Method and system for monitoring condition of emergency patient in transfer process

Abstract

The invention provides an illness state monitoring method and system for an emergency patient transfer process, and relates to the technical field of transfer illness state monitoring, transfer demand information is acquired, illness state data evaluation, processing, classified risk analysis and labeling are performed on a patient, and illness state category risk labeling information is acquired; the method comprises the following steps: acquiring patient transfer path information, further generating a relay position, calculating a patient disease development coefficient, acquiring a disease development time sequence of the patient transfer path information, labeling abnormal disease nodes, further labeling abnormal positions of the transfer path information, and acquiring development position abnormal labeling information; the shortest distance between the development position abnormal labeling information and the relay position information is obtained, then the first conveying distance of the shortest distance is obtained, the conveying path is determined, and secondary transferring is carried out, and comprehensive monitoring and intelligent adjustment of the emergency patient transferring process can be achieved according to the illness state monitoring data.

Description

Technical Field

[0001] The present invention provides a method and system for monitoring the condition of emergency patients during the transfer process, which relates to the technical field of condition monitoring, specifically to the technical field of monitoring the condition of emergency patients during the transfer process. Background Art

[0002] The traditional transfer process of emergency patients often relies on the empirical judgment of medical staff and lacks systematic and intelligent means for monitoring the condition. This results in the difficulty of timely detection and effective response to the changes in the patient's condition during the transfer process. In addition, there are few relay nodes required for dealing with emergencies in the traditional transfer route planning, resulting in the difficulty of flexible and automated adjustment of the transfer route according to the actual situation, lacking the ability of real-time monitoring and dynamic assessment of the patient's condition, being unable to detect and handle the changes in the condition in a timely manner, and the unreasonable transfer route planning, leading to too long transfer time or potential safety hazards during the transfer process; if the relay position is not properly selected, the patient cannot receive timely medical treatment during the transfer process. Summary of the Invention

[0003] The present invention provides a method and system for monitoring the condition of emergency patients during the transfer process to solve the above problems:

[0004] A method and system for monitoring the condition of emergency patients during the transfer process proposed by the present invention, the method includes:

[0005] S1. Obtain transfer requirement information, evaluate and process the condition data of the patient to obtain patient evaluation and processing data, perform classification risk analysis and annotation on the patient evaluation and processing data to obtain condition category risk annotation information;

[0006] S2. Obtain the patient transfer path information, obtain preset transfer process nodes according to the patient transfer path information, and then generate relay positions to obtain relay position information;

[0007] S3. Calculate the patient condition development coefficient, obtain the condition development time sequence of the patient transfer path information according to the patient condition development coefficient, perform abnormal condition node annotation, and then perform abnormal position annotation on the transfer path information to obtain development position abnormal annotation information;

[0008] S4. Obtain the shortest distance between the development position abnormal annotation information and the relay position information, and then obtain the first transportation distance of the shortest distance, determine the transportation path, and perform secondary transfer.

[0009] Further, the S1 includes:

[0010] Obtain the transfer requirement information of the patient, and trigger a patient evaluation instruction according to the transfer requirement information;

[0011] Perform a patient condition assessment alarm according to the patient assessment instruction, and then obtain patient condition assessment data;

[0012] Preprocess the patient condition assessment data to obtain patient assessment processed data;

[0013] Classify the patient assessment processed data according to the preset disease types to obtain patient condition category data of multiple types;

[0014] Compare the patient condition category data with the preset category disease thresholds to obtain patient condition comparison information;

[0015] Determine the patient condition risk category according to the patient condition comparison information, and perform category risk annotation on the patient condition risk category to obtain disease category risk annotation information.

[0016] Further, the S2 includes:

[0017] Obtain the transfer starting point information and transfer ending point information of the patient, set the patient transfer path according to the transfer starting point information and transfer ending point information according to the shortest transfer time, and obtain patient transfer path information;

[0018] Obtain the preset transfer process nodes (such as passing hospitals, etc.) of the patient transfer path information, and set the preset transfer process nodes as relay positions to obtain multiple relay position information.

[0019] Further, the S3 includes:

[0020] Obtain the preset monitoring time node information, and obtain the disease category risk annotation information and patient assessment processed data of the patient at each preset monitoring time node;

[0021] Calculate the patient condition development coefficient according to the disease category risk annotation information combined with the patient assessment processed data;

[0022] Sort the patient condition development coefficients according to the preset monitoring time node information to obtain the disease development time sequence;

[0023] Obtain the path position information of each preset monitoring time node, and bind the disease development time sequence with the path position information to obtain position development binding data;

[0024] Compare each patient condition development coefficient in the disease development time sequence with the preset development threshold in turn to obtain the disease development comparison result;

[0025] Perform abnormal disease node annotation on the disease development time sequence according to the disease development comparison result;

[0026] Obtain the patient's disease development coefficient corresponding to the annotation of the first abnormal disease node in the time sequence of disease development;

[0027] Perform abnormal position annotation on the corresponding path position information of the patient's disease development coefficient corresponding to the annotation of the first abnormal disease node in the position development binding data to obtain development position abnormal annotation information.

[0028] Further, the S4 includes:

[0029] Obtain the development position abnormal annotation information and the relay position information, and calculate the shortest transportation distance between the development position abnormal annotation information and multiple relay position information;

[0030] Obtain the first transportation distance from among multiple shortest transportation distances;

[0031] Obtain the transportation path corresponding to the first transportation distance;

[0032] Perform secondary shipment on the patient through the transportation path to obtain secondary shipment information.

[0033] Further, the system includes:

[0034] A disease analysis annotation module, used to obtain the transfer requirement information, evaluate and process the patient's disease data to obtain the patient's evaluation and processing data, perform classification risk analysis and annotation on the patient's evaluation and processing data to obtain disease category risk annotation information;

[0035] A path relay setting module, used to obtain the patient's transfer path information, obtain preset transfer process nodes according to the patient's transfer path information, and then generate relay positions to obtain relay position information;

[0036] A disease development monitoring module, used to calculate the patient's disease development coefficient, obtain the time sequence of disease development of the patient's transfer path information according to the patient's disease development coefficient, perform abnormal disease node annotation, and then perform abnormal position annotation on the transfer path information to obtain development position abnormal annotation information;

[0037] An emergency transfer module, used to obtain the shortest distance between the development position abnormal annotation information and the relay position information, then obtain the first transportation distance of the shortest distance, determine the transportation path, and perform secondary transfer.

