Hospital disaster vulnerability event control system and method

Abstract

The invention relates to a hospital disaster vulnerability event control system and method, relates to the technical field of computer intelligent computing, and efficiently realizes timely discovery, treatment and tracking of weak and wrong events. The hospital disaster vulnerability event control system comprises an early warning category detection module used for identifying the service category of a disaster vulnerability event damage object; the early warning grade identification module is used for predicting the damage grade of the disaster vulnerability event on the damaged object; the early warning distribution module is used for selecting a target management port from a plurality of management ports associated with the service category according to the hazard level, the target management port is connected with a specified storage area, and data in the specified storage area is called and displayed on a user interface of a person who processes the service category when a program runs; and the early warning execution module is used for sending an early warning message of the occurrence of the disaster vulnerability event to the target management port.

Description

Technical Field

[0001] The present application relates to the field of computer intelligent computing technology, and in particular to a hospital disaster vulnerability event control system and method. Background Art

[0003] Currently, more emphasis is placed on building systems or platforms for information sharing and data analysis of medical information itself, such as the Hospital Information System (HIS). Therefore, the current systems or platforms are still lacking in achieving or assisting in achieving risk resistance uncertainty, as well as in timely estimating, discovering, managing, and tracking potential vulnerability risk events. Summary of the invention

[0004] The present application aims to provide a hospital disaster vulnerability event control system, which conducts intelligent analysis of existing data, predicts or promptly discovers disaster vulnerability events, and reports disaster vulnerability events to users who have the ability to handle corresponding events through the system's internal structure and circulation methods. At the same time, the system supervises the handling of vulnerability events to ensure that vulnerability events can be handled in a timely manner. The above method does not require human participation, and efficiently realizes the timely discovery, governance and tracking of vulnerability events.

[0005] In a first aspect, an embodiment provides a hospital disaster vulnerability event control system, the hospital disaster vulnerability event control system comprising: an early warning category detection module, used to identify the business category of the disaster vulnerability event damage object; an early warning level identification module, used to predict the hazard level of the disaster vulnerability event to the damage object; an early warning allocation module, used to select a target management port from multiple management ports associated with the business category according to the hazard level, the target management port is connected to a designated storage area, and the data of the designated storage area is called when the program is running to be displayed on the user interface of the person handling the business category; an early warning execution module, used to send an early warning message of the occurrence of the disaster vulnerability event to the target management port.

[0006] In one embodiment, the warning allocation module is specifically used to determine the specialized subject corresponding to the damage object in the business category; Taking the junior college subject as the starting point, the first level difference between the current hazard level and the minimum hazard level is the number of steps, and accumulation is performed on the basis of the junior college subject to search for the current subject node that matches the current hazard level, and the second level difference between the current subject node and the junior college subject is the same as the first level; The user interface connection storage area for processing the current subject node is determined to be the designated storage area.

[0007] In one embodiment, the hospital disaster vulnerability event control system further includes: An image acquisition module, connected to an image acquisition device, and used to acquire a first image file acquired by the image acquisition device; The warning category detection module is specifically used to perform image recognition on the first image file, identify the target scene that may cause the disaster vulnerability event to occur, and identify the business category of the object damaged by the disaster vulnerability event based on the target scene.

[0008] In one embodiment, the hospital disaster vulnerability event control system further includes: A data acquisition module, connected to the information input system, is used to extract the recorded historical text data from the information input system and to back up the current text data input by the user; The warning category detection module is specifically used to perform semantic recognition and keyword query on the historical text data and the current text data. When the target semantics or target keywords associated with the disaster vulnerability event are identified, the business category of the object damaged by the disaster vulnerability event is identified based on the target semantics and the target keywords.

[0009] In one embodiment, the hospital disaster vulnerability event control system further includes: A feedback module is used to monitor the designated storage area connected to the target management port when the warning message is obtained based on the historical text data, capture the feedback information input by the user based on the corresponding display area of ​​the user interface; perform semantic recognition on the feedback information, and determine whether the user processes the warning message; The warning cancellation module is used to delete the warning message in the designated storage area when it is detected that the user processes the warning message.

[0010] In one embodiment, the hospital disaster vulnerability event control system further includes: A feedback module is used to monitor the designated storage area connected to the target management port, capture the feedback information input by the user based on the corresponding display area of ​​the user interface; perform semantic recognition on the feedback information to determine whether the user handles the warning message, or perform image recognition on the second impact file to determine whether the user handles the warning message; The warning upgrade module is used to send the warning message of the disaster vulnerability event to the upper-level port when it is detected that the delay time for the user to not process the warning message exceeds the preset time length; the upper-level port is the port of the storage area corresponding to the upper-level node of the current subject node.

