Hospital outpatient emergency service system based on cloud server

Abstract

The invention discloses a hospital outpatient emergency service system based on a cloud server, and relates to the technical field of outpatient emergency services. The cloud data center is in communication connection with a medical data acquisition module, an abnormity identification module, an abnormity analysis module, an emergency early warning evaluation module, a medical care resource allocation module, a medical material management module and a mobile application module. According to the hospital outpatient service emergency service system based on the cloud server, potential emergency requirements or risk points are rapidly identified by monitoring medical material inventory, patient flow and medical staff working state data of all departments in real time, the emergency early warning module sends out an early warning signal, and the emergency early warning module sends out an early warning signal. According to the method and the system, the emergency response process of triggering replenishment reminding and deploying medical staff or medical supplies can be immediately started, so that the processing efficiency of hospital outpatient service in dealing with emergencies is remarkably improved, and delay and loss caused by information lag or untimely processing are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of outpatient emergency services, and in particular to a hospital outpatient emergency service system based on a cloud server. Background Art

[0002] With the population growth and people's increasing attention to health, the patient flow in hospital outpatient clinics will increase dramatically during peak visiting periods, emergencies or outbreaks of special diseases, which will put tremendous pressure on medical resources. In addition, the medical information of patients needs to be shared among various departments within the hospital. The use of hospital outpatient emergency services can effectively respond to emergencies, peak visiting periods, outbreaks of special diseases, etc., ensure that patients receive timely and effective medical services and establish a series of response measures and plans.

[0003] In the prior art, in the event of an emergency service incident, it is easy to have an unbalanced allocation of medical resources and a chaotic allocation of medical supplies, which leads to untimely emergency treatment and interference from shortages of medical supplies. Therefore, how to conduct a comprehensive analysis of the allocation of medical resources and medical supplies, and to give timely warnings of emergencies to ensure the timeliness of the outpatient emergency service process is a problem we need to solve. To this end, a hospital outpatient emergency service system based on a cloud server is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a hospital outpatient emergency service system based on a cloud server, including a cloud data center, the cloud data center is communicatively connected with a medical data acquisition module, an abnormality identification module, an abnormality analysis module, an emergency warning evaluation module, a medical care resource allocation module, a medical supplies management module and a mobile application module, wherein the modules are connected by electrical signals;

[0005] The medical data acquisition module is used to collect relevant medical data from all aspects of the hospital outpatient department, including the real-time number of patients in each department, the on-duty status of medical staff, and the inventory status of medical supplies, and pre-process the medical data;

[0006] The abnormality identification module monitors the emergency service status of the hospital outpatient department in real time based on the acquired medical data, detects and marks abnormal situations, discovers potential problems in advance, buys valuable time for emergency response, and reduces the negative impact of emergencies. Abnormal situations include overload of patients, insufficient medical resources, and shortage of medical supplies;

[0007] The abnormality analysis module is used to analyze the identified abnormal situations, clarify the urgency of each abnormal situation, and determine the corresponding response measures;

[0008] The emergency warning evaluation module comprehensively evaluates the severity of the abnormal situation based on the urgency analysis results of the abnormal situation and determines the corresponding warning level;

[0009] The medical resources allocation module allocates medical staff in the hospital according to the information of the emergency warning module and the warning evaluation module;

[0010] The medical supplies management module monitors the inventory of medical supplies in real time, analyzes the demand for supplies and the consumption in emergency events in combination with the warning results of the emergency warning module and the warning evaluation module, and allocates medical supplies;

[0011] The mobile application module provides mobile emergency service support for medical staff and managers, including information viewing, task reception and feedback, and provides communication and command functions in emergency situations.

[0012] Preferably, in the medical data acquisition module, the medical data collection process includes:

[0013] Collect relevant medical data from the hospital's electronic medical record system, hospital information system, laboratory information system, image archiving and communication system, including the real-time number of patients, the on-duty status of medical staff, the inventory status of medical supplies, and the use of equipment. The electronic medical record system collects and records the patient's detailed medical information, medical history, diagnosis results, etc., and the hospital information system obtains comprehensive information on hospital operations, management, and clinical aspects. The laboratory information system collects laboratory test results, sample information, etc., and the image archiving and communication system extracts, stores, and manages medical imaging data;

[0014] Preprocess the collected medical data to ensure the quality and availability of the data. The preprocessing steps include data cleaning, data conversion and data merging. Data cleaning can remove missing values, process outliers and remove duplicate data. Data conversion includes format conversion and encoding conversion to ensure that the data can be correctly understood and processed by the system. Data merging can integrate data from different sources to form a unified data view.

[0015] The pre-processed medical data is transmitted to the cloud data center, and the data is stored and archived in the data warehouse built in the cloud data center for subsequent analysis and use.