[0038] Further, the disease analysis annotation module includes:

[0039] A disease evaluation and processing module, used to obtain the patient's transfer requirement information and trigger a patient evaluation instruction according to the transfer requirement information;

[0040] Perform a patient disease evaluation alarm according to the patient evaluation instruction, and then obtain the patient disease evaluation data;

[0041] Preprocess the patient's condition assessment data to obtain patient assessment processed data;

[0042] A classification and comparison annotation module for classifying the patient assessment processed data according to preset disease types to obtain patient disease category data of multiple types;

[0043] Compare the patient disease category data with preset category disease thresholds to obtain patient disease comparison information;

[0044] Determine the patient disease risk category according to the patient disease comparison information, and perform category risk annotation on the patient disease risk category to obtain disease category risk annotation information.

[0045] Furthermore, the path relay setting module includes:

[0046] A path information acquisition module for acquiring the patient's transfer starting point information and transfer ending point information, setting the patient transfer path according to the transfer starting point information and transfer ending point information according to the shortest transfer time, and acquiring patient transfer path information;

[0047] A relay position determination module for acquiring preset transfer process nodes (such as passing hospitals, etc.) of the patient transfer path information, setting the preset transfer process nodes as relay positions, and obtaining multiple relay position information.

[0048] Furthermore, the disease development monitoring module includes:

[0049] A disease development analysis module for acquiring preset monitoring time node information, and acquiring the disease category risk annotation information and patient assessment processed data of the patient at each preset monitoring time node;

[0050] Calculate the patient disease development coefficient according to the disease category risk annotation information combined with the patient assessment processed data;

[0051] A development time sequence acquisition module for sorting the patient disease development coefficients according to the preset monitoring time node information to obtain a disease development time sequence;

[0052] A disease position binding module for acquiring the path position information of each preset monitoring time node, and binding the disease development time sequence with the path position information to obtain position development binding data;

[0053] A disease comparison annotation module for sequentially comparing each patient disease development coefficient in the disease development time sequence with a preset development threshold to obtain a disease development comparison result;

[0054] Annotate abnormal disease nodes for the disease development time sequence according to the comparison result of the disease development;

[0055] Obtain the patient's disease development coefficient corresponding to the first abnormal disease node annotation in the disease development time sequence;

[0056] The position abnormal annotation module is used to perform abnormal position annotation on the corresponding path position information of the patient's disease development coefficient corresponding to the first abnormal disease node annotation in the position development binding data, and obtain the development position abnormal annotation information.

[0057] Further, the emergency transfer module includes:

[0058] The transportation distance comparison module is used to obtain the development position abnormal annotation information and the relay position information, and calculate the shortest transportation distance between the development position abnormal annotation information and multiple relay position information;

[0059] The optimal path transfer module is used to obtain the first transportation distance from multiple shortest transportation distances;

[0060] Obtain the transportation path corresponding to the first transportation distance;

[0061] Perform secondary shipment on the patient through the transportation path to obtain secondary shipment information.

[0062] The beneficial effects of the present invention: Through automated evaluation and risk annotation, it can quickly identify the severity of the patient's condition and the transfer requirements, thereby optimizing the transfer process and improving the transfer efficiency. It can monitor the patient's disease development in real time and perform abnormal annotation at key nodes, which can timely discover and handle potential risks and enhance the safety of the transfer process. According to the patient's disease classification and risk annotation, it can reasonably allocate medical resources, such as arranging appropriate transfer vehicles, medical staff, and first aid equipment, to ensure the efficient use of resources. Through rapid and accurate transfer and treatment, the system can reduce the waiting time and pain of patients. When the patient's condition suddenly deteriorates rapidly during the transfer process, it can automatically generate the optimal relay route to ensure timely treatment. The disease assessment, risk annotation, and transfer path information provided by the system can automatically generate a disease control strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic diagram of a method for monitoring the condition of emergency patients during the transfer process;

[0064] Figure 2 It is a schematic diagram of a system for monitoring the condition of emergency patients during the transfer process. DETAILED DESCRIPTION OF THE INVENTION

[0065] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not intended to limit the present invention.

[0066] In one embodiment of the present invention, a method and system for monitoring the condition of emergency patients during transportation are proposed. The method includes:

[0067] S1. Obtain transportation requirement information, evaluate and process the condition data of the patient to obtain patient evaluation and processing data, perform classification risk analysis and annotation on the patient evaluation and processing data, and obtain condition category risk annotation information;

[0068] S2. Obtain the patient transportation route information, obtain preset transportation process nodes according to the patient transportation route information, and then generate relay positions to obtain relay position information;

[0069] S3. Calculate the patient's condition development coefficient, obtain the condition development time sequence of the patient transportation route information according to the patient's condition development coefficient, perform abnormal condition node annotation, and then perform abnormal position annotation on the transportation route information to obtain development position abnormal annotation information;

[0070] S4. Obtain the shortest distance between the development position abnormal annotation information and the relay position information, and then obtain the first transportation distance of the shortest distance, determine the transportation route, and perform secondary transportation, as Figure 1 shown.

