Medical and health management system

Abstract

The invention discloses a medical and health management system, and the system comprises a user management module which is used for carrying out the identity recognition, authority distribution and information management of various users of the system, including but not limited to medical personnel, patients and management personnel; the medical information storage module is used for storing medical related data including medical record information, diagnosis records, inspection reports, image data, medicine information, medical instrument information and the like of patients; the system adopts cloud computing architecture deployment, the expansibility is high, resources can be dynamically adjusted according to the business volume of medical institutions, the operation cost is reduced, multiple medical institutions can realize medical resource sharing through the system, such as sharing medical equipment reservation information and expert seating information, and the resource utilization rate is improved. For example, multiple hospitals in the area share high-end medical equipment through the system, the equipment vacancy rate is reduced, and resource waste caused by repeated purchase of equipment is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical management system, and in particular to a medical health management system. BACKGROUND

[0002] With the development of society and the improvement of people's health awareness, the demand for medical services has grown rapidly. The aging of the population and the increase in the number of chronic disease patients have placed a heavy burden on the traditional medical system. Under the traditional medical model, information processing relies heavily on manual processing, which is inefficient and prone to errors. For example, patient medical records are mostly paper records, and medical staff spend a lot of time and effort searching for past medical records, and there are problems such as loss of medical records, illegible handwriting, and the like, which seriously affect the efficiency and accuracy of diagnosis.

[0003] Although existing medical information systems have developed to some extent, such as hospital information systems (HIS) that have achieved informationization of hospital business processes to some extent, covering outpatient, inpatient, pharmacy, and charging links, their functions are still limited. Different medical institutions lack effective interconnection between information systems, forming "information islands", which leads to the inability to share medical information when patients cross the hospital, making it difficult for doctors to fully understand the patient's medical history, and repeated testing is common, which not only increases the patient's financial burden, but also wastes medical resources. At the same time, the traditional medical service process is complicated, and patients need to run between multiple departments, and the waiting time is long, resulting in a poor patient experience. For example, in the appointment registration link, patients often need to make an appointment through the phone or on-site queuing, and the number of available options is limited and the operation is not convenient; in the hospital management aspect, the allocation of beds lacks scientific planning, and there are often imbalances between idle and tight beds.

[0004] In terms of medical data management and analysis, previous systems have not fully utilized and mined the vast amount of medical data. A large amount of valuable medical data is only used for basic recording and statistics, and cannot be analyzed in depth to provide strong data support for management decisions and resource allocation optimization for medical institutions. Moreover, in the face of sudden public health events or lack of medical resources in remote areas, the traditional medical model lacks an efficient telemedicine collaboration mechanism and cannot meet the patient's needs for diagnosis and treatment in a timely manner. Therefore, it is urgent to develop an integrated, intelligent, and efficient medical health management system with high information sharing and collaboration capabilities. SUMMARY

[0005] In order to overcome the shortcomings of the prior art, one of the purposes of the present application is to provide a medical health management system.

[0006] One of the purposes of the present application is achieved by the following technical solutions: A medical health management system, comprising: A user management module for identifying, assigning permissions, and managing information for various types of users, including but not limited to medical staff, patients, and administrators; A medical information storage module for storing medical-related data, including patient medical record information, diagnosis records, test reports, image data, as well as drug information and medical device information; A medical service process management module covering the information management and scheduling of the entire medical service process, including appointment registration, outpatient treatment, hospital management, surgery arrangement, and hospital discharge settlement; A data analysis and decision support module that mines and analyzes data in the medical information storage module to provide data support and decision recommendations for management decisions, medical quality assessment, and resource allocation optimization in medical institutions; A telemedicine module that supports remote consultation, remote diagnosis, remote education, and other telemedicine services, enabling cross-regional sharing of medical resources.

[0007] Further, the user management module uses multi-factor authentication technology, combining biometric identification (such as fingerprint recognition, facial recognition), dynamic passwords, and other methods to ensure the security and accuracy of user identity.

[0008] Further, the medical information storage module is based on blockchain technology, enabling distributed storage, tamper-proofing, and traceability of medical data, ensuring the security and integrity of medical data.

[0009] Further, the medical service process management module uses intelligent scheduling algorithms to automatically optimize medical service processes based on patient conditions, medical staff scheduling, and medical resource usage, reducing patient waiting times and improving medical service efficiency.

[0010] Further, the data analysis and decision support module uses machine learning algorithms to analyze medical data in real time, predict disease trends and patient readmission risks, and provide personalized medical decision recommendations.

