Distributed medical management and control system for plateau alpine region

Abstract

The invention discloses a distributed medical management and control method and system for a plateau alpine region, and the system is designed according to the specific environmental conditions of the plateau alpine region, comprises a health data collection module, a health station module, a doctor seeing module and an accounting analysis module, and integrally aims at providing a set of comprehensive and integrated medical management solution. Through the mutually associated modules, the system can effectively realize the optimal configuration and emergency response of medical resources, and ensure the health and safety of employees in an extreme environment.

Description

Technical Field

[0001] The present invention relates to the field of medical management and control technology, and in particular to a decentralized medical management and control system for high altitude and cold regions. Background Art

[0002] The application of the medical and health big data service platform in engineering projects aims to improve the health management and safety of project workers. By integrating medical records from project clinics, employee health monitoring data, and related medical and treatment information, the platform can achieve real-time monitoring and analysis of the health status of workers. Using this data, the platform can predict potential health risks and provide preventive medical advice, thereby optimizing the human resource management of engineering projects and reducing work interruptions caused by health problems.

[0003] Although the medical and health big data service platform has brought significant benefits to the project, it still faces a series of challenges in its implementation in high-altitude and cold regions. The severe weather and unstable network environment unique to high-altitude and cold regions have seriously affected the efficiency of data collection and transmission, resulting in untimely updates of health data and affecting the timeliness of decision-making. In addition, medical resources in high-altitude and cold regions are scarce, and there is limited support for emergency medical response and professional health analysis, which increases the dependence and complexity of the platform in actual operations, especially in terms of the application effect of maintaining the health and safety of staff.

[0004] Existing technologies have the following major shortcomings in the field of medical management in high altitude and cold regions, which limit their effectiveness and efficiency in extreme environments:

[0005] Poor environmental adaptability: Existing technologies are usually not designed specifically for extreme conditions in high-altitude and cold regions, such as low oxygen, low air pressure, and large temperature differences. This results in reduced stability and accuracy of equipment and systems, and is unable to meet medical needs in special environments.

[0006] 2. Insufficient data integration: Existing medical management systems often have information island problems. Data sharing between various parts such as health data collection, medical resource management, medical treatment process and cost control is insufficient, resulting in unreasonable resource allocation and delayed decision-making.

[0007] 3. Insufficient response speed and accuracy: The lack of effective data analysis and prediction mechanisms makes the existing system not respond promptly or accurately enough when dealing with sudden health problems, such as altitude sickness, and cannot effectively prevent and deal with health risks.

[0008] 4. Unsatisfactory cost control and resource optimization: Existing technologies often lack automation and intelligent means in the management of drugs and medical devices, leading to problems such as waste of resources, excessive costs, and drug expiration.

[0009] 5. Patient safety and medical quality issues: The lack of intelligent drug interaction detection systems and medical diagnostic support may lead to adverse drug reactions and diagnostic errors, affecting patient treatment outcomes and safety.

[0010] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0011] The purpose of the present invention is to provide a decentralized medical management and control system for high altitude and cold regions to solve the problems existing in the prior art.

[0012] In order to achieve the above object, the present invention adopts the following technical solutions:

[0013] The present invention provides a decentralized medical management and control system for high-altitude and cold regions, including a health data collection module, a clinic module, a medical consultation module, and a calculation and analysis module; wherein:

[0014] The health data collection module is not only responsible for collecting employees' daily physical examination reports and health data obtained through monitoring by smart devices, but also integrates employees' living habits information; by analyzing these data through algorithms, the module can predict potential health risks and generate personalized health improvement suggestions;

[0015] The health clinic module is used for the management of medicines and medical devices. This module receives information provided by the health data collection module and distributes corresponding medicines and medical devices according to the health status and medical needs of employees. At the same time, it also provides emergency medical response and basic medical training;

[0016] The consultation module improves the consistency and efficiency of treatment by maintaining and managing consultation forms and detailed consultation records, and manages the consultation process of employees, including creating and maintaining consultation forms, and recording in detail the diagnosis and treatment information during the consultation process;

[0017] The accounting and analysis module is used to monitor and analyze the consumption of medicines and medical devices; by evaluating consumption trends and cost-effectiveness, it helps management formulate more scientific procurement and use strategies, optimize resource allocation, thereby reducing costs and improving service quality.