[0011] In one embodiment, when the warning message is obtained based on the first image file, the image acquisition module is further used to continuously acquire a second image file acquired by an image acquisition device corresponding to the target scene; The hospital disaster vulnerability event control system further includes a feedback module for performing image recognition on the second impact file to determine whether the user processes the warning message; The warning cancellation module is used to delete the warning message in the designated storage area when it is detected that the user processes the warning message.

[0012] In one embodiment, the hospital disaster vulnerability event control system further includes: The sorting module is used to add the processed information of the warning message deleted by the warning cancellation module in the specified storage area to the general storage area, and the data of the general storage area is called to display on the user interface of each person when the program is running.

[0013] In a second aspect, an embodiment provides a method for controlling hospital disaster vulnerability events, the method comprising: Identify the business categories of objects damaged by disaster vulnerability events through the early warning category detection module; Predicting the hazard level of the disaster vulnerability event to the damaged object through a warning level identification module; A target management port is selected from a plurality of management ports associated with the business category according to the hazard level by the early warning allocation module, the target management port is connected to a designated storage area, and the data of the designated storage area is called to be displayed on the user interface of the person handling the business category when the program is running; The warning execution module sends the warning message of the disaster vulnerability event to the target management port.

[0014] The beneficial effects of this application are: The embodiment of the present application sets up an early warning category detection module to connect the image acquisition module and the data acquisition module. The image acquisition module is connected to the image acquisition device to automatically obtain the monitoring video and monitoring image of the hospital scene. The data acquisition module is connected to the HIS hospital information system to automatically capture the text data entered into the hospital information system; thus, the early warning category detection module can perform intelligent analysis on the text data, monitoring video, etc., identify disaster vulnerability events, and identify the business category of disaster vulnerability events, and then generate early warning messages for disaster vulnerability events, and send the disaster vulnerability events to the file storage area called when the processing interface of the business category-related personnel is displayed; timely discovery of disaster vulnerability events and automatic processing assigned to corresponding processing personnel are achieved, and different types of vulnerability events are intelligently notified to the responsible person. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the structure of the vulnerability event control system proposed in the embodiment of the present application; Figure 2 This is a schematic diagram of information flow of an example early warning execution module execution program of the present application; Figure 3 is another structural schematic diagram of a vulnerability event control system provided in an embodiment of the present application; Figure 4 It is a flowchart of the steps of the vulnerability event control method proposed in the embodiment of the present application. DETAILED DESCRIPTION

[0016] The present application is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present application to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification, in order to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0017] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0018] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0019] Figure 1 is a schematic diagram of the structure of the vulnerability event control system proposed in the embodiment of the present application, such as Figure 1 As shown in Figure 1, the vulnerability event control system includes: Warning category detection module 11, warning level identification module 12, warning allocation module 13, warning execution module 14.

[0020] The warning category detection module and the warning level identification module are respectively connected to the warning allocation module, and the warning allocation module is connected to the warning execution module.

[0021] The warning category detection module is used to identify the business category of the object damaged by the disaster vulnerability event. Business categories include medical safety, nursing safety, general affairs support, and medical equipment. For example, if the object damaged by the disaster vulnerability event is identified as a person in the hospital scene, such as medical staff, the business category can be determined as general affairs support; if the object damaged by the disaster vulnerability event is identified as a medical instrument, the business category can be determined as medical equipment; if the object damaged by the disaster vulnerability event is identified as a part damaged by a disease other than the disease currently being treated by the patient, or a part damaged by a new symptom of the current patient, the business category can be determined as medical safety.

[0022] In one example, the warning category detection module can be connected to the image acquisition module 111 and the data acquisition module 112, and similarly, the warning level recognition module can also be connected to the image acquisition module and the data acquisition module.

[0023] The image acquisition module can be connected to the image acquisition device to obtain the first image file acquired by the image acquisition device. The data acquisition module is connected to the information input system to extract the recorded historical text data from the information input system and back up the current text data input by the user.

[0024] For example, the information input system can be the hospital's HIS hospital information system. The data acquisition module is connected to the HIS hospital information system and can extract case data, consultation records, examination data, etc. input by users from the HIS hospital information system as historical text data. The data acquisition module captures the above historical text data and stores it locally for the early warning category detection module to perform further text analysis and identify business categories.

[0025] For example, when the data acquisition module detects that the user has entered the corresponding display area and inputs text data based on the display area, the text data currently input by the user is backed up and stored; for example, when it recognizes that the interface for reporting disaster vulnerability events is started, and the user enters "current text data" as {the network on the second floor is not accessible} based on the started page, the text data of {the network on the second floor is not accessible} is backed up and stored for the early warning category detection module to perform further text analysis and identify the business category.

