Integrated intelligent medical guide management method and system

Abstract

The present invention discloses an integrated intelligent medical guide management method and system, which relates to data processing related fields. The method includes: transmitting action suggestion information to a target workstation, setting multiple service nodes based on the target workstation, and triggering a medical guide service evaluator if the service progress information of the service node reaches a critical threshold, generating a service feedback information set to automatically combine and adjust the multiple service nodes, optimizing the action suggestion information, and realizing the integrated management of intelligent medical guides. The technical problem of incorrect guidance due to insufficient manpower and lack of professional knowledge of medical guides, resulting in untimely service response and reduced medical efficiency of patients is solved, and the technical effect of accurately and quickly providing medical guide services to patients through intelligent medical guide services, reducing patients' waiting time and ineffective flow, and improving the operating efficiency of hospitals is achieved.

Description

Technical Field

[0001] The present application relates to data processing related fields, and in particular to an integrated intelligent medical guide management method and system. Background Art

[0002] With the rapid development of medical information and intelligent technology, medical guide management covers many aspects such as the training of medical guides, optimization of service processes, and construction of information systems, aiming to improve the professionalism and efficiency of medical guide services and provide patients with a more convenient and personalized medical experience. Through medical guide management, hospitals can achieve intelligent guidance of patients' medical processes. Traditional medical guide management methods can no longer meet the efficient and convenient service requirements of modern hospitals.

[0003] There are technical problems in the existing technology that due to insufficient manpower and lack of professional knowledge of medical guides, incorrect guidance results in untimely service response and reduced patient medical efficiency. Summary of the invention

[0004] This application solves the technical problem of incorrect guidance due to insufficient manpower and lack of professional knowledge of medical guides, resulting in untimely service response and reduced patient medical efficiency by providing an integrated intelligent medical guide management method and system. It achieves the technical effect of providing patients with accurate and fast medical guidance services through intelligent medical guide services, reducing patients' waiting time and ineffective flow, and improving the hospital's operating efficiency.

[0005] The present application provides an integrated smart medical guide management method, which is applied to an integrated smart medical guide management system, including: receiving medical data of a target user, generating action suggestion information according to the medical data combined with the medical needs of the target user;

[0006] Transmitting the action suggestion information to a target workstation, and setting a plurality of service nodes based on the target workstation;

[0007] Acquire service progress information of the plurality of service nodes, and determine whether the service progress information of the service nodes reaches a critical threshold;

[0008] If the service progress information of the service node reaches the critical threshold, a medical guide service evaluator is triggered, and a service feedback information set is generated based on the target user providing service feedback to the service node through the medical guide service evaluator;

[0009] The multiple service nodes are automatically combined and adjusted according to the service feedback information set, and the action suggestion information is optimized to achieve integrated management of smart medical guidance.

[0010] In a possible implementation, medical data of a target user is received, action suggestion information is generated according to the medical data combined with the medical needs of the target user, and the following processing is performed:

[0011] Analyze the medical data by using data mining, and determine the medical information set of the target user based on the medical data analysis results, wherein the medical information set includes the disease development trend and historical medical treatment of the target user;

[0012] Obtaining the target user's medical needs based on the disease development trend;

[0013] Based on the medical needs, planning the medical process of the target user according to the medical data and the historical medical conditions;

[0014] Identify multiple medical treatment locations according to the medical treatment process and generate a medical treatment route;

[0015] The action suggestion information is generated based on the medical consultation route and the medical consultation process.

[0016] In a possible implementation, the action suggestion information is transmitted to a target workstation, a plurality of service nodes are set based on the target workstation, and the following processing is performed: the target workstation is determined according to the end point of the medical treatment route in the action suggestion information, and the action suggestion information is received through the target workstation;

[0017] Extract the workflow record log of the target workstation;

[0018] Based on the workflow record log and the medical treatment needs, multiple managers are matched to determine a management work data set;

[0019] The plurality of service nodes are obtained based on the partitioning of the management work data set, and a monitoring mechanism is deployed by traversing the plurality of service nodes.

[0020] In a possible implementation, service progress information of the multiple service nodes is obtained, and it is determined whether the service progress information of the service nodes reaches a critical threshold, and the following processing is performed: a plurality of monitoring data is obtained through a monitoring mechanism of the multiple service nodes, and the plurality of monitoring data includes service status information and service progress information of each service node;

[0021] Continuously tracking the service progress information of the multiple service nodes based on the service status information to generate first progress tracking distance data;

[0022] Determine the service full process distance data based on the service progress information of the multiple service nodes;

[0023] Subtracting the first progress tracking distance data from the service full process distance data to obtain a distance difference;

[0024] Determine whether the distance difference is less than a preset distance interval. If it is greater, it is deemed that the service progress information of the service node has not reached the critical threshold, and a progress tracking instruction is generated to track the service progress information for secondary calculation, and generate second progress tracking distance data, thereby iterating until the distance difference is less than the preset distance interval.