[0018] Furthermore, the health data collection module uses the environmental adaptability score E score =w1×O2+w2×P+w3×T is used to evaluate the employees' adaptability to the high-altitude and cold environment, where O2, P and T represent blood oxygen saturation, air pressure and temperature respectively, and w1, w2, w3 are weight factors.

[0019] Furthermore, the health data collection module inputs the collected data into the random forest model, and the random forest algorithm is applied to prediction and risk assessment to improve the prediction accuracy and early identification capability of employee health risks; specifically as follows:

[0020] a) Model input

[0021] The input of the random forest model includes employees’ physical examination data and lifestyle information:

[0022] Physical examination data: covering blood pressure, heart rate, and blood oxygen saturation, which are collected by medical testing equipment during regular health examinations;

[0023] Lifestyle information: including employees’ eating habits, sleep quality, and daily physical activity, which are automatically recorded through smart watches or other health tracking apps, and supplemented by employees manually entering information through health apps;

[0024] b) Model output

[0025] The output of the model is the employee’s health risk ratings, which predict potential health issues based on the analyzed data and categorize the risk level as low, medium, or high;

[0026] c) Output result application

[0027] Personalized health management recommendations: Provide customized health management and intervention recommendations based on risk ratings;

[0028] Early warning system: The system can identify health risks at an early stage, thereby initiating preventive measures to reduce the incidence of health problems;

[0029] d) Model building

[0030] Feature selection: Identify the most predictive indicators from a large amount of health data through feature importance analysis;

[0031] Data preprocessing: missing value filling and data normalization;

[0032] Training the model: The model is trained using the random forest algorithm, which builds multiple decision trees and aggregates the results between them to improve the accuracy and stability of predictions. Model training involves selecting the optimal number and depth of trees, as well as other related hyperparameters, using grid search.

[0033] Validation: Use cross-validation methods to test the accuracy and generalization ability of the model to ensure that the performance of the model on new data is consistent with that during training, thereby verifying the effectiveness of the model.

[0034] Furthermore, the drug management in the clinic module includes the purchase, storage, distribution and safe use of drugs; to ensure that all drugs are stored in accordance with the prescribed standards, track the inventory level of drugs, replenish them in time, and manage drug use records to ensure reasonable and safe drug use; the system automatically tracks drug batches and expiration dates through the intelligent drug management system, and implements the first expired first used rule to manage drug inventory, ensure the effective use of drugs, and reduce the waste caused by expired drugs;

[0035] Medical device management includes the procurement, maintenance, storage and use of all necessary medical devices; systematic monitoring of the status of devices to ensure that all equipment is in good working condition, and timely replacement of damaged or expired equipment.

[0036] Furthermore, the medical consultation module supports the complete functions of electronic medical records, including the creation, access, update and confidentiality management of medical records; allows doctors to access medical records at any location through mobile devices, thereby improving the flexibility and efficiency of medical consultations; adds an intelligent diagnosis support system to analyze historical medical consultation data through machine learning technology to assist doctors in making more accurate diagnosis and treatment decisions; the medical consultation module also integrates an online appointment system, allowing employees to make appointments for medical services through mobile phones or other devices, thereby optimizing the allocation of medical resources.

[0037] Furthermore, the accounting analysis module supports advanced algorithms to analyze medical cost-effectiveness, evaluate the financial impact of medical activities, and provide suggestions for cost reduction and resource optimization; cost-effectiveness analysis is performed through formula Carry out, where B benefits is the economic benefit brought by using the system, C costs It is the total cost of system operation; an automatic report generator is added to provide management with regular medical consumption reports and budget execution status, helping decision-makers make more informed financial decisions; in addition, the module also implements an automated billing system to automatically process and record bills for all medical services, reduce administrative burdens, and improve work efficiency.

