CN111462876A - Smart city management method and system based on cloud platform - Google Patents
Smart city management method and system based on cloud platform Download PDFInfo
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- CN111462876A CN111462876A CN202010237661.1A CN202010237661A CN111462876A CN 111462876 A CN111462876 A CN 111462876A CN 202010237661 A CN202010237661 A CN 202010237661A CN 111462876 A CN111462876 A CN 111462876A
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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Abstract
The embodiment of the application provides a smart city management method and system based on a cloud platform. The method comprises the following steps: setting a hospital cloud node in each hospital, predicting the patient handling capacity of the current hospital cloud node, and sending the patient handling capacity to a central control cloud node; when the predicted patient processing capacity is lower than a specified threshold value, distributing mobile cloud nodes for patients who cannot be seen in the current hospital, sequencing all hospitals to obtain recommended hospitals with the distances and the reception capacity matched with the patients, and writing the geographical position information of the recommended hospitals into the mobile cloud nodes; the method comprises the steps of transmitting an initial medical record of a patient to a cloud node of a recommended hospital, generating a treatment plan according to the initial medical record, and sending a treatment instruction to treatment equipment and personnel; and the mobile cloud node continuously monitors the health state of the patient and transmits the health state to the cloud node of the recommendation hospital in real time, and the cloud node of the recommendation hospital sends an early warning message to the city terminal user according to the health state of the patient. The urban epidemic prevention treatment efficiency is improved.
Description
Technical Field
The application relates to the field of edge computing, in particular to a smart city management method and system based on a cloud platform.
Background
In the process of urban infectious diseases, the condition that the supply and demand of patients are not matched with the supply and demand of medical resources often occurs, on one hand, infectious patients suffer from pain, and a treatment hospital is urgently needed to be found; on the other hand, the software and hardware conditions of each hospital in the city for receiving a doctor and infecting patients are different. This asymmetry of resources and information has placed a great deal of pressure on the prevention and control of infectious diseases. For example, some hospitals have limited resources for receiving a consultation, but an outbreak of an infectious disease may instantly gather a large number of patients to see a doctor before the disease, and the patients who cannot receive the treatment can flow into various regions of a city, which can cause further spread of the infectious epidemic; meanwhile, some hospitals may have sufficient hospital receiving resources, but the number of patients receiving the treatment is small, the redundant resources are not fully utilized, and the gold time for controlling the infected patients is missed.
In the traditional urban infectious disease prevention and control process, infectious disease prevention and control resources are allocated in a telephone communication mode among hospitals, so that the accuracy is low, the efficiency is low, and the prevention and control gold period of epidemic situations is easy to miss. With the wide application of the cloud computing technology in smart cities, the intelligent allocation and control of infectious disease resources can be performed by means of the cloud computing technology in the process of preventing and controlling the urban infectious diseases.
Disclosure of Invention
In view of this, the present application aims to provide a cloud platform-based smart city management method and system, so as to improve infectious disease control efficiency and solve the technical problems of low efficiency and low accuracy in current public health emergencies.
Based on the purpose, the application provides a smart city management method based on a cloud platform, which comprises the following steps:
each hospital cloud node is provided with hospital cloud nodes, data and instructions are transmitted among the hospital cloud nodes through communication connection, and the patient handling capacity of the current hospital cloud node is predicted by analyzing outpatient service data and hospitalization service data and is sent to the central control cloud node;
when the predicted patient processing capacity is lower than a specified threshold value, distributing mobile cloud nodes for patients who cannot be seen at the current hospital, sequencing all hospitals by the central control cloud node according to the processing capacity of each hospital and the distance between each hospital and the patient to obtain recommended hospitals of which the distances and the reception capacity are matched with the patients, and writing the geographical position information of the recommended hospitals into the mobile cloud nodes;
the initial medical record of the patient is transmitted to the cloud node of the recommended hospital, the cloud node of the recommended hospital predicts the arrival time of the patient, generates a diagnosis receiving plan according to the initial medical record, and sends a diagnosis receiving instruction to diagnosis receiving equipment and personnel;
the mobile cloud node continuously monitors the health state of the patient and transmits the health state to the cloud node of the recommendation hospital in real time, and the cloud node of the recommendation hospital sends an early warning message to the city terminal user according to the health state of the patient.
In some embodiments, the method further comprises:
and the mobile cloud node acquires the geographical position of the patient in real time, and navigates the optimal path and the traffic mode leading to the recommended hospital cloud node for the patient by combining the stored information of the recommended hospital cloud node.