[0026] The image acquisition device can be a camera set in a hospital scene, and the image acquisition module can be a camera. The camera transmits the acquired images or videos to the image acquisition module. The image acquisition module can store the images or videos for the early warning category detection module to perform further text analysis and identify business categories.

[0027] The warning category detection module can be embedded in the text recognition model, semantic recognition model and image recognition model.

[0028] The semantic recognition model can be a deep neural network built and trained based on a deep learning natural language processing model (Bidirectional Encoder Representations from Transformer, BERT), which can intelligently recognize the meaning of text and extract corresponding keywords in the text. It can include a fully connected layer, a Transform layer, and a logistic regression layer, etc., which is not limited in the embodiments of the present application.

[0029] The image recognition model may include a convolutional neural network (CNN), a recurrent neural network (RNN) and a generative adversarial network (GAN). After the image recognition model learns samples carrying specific object labels, it can recognize a deep neural network of a specific object. The specific architecture and training method of the image recognition model are not limited in the embodiments of this application.

[0030] The text recognition model can be trained using variants such as training loop neural network (RNN), long short-term memory network (LSTM) and gated recurrent unit (GRU) as the basic architecture, which is not limited in the embodiments of the present application.

[0031] Based on the embedded semantic recognition model and image recognition model, the specific method for the early warning category detection module to identify the business category can be: For the text data input by the data collection module, the warning category detection module performs semantic recognition and keyword query on the historical text data and the current text data. When the target semantics or target keywords associated with the disaster vulnerability event are identified, the business category of the object damaged by the disaster vulnerability event is identified based on the target semantics and target keywords.

[0032] For example, the warning category detection module performs semantic recognition on the "current text data" input by the user and obtains the semantics: pneumothorax occurs after acupuncture treatment; or, the warning category detection module detects the keywords: dilated cardiomyopathy and swelling and pain, and finds the corresponding keyword phrases in the pre-built keyword thesaurus, so it can be determined that the business category is medical safety.

[0033] An example of the present application provides a method of pre-establishing a keyword thesaurus, counting and sorting case data and outpatient data input by users, confirming entries of the case data and outpatient data, responding to user confirmation operations on entries that may have vulnerability risks, marking corresponding entries, and storing them in the keyword thesaurus. For example, the outpatient data "The patient had paroxysmal atrial fibrillation, dilated cardiomyopathy, and gradually developed swelling and pain in the left upper limb during the process of pumping iodine ketone, dopamine, and dobutamine" is counted and sorted. This data indicates that atrial fibrillation and dilated cardiomyopathy may lead to vulnerable events of swelling and pain symptoms. The user's confirmation operation on the data is detected, and the entry is marked: (atrial fibrillation-dilated cardiomyopathy)-pumping-(dopamine-dobutamine)-swelling and pain, and the entry is stored in the keyword thesaurus, or the above entries can be segmented to obtain the entries: atrial fibrillation-pumping-swelling and pain, dilated cardiomyopathy-pumping-dopamine-swelling and pain, etc., which are stored in the keyword thesaurus; further, sub-lexicons can be established for medical safety, nursing safety, general affairs support, and medical equipment, and atrial fibrillation-pumping-swelling and pain, dilated cardiomyopathy-pumping-dopamine-swelling and pain, etc. are stored in the sub-lexicon of medical safety.

[0034] In the application stage, the early warning category detection module recognizes that the phrases such as atrial fibrillation-pumping-swelling and pain, or dilated cardiomyopathy-pumping-dopamine-swelling and pain appear in the historical text data or the current text data, and searches for the same phrases in the keyword vocabulary to determine that the target keywords associated with the disaster vulnerability event are identified, analyze the target keywords, and determine that the business category is medical safety; or searches for the phrases such as atrial fibrillation-pumping-swelling and pain, or dilated cardiomyopathy-pumping-dopamine-swelling and pain in the sub-lexicon of medical safety to determine that the business category is medical safety.

[0035] With respect to the first image file input by the image acquisition module, the warning category detection module performs image recognition on the first image file, identifies the target scene that may cause a disaster vulnerability event, and identifies the business category of the object damaged by the disaster vulnerability event based on the target scene.