[0025] In a possible implementation, if the service progress information of the service node reaches the critical threshold, a medical guide service evaluator is triggered, and based on the target user providing service feedback to the service node through the medical guide service evaluator, a service feedback information set is generated, and the following processing is performed: if the distance difference is less than the preset distance interval, it is deemed that the service progress information of the service node has reached the critical threshold;

[0026] If the service progress information of the service node reaches a critical threshold, the medical guide service evaluator is triggered;

[0027] The target user uses the medical guide service evaluator to provide feedback to the service node, thereby generating a plurality of feedback evaluation data;

[0028] The plurality of feedback evaluation data are stored offline according to the evaluation levels and in combination with the workstation location information of the service node to generate an offline medical guidance database;

[0029] The service feedback information set is extracted based on the offline medical guide database.

[0030] In a possible implementation, the plurality of feedback evaluation data are stored offline according to the evaluation levels and in combination with the workstation location information of the service node, and an offline medical guide database is generated, and the following processing is performed: the workstation location information of the plurality of service nodes is entered based on an offline map of the target medical area, and an offline map of the workstation is obtained;

[0031] Retrieving historical feedback evaluation data for cluster analysis, and generating the evaluation level according to the cluster analysis results;

[0032] Classifying the plurality of feedback evaluation data according to the evaluation levels to generate a plurality of feedback evaluation categories, wherein the plurality of feedback evaluation categories are associated with the workstation location information of the plurality of service nodes in the workstation offline graph;

[0033] Based on the workstation offline graph, the plurality of feedback evaluation data are regularly integrated according to the plurality of feedback evaluation categories to generate the offline medical guidance database.

[0034] In a possible implementation, the plurality of service nodes are automatically combined and adjusted according to the service feedback information set, the action suggestion information is optimized, and the following processing is performed: data analysis is performed on the service feedback information set to generate service expectation information and service demand information of the target user;

[0035] Taking the service expectation information as an adjustment target, traversing the service demand information, automatically combining and adjusting the multiple service nodes, and generating user preference information;

[0036] The action suggestion information is optimized according to the user preference information.

[0037] The present application also provides an integrated intelligent medical guide management system, including: an information generation module, the information generation module is used to receive medical data of a target user, and generate action suggestion information according to the medical data combined with the medical needs of the target user;

[0038] A service node acquisition module, the service node acquisition module is used to transmit the action suggestion information to a target workstation, and set a plurality of service nodes based on the target workstation;

[0039] A first judgment module, the first judgment module is used to obtain the service progress information of the multiple service nodes, and judge whether the service progress information of the service node reaches a critical threshold;

[0040] a second judgment module, wherein the second judgment module is configured to trigger a medical guidance service evaluator if the service progress information of the service node reaches the critical threshold, and generate a service feedback information set based on the service feedback of the target user to the service node through the medical guidance service evaluator;

[0041] The integrated management module is used to automatically combine and adjust the multiple service nodes according to the service feedback information set, optimize the action suggestion information, and realize the integrated management of the smart medical guide.

[0042] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0043] The integrated intelligent medical guide management method and system provided in this application relates to the field of data processing technology. It solves the technical problem that insufficient manpower and lack of professional knowledge of medical guides lead to incorrect guidance, resulting in untimely service response and reduced patient medical efficiency. It achieves the technical effect of providing patients with accurate and rapid medical guidance services through intelligent medical guide services, reducing patients' waiting time and ineffective flow, and improving the hospital's operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0045] Figure 1 A flowchart of an integrated intelligent medical guide management method provided in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of the structure of the integrated intelligent medical guide management system provided in the embodiment of the present application. DETAILED DESCRIPTION

[0047] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0048] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0049] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0050] The embodiment of the present application provides an integrated intelligent medical guide management method, which is applied to an integrated intelligent medical guide management system, such as Figure 1As shown, the method includes:

[0051] Step A100, receiving medical data of a target user, and generating action suggestion information according to the medical data and the medical needs of the target user; in a possible implementation, step A100 further includes executing step A110, analyzing the medical data by using data mining, and determining a medical information set of the target user based on the medical data analysis result, wherein the medical information set includes the disease development trend and historical medical conditions of the target user;