[0038] Furthermore, the accounting and analysis module analyzes the cost and consumption of medical services to help management optimize procurement strategies and resource allocation; this module uses data collected from other modules to evaluate the cost-effectiveness of medical activities, generate regular consumption reports and budget execution, thereby improving the overall efficiency and quality of medical services.

[0039] Furthermore, the accounting analysis module also supports the use of genetic algorithms for resource optimization. The model construction, objective function, constraints, algorithm details and implementation steps are described in detail as follows:

[0040] a) Objective function and constraints

[0041] (1) Objective function:

[0042] The goal is to minimize the total cost, which can be expressed as:

[0043] Minimize Z=C p ·x p +C s ·x s +C e ·x e

[0044] Among them C p ,C s and C e are the purchase cost, storage cost and expiration loss cost, and x p ,x s , and x e are the corresponding decision variables;

[0045] (2) Constraints:

[0046] ① Inventory demand is met:

[0047] x s ≥D t

[0048] Here x s is the inventory, D t It is to forecast demand and ensure that inventory can meet future demand;

[0049] ②Inventory capacity limit:

[0050] x s ≤M

[0051] Where M is the maximum inventory capacity;

[0052] ③Budget constraints:

[0053] C p ·x p +C s ·x s ≤B

[0054] B represents the budget cap, which ensures that the total cost does not exceed the budget;

[0055] b) Genetic Algorithm Model

[0056] (1) Encoding method:

[0057] Real number encoding method, each individual is represented by a real number vector, and each element in the vector corresponds to a decision variable;

[0058] (2) Initialize the population:

[0059] The initial population is randomly generated, and each individual represents a possible inventory strategy to ensure the diversity of the population:

[0060] (3) Fitness function:

[0061] The fitness function is used to evaluate the quality of an individual and is defined as:

[0062]

[0063] Z(x) is the objective function value. The larger the value of the fitness function, the lower the cost and the better the individual.

[0064] (4) Genetic manipulation:

[0065] Selection: Tournament selection is used to randomly select several individuals to compare their fitness and select the one with the highest fitness to enter the next generation;

[0066] Crossover: Use single-point crossover to randomly select crossover points and exchange some genes of parent individuals;

[0067] Mutation: Randomly change certain genes of individuals with a lower probability to increase the diversity of the population;

[0068] c) Solution and implementation

[0069] ①Iterative evolution:

[0070] Apply selection, crossover and mutation operations to the current population to generate a new population;

[0071] Evaluate the fitness of each individual in the new population;

[0072] Repeat this process until the termination condition is met;

[0073] ② Optimal solution extraction:

[0074] Select the individual with the highest fitness from the final population as the optimal solution;

[0075] ③Implementation suggestions:

[0076] Adjust the actual purchasing and inventory management strategies according to the optimal configuration solution found by the genetic algorithm;

[0077] Through the above detailed steps, genetic algorithms can effectively solve the problem of medical resource allocation, ensure the optimal use of resources, reduce costs and improve service quality; in addition, the flexibility and adaptability of the algorithm enable it to cope with changing needs and environments, making it an ideal tool for managing complex systems.

[0078] By adopting the above technical solution, the present invention has the following beneficial effects:

[0079] Improve environmental adaptability: A medical management system specially adapted to high altitude and cold regions has been designed. By adding special physiological monitoring items and improving equipment design, the stability and accuracy of the system in extreme environments are ensured.

[0080] Achieve high degree of data integration: Through the integrated medical management platform, achieve seamless connection between health data, drug and medical device management, medical treatment and cost accounting, optimize resource allocation and accelerate the decision-making process.

[0081] Improve response speed and accuracy: Use advanced algorithms to conduct real-time analysis and risk prediction of collected health data, and promptly detect and deal with health problems, especially emergencies such as altitude sickness.

[0082] Optimize cost control and resource management: Introduce automated and intelligent management tools, such as smart drug management systems and automated billing systems, to reduce resource waste, lower operating costs, and improve resource utilization efficiency.