[0071] The working principle of the above technical solution is as follows: When an emergency patient needs to be transported, obtain the transportation requirement information, which includes the patient's basic information, preliminary diagnosis, current vital signs, etc. Obtain the patient evaluation and processing data generated by the doctor's evaluation and processing of the patient's condition data. Perform classification risk analysis on the patient's condition according to the evaluation and processing data, evaluate blood pressure, blood sugar, and heart rate, and perform risk annotation on each category greater than the corresponding threshold to generate condition category risk annotation information. Obtain the patient's transportation route information according to information such as the starting point, ending point, hospital layout, and traffic conditions. Preset some key nodes on the transportation route as relay positions, which may be important medical facilities, first aid stations, or traffic nodes, etc. Calculate the condition development coefficient, which reflects the trend of the patient's condition changing over time. According to the condition development coefficient, annotate the nodes where abnormal conditions may occur on the transportation route, that is, abnormal condition node annotation. Calculate the shortest distance between the development position abnormal annotation information and the relay position information, which can quickly respond to and handle abnormal conditions. Determine the optimal transportation route according to the shortest distance and perform secondary transportation to ensure that necessary medical treatment can be obtained in a timely manner when the patient has a sudden situation.

[0072] The technical effects of the above technical solution are as follows: Through automated evaluation and risk annotation, the severity of the patient's condition and the transportation requirements can be quickly identified, thereby optimizing the transportation process and improving transportation efficiency. The development of the patient's condition can be monitored in real time, and abnormal annotations can be made at key nodes, enabling timely discovery and handling of potential risks and enhancing the safety of the transportation process. According to the classification of the patient's condition and risk annotation, medical resources can be reasonably allocated, such as arranging appropriate transportation vehicles, medical staff, and first aid equipment, to ensure the efficient use of resources. Through rapid and accurate transportation and treatment, the system can reduce the waiting time and pain of patients. When the patient's condition suddenly deteriorates rapidly during transportation, the optimal relay route can be automatically generated to ensure timely treatment. The condition assessment, risk annotation, and transportation route information provided by the system can automatically generate a condition control strategy.

[0073] In one embodiment of the present invention, S1 includes:

[0074] Obtain the transportation requirement information of the patient, and trigger a patient evaluation instruction according to the transportation requirement information;

[0075] Conduct a patient condition evaluation alarm according to the patient evaluation instruction, and then obtain patient condition evaluation data;

[0076] Preprocess the patient condition evaluation data to obtain patient evaluation processed data;

[0077] Classify the patient evaluation processed data according to the preset disease types to obtain multiple types of patient condition category data;

[0078] Compare the patient condition category data with the preset category disease thresholds to obtain patient condition comparison information;

[0079] Determine the patient condition risk category according to the patient condition comparison information, and perform category risk annotation on the patient condition risk category to obtain condition category risk annotation information. When the patient condition category data is greater than the preset category disease threshold, perform category risk annotation on the patient condition risk category corresponding to the patient condition category data.

[0080] The working principle of the above technical solution is as follows: Receive transfer requests from inside or outside the medical institution, which may come from doctors, nurses, or other medical staff. The requests contain the basic information of the patient, as well as the destination and reason for the transfer. According to the received transfer requirement information, the system automatically triggers a patient assessment process. This process may include a series of standardized assessment steps for collecting information such as the patient's vital signs, medical history, and current condition. During the assessment, if the system detects abnormal vital signs or a deterioration in the patient's condition, it will automatically trigger an alarm mechanism. This can alert medical staff to pay immediate attention and take necessary first aid measures. The patient condition assessment data collected by the system may include readings of various vital signs, laboratory test results, imaging data, etc. These data need to be preprocessed, such as cleaning, formatting, and standardizing. The preprocessed data will be classified according to the preset disease types. These classifications may be based on factors such as the type of disease, severity, and treatment requirements. The classified data forms multiple types of patient condition category data. Each type of condition data will be compared with the preset category condition thresholds. These thresholds are set based on clinical experience and medical research. According to the comparison results, the system will determine the patient's condition risk category. If the patient's condition category data is greater than the preset category condition threshold, the system will label the category.

[0081] The technical effects of the above technical solution are as follows: The automated assessment process reduces the time and errors of manual assessment, improving the accuracy and efficiency of assessment. The real-time alarm mechanism can detect and respond to high-risk situations in a timely manner, ensuring that patients receive timely and effective medical care during the transfer. The system can intelligently allocate medical resources according to the patient's condition risk category, such as giving priority to the transfer and treatment of high-risk patients. By providing timely and accurate condition assessment and transfer arrangements, the system can improve patient satisfaction and trust. The condition classification and risk labeling information provided by the system can provide strong support for the clinical decision-making of medical staff. Through methods such as automated assessment, real-time alarm, intelligent classification, and risk labeling, the safety and efficiency of the patient transfer process are significantly improved, while also optimizing the allocation of medical resources and enhancing patient satisfaction.

[0082] In one embodiment of the present invention, S2 includes:

[0083] Obtain the transfer starting point information and transfer ending point information of the patient, set the patient transfer path according to the transfer starting point information and transfer ending point information with the shortest transfer time, and obtain the patient transfer path information (the patient transfer path is the path where the road is passable);

[0084] Obtain the preset transfer process nodes (such as passing hospitals) of the patient transfer path information, set the preset transfer process nodes as relay positions, and obtain multiple relay position information.

[0085] The working principle of the above technical solution is as follows: Receive or input the specific location information of the patient's transfer starting point (such as the current hospital, first aid scene, etc.) and the ending point (such as the target treatment hospital). This information can include the address, longitude and latitude coordinates, etc. Based on the obtained starting point and ending point information, the system uses path planning algorithms (such as Dijkstra algorithm, A* algorithm, etc.) to search for the path with the shortest transfer time in the current road network data. The factors considered here include road conditions, traffic flow, possible traffic control, etc., to ensure that the path is practically feasible and time-optimal. When planning the path, the passability of the road is considered, and those roads that are impassable due to construction, closure, etc. are excluded. Once the optimal path is determined, the system will output detailed transfer path information, including the roads, intersections, and estimated travel time along the way. On the transfer path, the system identifies and marks the preset transfer process nodes, which are usually locations such as hospitals and first aid stations where medical operations or handovers may be required. The system sets these nodes as relay positions. According to the distribution of nodes on the path, the system finally generates a list containing multiple relay position information. This information is of great reference value for resource scheduling, personnel arrangement, and emergency response during the transfer process.