[0052] First, the target user's medical data is collected from the hospital's information system, electronic medical records, test reports, medical images and other sources. The collected medical data can include the patient's personal information, medical history, diagnosis results, treatment plans, medication records, etc. Then, according to the purpose of the analysis and the characteristics of the data, time series analysis, regression analysis, machine learning and other algorithms can be used to predict the target user's disease development trend. At the same time, association rule mining, cluster analysis and other data mining algorithms can be used to analyze historical medical conditions to predict the target user's possible future disease development trend, such as the probability of disease occurrence, the speed of disease progression, etc. At the same time, by mining historical medical data, the target user's medical habits, disease type, treatment effect and other information can be obtained.

[0053] Execute step A120 to obtain the medical treatment needs of the target user according to the disease development trend; execute step A130 to plan the medical treatment process of the target user based on the medical treatment needs, according to the medical data and the historical medical treatment situation;

[0054] According to the disease development trend obtained above, combined with the personal situation of the target user, whose personal situation may be age, gender, occupation, living habits, etc., the potential medical needs of the target user are identified. The identified medical needs may include further diagnosis, treatment plan adjustment, specialist consultation, surgery appointment and other needs for the target user. The historical medical records of regional target users may include relevant information of the target user's historical medical treatment, such as diagnosis department, doctor, examination items, treatment plan, etc. Further analysis of historical medical treatment situations, the medical habits, preferences and treatment effects of the target user are obtained, and the medical treatment process of the target user is planned based on the medical needs and historical medical treatment situations. The planned medical treatment process refers to determining the target user's diagnosis department, doctor and consultation time, and trying to arrange experts who match the target user's disease development trend for diagnosis and treatment.

[0055] Execute step A140, identify multiple medical treatment locations according to the medical treatment process, and generate a medical treatment route; execute step A150, generate the action suggestion information based on the medical treatment route and the medical treatment process.

[0056] Analyze the medical treatment process to determine the specific medical treatment locations such as departments, examination rooms, and pharmacies that the target users need to visit. You can assign a unique identifier to each medical treatment location in the hospital's electronic map or information system, and use the hospital's map information to plan the path from the starting point to the end point as the medical treatment route based on the sequence of medical treatment locations in the medical treatment process. Finally, integrate the generated medical treatment route with the medical treatment process to ensure that each medical treatment location corresponds to the corresponding step in the process, thereby generating action suggestion information for the target user.

[0057] Execute step A200, transmit the action suggestion information to the target workstation, and set a plurality of service nodes based on the target workstation;

[0058] In a possible implementation, step A200 further includes step A210, determining a target workstation according to the destination of the medical treatment route in the action suggestion information, and receiving the action suggestion information through the target workstation; executing step A220, extracting the workflow record log of the target workstation; executing step A230, matching multiple managers based on the workflow record log and the medical treatment needs, and determining a management work data set;

[0059] The destination of the medical route in the action suggestion information is analyzed, and the specific workstation corresponding to the destination, such as the department, examination room, pharmacy, etc., is determined as the target workstation. At the same time, the action suggestion information generated above is received through the target workstation, and there is a corresponding workflow record log in the target workstation. The workflow record log can include the workflow, personnel activities, equipment usage, etc. in the target workstation, and then some record data related to the medical needs of the target user are extracted in the workflow record, and the work experience, professional ability and time arrangement of the manager are analyzed according to the medical needs to determine the type and number of managers required to provide medical services to the target user. At the same time, the information of the matched managers is integrated into a data set recorded as a management work data set. The management work data set includes the identity information, scope of responsibilities, etc. of the managers, which can be used for subsequent management and scheduling work, such as notifying the managers to prepare to receive the target users, arrange assistance work, etc.

[0060] Execute step A240 to obtain the multiple service nodes based on the management work data set partition, and traverse the multiple service nodes to deploy a monitoring mechanism.

[0061] Based on the information in the management work data set, the service process is divided into multiple service nodes. The multiple service nodes can be a specific department, examination room, window, ward, etc. in the hospital, or a specific service link, such as registration, medication, payment, etc., and each service node should have clear responsibilities, service content and quality standards. Further detailed analysis is conducted on each service node to obtain information such as the workflow, staffing, equipment usage, service time, etc. of each service node. The monitoring mechanism is deployed according to the characteristics and needs of the service node. The deployed monitoring mechanism may include video monitoring, audio monitoring, real-time data monitoring, etc. At the same time, the frequency, scope and method of monitoring are determined to ensure that the operation of the service node can be fully and accurately grasped.