[0016] Preferably, in the anomaly identification module, the abnormal situation detection and marking process includes:

[0017] According to the historical data and operation standards of the hospital operation, abnormal thresholds are set for the real-time number of patients, the on-duty status of medical staff, and the inventory of medical supplies to determine the abnormal situations of overload of patients, insufficient medical resources, and shortage of medical supplies. Among them, the historical data of hospital operation is analyzed to determine the average number of patients and the peak number of patients in each department, and the overload abnormal threshold of the number of patients is set according to the hospital operation standards and actual service capabilities. The overload abnormal threshold is set to 1.5 times the average number of patients. The minimum number of medical staff required for each department in the daily operation of the hospital is evaluated, and the abnormal threshold of insufficient medical resources is set. The abnormal threshold of insufficient medical resources is set to 80% of the minimum number required for daily use. The historical consumption data and replenishment cycle of medical supplies are analyzed, and the abnormal threshold of shortage of medical supplies is set, which is triggered when the inventory level is lower than the safety stock;

[0018] Real-time monitoring of pre-processed medical data, comparing actual data with abnormal thresholds. When the actual data of the number of patients and medical supplies exceeds the abnormal threshold, the abnormal identification mechanism is triggered; when the actual data of medical resources is lower than the abnormal threshold, the abnormal identification mechanism is triggered;

[0019] Based on the real-time monitoring results, abnormal situations such as overload of patient numbers, insufficient medical resources, and shortage of medical supplies are identified, and the identified abnormal situations are marked, and information such as the abnormality type, occurrence time, and impact scope is recorded. The marked abnormal data is stored in the data warehouse for subsequent analysis and processing.

[0020] Preferably, in the abnormality analysis module, the analysis process of the urgency of the abnormality includes:

[0021] Based on the results of abnormal situation identification, further analysis is conducted on the identified abnormal situations of overload of patients, insufficient medical resources, and shortage of medical supplies to clarify the urgency of each abnormal situation;

[0022] According to the comparison result between the real-time number of patients and the set overload abnormal threshold, the patient number evaluation index is calculated, the degree of overload of the number of patients is analyzed, and the degree of overload is divided into mild, moderate and severe according to the patient number evaluation index;

[0023] Based on the comparison between the on-the-job status of medical staff and the set abnormal threshold of medical staff shortage, the medical resources evaluation index is calculated to analyze the shortage of medical resources. According to the medical resources evaluation index, the shortage degree is divided into mild, moderate and severe;

[0024] Based on the comparison results of the medical supplies inventory and the set shortage abnormality threshold, the medical supplies evaluation index is calculated to analyze the impact of the shortage of supplies. According to the medical supplies evaluation index, the impact of the shortage is divided into mild, moderate and severe;

[0025] For each abnormal situation, corresponding response measures are formulated according to the degree of urgency, including increasing medical staff, allocating supplies, optimizing medical treatment processes, strengthening patient management, and allocating resources according to the response measures.

[0026] Preferably, the calculation formula of the patient number evaluation index is:

[0027] ;

[0028] in, is the patient visit evaluation index, The real-time number of patients. Overload abnormal threshold, slight overload: , moderate overload: , heavy overload: ;

[0029] The calculation formula of the medical resources evaluation index is:

[0030] ;

[0031] in, is the medical resources evaluation index, is the number of medical staff currently on duty, Abnormal threshold for insufficient medical staff, mild shortage: , moderate shortage: , severe shortage: ;

[0032] The calculation formula of the medical supplies evaluation index is:

[0033] ;

[0034] in, is the medical supplies evaluation index. is the current inventory of medical supplies, The abnormal threshold is short, which has a slight impact on: , medium impact: , seriously affecting: .

[0035] Preferably, in the emergency warning evaluation module, the evaluation process of the severity of the abnormal situation includes:

[0036] Extract real-time data on the number of patients, the number of medical staff on duty, and the inventory of medical supplies to ensure the accuracy and completeness of the data, and obtain the number of patients evaluation index, medical resources evaluation index, and medical supplies evaluation index calculated based on the number of patients, the number of medical staff on duty, and the inventory of medical supplies;

[0037] The three evaluation indexes obtained were standardized and unified on the same scale for comparison and weighting, and weights were assigned to each evaluation index according to the hospital's operating strategy and resource allocation;

[0038] Combine the patient number evaluation index, medical resources evaluation index, and medical supplies evaluation index, and combine their respective weights to calculate the emergency warning evaluation coefficient and evaluate the severity of the abnormal situation;

[0039] According to the value of the emergency warning evaluation coefficient, warning levels of different severity levels are set, namely green warning level, yellow warning level, orange warning level and red warning level, and corresponding warning threshold ranges are set for each warning level, where the warning level increases from green to red, and the severity increases step by step;

[0040] An urgency analysis is conducted for each warning level, and based on the results of the urgency analysis, corresponding response measures are recommended. The response measures include increasing medical staff, allocating supplies, optimizing medical treatment processes, and strengthening patient management.