[0086] The technical effects of the above technical solution are as follows: Through precise path planning and the application of real-time traffic information, the system can ensure that the patient is transferred from the starting point to the ending point in the shortest time, thereby improving the transfer efficiency and reducing the risks during the transfer process. The system can identify and mark the key relay positions, enabling the transfer team to perform effective medical operations or handovers at these positions, thus optimizing the allocation and use of medical resources. In case of an emergency, the system can quickly generate the optimal transfer path and relay position information, enhancing the emergency response ability. The present invention improves the intelligent and flexible level of the transfer process of medical services.

[0087] In an embodiment of the present invention, S3 includes:

[0088] Obtain the preset monitoring time node information, and obtain the patient's disease category risk annotation information and patient evaluation and treatment data at each preset monitoring time node;

[0089] Calculate the patient's disease development coefficient according to the disease category risk annotation information combined with the patient evaluation and treatment data;

[0090] The calculation formula of the patient's disease development coefficient is:

[0091]

[0092] Among them, BF is the patient's disease development coefficient, α is the preset weight data for categories, β is the preset weight data for evaluation, y is the number of risk annotations for disease categories, w is the total number of categories, and Z i is the patient's disease category data for the i-th risk annotation of the disease category, and Z a is the patient's disease category data for the a-th category, ΔB is the current evaluation change data, and P s is the initial patient evaluation data;

[0093] The initial patient evaluation data is the average value of the ratios of the actual data of all categories to the threshold.

[0094] Sort the patient's disease development coefficient according to the preset monitoring time node information to obtain the disease development time sequence;

[0095] Obtain the path position information of each preset monitoring time node, and bind the disease development time sequence to the path position information to obtain the position development binding data;

[0096] Compare each patient's disease development coefficient in the disease development time sequence with the preset development threshold in turn to obtain the disease development comparison result;

[0097] Mark the abnormal disease nodes in the disease development time sequence according to the disease development comparison result;

[0098] Obtain the patient's disease development coefficient corresponding to the first abnormal disease node annotation in the disease development time sequence;

[0099] Mark the corresponding path position information of the patient's disease development coefficient corresponding to the first abnormal disease node annotation in the position development binding data to obtain the abnormal position annotation information of the development position.

[0100] The working principle of the above technical solution is as follows: Obtain preset monitoring time nodes, which can be fixed time intervals (such as every minute or hour, etc.) or time points triggered based on specific events (presence of sudden symptoms). At each preset monitoring time node, the system collects the risk annotation information of the patient's disease category and also obtains the patient's evaluation and treatment data, such as vital sign monitoring data, laboratory test results, imaging examination reports, etc. These data are used to comprehensively evaluate the patient's health status. Combine the risk annotation information of the disease category and the patient's evaluation and treatment data to calculate the patient's disease development coefficient. This coefficient reflects the dynamic change of the patient's condition at the monitoring time node. The formula combines the consideration of the risk annotation of the disease category and the change of the patient's evaluation data through two weight coefficients, α and β, to form a comprehensive disease development coefficient (BF). The values of α and β can be adjusted according to the actual situation to balance the influence of the risk annotation of the disease category and the change of the patient's evaluation data on the disease development coefficient. The finally obtained disease development coefficient (BF) is a value between 0 and 1, which is used to quantitatively evaluate the development trend of the patient's condition. The larger the value (or the closer it is to 1), the more serious the development trend of the patient's condition; the smaller the value (or the closer it is to 0), the smoother the development trend of the patient's condition. Relatively speaking And / or the larger ΔB is, the larger the patient's disease development coefficient is; Sort the patient's disease development coefficients at each monitoring time node in chronological order to form a disease development time series. This time series shows the trend of the patient's condition changing over time. Obtain the path position information at each preset monitoring time node, which can be the actual geographical location of the patient, etc. Bind the disease development time series with the path position information to form position-development binding data. In this way, each disease development coefficient is associated with a specific path position. Compare each patient's disease development coefficient in the disease development time series with a preset development threshold. These thresholds are usually set based on clinical experience and statistical data. According to the comparison results, the system marks the disease development coefficients exceeding the threshold in the disease development time series as abnormal disease nodes. These marks indicate the time points when the patient's condition may deteriorate. Obtain and mark the position information of the first abnormal disease node: The system finds the first abnormal disease node mark in the disease development time series and obtains the corresponding patient's disease development coefficient. Search for the path position information corresponding to this disease development coefficient in the position-development binding data and perform abnormal position marking. In this way, the system determines the specific position and time when the patient's condition first appears abnormal.

[0101] The technical effects of the above technical solution are as follows: By presetting monitoring time nodes and collecting real-time data, the system can monitor the changes in the patient's condition in real time and issue an early warning in a timely manner when the condition shows abnormalities. Binding the sequence of disease development with the path location information realizes the precise positioning and tracking of the patient's condition. This can help doctors quickly understand the patient's condition and its changes in space and time. By analyzing the sequence of disease development and the location information of abnormal disease nodes, the system can provide suggestions for the allocation and scheduling of medical resources for the patient. The information on the sequence of disease development and the annotation of abnormal disease nodes provided by the system provides a comprehensive basis for doctors to evaluate the condition. This method can achieve quantitative monitoring of the disease development at each transfer location.

[0102] In one embodiment of the present invention, S4 includes:

[0103] Obtain the abnormal development location annotation information and relay location information, and calculate the shortest transportation distance between the abnormal development location annotation information and multiple relay location information;

[0104] Obtain the first transportation distance from among the multiple shortest transportation distances (the shortest distance among the multiple shortest transportation distances);

[0105] Obtain the transportation path corresponding to the first transportation distance;

[0106] Perform secondary shipment of the patient through the transportation path to obtain secondary shipment information. (Relatively speaking, due to the relatively serious condition, choose to seek medical treatment nearby).