[0062] Execute step A300, obtain the service progress information of the multiple service nodes, and determine whether the service progress information of the service nodes reaches a critical threshold; in a possible implementation, step A300 further includes step A310, obtain multiple monitoring data through the monitoring mechanism of the multiple service nodes, and the multiple monitoring data include service status information and service progress information of each service node; execute step A320, continuously track the service progress information of the multiple service nodes based on the service status information, and generate first progress tracking distance data;

[0063] Start a monitoring mechanism for multiple service nodes, and collect multiple monitoring data of each service node in real time or periodically. The multiple monitoring data may include service status information (such as idle, busy, faulty, etc.) and service progress information (such as completed workload, estimated completion time, etc.) of each service node. Then, the current status of each service node is judged according to the service status information. If the service node is in a faulty state, the fault handling process is triggered, and the service node is temporarily removed from the progress tracking. The starting node and the ending node of each service node of the multiple service nodes are obtained. At the same time, according to the service progress information, the process of each service node from the starting point to the ending point is continuously tracked. The ratio of the completed workload to the total workload in each service node can be calculated, and the remaining workload ratio can be obtained by subtracting this ratio from 1, which will be recorded as the first progress tracking distance data. The first progress tracking distance data is used to represent the distance between the service process and the ending node.

[0064] Execute step A330 to determine the service full process distance data based on the service progress information of the multiple service nodes; execute step A340 to subtract the first progress tracking distance data from the service full process distance data to obtain a distance difference value;

[0065] Taking service time or service workload as a quantitative indicator, the service full process distance data is defined according to the service progress of multiple service nodes, that is, the distance between the starting point and the end point of the service process after the service is completed is identified according to the quantitative indicator. For example, if the service full process distance is based on time, then it may be the total length of time from the start of the service to the completion of the service. If it is based on workload, then it may be the total number of tasks or operations required to be completed from the start to the completion, and it is necessary to ensure that the first progress tracking distance data and the service full process distance data use the same measurement unit for comparison. Further, the first progress tracking distance data is subtracted from the service full process distance data to obtain the distance difference, which represents the remaining distance or remaining time from the current service node to the completion of the service full process.

[0066] Execute step A350 to determine whether the distance difference is less than the preset distance interval. If it is greater, it is deemed that the service progress information of the service node has not reached the critical threshold, and a progress tracking instruction is generated to track the service progress information for secondary calculation to generate second progress tracking distance data, thereby iterating until the distance difference is less than the preset distance interval.

[0067] First, a preset distance interval is defined, and the preset distance interval is obtained by demarcating the distance between the end node and the previous service node. Then, it is determined whether the distance difference obtained by the above calculation is less than the preset distance interval. When the distance difference is greater than the critical threshold, the system generates a progress tracking instruction. The progress tracking instruction may include information such as the progress indicator and tracking frequency that the service node needs to track. According to the progress tracking instruction, the system starts to track the service progress information of the service node. After a preset time interval or when a specific condition is met, the progress tracking distance data of the current service node is calculated again, that is, the second progress tracking distance data. On this basis, the new distance difference is continuously compared with the critical threshold until the distance difference is less than the preset distance interval.

[0068] Execute step A400, if the service progress information of the service node reaches the critical threshold, trigger the medical guide service evaluator, and generate a service feedback information set based on the service feedback of the target user to the service node through the medical guide service evaluator; in a possible implementation, step A400 further includes step A410, if the distance difference is less than the preset distance interval, it is deemed that the service progress information of the service node has reached the critical threshold; execute step A420, if the service progress information of the service node reaches the critical threshold, trigger the medical guide service evaluator; execute step A430, by the target user using the medical guide service evaluator to provide feedback to the service node, generate multiple feedback evaluation data;

[0069] When the distance difference is less than the preset distance interval, it is judged that the service progress of the service node has reached the critical threshold, that is, the current service node enters the end process, and the medical guide service evaluator is triggered at the same time. The medical guide service evaluator can be an online form, an evaluation function in a mobile application, an electronic touch screen or other tools suitable for collecting user feedback. When the service in the service node is about to be completed or has been completed, the target user can be prompted to use the medical guide service evaluator in various ways such as sending text messages, pushing application notifications, and displaying prompt information on the screen. At the same time, the target user can use the medical guide service evaluator to provide feedback on the current service node that is about to be completed or has been completed according to the prompt, thereby generating multiple feedback evaluation data. The multiple feedback evaluation data may include the target user's score, text evaluation, suggestion or complaint on the service quality of the current service node.