[0083] Enhance patient safety and improve medical quality: Introduce drug interaction checking functions and intelligent diagnosis support systems to reduce adverse drug reactions and diagnostic errors, and improve medical service quality and patient satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0085] Figure 1 This is a system architecture diagram of the decentralized medical management and control system for high-altitude and cold regions proposed by the present invention. DETAILED DESCRIPTION

[0086] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0088] Combination Figure 1As shown, this embodiment provides a decentralized medical management and control system for high-altitude and cold regions. The system is designed for the unique environmental conditions in high-altitude and cold regions, and includes a health data collection module, a clinic module, a medical consultation module, and an accounting and analysis module. The overall purpose is to provide a comprehensive and integrated medical management solution. Through these interrelated modules, the system can effectively achieve the optimal allocation of medical resources and emergency response, ensuring the health and safety of employees in extreme environments.

[0089] The health data collection module is not only responsible for collecting employees' daily physical examination reports and health data obtained through monitoring by smart devices, but also integrates information on employees' living habits, such as diet, sleep, and physical activity. By analyzing this data through advanced algorithms, the module is able to predict potential health risks and generate personalized health improvement suggestions. In response to health problems unique to high altitude and cold weather, such as altitude sickness, the physical examination items have specially added blood oxygen saturation detection and heart function assessment, as well as the use of smart wearable devices to monitor employees' physiological indicators and environmental adaptability in real time, thereby ensuring timely medical intervention. Each employee's health data establishes a separate health file and is also analyzed through data models to detect abnormalities and health risks early.

[0090] The health data collection module is the data foundation of the system. It collects and analyzes employees' health data and provides support and data foundation for other modules. Real-time physiological data and lifestyle information collected by smart devices can predict health risks and generate improvement suggestions. This information is crucial for the health center module and the medical consultation module when conducting medical interventions and formulating treatment plans.

[0091] Each employee's health data is individually recorded in a health file and analyzed through data models to detect abnormalities and health risks at an early stage. score =w1×O2+w2×P+w3×T is used to evaluate the employees' adaptability to the high-altitude and cold environment, where O2, P and T represent blood oxygen saturation, air pressure and temperature respectively, and w1, w2, w3 are weight factors.

[0092] The data obtained from the health data collection module is further input into the random forest model, and the random forest algorithm is applied to the prediction and risk assessment modules to improve the prediction accuracy and early identification capabilities of employee health risks. The following is a detailed description:

[0093] a) Model input

[0094] The input of the random forest model includes employees’ physical examination data and lifestyle information:

[0095] Physical examination data: covers blood pressure, heart rate, blood oxygen saturation, etc. These data are collected during regular health examinations through medical testing equipment such as sphygmomanometers and pulse oximeters.

[0096] Lifestyle information: including employees’ eating habits, sleep quality, and daily physical activities. These data are mainly recorded automatically through smart watches or other health tracking applications, and employees can manually enter supplementary information through health applications.

[0097] b) Model output

[0098] The output of the model is health risk ratings for employees, which predict potential health issues based on the analyzed data and categorize the risk level as low, medium, or high.

[0099] c) Output result application

[0100] Personalized health management recommendations: Provide customized health management and intervention recommendations based on risk ratings, such as diet adjustments, exercise plans, or regular medical examinations.

[0101] Early warning systems: Systems that can identify health risks, such as high blood pressure or a tendency toward heart disease, early on, thereby initiating preventive measures to reduce the incidence of health problems.

[0102] d) Model building

[0103] Feature selection: Through feature importance analysis, the most predictive indicators are determined from a large amount of health data, such as historical fluctuations in blood pressure and heart rate, sleep quality scores, etc.

[0104] Data preprocessing: missing value processing and filling, data normalization

[0105] Training Model: The model is trained using the Random Forest algorithm, which builds multiple decision trees and aggregates results between them to improve the accuracy and stability of predictions. Model training involves choosing the optimal number and depth of trees, as well as other relevant hyperparameters, using grid search.

