scores; Trends in lung function indicators, including monthly data on vital capacity, expiratory flow, FEV1, etc., and providing comparative analysis with historical data; Changes in the frequency and symptoms of acute attacks to assess fluctuations in the condition; S53, Health Report Review and Diagnosis: The doctor views the dynamic health report generated by the smart app and reviews the data in the report. The doctor will focus on changes in the child's symptoms, medication compliance, and improvement or deterioration of lung function. Based on the data shown in the report, the doctor will assess whether the current treatment plan is effective and whether it needs to be adjusted; S54, Optimize long-term management strategy: Based on the dynamic health report, the doctor will optimize the long-term management strategy for the child. The optimization may include: Adjust the type or dosage of medication to better control the condition; Adjust treatment plans and add adjuvant treatment or other management measures; Consider more frequent follow-up, especially if symptoms are poorly controlled or exacerbations are frequent.

[0052] S55, Adjustment of follow-up frequency or drug dosage: Based on the evaluation results of the health report, the doctor will adjust the child's follow-up frequency or drug dosage. If the condition is stable and the medication compliance is good, the doctor may reduce the follow-up frequency and recommend a later time for the next follow-up visit. If symptoms recur or the C-ACT score is low, the doctor will increase the follow-up frequency or adjust the drug dosage to optimize the treatment effect. S56, Update Electronic Health Records: Adjusted follow-up frequency and medication dosage information will be updated in real time in the patient's electronic health record and synchronized to the cloud server. All medical team members can access the latest health reports and treatment adjustment information to ensure continued effective management of the child; S57, Report Push and Parent Notification: After the doctor adjusts the treatment plan, the smart app pushes a dynamic health report and the adjusted treatment plan to the parent, allowing parents to promptly understand the child's health status and changes in the treatment plan. The report will provide a detailed explanation to help parents understand the reasons for the treatment adjustment and follow-up action recommendations; Health reports and treatment plan adjustments are continuously tracked and updated. The system automatically generates the next month's health report based on the new health data and continues to optimize management strategies. Through long-term data accumulation, the system will gradually improve the accuracy and personalization of treatment plans.

[0053] S6 includes: S61, Historical Data Collection and Preprocessing: The smart app collects historical data from electronic health records, including medication records, C-ACT scores, lung function indicators, acute exacerbation records, and symptom feedback information. The collected historical data will undergo preprocessing, including data cleaning, denoising, and standardization, to ensure data quality and usability, and be prepared for input into the prediction model for training. S62, model training: A prediction model was constructed using the long short-term memory network algorithm to predict the risk of acute asthma attacks within the next 30 days; S63, Risk Assessment and Grading: Utilizing a trained prediction model, based on the patient's real-time data (including medication records, C-ACT scores, lung function indicators, acute exacerbation event records, and symptom feedback), the patient's risk of acute asthma exacerbation within the next 30 days is predicted. The patient's risk of acute exacerbation is then assessed and graded into low, moderate, and high risk categories. S64, High-risk Warning Information Push: For children assessed as high-risk, warning information will be pushed through the smart app. This information includes risk assessment results, possible acute attack time period, and preventive measures. The warning information will remind parents to pay attention to the health status of the child in advance and recommend necessary preventive measures, such as increasing the frequency of medication use and avoiding contact with allergens. S65, Priority Follow-up Mechanism Triggered: Based on the risk assessment results, the priority follow-up mechanism is triggered. For high-risk children, a doctor or medical team will be assigned to provide priority follow-up to ensure further health monitoring and intervention during the early warning period. Priority follow-up may include telephone consultations, video consultations, or in-person appointments to ensure that high-risk children receive timely medical attention.

[0054] S62 specifically includes: S621, Data Preparation: Collect historical data from the child's electronic health record. The specific steps are as follows: Data collection: Collect historical data from the child, including medication records, C-ACT scores, pulmonary function indicators (such as vital capacity, peak expiratory flow), acute exacerbation records, and symptom feedback information (such as wheezing, coughing, etc.). This data is usually presented in the form of a time series, such as daily medication records and weekly pulmonary function test data; Missing value processing: missing values ​​in the data are processed by the mean filling method; Time window segmentation: historical data is divided into time series datasets based on time windows. For example, medication data and C-ACT scores from the past 30 days are used as a window and as the input sequence for the prediction model.