[0107] The working principle of the above technical solution is as follows: When the system detects an abnormality in the patient's disease development, it will record and annotate this abnormal location, that is, the abnormal development location annotation information. This usually includes the specific location and time of the abnormality. The system maintains a relay location information database, and these relay locations can be the locations of key medical facilities such as first aid stations, operating rooms, and intensive care units within the hospital. These locations are possible locations for the patient to be transferred or receive further treatment. Calculate the shortest transportation distance from the location in the abnormal development location annotation information to each relay location. These distances take into account the physical layout of the traffic, etc. Among the multiple shortest transportation distances, the system identifies the shortest distance, that is, the first transportation distance, and obtains the corresponding transportation path. This path is the optimal path from the abnormal location to the nearest key medical facility. According to the obtained transportation path, medical staff perform secondary shipment of the patient, that is, transfer the patient from the abnormal location to the designated relay location). During the transfer process, the system records the detailed information of the secondary shipment, including the start and end times of the transfer, the transfer personnel, the changes in the patient's status, etc.

[0108] The technical effects of the above technical solution are as follows: By calculating the shortest transportation distance in real time and planning the optimal transportation route, the system can quickly guide medical staff to perform secondary shipment on patients, thereby shortening the response time and improving the efficiency and quality of medical services. The system can automatically select the nearest relay location for transfer, avoiding unnecessary resource waste. At the same time, by recording transfer information, the system can also provide data support for the hospital regarding the allocation and utilization of medical resources. In case of emergency, fast and accurate transfer can reduce the risks and discomfort of patients. The system helps to ensure the safety of patients during transfer by providing the optimal transportation route and secondary shipment information. The application of this system demonstrates the potential of medical informatization and intelligence. By integrating functions such as route planning, data recording, and analysis, the system provides a comprehensive, efficient, and intelligent medical management platform for the hospital. The shortest transportation distance, transportation route, and secondary shipment information provided by the system provide important decision-making support for doctors. The present invention improves the emergency response speed and optimizes the utilization of medical resources by calculating the shortest transportation distance in real time and planning the optimal transportation route.

[0109] In an embodiment of the present invention, the system includes:

[0110] A disease condition analysis and annotation module, configured to obtain transfer requirement information, evaluate and process the disease condition data of the patient to obtain patient evaluation and processing data, perform classification risk analysis and annotation on the patient evaluation and processing data to obtain disease condition category risk annotation information;

[0111] A path relay setting module, configured to obtain patient transfer path information, obtain preset transfer process nodes according to the patient transfer path information, and then generate relay positions to obtain relay position information;

[0112] A disease condition development monitoring module, configured to calculate the disease condition development coefficient of the patient, obtain the disease condition development time sequence of the patient transfer path information according to the disease condition development coefficient of the patient, perform abnormal disease condition node annotation, and then perform abnormal position annotation on the transfer path information to obtain development position abnormal annotation information;

[0113] An emergency transfer module, configured to obtain the shortest distance between the development position abnormal annotation information and the relay position information, and then obtain the first transportation distance of the shortest distance, determine the transportation route, and perform secondary transfer, as Figure 2 shown.

[0114] The working principle of the above technical solution is as follows: When an emergency patient needs to be transferred, transfer requirement information is obtained, which includes the patient's basic information, preliminary diagnosis, current vital signs, etc. The doctor is obtained to evaluate and process the patient's condition data, and the patient evaluation and processing data are generated. According to the evaluation and processing data, a classification risk analysis of the patient's condition is carried out, the blood pressure, blood sugar and heart rate are evaluated, and risk markings are made for each category greater than the corresponding threshold, generating the risk marking information for the condition category. According to information such as the starting point, ending point, hospital layout, and traffic conditions, the transfer route information of the patient is obtained. Some key nodes are preset on the transfer route as relay positions, which may be important medical facilities, first aid stations, or traffic nodes, etc. The disease development coefficient is calculated, which reflects the trend of the patient's condition changing over time. According to the disease development coefficient, nodes where abnormal conditions may occur are marked on the transfer route, that is, abnormal condition node marking. The shortest distance between the development position abnormal marking information and the relay position information is calculated, which can quickly respond to and handle abnormal conditions. The optimal transportation route is determined according to the shortest distance for secondary transfer to ensure that necessary medical treatment can be obtained in a timely manner when an emergency occurs to the patient.

[0115] The technical effects of the above technical solution are as follows: Through automated evaluation and risk marking, the severity of the patient's condition and transfer requirements can be quickly identified, thereby optimizing the transfer process and improving transfer efficiency. The development of the patient's condition can be monitored in real time, and abnormal markings are made at key nodes, which can timely detect and handle potential risks and enhance the safety of the transfer process. According to the classification and risk marking of the patient's condition, medical resources can be reasonably allocated, such as arranging appropriate transfer vehicles, medical staff, and first aid equipment to ensure the efficient use of resources. Through fast and accurate transfer and treatment, the system can reduce the waiting time and pain of the patient. When the patient's condition suddenly deteriorates rapidly during the transfer process, the optimal relay route can be automatically generated to ensure timely treatment. The condition evaluation, risk marking, and transfer route information provided by the system can automatically generate a condition control strategy.

[0116] In an embodiment of the present invention, the condition analysis and marking module includes:

[0117] A condition evaluation and processing module, configured to obtain the transfer requirement information of the patient, and trigger a patient evaluation instruction according to the transfer requirement information;

[0118] Perform a patient condition evaluation and alarm according to the patient evaluation instruction, and further obtain the patient condition evaluation data;

[0119] Preprocess the patient condition evaluation data to obtain patient evaluation and processing data;

[0120] A classification and comparison annotation module, which is used to classify the patient assessment and treatment data according to the preset disease types, and obtain patient disease category data of multiple types;

[0121] Compare the patient disease category data with the preset category disease threshold to obtain patient disease comparison information;

[0122] Determine the patient disease risk category according to the patient disease comparison information, and perform category risk annotation on the patient disease risk category to obtain disease category risk annotation information. When the patient disease category data is greater than the preset category disease threshold, perform category risk annotation on the patient disease risk category corresponding to the patient disease category data.