[0041] Preferably, the calculation formula of the emergency warning evaluation coefficient is:

[0042] ;

[0043] in, is the emergency warning evaluation coefficient, is the patient visit evaluation index, is the medical resources evaluation index, is the medical supplies evaluation index. , and They respectively represent the weights of the patient number evaluation index, medical resources evaluation index and medical supplies evaluation index. When all evaluation indices are close to 0, the numerator is close to 0 and the denominator is close to 1. Therefore, the emergency warning evaluation coefficient is close to 0, indicating that there is no abnormal situation. When any evaluation index increases, the numerator increases and the denominator also increases, but the numerator increases faster. Therefore, the emergency warning evaluation coefficient increases, indicating that the severity of the abnormal situation increases. Due to the increase in the denominator, the value of the emergency warning evaluation coefficient is limited to between 0 and 1.

[0044] Preferably, the plurality of warning levels correspond to the plurality of warning thresholds, wherein the warning thresholds include an upper threshold and a lower threshold;

[0045] The multiple warning levels and the multiple warning thresholds satisfy the following relationship:

[0046] Green warning level ;

[0047] Yellow warning level ;

[0048] Orange warning level ;

[0049] Red alert level 1;

[0050] in, is the emergency warning evaluation coefficient, is the lower threshold corresponding to the yellow warning level and the upper threshold corresponding to the green warning level. is the lower threshold corresponding to the orange warning level and the upper threshold corresponding to the yellow warning level. is the lower threshold corresponding to the red warning level and the upper threshold corresponding to the orange warning level. , , .

[0051] Preferably, in the medical resources deployment module, the process of deploying medical personnel includes:

[0052] Receive severity analysis results and warning signals from the emergency warning module, including warning levels (green, yellow, orange, red) and related abnormal descriptions. Analyze the urgency and number of patients in each department and assess department needs based on the warning signals and evaluation information.

[0053] Combined with the assessment results of department needs, identify departments with medical staff resource gaps, as well as the specific types and numbers of gaps, and analyze departments that are currently relatively idle and have professional medical staff that meet the needs;

[0054] According to the department's needs and resource conditions, select the appropriate medical staff as the deployment targets, formulate an emergency response plan, and dynamically adjust the medical staff's schedule to ensure that the deployed medical staff can arrive at the designated department within the required time;

[0055] Notify the deployed medical staff, clarify their tasks, arrival time and place, and matters that need attention; deploy the medical staff to the designated department or emergency site according to the shift adjustment plan, and monitor the operation of the department after deployment in real time, including the patient treatment situation and the working status of medical staff.

[0056] Preferably, in the medical supplies management module, the allocation process of medical supplies includes:

[0057] The medical supplies management module monitors the inventory of various medical supplies in real time through the hospital information system, including emergency medicines, medical equipment, and disinfectants. According to the warning level and related abnormal descriptions received from the emergency warning module, it analyzes the material needs of each department at different warning levels.

[0058] Evaluate the consumption rate and trend of various medical supplies based on historical data and current usage, predict the material needs of various departments in the future based on consumption analysis and early warning signals, and set safety inventory thresholds for various medical supplies to ensure timely replenishment before shortages occur;

[0059] When the inventory of a certain emergency medicine or medical device falls below the set safety threshold, the medical supplies management module automatically triggers a replenishment reminder, notifies the relevant departments to replenish the stock, and allocates medical devices and supplies between different departments, so that the emergency site and departments in urgent need of supplies have priority in obtaining the supply of medical supplies;

[0060] Monitor the use of medical supplies, including consumption rate, remaining inventory, and replenishment progress, to ensure the effective use of materials, and regularly evaluate the effectiveness of material allocation, including the efficiency of material use, collaboration between departments, and patient treatment outcomes.

[0061] The present invention provides a hospital outpatient emergency service system based on a cloud server. It has the following beneficial effects:

[0062] 1. The hospital outpatient emergency service system based on cloud servers can quickly identify potential emergency needs or risk points by real-time monitoring of the medical supplies inventory, patient flow, and medical staff work status data of each department. The emergency warning module sends out a warning signal, which can immediately trigger the emergency response process of replenishment reminders, deployment of medical staff or medical supplies, significantly improving the hospital outpatient department's processing efficiency in responding to emergencies and reducing delays and losses caused by information lags or untimely processing.

[0063] 2. The hospital outpatient emergency service system based on cloud servers optimizes the allocation of medical resources through data analysis and prediction. In terms of allocation of medical resources, it can deploy medical staff according to the urgency and number of patients in each department to ensure a rapid response in emergency situations. In terms of medical supplies management, it can monitor inventory in real time, predict future demand based on early warning signals and consumption analysis, replenish stocks in time, and avoid shortages of supplies. The intelligent resource allocation mechanism not only improves the efficiency of resource use, but also reduces waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a module structure diagram of a hospital outpatient emergency service system based on a cloud server of the present invention;

[0065] Figure 2 The flowchart of analyzing the emergency degree of abnormal situation of the present invention;

[0066] Figure 3 The figure is a flow chart for evaluating the severity of abnormal situations of the present invention. DETAILED DESCRIPTION

[0067] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0068] The first embodiment, as Figure 1 , Figure 2 As shown, the present invention provides a technical solution: a hospital outpatient emergency service system based on a cloud server, including a cloud data center, the cloud data center is communicatively connected with a medical data acquisition module, an abnormality identification module, an abnormality analysis module, an emergency warning evaluation module, a medical care resource allocation module, a medical material management module and a mobile application module, wherein the modules are connected by electrical signals;