In some embodiments, the method further comprises:
the central control cloud node scans the patient states of all hospital cloud nodes and generates a patient transfer strategy for hospitals with unbalanced patients;
the central control cloud node scans the resource states of all hospital cloud nodes and generates a resource allocation strategy for hospitals with unbalanced resources.
In some embodiments, each hospital cloud node predicts patient handling capacity of the current hospital cloud node by analyzing outpatient service data and hospitalization service data, comprising:
the patient handling capacity is evaluated by the waiting time, a single service desk model is established to estimate the waiting time of each hospital, and the waiting time is estimated by a formula
Calculating the average waiting time of the patients, wherein W is the average waiting time of the patients, σ is the negative index distribution of the patients when arriving at the hospital and obeying σ, and μ is the negative index distribution of the hospital service time obeying μ.
In some embodiments, the mobile cloud node collects vital signs of a patient in real time, and predicts whether the patient can reach the recommended hospital according to the vital signs of the patient;
and sending a help seeking signal to the cloud node of the recommendation hospital under the condition that the patient cannot reach the recommendation hospital.
In some embodiments, generating a treatment plan according to the initial medical record, and sending a treatment instruction to a treatment device and personnel, the treatment plan comprises:
searching the in-place state of the medical staff of the recommended hospital according to the initial medical record, determining the medical staff receiving the doctor, and pushing the initial medical record to the medical staff;
and predicting the type and the quantity of protection resources required by the patient to be subjected to treatment according to the initial medical record, and pushing the types and the quantity to medical personnel for preparation.
In some embodiments, the sending, by the cloud node of the recommended hospital, an early warning message to the city terminal user according to the health status of the patient includes:
predicting the time for the patient to reach the city street according to the geographical position of the patient;
and sending an avoidance protection message to the terminal user of the city street at a preset time before the time.
Based on above-mentioned purpose, this application has still provided a wisdom city management system based on cloud platform, includes:
the system comprises an initial module, a central control cloud node and a plurality of cloud nodes, wherein the initial module is used for setting hospital cloud nodes in each hospital, data and instructions are transmitted among the hospital cloud nodes through communication connection, and each hospital cloud node predicts the patient handling capacity of the current hospital cloud node by analyzing outpatient service data and hospitalization service data and sends the patient handling capacity to the central control cloud node;
the recommendation module is used for distributing mobile cloud nodes to patients who cannot be seen in the current hospital when the patient processing capacity is predicted to be lower than a specified threshold value, the central control cloud node sorts all hospitals according to the processing capacity of each hospital and the distance between each hospital and the patient to obtain recommended hospitals of which the distances and the reception capacity are matched with the patients, and the geographical position information of the recommended hospitals is written into the mobile cloud nodes;
the plan module is used for transmitting the initial medical record of the patient to the cloud node of the recommendation hospital, predicting the arrival time of the patient by the cloud node of the recommendation hospital, generating a diagnosis receiving plan according to the initial medical record, and sending a diagnosis receiving instruction to diagnosis receiving equipment and personnel;
and the blocking module is used for continuously monitoring the health state of the patient by the mobile cloud node and transmitting the health state to the cloud node of the recommendation hospital in real time, and the cloud node of the recommendation hospital sends an early warning message to the city terminal user according to the health state of the patient.
In some embodiments, the system further comprises:
and the navigation module is used for the mobile cloud node to acquire the geographical position of the patient in real time and navigate the optimal path and the optimal traffic mode leading to the recommended hospital cloud node for the patient by combining the stored information of the recommended hospital cloud node.
In some embodiments, the system further comprises:
the transfer module is used for scanning the patient states of all hospital cloud nodes by the central control cloud node and generating a patient transfer strategy for the hospitals with unbalanced patients;
and the resource module is used for scanning resource states of all hospital cloud nodes by the central control cloud node and generating a resource allocation strategy for hospitals with unbalanced resources.