[0106] Validation: Use cross-validation methods to test the accuracy and generalization ability of the model to ensure that the performance of the model on new data is consistent with that during training, thereby verifying the effectiveness of the model.

[0107] The health center module includes the management of medicines and medical devices. This module receives information provided by the health data collection module and distributes corresponding medicines and medical devices according to the health status and medical needs of employees. At the same time, it also provides emergency medical response and basic medical training, which are particularly important in high-altitude and cold areas.

[0108] Drug management focuses on the procurement, storage, distribution and safe use of drugs. The management system ensures that all drugs are stored according to the prescribed standards, tracks the inventory level of drugs, replenishes them in time, and manages drug use records to ensure reasonable and safe drug use. The system automatically tracks drug batches and expiration dates through the intelligent drug management system, and implements the rule of first expired, first used to manage drug inventory, ensuring the effective use of drugs and reducing the waste caused by expired drugs.

[0109] Medical device management includes the purchase, maintenance, storage and use of all necessary medical devices. The system monitors the status of the devices to ensure that all equipment is in good working condition and that damaged or expired equipment is replaced in a timely manner.

[0110] The health clinic module also expands emergency medical response and basic medical training services, such as primary care for CPR and altitude sickness. In addition, the newly added drug interaction check function automatically alerts doctors and nurses to potential adverse drug reactions and interactions, improving the safety of drug use. The module also provides mobile medical services, providing on-site health checks through portable medical devices to ensure medical coverage in remote work areas.

[0111] The consultation module improves the consistency and efficiency of treatment by maintaining and managing consultation forms and detailed consultation records, and manages the consultation process of employees, including creating and maintaining consultation forms, and recording in detail the diagnosis and treatment information during the consultation process. It supports the full functionality of electronic medical records, including the creation, access, update, and confidentiality management of medical records. Doctors can also access medical records from any location through mobile devices, improving the flexibility and efficiency of medical consultations. The intelligent diagnosis support system is added to analyze historical consultation data through machine learning technology to assist doctors in making more accurate diagnosis and treatment decisions. The consultation module also integrates an online appointment system, allowing employees to make appointments for medical services through mobile phones or other devices to optimize the allocation of medical resources.

[0112] The consultation module uses the data obtained from the health data collection module to help doctors better understand the health status of employees and develop personalized treatment plans. The intelligent diagnosis support system uses historical data to assist doctors in making diagnostic decisions, while the online appointment system optimizes resource allocation and improves service quality.

[0113] The accounting analysis module monitors and analyzes the consumption of drugs and medical devices, and conducts detailed monitoring and analysis of the use of drugs and medical devices. By evaluating consumption trends and cost-effectiveness, it helps management formulate more scientific procurement and use strategies, optimize resource allocation, thereby reducing costs and improving service quality. This module now supports advanced algorithms to analyze medical cost-effectiveness, evaluate the financial impact of medical activities, and provide suggestions for cost reduction and resource optimization. Cost-effectiveness analysis uses formulas Carry out, where B benefitsis the economic benefit brought by using the system, C costs It is the total cost of running the system. An automatic report generator is added to provide management with regular medical consumption reports and budget execution, helping decision-makers make more informed financial decisions. In addition, the module also implements an automated billing system to automatically process and record bills for all medical services, reducing administrative burdens and improving work efficiency.

[0114] Analyze the cost and consumption of medical services to help management optimize procurement strategies and resource allocation. This module uses data collected from other modules to evaluate the cost-effectiveness of medical activities, generate regular consumption reports and budget execution, and thus improve the overall efficiency and quality of medical services.

[0115] At the same time, the system also supports the use of genetic algorithms for resource optimization. The detailed description of model construction, objective function, constraints, algorithm details and implementation steps are as follows:

[0116] a) Objective function and constraints

[0117] (1) Objective function:

[0118] The goal is to minimize the total cost, which can be expressed as:

[0119] Minimize Z=C p ·x p +C s ·x s +C e ·x e

[0120] Among them C p ,C s and C e are the purchase cost, storage cost and expiration loss cost, and x p ,x s , and x e are the corresponding decision variables respectively.