[0055] Feature Engineering: Select appropriate input features to ensure that the model can learn effective information. Input features include: Daily medication use (such as drug type, dosage, frequency of use, etc.); C-ACT score (reflects asthma control); Pulmonary function indicators (such as vital capacity, expiratory flow, etc.); Allergen exposure conditions (such as weather, air quality, etc.); Records of acute attacks (e.g., whether acute attacks have occurred in the past); Information on changes in symptoms (such as wheezing, coughing, difficulty breathing, etc.); Labeling: Before training the prediction model, each data series is assigned a target output, i.e., a label. These labels indicate whether the child will have an acute asthma attack in the next 30 days. The specific steps are as follows: Label is 0 (no acute exacerbation): If the child does not have an acute asthma exacerbation in the next 30 days, the label is set to 0.

[0056] Label 1 (acute attack occurs): If the child has an acute asthma attack within the next 30 days, the label is set to 1; Label generation: Use the acute attack event records in the historical data to generate corresponding labels. For each time window (such as 30 days), if an acute attack event occurs within the window, the label is 1; otherwise, it is 0.

[0057] Generate a corresponding label for each time period based on a specific definition (such as the occurrence of any acute attack or symptom exacerbation).

[0058] Dataset division: historical data is divided into training set and validation set in chronological order; S622, Model Construction and Training: Use the long short-term memory network algorithm to build a prediction model and train the prediction model with the training set data. The specific steps are as follows: Prediction model structure design: Input layer: The input layer of the prediction model receives time series data. The input dimensions include the patient's medication records, C-ACT scores, lung function indicators, etc. Long Short-Term Memory (LSTM) layers: One or more LSTM layers are used to learn temporal dependencies in the input data. LSTM layers are effective in capturing long-term dependencies and nonlinear patterns in time series data. Fully connected layers: The output of the LSTM layer is processed through one or more fully connected layers to generate predictions. The fully connected layers further map the features extracted by the LSTM layer to the final predictions. Output layer: The output layer generates a predicted acute exacerbation risk value (a probability value between 0 and 1) through a sigmoid activation function (for a binary classification task); Model training: The prediction model is trained using training set data. Input features include medication records, C-ACT scores, and lung function indicators. The label is whether an acute attack event has occurred. S623, Risk Prediction and Classification: After training is complete, the prediction model predicts the risk of acute asthma attacks within the next 30 days based on the input data and classifies the risk of the child. The specific steps are as follows: Risk Prediction: Using a trained prediction model, current and historical data are input to predict the risk of an acute exacerbation within the next 30 days. The model outputs a value between 0 and 1, representing the risk of an acute exacerbation.

[0059] Risk level classification: Low risk (0-0.2): If the risk probability output by the prediction model is lower than 0.2, it is assessed as low risk, indicating that the child has a low probability of acute attack and the condition is stable.

[0060] Medium risk (0.2-0.5): If the risk probability output by the prediction model is between 0.2 and 0.5, it is assessed as medium risk, indicating that the child's condition may fluctuate and the risk of acute attack is increased, but it is still controllable.

[0061] High risk (0.5-1.0): If the risk probability output by the prediction model is higher than 0.5, it is assessed as high risk, indicating that the child has a high risk of acute attack and requires immediate intervention and close monitoring.

[0062] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0063] The above are only preferred embodiments of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for the comprehensive management and medication monitoring of childhood asthma based on an intelligent APP, characterized by: The following steps are involved: S1, Establishment and synchronization of electronic health records for the first visit: The patient's personal information and medical history, lung function test data, and initial diagnosis results are entered into the smart app to generate an electronic health record containing a unique identifier. The electronic health record is synchronized to the cloud server in real time for sharing by multiple teams; S2, Follow-up data integration and plan adjustment: During follow-up visits, historical data in the electronic health record is called up and combined with newly collected pulmonary function test results, medication records and C-ACT scores to generate a comprehensive assessment report. Based on the report, the doctor and the parents will adjust the treatment plan, update the electronic health record and synchronize it to the app; S3, real-time medication monitoring and symptom feedback after discharge: The smart app connects to the medication management device to record medication data in real time, including medication time, dosage, and correct operation. Parents submit symptom scores and acute exacerbation events daily through the smart app, which are automatically synchronized to the electronic health record. S4, remote multi-team collaborative intervention: The medical team monitors medication data and symptom feedback in real time through the smart app backend, sending personalized reminders to children who are not taking medication on time or whose condition is poorly controlled. Specialized nurses use the app's video module to guide drug inhalation techniques and provide health education content based on symptom feedback. S5, health report generation and management optimization: C-ACT scores in electronic health records are summarized monthly, and medication data and lung function indicators are summarized every three months to generate dynamic health reports. Doctors use these reports to optimize long-term management strategies and adjust follow-up frequency or medication dosage. S6, Intelligent Risk Prediction and Warning: Use historical data to train machine learning models to predict the risk of acute asthma attacks in the next 30 days, push warning information to high-risk children through the APP, and trigger a priority follow-up mechanism.