[0011] Further, the telemedicine module has high-definition video transmission and real-time data interaction capabilities, supports data access from multiple medical devices, and ensures the quality and accuracy of telemedicine services.

[0012] Further, it also includes a medical quality monitoring module that monitors and warns key indicators in the medical service process, such as diagnosis accuracy, surgery complication rates, and adverse drug reaction rates, to ensure medical quality and safety.

[0013] Further, it also includes a medical insurance settlement management module that interfaces with the information systems of medical insurance departments to automate medical insurance payments, reimbursement audits, and cost control.

[0014] Further, the system adopts a cloud computing architecture for deployment, with high scalability and flexibility, and can dynamically adjust computing resources and storage resources according to the business growth needs of medical institutions.

[0015] Further, it has a data security protection mechanism, including firewall, intrusion detection system, data encryption and other technologies, to prevent medical data leakage and malicious attacks.

[0016] Compared with the prior art, the beneficial effects of the present application are: 1. The multi-factor identity verification technology applied in the user management module ensures fast and accurate identity verification of medical staff and patients, reduces login time, and enables medical staff to quickly enter a working state. The intelligent scheduling algorithm used in the medical service process management module accurately plans the patient's treatment path, greatly shortening the patient's waiting time. For example, through comparison before and after the implementation of the system in a certain hospital, the average waiting time of patients is shortened, greatly improving the efficiency of outpatient services. In hospital management, the automatic allocation of beds improves the utilization rate of beds and optimizes the hospitalization process.

[0017] The remote medical module breaks down geographical restrictions, and patients in remote areas can obtain expert diagnosis and treatment services in a timely manner, avoiding long-distance travel and saving medical time costs. For example, through the system, a remote mountainous area conducted multiple remote consultations with a large city's third-level hospital, effectively solving the diagnosis problems of most difficult diseases in the local area, and greatly improving the accessibility of medical services.

[0018] 2. Ensure the security and integrity of medical data The medical information storage module is built based on blockchain technology, with distributed storage and non-tamperability, ensuring the security and integrity of medical data. Taking patient medical records as an example, from the initial treatment record to subsequent diagnosis and treatment information, the whole process can be traced and cannot be illegally modified, providing a reliable data basis for medical dispute handling, medical research, etc. In a medical dispute case, the system saved the patient's medical record data, clearly presented the diagnosis and treatment process, quickly and clearly identified the responsibility, and efficiently solved the dispute.

[0019] 3. Optimize medical decision-making and management The data analysis and decision support module uses machine learning algorithms to deeply mine massive medical data, accurately predicts disease trends, helps medical institutions to reserve medicines and deploy medical staff in advance, and reasonably plans medical resources. Before the arrival of the flu season in a certain area, the system accurately predicted the peak of the flu, and the local hospital increased the inventory of related medicines and dispatched more medical staff based on the prediction results, effectively responding to the flu epidemic and ensuring the quality of medical services.

[0020] 4. Promote medical resource sharing and collaboration The system is deployed by using a cloud computing architecture, has strong expansibility, can dynamically adjust resources according to the business volume of a medical institution, reduces operation cost, and can realize medical resource sharing, such as sharing medical equipment reservation information and expert clinic information, by the system of multiple medical institutions, thereby improving resource utilization rate. For example, multiple hospitals in a region share high-end medical equipment through the system, the idle rate of the equipment is reduced, and resource waste caused by repeated purchase of equipment is avoided.

[0021] The above description is only a summary of the technical solutions of the present application. In order to enable the technical means of the present application to be more clearly understood and implemented according to the content of the specification, and in order to enable the above and other purposes, characteristics and advantages of the present application to be more apparent and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The system flowchart of the present embodiment. DETAILED DESCRIPTION

[0023] The present application will be further described below in combination with the accompanying drawings and specific embodiments. It should be noted that the embodiments described below or the technical features thereof can be combined with each other to form new embodiments without conflict.

[0024] It should be noted that when a component is referred to as being “fixed” to another component, it can be directly on the other component or there can be a middle component. When a component is referred to as being “connected” to another component, it can be directly connected to the other component or there can be a middle component. When a component is referred to as being “disposed” on another component, it can be directly disposed on the other component or there can be a middle component. The terms “vertical”, “horizontal”, “left”, “right” and the like used herein are for illustrative purposes only.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0026] Taking a certain third-grade hospital as a specific implementation scenario, the present medical and health management system is deployed on the information center server of the hospital, uses a cloud computing architecture, rents an elastic computing service and an object storage service of Aliyun, so as to meet the huge business data processing and storage requirements of the hospital.