[0070] Execute step A440, store the multiple feedback evaluation data offline according to the evaluation level and in combination with the workstation location information of the service node, and generate an offline medical guide database; in a possible implementation, step A440 further includes step A441, inputting the workstation location information of the multiple service nodes based on the offline map of the target medical area, and obtaining the offline map of the workstation;

[0071] The offline map data of the target medical area can be obtained through map files that do not contain real-time network connections, such as vector graphics (such as SVG, GeoJSON, etc.) or raster graphics (such as PNG, JPG, etc.). At the same time, it is necessary to ensure that the offline map of the target medical area obtained contains key geographical information in the target medical area, such as roads, buildings, departments, etc., so as to accurately mark the location of the workstation, and then mark the workstation location of each service node one by one on the offline map of the target medical area by adding points, lines or surface elements on the map, and add necessary attribute information for each workstation, such as name, number, service type, etc. After completing the entry of the workstation location information, verify the offline map to check whether the workstation location is accurate and whether the attribute information is complete and correct, so as to save the modified offline map as a new file and record it as the workstation offline map for output.

[0072] Execute step A442, retrieve historical feedback evaluation data for cluster analysis, and generate the evaluation level according to the cluster analysis result; execute step A443, classify the multiple feedback evaluation data according to the evaluation level, and generate multiple feedback evaluation categories, wherein the multiple feedback evaluation categories are associated with the workstation location information of the multiple service nodes in the workstation offline map;

[0073] First, historical feedback evaluation data is retrieved from the database. The historical feedback evaluation data may include evaluation information of multiple service nodes in the target medical area. On this basis, text mining technology is used to extract key features. The key features may include scores, keyword frequencies, etc. At the same time, cluster analysis is performed on the historical feedback evaluation data, which means dividing the feedback evaluation data into different categories. Each category represents a similar evaluation pattern, and according to the cluster analysis results, an evaluation level is assigned to each category. The evaluation level can be defined as "very satisfied", "satisfied", "average", "unsatisfied", etc. Further, multiple feedback evaluation data are classified according to the evaluation level to generate multiple feedback evaluation categories. Finally, the service node positions of different evaluation levels are marked on the offline map, or the generated feedback evaluation categories are associated with the workstation position information of multiple service nodes in the workstation offline map by using visual elements such as color and shape.

[0074] Execute step A444 to regularly integrate the multiple feedback evaluation data according to the multiple feedback evaluation categories based on the workstation offline map to generate the offline medical guide database.

[0075] Feedback and evaluation data of multiple service nodes in the target medical area are collected regularly from various sources (such as online surveys, physical questionnaires, electronic medical record systems, etc.), and the feedback and evaluation data obtained are classified according to the multiple feedback and evaluation categories defined above. On this basis, the workstation offline map is updated to reflect the new changes in the service nodes, such as the addition of new workstations, workstation location adjustments, etc., to ensure that the information in the workstation offline map is consistent with the actual situation. Finally, the classified feedback and evaluation data are integrated with the workstation offline map, the location of each service node is marked on the offline map, and the corresponding feedback and evaluation data are associated, and the integrated data is imported into the database to generate an offline medical guide database.

[0076] Execute step A450 to extract the service feedback information set based on the offline medical guide database.

[0077] Information including user ratings, comment texts, service satisfaction, service time, service efficiency, etc. is queried in the offline medical guide database to retrieve the required service feedback information, and the required service feedback information set is extracted from the query results. The extracted service feedback information set can be one or more data tables, records or fields, etc.

[0078] Next, step A500 is executed to automatically combine and adjust the multiple service nodes according to the service feedback information set, optimize the action suggestion information, and realize the integrated management of smart medical guidance.

[0079] In one possible implementation, step A500 further includes step A510, performing data analysis on the service feedback information set to generate service expectation information and service demand information of the target user; executing step A520, taking the service expectation information as an adjustment target, traversing the service demand information to automatically combine and adjust the multiple service nodes to generate user preference information; and executing step A530, optimizing the action suggestion information according to the user preference information.