2. The method for comprehensive management and medication monitoring of childhood asthma based on an intelligent APP according to claim 1, characterized in that: Said S1 comprises: S11, Child Information Collection: The smart app provides parents with an input interface, allowing them to fill in their child's basic information, including name, gender, date of birth, contact information, and address, and upload their child's relevant medical history, including past medical history, allergy history, and family medical history; S12, pulmonary function test data collection: connect the smart app to the pulmonary function test equipment to automatically collect the child's pulmonary function test data, including vital capacity, respiratory rate and airflow, and enter the pulmonary function test data into the smart app; S13, input of initial diagnosis results: The doctor logs into the system through the smart app and inputs the child's initial diagnosis results, including the severity of asthma, control status, and associated symptoms. The doctor then conducts a comprehensive assessment based on the child's relevant medical history, lung function test data, and clinical symptoms. S14, generate electronic health records: generate the child's electronic health record based on the child's basic information, relevant medical history, pulmonary function test data and initial diagnosis results, and assign a unique identifier to each record; S15, electronic health records synchronization to the cloud: the generated electronic health records are automatically synchronized to the cloud server through the smart APP; S16, multi-team sharing and access rights management: The cloud server sets different access rights based on different team roles; S17, electronic health record storage backup: The cloud server regularly performs storage backup of electronic health records.

3. The method for comprehensive management and medication monitoring of childhood asthma based on an intelligent APP according to claim 2, characterized in that: The S2 includes: S21, follow-up information collection: During follow-up visits, the smart app provides parents and doctors with an input interface to collect and enter the child's latest lung function test results, medication records, and C-ACT scores; S22, call historical data: the smart app automatically calls the child's electronic health record from the cloud server and extracts historical data; S23, Data Integration and Analysis: Integrate historical and new data through data fusion algorithms and combine them with rule engines to analyze the changes in the child's condition and comprehensively assess lung function status, medication compliance, and asthma control; S24, generate comprehensive evaluation report: automatically generate a comprehensive evaluation report based on the results of integration and analysis; S25, Report Sharing and Discussion: The comprehensive assessment report is pushed to the parents and doctors’ interfaces in real time through the smart app. Doctors and parents review the report content together and discuss it; S26, Adjustment of treatment plan: Based on the results of the comprehensive assessment report, the doctor and the parents will discuss and decide whether the treatment plan needs to be adjusted; S27, Update electronic health records: The adjusted treatment plan and related decision information will be automatically updated to the child's electronic health record and synchronized to the cloud server; S28, synchronize data to APP: The updated electronic health record information is synchronized to the smart APP in real time, so that parents and doctors can access and track the latest treatment plan of the child at any time.

4. The method for comprehensive management and medication monitoring of childhood asthma based on an intelligent APP according to claim 3, characterized in that: The S3 includes: S31, smart APP connects to medication management device: wirelessly connects to medication management device via smart APP; S32, recording medication time and dosage: The medication management device automatically records the specific medication time and dosage each time medication is taken, and uploads the medication time and dosage to the electronic health record through the smart APP; S33, check the correctness of the operation: the smart APP automatically checks the correctness of the drug inhalation operation. If the operation is not standardized, the APP will send a reminder to the parent and suggest to perform the correct inhalation operation again; S34, parents submit symptom scores: After each medication, parents submit their child's symptom scores through the smart app. The symptom scores use the preset scoring criteria, and parents fill in the form based on their child's actual experience. S35, Record acute attacks: Parents record any acute asthma attacks through the smart app and fill in relevant details, including the time of the attack, the severity of the symptoms, and whether emergency treatment was provided.