[0036] For example, during the training phase, samples of scenes associated with disaster vulnerability events are collected and marked, such as an image of a scene of physical contact between two people. Since the physical contact between two people is a crowd, the image area marked as the scene of physical contact between two people is "general affairs support". The sample is used to train the image recognition model to regress the accuracy of the scene of physical contact between two people. The trained image recognition model can accurately identify the scene of physical contact between two people, and output the business category of the "scene of physical contact between two people" as "general affairs support". During the application phase, the image recognition model regresses the image area recorded with the "scene of physical contact between two people" in the first image file, determines that the target scene is identified, and obtains that the business category corresponding to the target scene is "general affairs support".

[0037] In the embodiment of the present application, an early warning category detection module is arranged to connect an image acquisition module and a data acquisition module. The image acquisition module is connected to an image acquisition device to automatically obtain surveillance videos and surveillance images of hospital scenes. The data acquisition module is connected to an HIS hospital information system to automatically capture text data entered into the hospital information system. Thus, the early warning category detection module can intelligently analyze text data, surveillance videos, etc., identify disaster vulnerability events, and identify the business categories of disaster vulnerability events, and then generate early warning messages for disaster vulnerability events, and send the disaster vulnerability events to a file storage area called when the processing interface of the business category-related personnel is displayed. Timely discovery of disaster vulnerability events and automatic processing assigned to corresponding processing personnel are achieved, and different types of vulnerability events are intelligently notified to the responsible persons.

[0038] Assuming that the disaster vulnerability event is network unavailability, the business category-associated personnel can be the network administrator; if the disaster vulnerability event is "bed sores in obese stroke patients", the business category-associated personnel can be dermatologists.

[0039] Furthermore, in order to more accurately warn related personnel of vulnerability events, the embodiment of the present application also provides a warning level identification module for predicting the hazard level of the disaster vulnerability event to the damaged object, so that more suitable handling personnel can be selected from the related personnel according to the hazard level, providing a basis for achieving graded handling of disaster vulnerability events.

[0040] This application provides an example of a method for the warning level identification module to perform "predicting the hazard level of the damaged object caused by the occurrence of a disaster vulnerability event": Collecting historical data: The process of collecting historical data may include: displaying text data input by the user, receiving the marking operation of the review user on the text data, and establishing an association between the text data and the marking operation information. The marking operation may include the selection of the possibility and the selection of the degree of consequence.

[0041] For example, a user inputs the text data "The patient suffered a pneumothorax on the spot after acupuncture treatment on August 1", and the text data is displayed on the operation interface corresponding to the reviewing user. The reviewing user reviews the text data and marks the possibility of the text data as possible and the degree of consequence as moderate. Then, a vulnerability event is established: "The patient suffered a pneumothorax on the spot after acupuncture treatment on August 1" has an association with the possibility of possible and the degree of consequence as moderate.

[0042] Establish a warning level recognition model. The warning level recognition model can be based on convolutional neural networks, recurrent neural networks, attention mechanisms, etc. The level recognition model learns historical data, adjusts the probability of different vulnerability events according to the frequency of vulnerability events, and learns the prediction logic based on the possibility and consequence of vulnerability events. In the application stage, it can predict the possibility and consequence of vulnerability events based on their information, and determine the hazard level of disaster vulnerability events to the damaged objects.

[0043] An example of the present application also establishes a reference matrix for determining hazards based on the probability and degree of consequence. The five levels of probability are set to include: almost certain, very likely, possible, unlikely, and almost impossible, and weight coefficients are set for the above five levels: almost certain 5K, very likely 4K, possible 3K, unlikely 2K, and almost impossible 1K; the five levels of consequence degree are set to include: unimportant, minor, moderate, major, and extreme, and weight coefficients are set for the above five levels: unimportant 1K, minor 2K, moderate 3K, major 4K, and extreme 5K, where K is a constant actually set according to the application process of the warning level identification model. The reference matrix is ​​set as shown in Table 1: , In Table 1, E indicates extreme risk and immediate measures need to be taken; H indicates high risk and measures need to be taken by personnel from senior management departments; M indicates medium risk and measures need to be taken by personnel from lower-level management departments; and L indicates low risk and measures can be taken by any personnel who can handle the corresponding incident.

[0044] After the warning level identification module of the embodiment of the present application detects the possibility and consequence degree of the disaster vulnerability event through the warning level identification model, it searches the above-mentioned reference matrix to obtain the hazard level of the disaster vulnerability event, and sends the hazard level to the warning allocation module. The warning allocation module sends the warning message of the disaster vulnerability event to the management port that matches the hazard level.

[0045] The warning allocation module is used to select a target management port according to the hazard level among multiple management ports associated with the business category. The target management port is connected to a designated storage area. When the program is running, the data of the designated storage area is called and displayed on the user interface of the person handling the business category.