[0080] Use text mining technology to extract user expectations and expected service features from the comment text in the service feedback information set, and combine user ratings and satisfaction data to analyze users' overall expectations for different service nodes and generate target users' service expectation information. Then, use topic models (such as LDA) to analyze and identify comment texts and user behavior data, obtain users' specific service needs, and generate target users' service demand information. Further, use service expectation information as an adjustment target to ensure that the combination of service nodes can meet users' expectations. Traverse users' service demand information, analyze the correlation and priority between different needs, and based on factors such as the geographic location, service time, and service capacity of multiple service nodes, select the target users' service demand information. factors, use optimization algorithms (such as genetic algorithms, simulated annealing, etc.) to automatically combine and adjust multiple service nodes, generate user preference information, and the user preference information includes the preference degree and selection tendency for different service nodes. The user preference information is integrated with the service node information in the offline medical guidance database. According to the user preference information, personalized action suggestions are provided to users, such as recommended service nodes, optimal service paths, etc. The action suggestion information is evaluated through user feedback and data analysis to obtain the effectiveness of the action suggestion information and user satisfaction, optimize the action suggestions, improve their practicality and accuracy, realize the integrated management of smart medical guidance, and provide users with more personalized and intelligent medical guidance services.

[0081] The embodiments of the present application solve the technical problem that due to insufficient manpower and lack of professional knowledge of medical guides, guidance errors occur, resulting in untimely service responses and reduced patient medical efficiency. The technical effect of providing patients with accurate and rapid medical guidance services through intelligent medical guidance services, reducing patients' waiting time and ineffective flow, and improving the hospital's operating efficiency is achieved.

[0082] In the above, refer to Figure 1 The integrated intelligent medical guide management method according to an embodiment of the present invention is described in detail. Figure 2 An integrated intelligent medical guide management system according to an embodiment of the present invention is described.

[0083] The integrated intelligent medical guide management system according to the embodiment of the present invention is used to solve the technical problem that due to insufficient manpower and lack of professional knowledge of medical guides, guidance errors occur, resulting in untimely service responses and reduced patient medical efficiency, and achieves the technical effect of accurately and quickly providing patients with medical guidance services through intelligent medical guidance services, reducing patients' waiting time and ineffective flow, and improving the operational efficiency of hospitals. The integrated intelligent medical guide management system includes: an information generation module 10, a service node acquisition module 20, a first judgment module 30, a second judgment module 40, and an integrated management module 50.

[0084] An information generation module 10, the information generation module 10 is used to receive medical data of a target user, and generate action suggestion information according to the medical data and the medical needs of the target user;

[0085] A service node acquisition module 20, the service node acquisition module 20 is used to transmit the action suggestion information to a target workstation, and set a plurality of service nodes based on the target workstation;

[0086] A first judgment module 30, the first judgment module 30 is used to obtain the service progress information of the multiple service nodes, and judge whether the service progress information of the service node reaches a critical threshold;

[0087] A second judgment module 40, wherein the second judgment module 40 is configured to trigger a medical guidance service evaluator if the service progress information of the service node reaches the critical threshold, and generate a service feedback information set based on the service feedback of the target user to the service node through the medical guidance service evaluator;

[0088] The integrated management module 50 is used to automatically combine and adjust the multiple service nodes according to the service feedback information set, optimize the action suggestion information, and realize the integrated management of the smart medical guide.

[0089] The specific configuration of the information generation module 10 will be described in detail below. As described above, the medical data of the target user is received, and action suggestion information is generated based on the medical data combined with the medical needs of the target user. The information generation module 10 may further include: a first analysis unit is used to analyze the medical data using data mining, and determine the medical information set of the target user based on the medical data analysis results, and the medical information set includes the target user's disease development trend and historical medical conditions; a demand acquisition unit is used to obtain the target user's medical needs based on the disease development trend; a planning unit is used to plan the target user's medical process based on the medical needs and the medical data combined with the historical medical conditions; a route generation unit is used to identify multiple medical locations according to the medical process and generate a medical route; a suggestion generation unit is used to generate the action suggestion information based on the medical route combined with the medical process.

[0090] The specific configuration of the service node acquisition module 20 will be described in detail below. As described above, the action suggestion information is transmitted to the target workstation, and multiple service nodes are set based on the target workstation. The service node acquisition module 20 may further include: a receiving unit is used to determine the target workstation according to the end point of the medical route in the action suggestion information, and receive the action suggestion information through the target workstation; a first extraction unit is used to extract the workflow record log of the target workstation; a first data determination unit is used to match multiple management personnel based on the workflow record log combined with the medical needs, and determine the management work data set; a first traversal unit is used to obtain the multiple service nodes based on the management work data set, and traverse the multiple service nodes to deploy a monitoring mechanism.