5. The method for comprehensive management and medication monitoring of childhood asthma based on smart APP according to claim 4 is characterized in that: Said S3 further comprises: S36, Data synchronization to electronic health records: Through the smart app, all medication data, symptom scores and acute exacerbation events will be automatically synchronized to the cloud server and updated to the child's electronic health record; S37, Data Storage and Backup: All recorded medication data, symptom scores, and acute episodes are encrypted and stored in a cloud server, and data backup is performed regularly; S38, Real-time Monitoring and Feedback: The smart app monitors medication records, symptom scores, and acute episodes in real time. If a child's symptoms worsen or medication compliance issues are detected, it will automatically alert parents and doctors and recommend appropriate intervention measures. S39, Data aggregation and report generation: Based on daily recorded medication data, symptom scores and acute attack events, dynamic health reports are generated regularly.

6. The method for comprehensive management and medication monitoring of childhood asthma based on smart APP according to claim 5, characterized in that: The S4 includes: S41, medical team monitors medication data and symptom feedback in real time: The medical team obtains and monitors the child's medication data, symptom scores, and acute exacerbations in real time through the smart APP backend; S42, personalized reminder push: Based on real-time monitoring data, the medical team pushes personalized reminders to parents through the smart APP background; S43, video guidance by specialist nurses: If a child is detected to have made an error in drug inhalation, the specialist nurse will provide remote guidance via the video module of the smart app; S44, Symptom Feedback Analysis and Health Education: The medical team analyzes the child's condition changes and evaluates the effectiveness of symptom control based on the symptom scores and acute attack records submitted by the parents; S45, personalized health guidance push: The medical team pushes personalized health guidance content through the smart app based on the individual condition and treatment effect of the child; S46, Real-time feedback and adjustment: The smart app collects parents' feedback on health education content in real time. If parents fail to adjust or take actions according to health recommendations in a timely manner, they will be reminded again and relevant content will be pushed; S47, multi-team collaboration and information sharing: The medical team, specialist nurses and doctors share the child's health data and treatment progress through the smart APP. After each intervention, all relevant data will be synchronized to the electronic health record in real time for reference and use by all team members.

7. The method for comprehensive management and medication monitoring of childhood asthma based on smart APP according to claim 6, characterized in that: The S5 includes: S51, Data Aggregation and Integration: Automatically aggregate key health data from electronic health records monthly; S52, generating a dynamic health report: generating a dynamic health report based on the summarized key health data; S53, Health report review and diagnosis: The doctor views the generated dynamic health report through the smart app and reviews the data in the report; S54, Optimize long-term management strategy: Based on the dynamic health report, the doctor will optimize the long-term management strategy for the child; S55, Adjustment of follow-up frequency or drug dosage: Based on the evaluation results of the health report, the doctor adjusts the follow-up frequency or drug dosage of the child; S56, Update electronic health records: The adjusted follow-up frequency and medication dosage information will be updated in real time to the child's electronic health record and synchronized to the cloud server; S57, report push and parent notification: After the doctor adjusts the treatment plan, the smart APP will push the dynamic health report and adjusted treatment plan to the parent side, so that parents can timely understand the health status of the child and changes in the treatment plan.

8. The method for comprehensive management and medication monitoring of childhood asthma based on smart APP according to claim 7, characterized in that: The S6 includes: S61, historical data collection and preprocessing: collecting historical data of children from electronic health records through smart APP; S62, model training: A prediction model was constructed using the long short-term memory network algorithm to predict the risk of acute asthma attacks within the next 30 days; S63, Risk Assessment and Grading: Using a trained prediction model, the patient's risk of acute asthma exacerbation within the next 30 days is predicted based on the patient's real-time data. The patient's risk of acute exacerbation is assessed and graded into low, moderate, and high risk categories. S64, high-risk warning information push: For children assessed as high-risk, warning information will be pushed through the smart APP; S65, priority follow-up mechanism triggered: Based on the risk assessment results, the priority follow-up mechanism is triggered, and doctors or medical teams are arranged to conduct priority follow-up for high-risk children.

9. The method for comprehensive management and medication monitoring of childhood asthma based on smart APP according to claim 8, characterized in that: The S62 specifically includes: S621, Data Preparation: Collect historical data of children from electronic health records and divide the historical data into training and validation sets in chronological order; S622, Model Construction and Training: Use the long short-term memory network algorithm to build a prediction model and train the prediction model with the training set data; S623, Risk prediction and grading: After training is completed, the prediction model predicts the risk of acute asthma attacks within the next 30 days based on the input data, and grading the risk based on the prediction results of the prediction model.

Images