[0123] The working principle of the above technical solution is as follows: Receive transfer requests from inside or outside the medical institution. These requests may come from doctors, nurses or other medical staff. The requests contain the basic information of the patient, as well as the destination and reason for the transfer. According to the received transfer requirement information, the system automatically triggers a patient assessment process. This process may include a series of standardized assessment steps for collecting information such as the patient's vital signs, medical history, current condition, etc. During the assessment, if the system detects that one or more of the patient's vital signs are abnormal or the condition deteriorates, it will automatically trigger an alarm mechanism. This can remind the medical staff to pay attention immediately and take necessary first aid measures. The patient condition assessment data collected by the system may include readings of various vital signs, laboratory test results, imaging data, etc. These data need to be preprocessed, such as cleaning, formatting, standardization, etc. The preprocessed data will be classified according to the preset disease types. These classifications may be based on factors such as the type of disease, severity, treatment needs, etc. The classified data forms patient disease category data of multiple types. Each type of disease data will be compared with the preset category disease threshold. These thresholds are set based on clinical experience and medical research. According to the comparison results, the system will determine the patient's disease risk category. If the patient's disease category data is greater than the preset category disease threshold, the system will mark the category.

[0124] The technical effects of the above technical solution are as follows: The automated evaluation process reduces the time and errors of manual evaluation, improving the accuracy and efficiency of evaluation. The real-time alarm mechanism can detect and respond to high-risk situations in a timely manner, ensuring that patients receive timely and effective medical care during transportation. The system can intelligently allocate medical resources according to the risk category of the patient's condition, such as giving priority to arranging the transportation and treatment of high-risk patients. By providing timely and accurate condition evaluation and transportation arrangements, the system can improve patients' satisfaction and trust. The condition classification and risk annotation information provided by the system can provide strong support for the clinical decision-making of medical staff. Through methods such as automated evaluation, real-time alarm, intelligent classification, and risk annotation, the safety and efficiency of the patient transportation process are significantly improved, while the allocation of medical resources is optimized and patients' satisfaction is enhanced.

[0125] In one embodiment of the present invention, the path relay setting module includes:

[0126] A path information acquisition module, configured to acquire the transfer starting point information and transfer ending point information of the patient, set the patient transfer path according to the transfer starting point information and transfer ending point information according to the shortest transfer time, and acquire the patient transfer path information (the patient transfer path is a path where the road is passable);

[0127] A relay position determination module, configured to acquire the preset transfer process nodes (such as passing hospitals, etc.) of the patient transfer path information, set the preset transfer process nodes as relay positions, and obtain a plurality of relay position information.

[0128] The working principle of the above technical solution is as follows: Receive or input the specific location information of the transfer starting point (such as the current hospital, first aid scene, etc.) and ending point (such as the target treatment hospital) of the patient. This information can include addresses, longitude and latitude coordinates, etc. Based on the acquired starting point and ending point information, the system uses path planning algorithms (such as Dijkstra algorithm, A* algorithm, etc.) to search for the path with the shortest transfer time in the current road network data. The factors considered here include road conditions, traffic flow, possible traffic control, etc., to ensure that the path is actually feasible and time-optimal. When planning the path, the passability of the road is considered, and those roads that are impassable due to construction, closure, etc. are excluded. Once the optimal path is determined, the system will output detailed transfer path information, including the roads, intersections, and estimated travel time passed. On the transfer path, the system identifies and marks the preset transfer process nodes, which are usually locations such as hospitals and first aid stations where medical operations or handovers may be required. The system sets these nodes as relay positions. According to the node distribution on the path, the system finally generates a list containing a plurality of relay position information. This information has important reference value for resource scheduling, personnel arrangement, and emergency response during the transfer process.

[0129] The technical effects of the above technical solution are as follows: Through precise path planning and the application of real-time traffic information, the system can ensure that patients are transported from the starting point to the ending point in the shortest time, thereby improving the transportation efficiency and reducing the risks during transportation. The system can identify and mark key relay positions, enabling the transportation team to perform effective medical operations or handovers at these positions, thus optimizing the allocation and use of medical resources. In case of emergencies, the system can quickly generate the optimal transportation path and relay position information, enhancing the emergency response ability. The present invention improves the intelligence and flexibility levels of the transportation process of medical services.

[0130] In one embodiment of the present invention, the disease development monitoring module includes:

[0131] A disease development analysis module, configured to obtain preset monitoring time node information, and obtain the disease category risk annotation information and patient evaluation and treatment data of the patient at each preset monitoring time node;

[0132] Calculate the patient's disease development coefficient according to the disease category risk annotation information in combination with the patient evaluation and treatment data;

[0133] A development time sequence acquisition module, configured to sort the patient's disease development coefficients according to the preset monitoring time node information to obtain a disease development time sequence;

[0134] A disease position binding module, configured to obtain the path position information at each preset monitoring time node, and bind the disease development time sequence with the path position information to obtain position development binding data;

[0135] A disease comparison annotation module, configured to sequentially compare each patient's disease development coefficient in the disease development time sequence with a preset development threshold to obtain a disease development comparison result;

[0136] Perform abnormal disease node annotation on the disease development time sequence according to the disease development comparison result;

[0137] Obtain the patient's disease development coefficient corresponding to the first abnormal disease node annotation in the disease development time sequence;

[0138] The calculation formula of the patient's disease development coefficient is:

[0139]

[0140] Where BF is the patient's disease development coefficient, α is the preset weight data for categories, β is the preset weight data for evaluation, y is the number of disease category risk annotations, w is the total number of categories, Z i is the patient's disease category data for the i-th disease category risk annotation, Z a is the patient's disease category data for the a-th category, and ΔB is the current evaluation change data, Ps is the initial patient assessment data;

[0141] A position anomaly annotation module, which is used to perform anomaly position annotation on the corresponding path position information of the patient's disease development coefficient marked by the first abnormal disease condition node in the position development binding data, and obtain the development position anomaly annotation information.