In summary, the idea of the application is that hospital cloud nodes are arranged in each hospital, data and instructions are transmitted among the hospital cloud nodes through communication connection, and each hospital cloud node predicts the patient handling capacity of the current hospital cloud node by analyzing outpatient service data and hospitalization service data and sends the patient handling capacity to a central control cloud node; when the predicted patient processing capacity is lower than a specified threshold value, a mobile cloud node is distributed to the patient who cannot be seen at the current hospital, the central control cloud node searches the hospital cloud nodes from near to far according to examples and the processing capacity to obtain recommended hospital cloud nodes with the distance and the reception capacity matched with the patient, the initial case of the patient is transmitted to the recommended hospital cloud nodes, and the initial case of the patient is stored in the mobile cloud nodes; the mobile cloud node continuously monitors the health state of the patient and transmits the health state to the recommended hospital cloud node in real time, and the recommended hospital cloud node conducts infection blocking coaching according to the health state of the patient; and the mobile cloud node acquires the geographical position of the patient in real time and navigates the optimal path leading to the recommended hospital cloud node for the patient.
By the aid of the method and the system, under the condition of infectious disease outbreak, the problem that patients who cannot accept diagnosis and treatment flow into cities due to limited hospital diagnosis receiving capacity is avoided, the infection scale is enlarged, and the infectious epidemic situation cannot be controlled.
Drawings
In the drawings, like reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily to scale. It is appreciated that these drawings depict only some embodiments in accordance with the disclosure and are therefore not to be considered limiting of its scope.
Fig. 1 is a flowchart illustrating a smart city management method based on a cloud platform according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating a smart city management method based on a cloud platform according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a smart city management method based on a cloud platform according to an embodiment of the present invention.
Fig. 4 is a block diagram illustrating a smart city management system based on a cloud platform according to an embodiment of the present invention.
Fig. 5 is a block diagram illustrating a smart city management system based on a cloud platform according to an embodiment of the present invention.
Fig. 6 illustrates a constitutional diagram of a smart city management system based on a cloud platform according to an embodiment of the present invention.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 is a flowchart illustrating a smart city management method based on a cloud platform according to an embodiment of the present invention. As shown in fig. 1, the smart city management method based on the cloud platform includes:
step S11, hospital cloud nodes are arranged in each hospital, data and instructions are transmitted among the hospital cloud nodes through communication connection, and the patient handling capacity of the current hospital cloud node is predicted by analyzing outpatient service data and hospitalization service data through each hospital cloud node and is sent to the central control cloud node.
Specifically, the hospital cloud node can access an existing information system of a hospital and access hospital visit data and medical resource data from the existing information system of the hospital. For example, the hospital cloud node may obtain the number of visits of each department at present through an api (application programming interface) access interface provided by an existing information system of the hospital, and may also obtain the number of idle beds of each department at present. In addition, the hospital cloud node can analyze and count the data, for example, the change of the hospital patient in the scheduled time period compared with the historical synchronization level can be analyzed.
In one embodiment, each hospital cloud node predicts patient handling capacity of the current hospital cloud node by analyzing outpatient service data and hospitalization service data, comprising:
the patient handling capacity is evaluated by the waiting time, a single service desk model is established to estimate the waiting time of each hospital, and the waiting time is estimated by a formula
Calculating the average waiting time of the patients, wherein W is the average waiting time of the patients, σ is the negative index distribution of the patients when arriving at the hospital and obeying σ, and μ is the negative index distribution of the hospital service time obeying μ.
Through the queuing theory model, the current treatment pressure of the hospital can be predicted, so that reference is provided for judging whether actions are needed to be taken on patients who cannot receive symptoms.
Step S12, when the fact that the processing capacity of the patient is lower than the specified threshold value is predicted, a mobile cloud node is distributed to the patient who cannot be seen in the current hospital, the central control cloud node sorts all hospitals according to the processing capacity of each hospital and the distance between the central control cloud node and the patient to obtain a recommended hospital with the distance and the reception capacity matched with the patient, and geographical position information of the recommended hospital is written into the mobile cloud node.
For example, if the daily number of patients receiving a treatment in the infectious department of a hospital is 100, the designated threshold value may be set to 100, and when the predicted treatment capacity of the patient is lower than 100, the patient who cannot be treated in the current hospital is transferred to a hospital with abundant medical resources nearby, so that the disease condition can be prevented from further deteriorating and the best time for treatment can be delayed under the condition that the patient with the disease cannot be treated during the spreading period of the epidemic situation; on the other hand, the disease infection prevention system can effectively prevent the disease infected patients from transmitting the disease to other normal people to cause the uncontrolled epidemic situation.
In one embodiment, the mobile cloud node collects vital signs of a patient in real time, and predicts whether the patient can reach the recommended hospital according to the vital signs of the patient;
and sending a help seeking signal to the cloud node of the recommendation hospital under the condition that the patient cannot reach the recommendation hospital.