[0069] The cloud data center, as the data storage and processing center of the entire system, combines cloud servers to collect, integrate and analyze data from various hospital subsystems to ensure the real-time and accuracy of data and provide strong data support for decision-making;

[0070] The medical data acquisition module is used to collect relevant medical data from all aspects of the hospital outpatient department, including the real-time number of patients in each department, the on-duty status of medical staff, and the inventory status of medical supplies. It also pre-processes the medical data and collects relevant medical data from the hospital's electronic medical record system, hospital information system, laboratory information system, image archiving and communication system, including the real-time number of patients, the on-duty status of medical staff, the inventory status of medical supplies, and the use of equipment. Among them, the electronic medical record system collects and records the patient's detailed medical information, medical history, diagnosis results, etc., and the hospital information system obtains comprehensive information on hospital operations, management, and clinical aspects. The laboratory information system collects laboratory test results and samples. Information, etc., extract the medical imaging data stored and managed by the image archiving and communication system, pre-process the collected medical data to ensure the quality and availability of the data, where the pre-processing steps include data cleaning, data conversion and data merging. Data cleaning is used to delete missing values, process outliers and remove duplicate data. Data conversion includes format conversion, encoding conversion, etc. to ensure that the data can be correctly understood and processed by the system. Data from different sources are integrated together through data merging to form a unified data view. The pre-processed medical data is transmitted to the cloud data center, and the data is stored and archived in the data warehouse built in the cloud data center for subsequent analysis and use;

[0071] The anomaly identification module monitors the emergency service status of the hospital outpatient department in real time based on the acquired medical data, detects and marks abnormal situations, discovers potential problems in advance, buys valuable time for emergency response, and reduces the negative impact of emergencies. Abnormal situations include overload of patient numbers, insufficient medical resources, and shortage of medical supplies. According to the historical data and operating standards of hospital operations, abnormal thresholds are set for the real-time number of patients, the on-the-job status of medical staff, and the inventory of medical supplies to determine abnormal situations such as overload of patient numbers, insufficient medical resources, and shortage of medical supplies. Among them, the historical data of hospital operations is analyzed to determine the average number of patients and the peak number of patients in each department, and the overload abnormal threshold of the number of patients is set according to the hospital operating standards and actual service capabilities. The overload abnormal threshold is set to 1.5 times the average number of patients, and the daily operation of the hospital is evaluated. The minimum number of medical staff required for the department, set the abnormal threshold for insufficient medical resources, which is 80% lower than the minimum number required for daily use, analyze the historical consumption data and replenishment cycle of medical supplies, set the abnormal threshold for shortage of medical supplies, and trigger it when the inventory is lower than the safety inventory. Real-time monitoring of pre-processed medical data, compare the actual data with the abnormal threshold, and trigger the abnormal identification mechanism when the actual data of the number of patients and medical supplies exceeds the abnormal threshold. When the actual data of medical resources is lower than the abnormal threshold, the abnormal identification mechanism is triggered. According to the real-time monitoring results, the abnormal situations of overload of patients, insufficient medical resources and shortage of medical supplies are identified, and the identified abnormal situations are marked, and the information of abnormal type, occurrence time and impact range is recorded. The marked abnormal data is stored in the data warehouse for subsequent analysis and processing;

[0072] The abnormal analysis module is used to analyze the identified abnormal situations, clarify the urgency of each abnormal situation, and determine the corresponding response measures. Based on the identification results of the abnormal situations, further analysis is conducted on the identified abnormal situations of overload of patient numbers, insufficient medical resources, and shortage of medical supplies, and the urgency of each abnormal situation is clarified. According to the comparison results of the real-time number of patients and the set overload abnormal threshold, the patient number evaluation index is calculated, and the degree of overload of the number of patients is analyzed. According to the patient number evaluation index, the degree of overload is divided into mild, moderate and severe. Mild overload means that the number of patients is slightly higher than the average level, but still within the controllable range. Moderate overload means that the number of patients has increased significantly and certain measures need to be taken. Measures to alleviate the situation are taken. Severe overload means that the number of patients seriously exceeds the carrying capacity, and immediate measures need to be taken. Based on the comparison results of the on-the-job situation of medical staff and the set abnormal threshold of insufficient medical staff, the medical resource evaluation index is calculated to analyze the shortage degree of medical resources. According to the medical resource evaluation index, the shortage degree is divided into mild, moderate and severe. Mild shortage means that medical resources are slightly insufficient, but it does not affect the overall operation. Moderate shortage means that medical resources are obviously insufficient and resources need to be deployed. Severe shortage means that medical resources are seriously insufficient, which may endanger patient safety. Based on the comparison results of the inventory of medical supplies and the set abnormal shortage threshold, the medical supplies evaluation index is calculated to analyze the impact of the shortage of supplies. The shortage evaluation index is used to divide the impact of shortages into slight, moderate and severe. Slight impact means that the shortage of materials has little impact on operations, moderate impact means that the shortage of materials has a certain impact on operations and replenishment needs to be accelerated, and severe impact means that the shortage of materials has a serious impact on operations and immediate measures need to be taken. For each abnormal situation, corresponding response measures are formulated according to the degree of urgency, including increasing medical staff, allocating materials, optimizing the medical treatment process, strengthening patient management, and allocating resources according to the response measures. In response to the overload of the number of patients, slight overload optimizes the medical treatment process, such as adding registration windows and guiding patient diversion, etc. Moderate overload increases the number of medical staff, such as deploying medical staff from other departments for support, and severe overload increases the number of medical staff. In case of overload, the emergency plan will be activated, such as temporarily closing some registration channels, extending consultation hours, etc., and reporting to the superior department; in response to insufficient medical resources, mild shortages will be alleviated through internal deployment, such as adjusting shifts, using rest days to work overtime, etc., moderate shortages will be alleviated by deploying medical staff from other departments, or contacting external agencies for support, and severe shortages will initiate emergency recruitment procedures and apply for reinforcements from the superior department; in response to shortages of medical supplies, minor impacts will speed up replenishment and maintain close contact with suppliers, moderate impacts will initiate emergency procurement procedures, find alternative supplies or emergency procurement channels, and severe impacts will be reported to the superior department and request material deployment or emergency procurement support, while optimizing the material use process to reduce waste;