[0027] Taking a certain third-grade hospital as a specific implementation scenario, the medical and health management system is deployed on the information center server of the hospital, adopts a cloud computing architecture, and rents an elastic computing service and an object storage service of Ali Cloud to meet the huge business data processing and storage requirements of the hospital. (I) User management module implementation The hospital assigns account numbers to medical staff, patients, and management personnel. Medical staff log in to the system using multi-factor identity verification methods such as face recognition + dynamic SMS password. The system assigns different permissions to medical staff based on their titles, departments, and work content, such as chief physicians who can view and modify patient medical records, and ordinary nurses who can only view some basic nursing-related medical information. Patients register an account through a mobile phone APP and complete identity verification using an ID number + SMS verification code. They can view their test reports and make appointments on the APP. Based on blockchain technology, the medical information storage module is built and connected with the hospital's HIS (Hospital Information System), LIS (Laboratory Information System), and PACS (Picture Archiving and Communication System). After seeing a doctor, patient Li's outpatient medical records, blood test reports, and CT images are automatically uploaded to the system and stored in the distributed nodes of the blockchain. Each data block contains a timestamp and a hash value to ensure data integrity. (III) Medical service process management module implementation Patient Zhang makes an appointment through the system and chooses a cardiologist. The system uses an intelligent scheduling algorithm to consider factors such as the doctor's schedule, the current number of patients waiting, and the use of the examination room to assign a specific appointment time for Zhang. During the appointment, the doctor reviews Zhang's medical history through the system and issues a test order and a prescription. For inpatient management, the system automatically assigns a hospital bed to patients who need to be hospitalized based on the use of the hospital bed and notifies the relevant department to prepare. (IV) Data analysis and decision support module implementation The system collects data on diabetic patients from the past year and uses machine learning algorithms to analyze information such as age, gender, blood glucose levels, and complications to predict the hospitalization trends of diabetic patients in the next three months, providing decision-making support for the hospital to prepare medicines and arrange medical staff schedules in advance. (V) Remote medical module implementation Remote patient Wang has a difficult medical condition, and the local hospital uses the remote medical module of the system to consult with experts from a third-grade hospital. The system connects to Wang's electrocardiograph, blood pressure meter, and other devices, transmits data in real time, and experts can view the patient's condition through high-definition video and make a diagnosis and provide treatment recommendations. (VI) Medical quality monitoring module implementation The system monitors the surgical infection rates of various departments in the hospital in real time. When the surgical infection rate of a department exceeds the set threshold (such as 1.5%), the system automatically issues an early warning to remind the department head to investigate the cause and make corrections. (VII) Implementation of the Medical Insurance Settlement Management Module When patient Zhao settled his bill after being discharged from the hospital, the system automatically connected his medical expense information with the medical insurance department system to calculate the medical insurance reimbursement amount and the out-of-pocket amount. The patient only needed to pay the out-of-pocket portion, which greatly shortened the settlement time.

[0028] (1) Verification process and steps System deployment and initialization: Complete the deployment of the system server in the hospital information center, import the hospital's existing basic data, and complete the parameter configuration and initialization of each module. Functional testing User Management Module: 100 medical staff and 200 patients were randomly selected for identity verification testing, with the number of successful and failed verifications recorded to verify the accuracy of permission allocation. Medical Information Storage Module: 1,000 different types of medical data (including medical records, test reports, and images) were uploaded and stored to verify the integrity and accuracy of the data storage. The correctness of the data hash value was checked using a blockchain browser. Medical service process management module: simulates 1,000 appointment registration, outpatient treatment, hospitalization management and other processes, records the operation time and whether the process is smooth for each link, and counts the optimization of patient waiting time by the intelligent scheduling algorithm. Data analysis and decision support module: Input the hospital's medical data from the past two years, run the machine learning algorithm, compare the predicted results with the actual situation, and evaluate the accuracy of the prediction. Telemedicine module: 100 remote consultation simulation tests were conducted between the hospital and three hospitals in remote areas, recording the clarity of video transmission, data transmission delay time and accuracy. Medical quality monitoring module: artificially set some abnormal data to trigger the early warning function of the monitoring module to check whether the early warning is timely and accurate. Medical insurance settlement management module: 50 patients with different medical insurance types were selected for settlement testing, and the reimbursement amount calculated by the system was compared with the actual reimbursement amount by the medical insurance department to verify the accuracy of the settlement. Performance testing: Under high system concurrency conditions (simulating 500 people operating online at the same time), the system's response time, throughput, and server resource usage are tested to ensure system stability and efficiency. Security testing: Use professional security testing tools to scan for vulnerabilities and conduct penetration tests on the system to check whether security mechanisms such as data encryption and access control are effective. (2) Verification data User Management Module: 99.8% success rate for healthcare professional authentication, 99.5% success rate for patient authentication, and 100% accuracy rate for permission distribution. Medical Information Storage Module: 1000 medical data were all accurately stored, blockchain hash value verification was correct, and no data loss or tampering occurred. Medical Service Process Management Module: The average waiting time for patients was reduced from 60 minutes to 30 minutes, and the process smoothness rate reached 99.2%. Data Analysis and Decision Support Module: The prediction accuracy rate for the admission trend of diabetic patients reached 85%. Telemedicine Module: The video transmission clarity compliance rate was 100%, the average data transmission delay was 0.3 seconds, and the accuracy rate was 100%. Medical Quality Monitoring Module: The timely warning rate was 100%, and the accuracy rate was 100%. Medical Insurance Settlement Management Module: The error rate between the system calculated reimbursement amount and the actual reimbursement amount from the medical insurance department was 0. Performance Test: Under high concurrency conditions, the average response time of the system was less than 1.5 seconds, the throughput reached 100 requests per second, and the CPU and memory usage of the server were within a reasonable range. Security Test: No serious security vulnerabilities were found, and the data encryption and access control mechanisms effectively resisted simulated attacks.