[0046] In order to ensure that different warning messages are notified to corresponding processing personnel, the embodiment of the present application allocates storage areas to the processing interfaces of different departments and personnel of different levels, so that different storage areas are called when the processing interfaces of different personnel are generated, thereby displaying different contents.

[0047] The embodiment of the present application provides a method for the early warning allocation module to execute "selecting a target management port according to the hazard level": Determine the specialized subject corresponding to the destroyed object in the business category; Starting from the junior college subject, the first level difference between the current hazard level and the minimum hazard level is the number of steps, and the number is accumulated on the basis of the junior college subject to search for the current subject node that matches the current hazard level, and the second level difference between the current subject node and the junior college subject is the same as the first level; Determine the user interface connection storage area for processing the current subject node as the specified storage area.

[0048] Specialized subjects refer to the most direct departments of business categories. For example, the specialized subject dealing with nursing safety can be nurses. Then the current subject node one level higher than the specialized subject is the dermatology nurse, the current subject node two levels higher than the specialized subject is the dermatology head nurse, the current subject node three levels higher than the specialized subject is the dermatology nursing department, and the current subject node three levels higher than the specialized subject is the dean in charge.

[0049] For example, assuming that the current disaster vulnerability event is "the patient developed pneumothorax after acupuncture treatment on August 1", the specialist subject may be respiratory medicine, the current subject node one level higher than respiratory medicine is the director of respiratory medicine, and the current subject node two levels higher than respiratory medicine is the director of internal medicine. Then, assuming that the warning level identification module outputs the disaster vulnerability event "the patient developed pneumothorax after acupuncture treatment on August 1" as L, then the warning message is sent to the storage area corresponding to the operation interface of the attending physician of the respiratory medicine department; if the warning level identification module outputs the disaster vulnerability event "the patient developed pneumothorax after acupuncture treatment on August 1" as M, then the warning message is sent to the storage area corresponding to the operation interface of the director of respiratory medicine.

[0050] The early warning execution module is used to send the early warning message of the disaster vulnerability event to the target management port.

[0051] Figure 2 This is a schematic diagram of information flow of an example early warning execution module execution program of this application, such as Figure 2 As shown, the early warning execution module generates an early warning message for the disaster vulnerability event "bed sores in obese stroke patients". The early warning execution module can be connected to port 1, port 2, port 3 and port 4, port 1 is connected to storage area 1, port 2 is connected to storage area 2, port 3 is connected to storage area 3, port 4 is connected to storage area 4, interface 1 generates and calls data in the storage area, interface 2 generates and calls data in storage area 2, and so on; wherein interface 1 can be the operation interface of a dermatology nurse, interface 2 can be the operation interface of the head nurse of the dermatology department, interface 3 can be the operation interface of the nurse station, and interface 4 can be the operation interface of the dean in charge.

[0052] Taking port 1 as an example, assuming that the warning category detection module identifies the business category as "nursing safety" and the warning level identification module identifies the hazard level as L, the warning execution module can send the message to storage area 1 through port 1. The system receives the login information of the dermatology nurse and enters interface 1. Interface 1 generates data for calling storage area 1. If the warning message is sent to storage area 1, interface 1 finally displays the warning message, thereby realizing the purpose of intelligently identifying disaster vulnerability events and informing the most relevant responsible persons of the disaster vulnerability events.

[0053] Figure 3 FIG. 1 is another structural diagram of a vulnerability event control system provided in an embodiment of the present application. Figure 3 As shown, the hospital disaster vulnerability event control system also includes a feedback module 15 , an early warning upgrade module 16 , an early warning cancellation module 17 , and a sorting module 18 .

[0054] The feedback module is used to monitor the designated storage area connected to the target management port, capture the feedback information input by the user based on the corresponding display area of ​​the user interface; perform semantic recognition on the feedback information to determine whether the user handles the warning message, or perform image recognition on the second impact file to determine whether the user handles the warning message; or, the feedback module is used to monitor the designated storage area connected to the target management port when the warning message is obtained based on historical text data, capture the feedback information input by the user based on the corresponding display area of ​​the user interface; perform semantic recognition on the feedback information to determine whether the user handles the warning message.

[0055] The warning cancellation module is used to delete the warning message in the specified storage area to cancel the warning when it is detected that the user processes the warning message.

[0056] The early warning upgrade module is used to send the early warning message of the disaster vulnerability event to the upper-level port when it detects that the delay time of the user's unprocessed early warning message exceeds the preset time length; the upper-level port is the port of the storage area corresponding to the upper-level node of the current subject node.