[0091] The specific configuration of the first judgment module 30 will be described in detail below. As described above, the service progress information of the multiple service nodes is obtained, and it is determined whether the service progress information of the service node reaches the critical threshold. The first judgment module 30 may further include: a data acquisition unit for obtaining multiple monitoring data through the monitoring mechanism of the multiple service nodes, and the multiple monitoring data include service status information and service progress information of each service node; a continuous tracking unit for continuously tracking the service progress information of the multiple service nodes based on the service status information to generate first progress tracking distance data; a second data determination unit for determining the service full process distance data based on the service progress information of the multiple service nodes; a difference calculation unit for subtracting the first progress tracking distance data from the service full process distance data to obtain a distance difference; a third judgment unit for determining whether the distance difference is less than a preset distance interval. If it is greater, it is deemed that the service progress information of the service node has not reached the critical threshold, and a progress tracking instruction is generated to track the service progress information for secondary calculation to generate second progress tracking distance data, thereby iterating until the distance difference is less than the preset distance interval.

[0092] The specific configuration of the second judgment module 40 will be described in detail below. As described above, if the service progress information of the service node reaches the critical threshold, the medical guidance service evaluator is triggered, and based on the target user's service feedback to the service node through the medical guidance service evaluator, a service feedback information set is generated. The second judgment module 40 may further include: a fourth judgment unit is used to regard the service progress information of the service node as reaching the critical threshold if the distance difference is less than the preset distance interval; a fifth judgment unit is used to trigger the medical guidance service evaluator if the service progress information of the service node reaches the critical threshold; a feedback unit is used to generate multiple feedback evaluation data by using the medical guidance service evaluator to provide feedback to the service node by the target user; an offline storage unit is used to store the multiple feedback evaluation data offline according to the evaluation level and in combination with the workstation location information of the service node to generate an offline medical guidance database; a second extraction unit is used to extract the service feedback information set based on the offline medical guidance database.

[0093] The specific configuration of the offline storage unit will be described in detail below. As described above, the multiple feedback evaluation data are stored offline according to the evaluation level and combined with the workstation location information of the service node to generate an offline medical guide database. The offline storage unit may further include: an information entry unit is used to enter the workstation location information of the multiple service nodes based on the offline map of the target medical area to obtain the workstation offline map; a second analysis unit is used to retrieve historical feedback evaluation data for cluster analysis, and generate the evaluation level according to the cluster analysis result; a classification unit is used to classify the multiple feedback evaluation data according to the evaluation level to generate multiple feedback evaluation categories, and the multiple feedback evaluation categories are associated with the workstation location information of the multiple service nodes in the workstation offline map; a data integration unit is used to regularly integrate the multiple feedback evaluation data according to the multiple feedback evaluation categories based on the workstation offline map to generate the offline medical guide database.

[0094] The specific configuration of the integrated management module 50 will be described in detail below. As described above, the multiple service nodes are automatically combined and adjusted according to the service feedback information set, and the action suggestion information is optimized. The integrated management module 50 may further include: a third analysis unit for performing data analysis on the service feedback information set to generate service expectation information and service demand information of the target user; a second traversal unit for taking the service expectation information as an adjustment target, traversing the service demand information to automatically combine and adjust the multiple service nodes, and generating user preference information; and an optimization unit for optimizing the action suggestion information according to the user preference information.

[0095] The integrated smart medical guide management system provided by the embodiment of the present invention can execute the integrated smart medical guide management method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0096] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0097] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. An integrated intelligent medical guide management method, characterized in that: The method comprises: Receiving medical data of a target user, and generating action suggestion information based on the medical data and the medical needs of the target user; Transmitting the action suggestion information to a target workstation, and setting a plurality of service nodes based on the target workstation; Acquire service progress information of the plurality of service nodes, and determine whether the service progress information of the service nodes reaches a critical threshold; If the service progress information of the service node reaches the critical threshold, a medical guide service evaluator is triggered, and a service feedback information set is generated based on the target user providing service feedback to the service node through the medical guide service evaluator; Automatically combining and adjusting the multiple service nodes according to the service feedback information set, optimizing the action suggestion information, and realizing integrated management of smart medical guidance; The method of automatically combining and adjusting the plurality of service nodes according to the service feedback information set and optimizing the action suggestion information includes: Performing data analysis on the service feedback information set to generate service expectation information and service demand information of target users; Taking service expectation information as the adjustment target, ensuring that the combination of service nodes meets the user's expectations, traversing the user's service demand information, analyzing the correlation and priority between different demands, and using optimization algorithms to automatically combine and adjust multiple service nodes based on their geographical locations, service times, and service capacity factors, generating user preference information, which includes the degree of preference and selection tendency for different service nodes, and integrating the user preference information with the service node information in the offline medical guide database; The action suggestion information is optimized according to the user preference information.