[0073] Furthermore, the calculation formula of the patient number evaluation index is:

[0074] ;

[0075] in, is the patient visit evaluation index, The real-time number of patients. is the overload abnormal threshold, It represents the square root of the ratio of the number of patients to the threshold minus 1. Slightly higher , this value will be a small positive number, indicating a slight overload. It represents the natural exponent of the ratio of the number of patients to the threshold minus 1. Significantly higher than This value increases rapidly when hour, ,therefore and will be 0 or negative, but since the maximum value is taken, the patient number evaluation index is 0, indicating no overload. hour, ,along with increase, and Both increase, but the exponential function grows faster, so the exponential function will dominate the evaluation index, slightly overloading it: , moderate overload: , heavy overload: ;

[0076] The calculation formula of the medical resources evaluation index is:

[0077] ;

[0078] in, is the medical resources evaluation index, is the number of medical staff currently on duty, is the abnormal threshold for insufficient medical staff, The square root of the complement of the ratio of the number of medical staff on duty to the threshold value. near When this value is close to 0, it means that medical resources are sufficient. Much lower than When this value increases, it indicates a shortage of medical resources. It represents the negative index of the ratio of the number of medical staff on duty to the threshold minus 0.8. near When , this value is close to 1, and the impact on the denominator is small. Much lower than This value decreases rapidly when , causing the denominator to increase, thereby reducing the value of the entire formula. hour, ,therefore is 0, and the exponential function part is close to 1, so the medical resources evaluation index is close to 0, indicating that there is no shortage. hour, ,along with The decrease in the radical part increases and the exponential function part decreases, resulting in an increase in the value of the entire formula, indicating an increase in the shortage of medical resources, and a mild shortage: , moderate shortage: , severe shortage: ;

[0079] The calculation formula of the medical supplies evaluation index is:

[0080] ;

[0081] in, is the medical supplies evaluation index. is the current inventory of medical supplies, is the shortage exception threshold, The part represents the square root of the complement of the ratio of the inventory to the threshold. near When the value is close to 1, it means that the inventory is sufficient. Much lower than When , this value decreases, indicating a shortage of inventory, The part represents the logarithm of the root part plus 1. The logarithmic function increases the nonlinearity of the formula, making the value of the formula more sensitive when the inventory level approaches the threshold. The part represents the negative exponent of the ratio of inventory to the threshold minus 0.5. near When , this value is close to 1, and the impact on the denominator is small. Much lower than , this value decreases rapidly, causing the denominator to increase, thus reducing the value of the entire formula. Partially ensure that the denominator of the formula is always greater than 1 to avoid division by zero. hour, ,therefore The logarithmic function part is close to 0, and the exponential function part is close to 1, so the medical supplies evaluation index is close to 0, indicating that there is no shortage. hour, ,along with The decrease in the radical part, the logarithmic function part, and the exponential function part leads to an increase in the value of the entire formula, indicating an increase in the shortage of medical supplies, with a slight impact: , medium impact: , seriously affecting: ;

[0082] The emergency warning evaluation module comprehensively evaluates the severity of abnormal situations based on the results of the emergency analysis of abnormal situations and determines the corresponding warning level;

[0083] The medical resource allocation module allocates medical staff in the hospital based on the information from the emergency warning module and the warning evaluation module. According to the urgency and number of patients in each department, doctors and nurses with appropriate expertise are drawn from relatively idle departments to go to the emergency site or the department where patients gather. The medical resource allocation module dynamically adjusts the medical staff shifts to ensure that every patient who needs medical services can receive timely treatment from professionals, optimizes human resource allocation, and improves the efficiency and quality of emergency response.