[0057] The feedback module can also embed text recognition models, semantic recognition models and image recognition models. The image recognition model can be used to perform target recognition on the second impact file to determine whether the user handles the warning message. The text recognition model and semantic recognition model can be used to capture the information displayed on the user interface of the processing personnel and analyze the information displayed on the user interface of the processing personnel, or directly retrieve data from the corresponding storage area of ​​the user interface of the processing personnel for analysis to determine whether the user handles the warning message.

[0058] Continue to refer Figure 2For example, if the warning execution module generates a warning message for "bed sores in obese stroke patients", determines that the danger level is L, and sends the warning message to port 1 corresponding to storage area 1, the feedback module can periodically extract data from storage area 1, or periodically capture the text displayed on the display interface corresponding to storage area 1 as feedback information, and perform semantic recognition on the feedback information. If keywords such as "processed" are recognized and it is determined that the user has processed the warning message, the warning message can be deleted in storage area 1, thereby canceling the warning for the vulnerability event "bed sores in obese stroke patients".

[0059] If the delay time for not recognizing keywords such as "processed" exceeds the preset time length, it can be determined that the user has not processed the warning message, and a signal is sent to the warning upgrade module to trigger the warning upgrade module to execute the steps to send the warning message of the disaster vulnerability event to the upper-level port; the upper-level port is the port of the storage area corresponding to the upper-level node of the current subject node. In this example, the warning upgrade module can send the warning message to port 2, so that storage area 2 stores the warning message, and interface 2 generates data to call storage area 2. The head nurse of the dermatology department enters the system, and interface 2 displays the content of the warning message, thereby achieving the purpose of upgrading the warning message.

[0060] The sorting module is used to add the warning messages deleted by the warning cancellation module in the specified storage area to the general storage area. When the program is running, the data in the general storage area is called to display on the user interface of each person.

[0061] When the sorting module detects that the warning message has been deleted by the warning cancellation module in the designated storage area, it can determine that the associated disaster vulnerability event has been processed and add the warning message to the general storage area. When all users log in to the system and the system interface is generated, the general storage area will be called, so that the processing information of the warning message can be displayed to all users and subject to supervision by all employees.

[0062] The embodiment of the present application monitors the progress of handling disaster vulnerability events through a feedback module, and intelligently identifies whether relevant personnel have completed the handling of disaster vulnerability events. On the one hand, when it is identified that relevant personnel have completed the handling of disaster vulnerability events, the warning message in the storage area is deleted, and the relevant personnel enter the system, and their operation interface will no longer display the warning message. At the same time, the information that the warning message has been processed is stored in the general storage area. When all users enter the system, the system-generated interface will call the data in the general storage area. Therefore, the interface displays the message that the warning message has been processed to all users, thereby completing the notification of all employees about the progress of handling disaster vulnerability events. On the other hand, when it is identified that relevant personnel have not completed the handling of disaster vulnerability events, the warning message is sent to the port of the storage area corresponding to the upper-level node of the current subject node to notify higher-level users to handle the disaster vulnerability event. The above process not only automatically identifies the occurrence of disaster vulnerability events, automatically notifies related personnel of disaster vulnerability events, but also more intelligently identifies the processing progress of disaster vulnerability events, and automatically further processes disaster vulnerability events according to the processing progress of disaster vulnerability events. If the disaster vulnerability event is not processed, higher-level personnel will be notified. If the disaster vulnerability event has been processed, all personnel will be automatically notified. In this way, the entire process of disaster vulnerability events can be supervised without human intervention, the responsibility for disaster vulnerability events can be implemented, and the processing of disaster vulnerability events can be ensured.

[0063] Figure 4 is a flowchart of the steps of the vulnerability event control method proposed in the embodiment of the present application, such as Figure 4 As shown, the vulnerability event control method includes the following steps: S401: Identify the business category of the object damaged by the disaster vulnerability event through the early warning category detection module; S402: Predicting the hazard level of the disaster vulnerability event to the damaged object through the early warning level identification module; S403: selecting a target management port from among multiple management ports associated with the business category according to the hazard level through the early warning allocation module, the target management port is connected to a designated storage area, and the data of the designated storage area is called when the program is running and displayed on the user interface of the person handling the business category; S404: Sending a warning message of the occurrence of a disaster vulnerability event to a target management port through the warning execution module.

[0064] Figure 4 The implementation principle and technical effects of the hospital disaster vulnerability event control method provided by the illustrated embodiment may be further referred to the relevant description in the hospital disaster vulnerability event control system embodiment.

[0065] Optionally, the warning allocation module selects a target management port from among multiple management ports associated with the service category according to the hazard level, and the target management port is connected to the designated storage area, including: Determine the specialized subject corresponding to the destroyed object in the business category; Starting from the junior college subject, the first level difference between the current hazard level and the minimum hazard level is the number of steps, and the number is accumulated on the basis of the junior college subject to search for the current subject node that matches the current hazard level, and the second level difference between the current subject node and the junior college subject is the same as the first level; Determine the user interface connection storage area for processing the current subject node as the specified storage area.