[0121] (2) Constraints:

[0122] 1. Inventory requirements are met:

[0123] x s ≥D t

[0124] Here x s is the inventory, D t It is to predict demand and ensure that inventory can meet future demand.

[0125] 2. Inventory capacity limit:

[0126] x s≤M

[0127] Where M is the maximum inventory capacity.

[0128] 3. Budget constraints:

[0129] C p ·x p +C s ·x s ≤B

[0130] B represents the budget cap, which ensures that the total cost does not exceed the budget.

[0131] b) Genetic Algorithm Model

[0132] (1) Encoding method

[0133] In real number encoding, each individual is represented as a real number vector, and each element in the vector corresponds to a decision variable, such as purchase quantity, storage quantity, etc.

[0134] (2) Initialize the population

[0135] The initial population is randomly generated, and each individual represents a possible inventory strategy to ensure the diversity of the population.

[0136] (3) Fitness function

[0137] The fitness function is used to evaluate the quality of an individual and is defined as:

[0138]

[0139] Z(x) is the objective function value. The larger the value of the fitness function, the lower the cost and the better the individual.

[0140] (4) Genetic manipulation

[0141] Selection: Use tournament selection to randomly select several individuals to compare their fitness and select the ones with the highest fitness to enter the next generation.

[0142] Crossover: Use single-point crossover to randomly select the crossover point and exchange some of the genes of the parent individuals.

[0143] Mutation: Randomly change certain genes of an individual with a lower probability to increase the diversity of the population.

[0144] c) Solution and implementation

[0145] 1. Iterative Evolution:

[0146] Apply selection, crossover, and mutation operations to the current population to generate a new population.

[0147] Evaluate the fitness of each individual in the new population.

[0148] This process is repeated until the termination condition is met, such as reaching the maximum number of iterations or the fitness is high enough.

[0149] 2. Optimal solution extraction:

[0150] The individual with the highest fitness is selected from the final population as the optimal solution.

[0151] 3. Implementation suggestions:

[0152] Adjust the actual purchasing and inventory management strategies according to the optimal configuration solution found by the genetic algorithm.

[0153] Through these detailed steps, genetic algorithms can effectively solve the problem of medical resource allocation, ensure the optimal use of resources, reduce costs and improve service quality. In addition, the flexibility and adaptability of the algorithm enable it to cope with changing needs and environments, making it an ideal tool for managing complex systems.

[0154] In summary, compared with the prior art, the present invention has the following significant technical advantages and beneficial effects:

[0155] 1. Targeted design:

[0156] This system is designed for the special environmental conditions in high-altitude and cold areas, solving the problem that conventional medical systems in existing technologies cannot adapt to extreme environments. In particular, targeted physical examination items such as blood oxygen saturation detection and heart function assessment have been added, as well as real-time monitoring of employees' physiological indicators through smart wearable devices. These designs have significantly improved the ability of medical monitoring and emergency response in high-altitude and cold areas.

[0157] 2. Integrated management:

[0158] The system realizes the comprehensive integration of medical management processes, from health data collection, drug and medical device management, medical treatment to cost accounting analysis, and the data of each module is interconnected to form a closed-loop management. This integrated operation reduces redundancy between operations, improves processing speed and efficiency, and is significantly better than the data islands and resource waste caused by multiple independent system operations in existing technologies.

[0159] 3. Intelligent analysis and prediction:

[0160] By analyzing employees' health data through advanced algorithms, the system can predict potential health risks and generate personalized health improvement suggestions. This function solves the problems of insufficient data utilization and slow response in existing technologies, making medical intervention more timely and accurate, especially when dealing with high-risk health problems such as altitude sickness, which can greatly reduce the incidence of serious health events.