Specifically, it is necessary to refer to a hospital to send an ambulance to assist the patient in transferring the hospital when the patient is determined whether he or she has the ability to go to the recommended hospital by himself or herself, for example, some serious patients may not breathe hard, stumble and even walk normally.
And S13, transmitting the initial medical record of the patient to the cloud node of the recommendation hospital, predicting the arrival time of the patient by the cloud node of the recommendation hospital, generating a treatment plan according to the initial medical record, and sending a treatment instruction to treatment equipment and personnel.
Specifically, in order to win precious time for rescuing patients, when the patients are transferred to the recommendation hospital, the initial medical records of the patients can be transmitted to the doctor who visits the recommendation hospital through the cloud platform, so that the doctor can preliminarily know the basic conditions of the patients before the patients are brought.
In one embodiment, generating a treatment plan according to the initial medical record, and sending a treatment instruction to a treatment device and personnel, comprises:
searching the in-place state of the medical staff of the recommended hospital according to the initial medical record, determining the medical staff receiving the doctor, and pushing the initial medical record to the medical staff;
and predicting the type and the quantity of protection resources required by the patient to be subjected to treatment according to the initial medical record, and pushing the types and the quantity to medical personnel for preparation.
Specifically, when the original hospital makes a preliminary visit to a patient and provides a preliminary medical record, the general disease type of the patient can be predicted by an artificial intelligence method, and a doctor most suitable for treating the patient (for example, a doctor who has treated a similar patient) can be matched according to the disease type at the recommended hospital cloud node. On the other hand, the process of rescuing patients still needs sufficient medical resources and protection resources, the traditional rescue process is manually prepared, so that the patient condition is delayed due to inaccuracy and low efficiency, the medical resources needed for rescuing the patient are rapidly predicted according to the disease type of the patient through an artificial intelligence algorithm, the rescue efficiency can be improved, and on the other hand, the protection resources are predicted, so that the self infection of medical workers due to rescue can be prevented.
And S14, the mobile cloud node continuously monitors the health state of the patient and transmits the health state to the cloud node of the recommended hospital in real time, and the cloud node of the recommended hospital sends an early warning message to the city terminal user according to the health state of the patient.
Particularly, the health condition of the patient is monitored in real time, so that the disease can be prevented from being infected to common people after the patient leaves a hospital, for example, the disease can be infected to passers on the way of transferring the patient, and an avoidance reminding can be sent to a passer mobile phone which can be contacted with the disease on the way of transferring the patient; on the other hand, the health condition of the patient is monitored in real time, and accidents of the patient on the way to the recommendation hospital can be prevented, for example, the patient falls down on the way to the recommendation hospital due to aggravation of the disease condition, and at the moment, early warning can be sent to a mobile phone of a passerby on the way emergently to guide a correct processing mode of the passerby.
In one embodiment, the method for sending the early warning message to the city terminal user by the cloud node of the recommended hospital according to the health status of the patient includes:
predicting the time for the patient to reach the city street according to the geographical position of the patient;
and sending an avoidance protection message to the terminal user of the city street at a preset time before the time.
Fig. 2 is a flowchart illustrating a smart city management method based on a cloud platform according to an embodiment of the present invention. As shown in fig. 2, the smart city management method based on the cloud platform further includes:
step S15, the mobile cloud node acquires the geographical position of the patient in real time, and guides the patient with the optimal path and the optimal traffic mode leading to the recommended hospital cloud node by combining the stored information of the recommended hospital cloud node.
Particularly, the fastest arrival path and the traffic mode can be recommended for the user by quickly positioning the position of the patient and combining the recommended geographical position of the hospital and the traffic condition of the city. For example, some hospitals are in the moustache in downtown areas, the efficiency of the vehicles going to is far from the efficiency of the electric vehicles going to, and then the manpower vehicles can be recommended to go to and plan the fastest driving path for the manpower vehicles.
Fig. 3 is a flowchart illustrating a smart city management method based on a cloud platform according to an embodiment of the present invention. As shown in fig. 3, the cloud platform-based smart city management method further includes:
and S17, the central control cloud node scans the patient states of all hospital cloud nodes and generates a patient transfer strategy for the hospitals with unbalanced patients.
And S18, the central control cloud node scans the resource states of all hospital cloud nodes and generates a resource allocation strategy for hospitals with unbalanced resources.