[0142] The working principle of the above technical solution is as follows: Obtain preset monitoring time nodes, which can be fixed time intervals (such as every minute or hour, etc.) or time points triggered based on specific events. At each preset monitoring time node, the system collects the risk annotation information of the patient's disease category, and also obtains the patient's assessment and treatment data, such as vital sign monitoring data, laboratory test results, imaging examination reports, etc. These data are used to comprehensively evaluate the patient's health status. Combine the risk annotation information of the disease category and the patient's assessment and treatment data to calculate the patient's disease development coefficient. This coefficient reflects the dynamic change of the patient's disease condition at the monitoring time node. Sort the patient's disease development coefficients at each monitoring time node in chronological order to form a disease development time sequence. This time sequence shows the trend of the patient's disease condition changing over time. Obtain the path position information at each preset monitoring time node, which can be the actual geographical location of the patient, etc. Bind the disease development time sequence with the path position information to form position development binding data. In this way, each disease development coefficient is associated with a specific path position. Compare each patient's disease development coefficient in the disease development time sequence with a preset development threshold. These thresholds are usually set based on clinical experience and statistical data. According to the comparison results, the system marks the disease development coefficients exceeding the threshold in the disease development time sequence as abnormal disease condition nodes. These marks indicate the time points when the patient's disease condition may deteriorate. Obtain and mark the position information of the first abnormal disease condition node: The system finds the first abnormal disease condition node mark in the disease development time sequence, and obtains the corresponding patient's disease development coefficient. Search for the path position information corresponding to this disease development coefficient in the position development binding data and perform abnormal position annotation. In this way, the system determines the specific position and time when the patient's disease condition first appears abnormal.

[0143] The technical effects of the above technical solution are as follows: By presetting the monitoring time nodes and collecting real-time data, the system can monitor the changes in the patient's condition in real time and issue early warnings in a timely manner when the condition shows abnormalities. Binding the time sequence of the disease development with the path location information realizes the accurate positioning and tracking of the patient's condition. This can help doctors quickly understand the patient's condition status and its changes in space and time. By analyzing the time sequence of the disease development and the location information of abnormal disease nodes, the system can provide suggestions for the allocation and scheduling of medical resources for the patient. The time sequence of the disease development and the annotation information of abnormal disease nodes provided by the system provide a comprehensive basis for doctors to evaluate the condition. This method can realize the quantitative monitoring of the disease development at each transfer location.

[0144] In one embodiment of the present invention, the emergency transfer module includes:

[0145] A transportation distance comparison module, configured to obtain the abnormal development location annotation information and the relay location information, and calculate the shortest transportation distance between the abnormal development location annotation information and multiple relay location information;

[0146] An optimal path transfer module, configured to obtain the first transportation distance (the shortest distance among multiple shortest transportation distances) from multiple shortest transportation distances;

[0147] Obtain the transportation path corresponding to the first transportation distance;

[0148] Perform a secondary shipment of the patient through the transportation path to obtain secondary shipment information (relatively speaking, choose to seek medical treatment nearby due to the serious condition).

[0149] The working principle of the above technical solution is as follows: When the system detects an abnormality in the patient's disease development, it will record and mark this abnormal location, that is, the abnormal development location annotation information. This usually includes the specific location and time of the abnormality. The system maintains a relay location information database, and these relay locations can be the locations of key medical facilities such as first aid stations, operating rooms, and intensive care units within the hospital. These locations are possible places for the patient to be transferred or receive further treatment. Calculate the shortest transportation distance from the location in the abnormal development location annotation information to each relay location. These distances consider the physical layout of the traffic, etc. Among multiple shortest transportation distances, the system identifies the shortest distance, that is, the first transportation distance, and obtains the corresponding transportation path. This path is the optimal path from the abnormal location to the nearest key medical facility. According to the obtained transportation path, medical staff perform a secondary shipment of the patient, that is, transfer the patient from the abnormal location to the designated relay location. During the transfer process, the system records the detailed information of the secondary shipment, including the start and end times of the transfer, the transfer personnel, and the changes in the patient's status, etc.

[0150] The technical effects of the above technical solution are as follows: By calculating the shortest transportation distance in real time and planning the optimal transportation route, the system can quickly guide medical staff to perform secondary shipment on patients, thereby shortening the response time and improving the efficiency and quality of medical services. The system can automatically select the nearest relay location for transfer, avoiding unnecessary resource waste. At the same time, by recording transfer information, the system can also provide data support for the hospital regarding the allocation and utilization of medical resources. In case of an emergency, rapid and accurate transfer can reduce the risks and discomfort of patients. The system helps ensure the safety of patients during transfer by providing the optimal transportation route and secondary shipment information. The application of this system demonstrates the potential of medical informatization and intelligence. By integrating functions such as route planning, data recording, and analysis, the system provides a comprehensive, efficient, and intelligent medical management platform for the hospital. The shortest transportation distance, transportation route, and secondary shipment information provided by the system offer important decision-making support for doctors. The present invention improves the emergency response speed and optimizes the utilization of medical resources by calculating the shortest transportation distance in real time and planning the optimal transportation route.

[0151] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A method for monitoring the condition of an emergency patient during transport, characterized in that: The method comprises: S1. Obtain transfer demand information, evaluate and process the patient's condition data, obtain patient evaluation and processing data, perform classification risk analysis and labeling on the patient evaluation and processing data, and obtain condition category risk labeling information; S2. Obtain patient transfer path information, obtain preset transfer process nodes according to the patient transfer path information, and then generate a relay position to obtain relay position information; S3. Calculate the patient's disease progression coefficient, obtain the disease progression time sequence of the patient's transfer path information according to the patient's disease progression coefficient, mark abnormal disease nodes, and then mark abnormal positions of the transfer path information to obtain abnormal development position marking information; S4. Obtain the shortest distance between the abnormal marking information of the development position and the relay position information, and then obtain the shortest first transportation distance, determine the transportation path, and perform secondary transfer.

2. A method for monitoring the condition of an emergency patient during transport according to claim 1, characterized in that: The S1 includes: Acquire the patient's transfer requirement information, and trigger a patient assessment instruction according to the transfer requirement information; Perform patient condition assessment alarm according to patient assessment instructions, and then obtain patient condition assessment data; Preprocessing the patient condition assessment data to obtain patient assessment processing data; Classifying the patient assessment and processing data according to preset disease categories to obtain multiple types of patient disease category data; Compare the patient's condition category data with a preset condition category threshold to obtain patient condition comparison information; The patient's condition risk category is determined according to the patient's condition comparison information, and the patient's condition risk category is labeled with a category risk to obtain condition category risk labeling information.