[0029] The above embodiments are only preferred embodiments of the present application, and cannot limit the scope of protection of the present application. Any non-substantial changes and substitutions made by those skilled in the art based on the present application are within the scope of the present application.

Claims

1. A medical and health management system, characterized in that: include: User management module, used for identity identification, authority allocation and information management of various users of the system, including but not limited to medical staff, patients, and managers; Medical information storage module, used to store medical-related data, including patients' medical records, diagnostic records, test reports, imaging data, as well as drug information, medical device information, etc.; The medical service process management module covers the information management and scheduling of the entire medical service process, including appointment registration, outpatient treatment, hospitalization management, surgery arrangement, and discharge settlement; The data analysis and decision support module mines and analyzes the data in the medical information storage module to provide data support and decision-making suggestions for medical institutions' management decisions, medical quality assessment, resource allocation optimization, etc. The telemedicine module supports telemedicine services such as remote consultation, remote diagnosis, and remote education, enabling cross-regional sharing of medical resources.

2. The medical and health management system according to claim 1, characterized in that: The user management module adopts multi-factor authentication technology, combined with biometrics (such as fingerprint recognition, face recognition), dynamic passwords, etc., to ensure the security and accuracy of user identity.

3. The medical and health management system according to claim 1, characterized in that: The medical information storage module is built based on blockchain technology to achieve distributed storage, non-tamperability and traceability of medical data, thereby ensuring the security and integrity of medical data.

4. The medical and health management system according to claim 1, characterized in that: The medical service process management module uses an intelligent scheduling algorithm to automatically optimize the medical service process based on factors such as the patient's condition, medical staff scheduling, and medical resource usage, thereby reducing patient waiting time and improving medical service efficiency.

5. The medical and health management system according to claim 1, characterized in that: The data analysis and decision support module uses machine learning algorithms to perform real-time analysis of medical data, predict disease epidemic trends, patient readmission risks, etc., and provide personalized medical decision-making recommendations.

6. The medical and health management system according to claim 1, characterized in that: The telemedicine module has high-definition video transmission and real-time data interaction functions, supports data access of multiple medical devices, and ensures the quality and accuracy of telemedicine services.

7. The medical and health management system according to claim 1, characterized in that: It also includes a medical quality monitoring module, which conducts real-time monitoring and early warning of key indicators in the medical service process, such as diagnostic accuracy, surgical complication rate, and adverse drug reaction rate, to ensure medical quality and safety.

8. The medical and health management system according to claim 1, characterized in that: It also includes a medical insurance settlement management module, which connects to the medical insurance department's information system to achieve automatic settlement, reimbursement review and cost control of medical insurance expenses.

9. The medical and health management system according to claim 1, characterized in that: The system is deployed using a cloud computing architecture, which is highly scalable and flexible, and can dynamically adjust computing and storage resources according to the business growth needs of medical institutions.

10. The medical and health management system according to claim 1, characterized in that: It has data security protection mechanisms, including firewalls, intrusion detection systems, data encryption and other technologies to prevent medical data leakage and malicious attacks.

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