[0084] The medical supplies management module monitors the inventory of medical supplies in real time, analyzes the demand for supplies and the consumption in emergency events in combination with the warning results of the emergency warning module and the warning evaluation module, and allocates medical supplies. When the inventory of a certain emergency medicine is lower than the safety threshold, it automatically triggers a replenishment reminder, and reasonably allocates medical equipment among different departments to ensure that the emergency scene and departments in urgent need of supplies can get priority to obtain sufficient supplies, reduce shortages and waste of supplies, and improve the efficiency and benefits of the use of supplies;

[0085] The mobile application module provides mobile emergency service support for medical staff and managers, including information viewing, task receipt and feedback, improving the flexibility and convenience of the system, making emergency response faster and more efficient, and providing communication and command functions in emergency situations to ensure smooth information flow between departments and personnel, strengthen team collaboration, and improve the coordination and execution of emergency response.

[0086] The second embodiment is based on the first embodiment. Figure 3 As shown in the figure, in the emergency warning evaluation module, the evaluation process of the severity of abnormal situations includes:

[0087] Extract real-time patient number data, medical staff on-the-job status data, and medical supplies inventory data to ensure the accuracy and completeness of the data, and obtain the patient number evaluation index, medical resources evaluation index, and medical supplies evaluation index calculated based on the patient number, medical staff on-the-job status, and medical supplies inventory. Standardize the three evaluation indexes obtained and unify them on the same scale for comparison and weighting. According to the hospital's operating strategy and resource allocation, assign weights to each evaluation index, combine the patient number evaluation index, medical resources evaluation index, and medical supplies evaluation index, and combine the various The emergency warning evaluation coefficient is calculated based on the weight of the emergency warning evaluation coefficient, and the severity of the abnormal situation is evaluated. According to the value of the emergency warning evaluation coefficient, warning levels of different severity levels are set, namely green warning level, yellow warning level, orange warning level and red warning level, and the corresponding warning threshold range is set for each warning level. Among them, the warning level increases from green to red, and the severity increases step by step. For each warning level, an emergency analysis is conducted, and according to the results of the emergency analysis, corresponding response measures are proposed. The response measures include increasing medical staff, allocating materials, optimizing the treatment process, strengthening patient management and other measures;

[0088] Furthermore, the calculation formula of the emergency warning evaluation coefficient is:

[0089] ;

[0090] in, is the emergency warning evaluation coefficient, is the patient visit evaluation index, is the medical resources evaluation index, is the medical supplies evaluation index. , and They represent the weights of the patient number evaluation index, medical resources evaluation index, and medical supplies evaluation index, respectively. When all evaluation indexes are close to 0, the numerator is close to 0 and the denominator is close to 1. Therefore, the emergency warning evaluation coefficient is close to 0, indicating that there is no abnormal situation. When any evaluation index increases, the numerator increases and the denominator also increases, but the numerator increases faster. Therefore, the emergency warning evaluation coefficient increases, indicating that the severity of the abnormal situation increases. Due to the increase in the denominator, the value of the emergency warning evaluation coefficient is limited to between 0 and 1.

[0091] Furthermore, the multiple warning levels correspond to multiple warning thresholds, wherein the warning thresholds include an upper threshold and a lower threshold;

[0092] Multiple warning levels and multiple warning thresholds satisfy the following relationship:

[0093] Green warning level ;

[0094] Yellow warning level ;

[0095] Orange warning level ;

[0096] Red alert level 1;

[0097] in, is the emergency warning evaluation coefficient, is the lower threshold corresponding to the yellow warning level and the upper threshold corresponding to the green warning level. is the lower threshold corresponding to the orange warning level and the upper threshold corresponding to the yellow warning level. is the lower threshold corresponding to the red warning level and the upper threshold corresponding to the orange warning level. , , ;

[0098] In the medical resource deployment module, the process of medical staff deployment includes:

[0099] Receive severity analysis results and warning signals from the emergency warning module, including warning levels (green, yellow, orange, red) and related abnormal descriptions. According to the warning signals and evaluation information, analyze the urgency and number of patients in each department, evaluate department needs, and identify departments with medical staff resource gaps, as well as the specific types and numbers of gaps based on the department needs assessment results. Analyze departments that are currently relatively idle and have professional medical staff that meet the needs. According to department needs and resource conditions, select corresponding medical staff as deployment targets, formulate emergency response plans, dynamically adjust the medical staff schedule, ensure that the deployed medical staff can arrive at the designated department within the required time, notify the deployed medical staff, clarify their tasks, arrival time and location, and matters that need attention, deploy medical staff to designated departments or emergency sites according to the shift adjustment plan, and monitor the operation of the deployed departments in real time, including patient treatment and medical staff working status;

[0100] In the medical supplies management module, the allocation process of medical supplies includes:

[0101] The medical supplies management module monitors the inventory of various medical supplies in real time through the hospital information system, including emergency drugs, medical equipment, and disinfectants. According to the warning level and related abnormal descriptions received from the emergency warning module, it analyzes the material needs of each department at different warning levels. According to historical data and current usage, it evaluates the consumption rate and trend of various medical supplies. Based on consumption analysis and warning signals, it predicts the material needs of various departments in the future. It also sets safety inventory thresholds for various medical supplies to ensure that they can be replenished in time before the shortage of materials. When the inventory of a certain emergency drug or medical device is lower than the set safety threshold, the medical supplies management module automatically triggers a replenishment reminder, notifies the relevant departments to replenish the stock, and allocates medical equipment and supplies between different departments, so that the emergency site and the department in urgent need of materials have priority in obtaining the supply of medical supplies. It monitors the use of medical supplies, including consumption rate, remaining inventory, and replenishment progress, to ensure the effective use of materials, and regularly evaluates the effect of material allocation, including the efficiency of material use, the collaboration between departments, and the treatment effect of patients.

[0102] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A hospital outpatient emergency service system based on a cloud server, comprising a cloud data center, characterized in that: The cloud data center is communicatively connected with a medical data acquisition module, an abnormality identification module, an abnormality analysis module, an emergency warning evaluation module, a medical resources allocation module, a medical supplies management module and a mobile application module, wherein the electrical signals between the modules are connected; The medical data acquisition module is used to collect relevant medical data of each link of the hospital outpatient department; The abnormality identification module monitors the emergency service status of the hospital outpatient department in real time based on the acquired medical data, detects abnormal situations and marks them, wherein the abnormal situations include overload of the number of patients, insufficient medical resources and shortage of medical supplies; The abnormality analysis module is used to analyze the identified abnormal situations, clarify the urgency of each abnormal situation, and determine the corresponding response measures; The emergency warning evaluation module comprehensively evaluates the severity of the abnormal situation based on the urgency analysis results of the abnormal situation and determines the corresponding warning level; The medical resources allocation module allocates medical staff in the hospital according to the information of the emergency warning module and the warning evaluation module; The medical supplies management module monitors the inventory of medical supplies in real time, combines the warning results of the emergency warning module and the warning evaluation module, and allocates medical supplies; The mobile application module provides mobile emergency service support for medical staff and management personnel.

2. According to the cloud server-based hospital outpatient emergency service system of claim 1, it is characterized by: In the medical data acquisition module, the medical data collection process includes: Collect relevant medical data from the hospital's electronic medical record system, hospital information system, laboratory information system, image archiving and communication system, including the real-time number of patients, medical staff on duty, medical supplies inventory, and equipment usage; Preprocess the collected medical data, where the preprocessing steps include data cleaning, data conversion and data merging. Data cleaning is used to delete missing values, process outliers and remove duplicate data. Data merging is used to integrate data from different sources to form a unified data view. The pre-processed medical data is transmitted to the cloud data center, and the data is stored and archived in the data warehouse built in the cloud data center.

3. The hospital outpatient emergency service system based on a cloud server according to claim 2, characterized in that: In the anomaly identification module, the abnormal situation detection and marking process includes: According to the historical data and operation standards of hospital operations, abnormal thresholds are set for the real-time number of patients, the on-duty status of medical staff, and the inventory of medical supplies to determine abnormal situations such as overload of patients, insufficient medical resources, and shortage of medical supplies. Specifically, the historical data of hospital operations are analyzed to determine the average number of patients and the peak number of patients in each department, and an abnormal threshold for overload of patients is set. The overload abnormal threshold is set to 1.5 times the average number of patients. The minimum number of medical staff required for each department in the daily operation of the hospital is evaluated, and an abnormal threshold for insufficient medical resources is set. The abnormal threshold for insufficient medical resources is set to 80% of the minimum number required for daily use. The historical consumption data and replenishment cycle of medical supplies are analyzed, and an abnormal threshold for shortage of medical supplies is set, which is triggered when the inventory level is lower than the safety stock. Real-time monitoring of pre-processed medical data, comparing actual data with abnormal thresholds. When the actual data of the number of patients and medical supplies exceeds the abnormal threshold, the abnormal identification mechanism is triggered; when the actual data of medical resources is lower than the abnormal threshold, the abnormal identification mechanism is triggered; Based on the real-time monitoring results, abnormal situations such as overload of patient numbers, insufficient medical resources, and shortage of medical supplies are identified, and the identified abnormal situations are marked, and information such as the abnormality type, occurrence time, and scope of impact is recorded, and the marked abnormal data is stored in the data warehouse.

4. The hospital outpatient emergency service system based on a cloud server according to claim 3 is characterized by: In the abnormality analysis module, the analysis process of the emergency degree of the abnormal situation includes: Based on the results of abnormal situation identification, further analyze the abnormal situations of overload of patients, insufficient medical resources, and shortage of medical supplies that have been identified to clarify the urgency of each abnormal situation; According to the comparison result between the real-time number of patients and the set overload abnormal threshold, the patient number evaluation index is calculated to analyze the overload degree of the number of patients; Based on the comparison between the on-the-job status of medical staff and the set abnormal threshold of medical staff shortage, the medical resources evaluation index is calculated to analyze the shortage of medical resources; Based on the comparison between the inventory of medical supplies and the set shortage abnormality threshold, the medical supplies evaluation index is calculated to analyze the impact of the shortage of supplies; For each abnormal situation, corresponding response measures are formulated according to the degree of urgency, including increasing medical staff, allocating supplies, optimizing medical treatment processes, strengthening patient management, and allocating resources according to the response measures.