[0066] Optionally, the method further comprises the steps of: Connecting the image acquisition device via the image acquisition module to obtain a first image file acquired by the image acquisition device; The warning category detection module identifies the business categories of objects damaged by disaster vulnerability events, including: Image recognition is performed on the first image file to identify a target scene that may cause a disaster vulnerability event to occur, and the business category of an object destroyed by the disaster vulnerability event is identified based on the target scene.

[0067] Optionally, the method further comprises: Connecting to the information input system through the data acquisition module, extracting the recorded historical text data from the information input system, and backing up the current text data input by the user; The warning category detection module identifies the business categories of objects damaged by disaster vulnerability events, including: Semantic recognition and keyword query are performed on historical text data and current text data. When target semantics or target keywords associated with disaster vulnerability events are identified, the business category of the object damaged by the disaster vulnerability event is identified based on the target semantics and target keywords.

[0068] Optionally, the method further comprises: When the warning message is obtained based on historical text data, the feedback module monitors the designated storage area connected to the target management port, captures the feedback information input by the user based on the corresponding display area of ​​the user interface; performs semantic recognition on the feedback information to determine whether the user handles the warning message; When the warning cancellation module detects that a user processes a warning message, the warning message in the specified storage area is deleted.

[0069] Optionally, the method further comprises: When the warning message is obtained based on historical text data, the feedback module monitors the designated storage area connected to the target management port, captures the feedback information input by the user based on the corresponding display area of ​​the user interface; performs semantic recognition on the feedback information to determine whether the user handles the warning message; Through the early warning upgrade module, when it is detected that the delay time of the user's unprocessed early warning message exceeds the preset time length, the early warning message of the disaster vulnerability event will be sent to the upper-level port; the upper-level port is the port of the storage area corresponding to the upper-level node of the current subject node.

[0070] Optionally, the warning message is obtained based on the first image file, historical text data recorded is extracted from the information input system, and current text data input by the user is backed up, including: Continuously acquiring a second image file acquired by an image acquisition device corresponding to the target scene; The method also includes performing image recognition on the second impact file through a feedback module to determine whether the user handles the warning message; When the warning cancellation module detects that a user processes a warning message, the warning message in the specified storage area is deleted.

[0071] The method also includes: adding the processed information of the warning message deleted by the warning cancellation module in the designated storage area to the general storage area through the sorting module, and calling the data in the general storage area to display on the user interface of each person when the program is running.

[0072] Regarding the various modules / units included in the various devices described in the above embodiments, they can be software modules / units, or hardware modules / units, or they can be partially software modules / units and partially hardware modules / units. For example, for various devices applied to or integrated in a chip, the various modules / units included therein can all be implemented in the form of hardware such as circuits, or at least some of the modules / units can be implemented in the form of software programs, which run on a processor integrated inside the chip, and the remaining modules / units can be implemented in the form of hardware such as circuits; for various devices applied to or integrated in a chip module, the various modules / units included therein can all be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component of the chip module (such as a chip, circuit module, etc.) or in different components, or at least some of the modules / units can be implemented in the form of software programs. The software program may be implemented in the form of a program, which runs on a processor integrated in the chip module, and the remaining modules / units may be implemented in the form of hardware such as circuits; for each device applied to or integrated in the electronic terminal device, each module / unit contained therein may be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (for example, a chip, a circuit module, etc.) or in different components in the electronic terminal device, or at least some modules / units may be implemented in the form of a software program, which runs on a processor integrated in the electronic terminal device, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits.

[0073] In one embodiment of the present application, a computer-readable storage medium is provided, on which a program is stored. The stored program includes a method that can be loaded by a processor and process any of the above embodiments.

[0074] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0075] The above specific examples are used to illustrate the present application, which is only used to help understand the present application and is not intended to limit the present application. For technicians in the technical field to which the present application belongs, they can also make some simple deductions, deformations or substitutions based on the ideas of the present application.

Claims

1. A hospital disaster vulnerability event control system, characterized in that: The hospital disaster vulnerability event control system includes: The warning category detection module is used to identify the business category of the objects damaged by disaster vulnerability events; An early warning level identification module is used to predict the hazard level of the disaster vulnerability event to the damaged object; An early warning allocation module, used to select a target management port from among the multiple management ports associated with the business category according to the hazard level, the target management port is connected to a designated storage area, and when the program is running, the data of the designated storage area is called to be displayed on the user interface of the person handling the business category; The warning execution module is used to send the warning message of the occurrence of the disaster vulnerability event to the target management port.