Specifically, since the current status and the ability of each hospital to receive a doctor are changed in real time, the bearing capacity of each hospital needs to be controlled, balanced and adjusted macroscopically. For example, all hospitals are scanned at intervals, the bearing capacity of each hospital in a specified time in the future is predicted, and for a hospital with high visit capacity, mild patients can be transferred to a recommended hospital with rich medical resources, and upcoming patients can be recommended to go to the recommended hospital for treatment.
Fig. 4 is a block diagram illustrating a smart city management system based on a cloud platform according to an embodiment of the present invention. As shown in fig. 4, the smart city management system based on the cloud platform includes:
the system comprises an initial module 41, a central control cloud node and a plurality of cloud nodes, wherein the initial module is used for setting hospital cloud nodes in each hospital, data and instructions are transmitted among the hospital cloud nodes through communication connection, and each hospital cloud node predicts the patient handling capacity of the current hospital cloud node by analyzing outpatient service data and hospitalization service data and sends the patient handling capacity to the central control cloud node;
the recommendation module 42 is configured to, when it is predicted that the patient processing capacity is lower than a specified threshold, assign a mobile cloud node to a patient who cannot be seen at a current hospital, the central control cloud node sorts all hospitals according to the processing capacity of each hospital and the distance between the central control cloud node and the patient, obtains a recommended hospital whose distance and reception capacity are matched with the patient, and writes geographical location information of the recommended hospital into the mobile cloud node;
a plan module 43, configured to transmit the preliminary medical record of the patient to a cloud node of the recommended hospital, where the cloud node of the recommended hospital predicts arrival time of the patient, generates a plan for treatment according to the preliminary medical record, and sends a treatment instruction to treatment equipment and staff;
the blocking module 44 is configured to continuously monitor the health state of the patient by the mobile cloud node, and transmit the health state to the cloud node of the recommended hospital in real time, where the cloud node of the recommended hospital sends an early warning message to the city terminal user according to the health state of the patient.
Fig. 5 is a block diagram illustrating a smart city management system based on a cloud platform according to an embodiment of the present invention. As shown in fig. 5, the smart city management system based on the cloud platform further includes:
and the navigation module 45 is used for the mobile cloud node to acquire the geographical position of the patient in real time and navigate the optimal path and the optimal traffic mode leading to the recommended hospital cloud node for the patient by combining the stored information of the recommended hospital cloud node.
Fig. 6 illustrates a constitutional diagram of a smart city management system based on a cloud platform according to an embodiment of the present invention. As shown in fig. 6, the smart city management system based on the cloud platform further includes:
a transfer module 46, configured to scan the patient states of all hospital cloud nodes by the central control cloud node, and generate a patient transfer policy for a hospital with unbalanced patients;
and the resource module 47 is used for the central control cloud node to scan the resource states of all hospital cloud nodes and generate a resource allocation strategy for hospitals with unbalanced resources.
The functions of the modules in the systems in the embodiments of the present application may refer to the corresponding descriptions in the above methods, and are not described herein again.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer readable storage medium. The storage medium may be a read-only memory, a magnetic or optical disk, or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various changes or substitutions within the technical scope of the present invention, and these should be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A smart city management method based on a cloud platform is characterized by comprising the following steps:
each hospital cloud node is provided with hospital cloud nodes, data and instructions are transmitted among the hospital cloud nodes through communication connection, and the patient handling capacity of the current hospital cloud node is predicted by analyzing outpatient service data and hospitalization service data and is sent to the central control cloud node;
when the predicted patient processing capacity is lower than a specified threshold value, distributing mobile cloud nodes for patients who cannot be seen at the current hospital, sequencing all hospitals by the central control cloud node according to the processing capacity of each hospital and the distance between each hospital and the patient to obtain recommended hospitals of which the distances and the reception capacity are matched with the patients, and writing the geographical position information of the recommended hospitals into the mobile cloud nodes;
the initial medical record of the patient is transmitted to the cloud node of the recommended hospital, the cloud node of the recommended hospital predicts the arrival time of the patient, generates a diagnosis receiving plan according to the initial medical record, and sends a diagnosis receiving instruction to diagnosis receiving equipment and personnel;
the mobile cloud node continuously monitors the health state of the patient and transmits the health state to the cloud node of the recommendation hospital in real time, and the cloud node of the recommendation hospital sends an early warning message to the city terminal user according to the health state of the patient.