5. The hospital outpatient emergency service system based on a cloud server according to claim 4 is characterized by: The calculation formula of the patient number evaluation index is: ； in, is the patient visit evaluation index, The real-time number of patients. is the overload abnormal threshold; The calculation formula of the medical resources evaluation index is: ； in, is the medical resources evaluation index, is the number of medical staff currently on duty, The abnormal threshold for insufficient medical staff; The calculation formula of the medical supplies evaluation index is: ； in, is the medical supplies evaluation index. is the current inventory of medical supplies, is the shortage exception threshold.

6. The hospital outpatient emergency service system based on a cloud server according to claim 5, characterized in that: In the emergency warning evaluation module, the evaluation process of the severity of abnormal situations includes: Extract real-time patient number data, medical staff on-the-job status data, and medical supplies inventory data, and obtain the patient number evaluation index, medical resources evaluation index, and medical supplies evaluation index calculated based on the patient number, medical staff on-the-job status, and medical supplies inventory; The three evaluation indexes obtained were standardized, unified on the same scale, and weights were assigned to each evaluation index based on the hospital's operating strategy and resource allocation; Combine the patient number evaluation index, medical resources evaluation index, and medical supplies evaluation index, and combine their respective weights to calculate the emergency warning evaluation coefficient and evaluate the severity of the abnormal situation; According to the value of the emergency warning evaluation coefficient, warning levels of different severity levels are set, namely green warning level, yellow warning level, orange warning level and red warning level, and corresponding warning threshold ranges are set for each warning level, where the warning level increases from green to red, and the severity increases step by step; For each warning level, an urgency analysis is conducted, and corresponding response measures are recommended based on the results of the urgency analysis.

7. The hospital outpatient emergency service system based on a cloud server according to claim 6, characterized in that: The calculation formula of the emergency warning evaluation coefficient is: ； in, is the emergency warning evaluation coefficient, is the patient visit evaluation index, is the medical resources evaluation index, is the medical supplies evaluation index. , and They respectively represent the weights of the patient number evaluation index, medical care resources evaluation index and medical supplies evaluation index.

8. The hospital outpatient emergency service system based on a cloud server according to claim 7, characterized in that: A plurality of the warning levels correspond to a plurality of the warning thresholds, wherein the warning thresholds include an upper threshold and a lower threshold; The multiple warning levels and the multiple warning thresholds satisfy the following relationship: Green warning level ; Yellow warning level ; Orange warning level ; Red alert level 1; in, is the emergency warning evaluation coefficient, is the lower threshold corresponding to the yellow warning level and the upper threshold corresponding to the green warning level. is the lower threshold corresponding to the orange warning level and the upper threshold corresponding to the yellow warning level. is the lower threshold corresponding to the red warning level and the upper threshold corresponding to the orange warning level. , , .

9. The hospital outpatient emergency service system based on a cloud server according to claim 8, characterized in that: In the medical resources allocation module, the process of medical staff allocation includes: Receive severity analysis results and warning signals from the emergency warning module, including warning levels and related abnormal descriptions. Analyze the urgency and number of patients in each department and assess department needs based on the warning signals and evaluation information. Combined with the assessment results of department needs, identify departments with medical staff resource gaps, as well as the specific types and numbers of gaps, and analyze departments that are currently relatively idle and have professional medical staff that meet the needs; According to the department's needs and resource conditions, select the appropriate medical staff for deployment, formulate an emergency response plan, and dynamically adjust the medical staff's schedule; Notify the deployed medical staff, clarify their tasks, arrival time and place, and matters that require attention; deploy the medical staff to the designated department or emergency site according to the shift adjustment plan, and monitor the operation of the deployed department in real time.

10. A hospital outpatient emergency service system based on a cloud server according to claim 9, characterized in that: In the medical supplies management module, the allocation process of medical supplies includes: The medical supplies management module monitors the inventory of various medical supplies in real time through the hospital information system, including emergency medicines, medical equipment, and disinfectants. According to the warning level and related abnormal descriptions received from the emergency warning module, it analyzes the material needs of each department at different warning levels. Evaluate the consumption rate and trend of various medical supplies based on historical data and current usage, predict the material needs of each department based on consumption analysis and early warning signals, and set safety inventory thresholds for various medical supplies; When the inventory of emergency drugs or medical equipment is lower than the set safety threshold, the medical supplies management module automatically triggers a replenishment reminder, notifies relevant departments to replenish the stock, and allocates medical equipment and supplies between different departments, so that the emergency site and departments in urgent need of supplies have priority in obtaining the supply of medical supplies; Monitor the usage of medical supplies, including consumption rate, remaining inventory, replenishment progress, and regularly evaluate the effectiveness of material allocation.

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