2. The hospital disaster vulnerability event control system according to claim 1, Its features include that the warning allocation module is specifically used to determine the specialized subject corresponding to the damage object in the business category; Taking the junior college subject as the starting point, the first level difference between the current hazard level and the minimum hazard level is the number of steps, and accumulation is performed on the basis of the junior college subject to search for the current subject node that matches the current hazard level, and the second level difference between the current subject node and the junior college subject is the same as the first level; The user interface connection storage area for processing the current subject node is determined to be the designated storage area.

3. The hospital disaster vulnerability event control system according to claim 1, characterized in that: The hospital disaster vulnerability event control system also includes: An image acquisition module, connected to an image acquisition device, for acquiring a first image file acquired by the image acquisition device; The warning category detection module is specifically used to perform image recognition on the first image file, identify the target scene that may cause the disaster vulnerability event to occur, and identify the business category of the object damaged by the disaster vulnerability event based on the target scene.

4. The hospital disaster vulnerability event control system according to claim 1, characterized in that: The hospital disaster vulnerability event control system also includes: A data acquisition module, connected to the information input system, is used to extract the recorded historical text data from the information input system and to back up the current text data input by the user; The warning category detection module is specifically used to perform semantic recognition and keyword query on the historical text data and the current text data. When the target semantics or target keywords associated with the disaster vulnerability event are identified, the business category of the object damaged by the disaster vulnerability event is identified based on the target semantics and the target keywords.

5. The hospital disaster vulnerability event control system according to claim 4, characterized in that: The hospital disaster vulnerability event control system also includes: A feedback module is used to monitor the designated storage area connected to the target management port when the warning message is obtained based on the historical text data, capture the feedback information input by the user based on the corresponding display area of ​​the user interface; perform semantic recognition on the feedback information, and determine whether the user processes the warning message; The warning cancellation module is used to delete the warning message in the designated storage area when it is detected that the user processes the warning message.

6. The hospital disaster vulnerability event control system according to claim 2, characterized in that: The hospital disaster vulnerability event control system also includes: A feedback module is used to monitor the designated storage area connected to the target management port, capture the feedback information input by the user based on the corresponding display area of ​​the user interface; perform semantic recognition on the feedback information to determine whether the user handles the warning message, or perform image recognition on the second impact file to determine whether the user handles the warning message; The warning upgrade module is used to send the warning message of the disaster vulnerability event to the upper-level port when it is detected that the delay time for the user to not process the warning message exceeds the preset time length; the upper-level port is the port of the storage area corresponding to the upper-level node of the current subject node.

7. The hospital disaster vulnerability event control system according to claim 3, characterized in that: When the warning message is obtained based on the first image file, the image acquisition module is further used to continuously acquire a second image file acquired by the image acquisition device corresponding to the target scene; The hospital disaster vulnerability event control system further includes a feedback module for performing image recognition on the second impact file to determine whether the user processes the warning message; The warning cancellation module is used to delete the warning message in the designated storage area when it is detected that the user processes the warning message.

8. The hospital disaster vulnerability event control system according to claim 5 or 7, characterized in that: The hospital disaster vulnerability event control system also includes: The sorting module is used to add the processed information of the warning message deleted by the warning cancellation module in the specified storage area to the general storage area, and the data of the general storage area is called to display on the user interface of each person when the program is running.

9. A hospital disaster vulnerability event control method, characterized in that: The method comprises: Identify the business categories of objects damaged by disaster vulnerability events through the early warning category detection module; Predicting the hazard level of the disaster vulnerability event to the damaged object through a warning level identification module; A target management port is selected from a plurality of management ports associated with the business category according to the hazard level by the early warning allocation module, the target management port is connected to a designated storage area, and the data of the designated storage area is called to be displayed on the user interface of the person handling the business category when the program is running; The warning execution module sends the warning message of the disaster vulnerability event to the target management port.

10. The method according to claim 9, characterized in that Selecting a target management port from among a plurality of management ports associated with the service category according to the hazard level by the early warning allocation module, wherein the target management port is connected to a designated storage area and comprises: Determine the specialized subject corresponding to the destroyed object in the business category; Taking the junior college subject as the starting point, the first level difference between the current hazard level and the minimum hazard level is the number of steps, and accumulation is performed on the basis of the junior college subject to search for the current subject node that matches the current hazard level, and the second level difference between the current subject node and the junior college subject is the same as the first level; The user interface connection storage area for processing the current subject node is determined to be the designated storage area.

Images