[0161] 4. Resource optimization and cost control:

[0162] The addition of the accounting and analysis module enables the system to conduct detailed monitoring and cost-effectiveness analysis of the use of drugs and medical devices, optimize resource allocation, and reduce costs. The system's automatic report generator and automated billing system provide management with accurate financial data and medical consumption reports, which helps to formulate scientific procurement strategies and financial decisions, significantly better than the manual or semi-automatic processing methods in existing technologies.

[0163] 5. Improve medical service quality and patient safety:

[0164] The drug interaction check function of the health clinic module can automatically warn doctors and nurses of potential adverse drug reactions and interactions, greatly improving the safety of drug use. In addition, the application of intelligent diagnosis support system and online appointment system not only improves the convenience and flexibility of medical treatment, but also ensures the continuity and efficiency of treatment, thereby improving patient satisfaction while ensuring high quality standards of medical services.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A decentralized medical management and control system for high altitude and cold regions, characterized in that: It includes health data collection module, clinic module, medical consultation module and accounting analysis module; among them, The health data collection module is not only responsible for collecting employees' daily physical examination reports and health data obtained through monitoring by smart devices, but also integrates employees' living habits information; by analyzing these data through algorithms, the module can predict potential health risks and generate personalized health improvement suggestions; The health clinic module is used for the management of medicines and medical devices. This module receives information provided by the health data collection module and distributes corresponding medicines and medical devices according to the health status and medical needs of employees. At the same time, it also provides emergency medical response and basic medical training; The consultation module improves the consistency and efficiency of treatment by maintaining and managing consultation forms and detailed consultation records, and manages the consultation process of employees, including creating and maintaining consultation forms, and recording in detail the diagnosis and treatment information during the consultation process; The accounting and analysis module is used to monitor and analyze the consumption of medicines and medical devices; by evaluating consumption trends and cost-effectiveness, it helps management formulate more scientific procurement and use strategies, optimize resource allocation, thereby reducing costs and improving service quality.

2. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The health data collection module uses the environmental adaptability score E score =w1×O2+w2×P+w3×T is used to evaluate the employees' adaptability to the high-altitude and cold environment, where O2, P and T represent blood oxygen saturation, air pressure and temperature respectively, and w1, w2, w3 are weight factors.

3. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The health data collection module inputs the collected data into the random forest model, and the random forest algorithm is applied to prediction and risk assessment to improve the prediction accuracy and early identification ability of employee health risks; the details are as follows: a) Model input The input of the random forest model includes employees’ physical examination data and lifestyle information: Physical examination data: covering blood pressure, heart rate, and blood oxygen saturation, which are collected by medical testing equipment during regular health examinations; Lifestyle information: including employees’ eating habits, sleep quality, and daily physical activity, which are automatically recorded through smart watches or other health tracking apps, and supplemented by employees manually entering information through health apps; b) Model output The output of the model is the employee’s health risk ratings, which predict potential health issues based on the analyzed data and categorize the risk level as low, medium, or high; c) Output result application Personalized health management recommendations: Provide customized health management and intervention recommendations based on risk ratings; Early warning system: The system can identify health risks at an early stage, thereby initiating preventive measures to reduce the incidence of health problems; d) Model building Feature selection: Identify the most predictive indicators from a large amount of health data through feature importance analysis; Data preprocessing: missing value filling and data normalization; Training the model: The model is trained using the random forest algorithm, which builds multiple decision trees and aggregates the results between them to improve the accuracy and stability of predictions. Model training involves selecting the optimal number and depth of trees, as well as other related hyperparameters, using grid search. Validation: Use cross-validation methods to test the accuracy and generalization ability of the model to ensure that the performance of the model on new data is consistent with that during training, thereby verifying the effectiveness of the model.

4. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The drug management in the clinic module includes the purchase, storage, distribution and safe use of drugs; to ensure that all drugs are stored in accordance with the prescribed standards, track the inventory level of drugs, replenish them in time, and manage drug use records to ensure reasonable and safe drug use; the system automatically tracks drug batches and expiration dates through the intelligent drug management system, and implements the rule of first expired first used to manage drug inventory, ensure the effective use of drugs, and reduce the waste caused by expired drugs; Medical device management includes the procurement, maintenance, storage and use of all necessary medical devices; systematic monitoring of the status of devices to ensure that all equipment is in good working condition, and timely replacement of damaged or expired equipment.

5. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The medical consultation module supports the complete functions of electronic medical records, including the creation, access, update and confidentiality management of medical records; it allows doctors to access medical records at any location through mobile devices, thereby improving the flexibility and efficiency of medical consultations; it adds an intelligent diagnosis support system to analyze historical medical consultation data through machine learning technology to assist doctors in making more accurate diagnosis and treatment decisions; the medical consultation module also integrates an online appointment system, allowing employees to make appointments for medical services through mobile phones or other devices, thereby optimizing the allocation of medical resources.

6. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The accounting analysis module supports advanced algorithms to analyze medical cost-effectiveness, evaluate the financial impact of medical activities, and provide suggestions for cost reduction and resource optimization; cost-effectiveness analysis is performed through formula Carry out, where B benefits is the economic benefit brought by using the system, C costs It is the total cost of system operation; an automatic report generator is added to provide management with regular medical consumption reports and budget execution status, helping decision-makers make more informed financial decisions; in addition, the module also implements an automated billing system to automatically process and record bills for all medical services, reduce administrative burdens, and improve work efficiency.

7. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The accounting and analysis module analyzes the cost and consumption of medical services to help management optimize procurement strategies and resource allocation; this module uses data collected from other modules to evaluate the cost-effectiveness of medical activities, generate regular consumption reports and budget execution, thereby improving the overall efficiency and quality of medical services.

8. The distributed medical management and control system for high altitude and cold regions according to claim 1 is characterized in that: The accounting analysis module also supports the use of genetic algorithms for resource optimization. The model construction, objective function, constraints, algorithm details and implementation steps are described in detail as follows: a) Objective function and constraints (1) Objective function: The goal is to minimize the total cost, which can be expressed as: Minimize Z=C p ·x p +C s ·x s +C e ·x e Among them C p ,C s and C e are the purchase cost, storage cost and expiration loss cost, and x p ,x s , and x e are the corresponding decision variables; (2) Constraints: ① Inventory demand is met: x s ≥D t Here x s is the inventory, D t It is to forecast demand and ensure that inventory can meet future demand; ②Inventory capacity limit: x s ≤M Where M is the maximum inventory capacity; ③Budget constraints: C p ·x p +C s ·x s ≤B B represents the budget cap, which ensures that the total cost does not exceed the budget; b) Genetic Algorithm Model (1) Encoding method: Real number encoding method, each individual is represented by a real number vector, and each element in the vector corresponds to a decision variable; (2) Initialize the population: The initial population is randomly generated, and each individual represents a possible inventory strategy to ensure the diversity of the population: (3) Fitness function: The fitness function is used to evaluate the quality of an individual and is defined as: Z(x) is the objective function value. The larger the value of the fitness function, the lower the cost and the better the individual. (4) Genetic manipulation: Selection: Tournament selection is used to randomly select several individuals to compare their fitness and select the one with the highest fitness to enter the next generation; Crossover: Use single-point crossover to randomly select crossover points and exchange some genes of parent individuals; Mutation: Randomly change certain genes of individuals with a lower probability to increase the diversity of the population; c) Solution and implementation ①Iterative evolution: Apply selection, crossover and mutation operations to the current population to generate a new population; Evaluate the fitness of each individual in the new population; Repeat this process until the termination condition is met; ② Optimal solution extraction: Select the individual with the highest fitness from the final population as the optimal solution; ③Implementation suggestions: Adjust the actual purchasing and inventory management strategies according to the optimal configuration solution found by the genetic algorithm; Through the above detailed steps, genetic algorithms can effectively solve the problem of medical resource allocation, ensure the optimal use of resources, reduce costs and improve service quality; in addition, the flexibility and adaptability of the algorithm enable it to cope with changing needs and environments, making it an ideal tool for managing complex systems.

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