2. The method of claim 1, further comprising:
and the mobile cloud node acquires the geographical position of the patient in real time, and navigates the optimal path and the traffic mode leading to the recommended hospital cloud node for the patient by combining the stored information of the recommended hospital cloud node.
3. The method of claim 1, further comprising:
the central control cloud node scans the patient states of all hospital cloud nodes and generates a patient transfer strategy for hospitals with unbalanced patients;
the central control cloud node scans the resource states of all hospital cloud nodes and generates a resource allocation strategy for hospitals with unbalanced resources.
4. The method of claim 1, wherein each hospital cloud node predicts patient handling capacity of a current hospital cloud node by analyzing outpatient service data and hospitalization service data, comprising:
the patient handling capacity is evaluated by the waiting time, a single service desk model is established to estimate the waiting time of each hospital, and the waiting time is estimated by a formula
Calculating the average waiting time of the patients, wherein W is the average waiting time of the patients, σ is the negative index distribution of the patients when arriving at the hospital and obeying σ, and μ is the negative index distribution of the hospital service time obeying μ.
5. The method of claim 1,
the mobile cloud node collects the vital signs of a patient in real time, and predicts whether the patient can reach the recommendation hospital according to the vital signs of the patient;
and sending a help seeking signal to the cloud node of the recommendation hospital under the condition that the patient cannot reach the recommendation hospital.
6. The method of claim 1, wherein generating a treatment plan based on the initial medical record and issuing treatment instructions to treatment equipment and personnel comprises:
searching the in-place state of the medical staff of the recommended hospital according to the initial medical record, determining the medical staff receiving the doctor, and pushing the initial medical record to the medical staff;
and predicting the type and the quantity of protection resources required by the patient to be subjected to treatment according to the initial medical record, and pushing the types and the quantity to medical personnel for preparation.
7. The method according to claim 1, wherein the cloud node of the recommendation hospital sends an early warning message to the city terminal user according to the health status of the patient, and the method comprises the following steps:
predicting the time for the patient to reach the city street according to the geographical position of the patient;
and sending an avoidance protection message to the terminal user of the city street at a preset time before the time.
8. The utility model provides a wisdom city management system based on cloud platform which characterized in that includes:
the system comprises an initial module, a central control cloud node and a plurality of cloud nodes, wherein the initial module is used for setting hospital cloud nodes in each hospital, data and instructions are transmitted among the hospital cloud nodes through communication connection, and each hospital cloud node predicts the patient handling capacity of the current hospital cloud node by analyzing outpatient service data and hospitalization service data and sends the patient handling capacity to the central control cloud node;
the recommendation module is used for distributing mobile cloud nodes to patients who cannot be seen in the current hospital when the patient processing capacity is predicted to be lower than a specified threshold value, the central control cloud node sorts all hospitals according to the processing capacity of each hospital and the distance between each hospital and the patient to obtain recommended hospitals of which the distances and the reception capacity are matched with the patients, and the geographical position information of the recommended hospitals is written into the mobile cloud nodes;
the plan module is used for transmitting the initial medical record of the patient to the cloud node of the recommendation hospital, predicting the arrival time of the patient by the cloud node of the recommendation hospital, generating a diagnosis receiving plan according to the initial medical record, and sending a diagnosis receiving instruction to diagnosis receiving equipment and personnel;
and the blocking module is used for continuously monitoring the health state of the patient by the mobile cloud node and transmitting the health state to the cloud node of the recommendation hospital in real time, and the cloud node of the recommendation hospital sends an early warning message to the city terminal user according to the health state of the patient.
9. The system of claim 8, further comprising:
and the navigation module is used for the mobile cloud node to acquire the geographical position of the patient in real time and navigate the optimal path and the optimal traffic mode leading to the recommended hospital cloud node for the patient by combining the stored information of the recommended hospital cloud node.
10. The system of claim 8, further comprising:
the transfer module is used for scanning the patient states of all hospital cloud nodes by the central control cloud node and generating a patient transfer strategy for the hospitals with unbalanced patients;
and the resource module is used for scanning resource states of all hospital cloud nodes by the central control cloud node and generating a resource allocation strategy for hospitals with unbalanced resources.
Priority Applications (1)
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| CN115188458A (en) * | 2022-09-07 | 2022-10-14 | 武汉大学人民医院（湖北省人民医院） | Medical information management method and device based on cloud computing |
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