2. The integrated intelligent medical guide management method according to claim 1, characterized in that: Receiving medical data of a target user, and generating action suggestion information according to the medical data and the medical needs of the target user, the method comprising: Analyze the medical data by using data mining, and determine the medical information set of the target user based on the medical data analysis results, wherein the medical information set includes the disease development trend and historical medical treatment of the target user; Obtaining the target user's medical needs based on the disease development trend; Based on the medical needs, planning the medical process of the target user according to the medical data and the historical medical conditions; Identify multiple medical treatment locations according to the medical treatment process and generate a medical treatment route; The action suggestion information is generated based on the medical consultation route and the medical consultation process.

3. The integrated intelligent medical guide management method according to claim 2, characterized in that: The action suggestion information is transmitted to a target workstation, and a plurality of service nodes are set based on the target workstation, the method comprising: Determine a target workstation according to the end point of the medical treatment route in the action suggestion information, and receive the action suggestion information through the target workstation; Extract the workflow record log of the target workstation; Based on the workflow record log and the medical treatment needs, multiple managers are matched to determine a management work data set; The plurality of service nodes are obtained based on the partitioning of the management work data set, and a monitoring mechanism is deployed by traversing the plurality of service nodes.

4. The integrated intelligent medical guide management method according to claim 3, characterized in that: Acquiring service progress information of the plurality of service nodes and determining whether the service progress information of the service nodes reaches a critical threshold, the method comprising: Acquire multiple monitoring data through the monitoring mechanism of the multiple service nodes, the multiple monitoring data including service status information and service progress information of each service node; Continuously tracking the service progress information of the multiple service nodes based on the service status information to generate first progress tracking distance data; Determine the service full process distance data based on the service progress information of the multiple service nodes; Subtracting the first progress tracking distance data from the service full process distance data to obtain a distance difference; Determine whether the distance difference is less than a preset distance interval. If it is greater, it is deemed that the service progress information of the service node has not reached the critical threshold, and a progress tracking instruction is generated to track the service progress information for secondary calculation, and generate second progress tracking distance data, thereby iterating until the distance difference is less than the preset distance interval.

5. The integrated intelligent medical guide management method according to claim 4, characterized in that: If the service progress information of the service node reaches the critical threshold, a medical guide service evaluator is triggered, and a service feedback information set is generated based on the target user providing service feedback to the service node through the medical guide service evaluator. The method includes: If the distance difference is less than the preset distance interval, it is deemed that the service progress information of the service node reaches the critical threshold; If the service progress information of the service node reaches a critical threshold, the medical guide service evaluator is triggered; The target user uses the medical guide service evaluator to provide feedback to the service node, thereby generating a plurality of feedback evaluation data; The plurality of feedback evaluation data are stored offline according to the evaluation levels and in combination with the workstation location information of the service node to generate an offline medical guidance database; The service feedback information set is extracted based on the offline medical guide database.

6. The integrated intelligent medical guide management method according to claim 5, characterized in that: The plurality of feedback evaluation data are stored offline according to the evaluation levels and in combination with the workstation location information of the service node to generate an offline medical guidance database, the method comprising: Entering the workstation location information of the plurality of service nodes based on the offline map of the target medical treatment area to obtain an offline map of the workstations; Retrieving historical feedback evaluation data for cluster analysis, and generating the evaluation level according to the cluster analysis results; Classifying the plurality of feedback evaluation data according to the evaluation levels to generate a plurality of feedback evaluation categories, wherein the plurality of feedback evaluation categories are associated with the workstation location information of the plurality of service nodes in the workstation offline graph; Based on the workstation offline graph, the plurality of feedback evaluation data are regularly integrated according to the plurality of feedback evaluation categories to generate the offline medical guidance database.

7. The integrated intelligent medical guide management system is characterized by: The system is used to implement the integrated intelligent medical guide management method according to any one of claims 1 to 6, and the system includes: An information generation module, the information generation module is used to receive medical data of a target user, and generate action suggestion information according to the medical data and the medical needs of the target user; A service node acquisition module, the service node acquisition module is used to transmit the action suggestion information to a target workstation, and set a plurality of service nodes based on the target workstation; A first judgment module, the first judgment module is used to obtain the service progress information of the multiple service nodes, and judge whether the service progress information of the service node reaches a critical threshold; a second judgment module, wherein the second judgment module is configured to trigger a medical guidance service evaluator if the service progress information of the service node reaches the critical threshold, and generate a service feedback information set based on the service feedback of the target user to the service node through the medical guidance service evaluator; The integrated management module is used to automatically combine and adjust the multiple service nodes according to the service feedback information set, optimize the action suggestion information, and realize the integrated management of the smart medical guide.

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