3. A method for monitoring the condition of an emergency patient during transport according to claim 1, characterized in that: The S2 includes: Acquire the patient's transfer starting point information and transfer end point information, set the patient's transfer path according to the shortest transfer time based on the transfer starting point information and transfer end point information, and acquire the patient's transfer path information; A preset transfer process node of the patient transfer path information is obtained, the preset transfer process node is set as a relay position, and a plurality of relay position information is obtained.

4. The method for monitoring the condition of an emergency patient during transportation according to claim 1, characterized in that: The S3 includes: Obtain the preset monitoring time node information, and obtain the patient's condition category risk labeling information and patient assessment and processing data at each preset monitoring time node; Calculate the patient's disease progression coefficient based on the disease category risk labeling information combined with the patient assessment processing data; Sorting the patient's disease progression coefficient according to preset monitoring time node information to obtain a disease progression time sequence; Obtaining the path location information of each preset monitoring time node, binding the disease progression time sequence with the path location information, and obtaining location progression binding data; Compare the disease progression coefficient of each patient in the disease progression time series with the preset progression threshold in sequence to obtain a disease progression comparison result; Marking abnormal disease nodes in the disease progression time sequence according to the disease progression comparison result; Obtain the patient's disease progression coefficient corresponding to the first abnormal disease node label in the disease progression time series; The corresponding path position information of the patient's condition development coefficient corresponding to the first abnormal condition node mark in the position development binding data is marked with an abnormal position to obtain the development position abnormal marking information.

5. The method for monitoring the condition of an emergency patient during transportation according to claim 1, characterized in that: The S4 includes: Obtaining development position abnormality marking information and relay position information, and calculating the shortest transportation distance between the development position abnormality marking information and multiple relay position information; Obtaining a first transport distance from a plurality of shortest transport distances; Acquire a transportation path corresponding to the first transportation distance; The patient is re-shipped via the transport path to obtain re-shipping information.

6. A condition monitoring system for emergency patient transfer process, characterized in that: The system comprises: The condition analysis and annotation module is used to obtain transfer demand information, evaluate and process the patient's condition data, obtain patient evaluation and processing data, perform classification risk analysis and annotation on the patient evaluation and processing data, and obtain condition category risk annotation information; A path relay setting module is used to obtain patient transfer path information, obtain preset transfer process nodes according to the patient transfer path information, and then generate a relay position to obtain relay position information; The disease progression monitoring module is used to calculate the disease progression coefficient of the patient, obtain the disease progression time sequence of the patient's transfer path information according to the disease progression coefficient, mark abnormal disease nodes, and then mark abnormal positions of the transfer path information to obtain abnormal marking information of the development position; The emergency transfer module is used to obtain the shortest distance between the abnormal location marking information and the relay location information, and then obtain the shortest first transportation distance, determine the transportation path, and perform secondary transfer.

7. A condition monitoring system for emergency patient transfer according to claim 6, characterized in that: The disease analysis and annotation module includes: A condition assessment processing module is used to obtain the patient's transfer requirement information and trigger a patient assessment instruction according to the transfer requirement information; Perform patient condition assessment alarm according to patient assessment instructions, and then obtain patient condition assessment data; Preprocessing the patient condition assessment data to obtain patient assessment processing data; A classification, comparison and annotation module is used to classify the patient assessment and processing data according to preset disease types to obtain multiple types of patient disease category data; Compare the patient's condition category data with a preset condition category threshold to obtain patient condition comparison information; The patient's condition risk category is determined according to the patient's condition comparison information, and the patient's condition risk category is labeled with a category risk to obtain condition category risk labeling information.

8. The condition monitoring system for emergency patient transfer process according to claim 6, characterized in that: The path relay setting module includes: A path information acquisition module is used to acquire the patient's transfer starting point information and transfer end point information, set the patient's transfer path according to the shortest transfer time based on the transfer starting point information and transfer end point information, and acquire the patient's transfer path information; The relay position determination module is used to obtain a preset transfer process node of the patient transfer path information, set the preset transfer process node as a relay position, and obtain multiple relay position information.

9. A condition monitoring system for emergency patient transfer according to claim 6, characterized in that: The disease progression monitoring module comprises: The disease progression analysis module is used to obtain information on preset monitoring time nodes, and obtain the patient's disease category risk labeling information and patient assessment and processing data at each preset monitoring time node; Calculate the patient's disease progression coefficient based on the disease category risk labeling information combined with the patient assessment processing data; A development time sequence acquisition module is used to sort the patient's disease progression coefficient according to preset monitoring time node information to obtain a disease progression time sequence; A disease position binding module is used to obtain the path position information of each preset monitoring time node, bind the disease development time sequence with the path position information, and obtain position development binding data; The disease condition comparison and annotation module is used to compare the disease condition development coefficient of each patient in the disease condition development time series with the preset development threshold in turn to obtain the disease condition development comparison result; Marking abnormal disease nodes in the disease progression time sequence according to the disease progression comparison result; Obtain the patient's disease progression coefficient corresponding to the first abnormal disease node label in the disease progression time series; The position abnormality marking module is used to mark the abnormal position of the corresponding path position information of the patient's disease progression coefficient corresponding to the first abnormal disease node marking in the position development binding data, and obtain the development position abnormality marking information.

10. A condition monitoring system for emergency patient transfer according to claim 6, characterized in that: The emergency transport module comprises: A transport distance comparison module is used to obtain the development position abnormality marking information and the relay position information, and calculate the shortest transport distance between the development position abnormality marking information and multiple relay position information; An optimal path transfer module, used for obtaining a first transport distance from a plurality of shortest transport distances; Acquire a transportation path corresponding to the first transportation distance; The patient is re-shipped via the transport path to obtain re-shipping information.

Images