Medical platform management system based on big data

Abstract

The invention discloses a medical platform management system based on big data, which comprises a data acquisition module, a data processing module, a path planning module, a route recommendation module, a data storage module, a safety module and a system management module, the data processing module is used for processing the collected data, and the path planning module is used for planning an optimal path according to the current position of a patient, the position of an examination room of an item to be examined and the queuing condition; the route recommendation module is used for returning an optimal route to a user APP and providing navigation and prompting functions, the data storage module is used for storing collected data and processed data, the security module is used for guaranteeing personal information and privacy security of a patient, and the system management module is used for running and managing the system. The method has the characteristics of time saving and intelligent recommendation.

Description

Technical Field

[0001] The present invention relates to the technical field of medical platform management, and in particular to a medical platform management system based on big data. Background Art

[0002] The current medical platform management system has many functions and can reasonably dispatch various resources to improve the efficiency of patients' medical treatment. At present, doctors often ask patients to do some examinations first after the initial consultation. Modern hospitals have large capacity and many departments, which often wastes time on finding examination targets. Or they are not clear about the queues in each examination room, and they are all concentrated in one project queue, which makes patients spend a long time on the examination project. The existing technology does not provide a solution to this phenomenon. If big data can be used to reasonably plan the examination route for patients, it can save time, increase efficiency, and effectively use medical resources. Therefore, it is necessary to design a medical platform management system based on big data that saves time and makes intelligent recommendations. Summary of the invention

[0003] The purpose of the present invention is to provide a medical platform management system based on big data to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a medical platform management system based on big data, comprising: Data collection module, used to collect data on patient location, items to be examined, and number of people waiting in line; A data processing module, used for processing the collected data; The path planning module is used to plan the optimal path according to the patient's current location, the location of the examination room for the item to be examined, and the queue situation; Route recommendation module, used to return the planned optimal route to the user APP, providing navigation and prompt functions; A data storage module is used to store the collected data and processed data for subsequent use and analysis; Security module, used to protect the patient's personal information and privacy security; System management module, used for system operation and management.

[0005] According to the above technical solution, the path planning module includes: Point data unit, used to provide location nodes for path planning; A path planning algorithm unit is used to determine the optimal path by calculating the distance and time consumption between nodes in the map data; The path optimizer unit is used to optimize the planned path.

[0006] According to the above technical solution, the data storage module includes: A database unit for storing various data used in the system; Data warehouse unit, used to store large amounts of historical data; A data backup unit is used to back up data regularly.

[0007] According to the above technical solution, the system management module includes: User management unit, used for user account creation, deletion, modification and permission management; Network management unit, used for setting up and maintaining network topology, network resources and access control.

[0008] According to the above technical solution, the medical platform management method based on big data includes: Step 1: Obtain the patient's current location and the location of the examination room where the patient is to be examined; Step 2: Get the number of people currently waiting in line, estimate the waiting time, and determine whether there are any projects that will take more than half an hour to queue; Step 3: If there is no inspection item with a waiting time of more than half an hour, plan the route; Step 4: When there are inspection items with a waiting time of more than half an hour, plan the route; Step 5: Return the recommended route to the user's APP.

[0009] According to the above technical solution, the step of obtaining the patient's current position and the position of the examination room for the patient's examination item includes: The various areas on different floors of the hospital are divided into different location nodes. First, the system data is read to obtain the patient's current location, and then the items that the patient needs to examine are read. After that, the locations of the examination rooms for these items are confirmed. The patient's location is obtained by reading the patient's outpatient department through the system.

[0010] According to the above technical solution, the steps of obtaining the number of people currently waiting in line, estimating the waiting time in line, and determining whether there is an item whose waiting time exceeds half an hour include: First, obtain all the examination items of the patient. According to the obtained examination items, query the current number of people queuing for each item, estimate the current waiting time through big data, and determine whether there are examination items whose waiting time exceeds half an hour.

[0011] According to the above technical solution, when there is no inspection item with a waiting time exceeding half an hour, the step of planning a route includes: A1. Select the location node where the current patient is located as the starting point; A2. Select a node as the second visited node, calculate the distance from the point to other nodes, and select the node with the closest distance as the next visited node; A3. Select the point selected in step S2 as the starting point, and repeat step S2 until all points have been visited; A4. Calculate the total length of the path; A5. Repeat steps S2 to S4 with different starting points, compare the total lengths of all paths, and select the shortest path as the optimal route; A6. Use big data to calculate the time required for each route. For each selected examination item location node, estimate the time consumed for each section of the journey based on the distance between adjacent nodes. Based on the hospital process planning and historical data, estimate the average waiting time in line at the node, and add this time to the route. Later, estimate the total estimated time for the entire route.

[0012] According to the above technical solution, when there is an inspection item with a waiting time of more than half an hour, the step of planning a route includes: S1. Traverse all points and return the points An{a1,...an} for the inspection items whose waiting time exceeds half an hour, and return the points Bn{b1,...,bn} for the inspection items whose waiting time is within half an hour; S2. Select the point with the longest queue time in An, traverse the Bn points, calculate the time it takes to start from this node, complete the inspection items at Bn and return to this node, sort them from small to large according to the length of time, return to the point with the shortest time, delete the point from Bn and update Bn; S3. Starting from the returned point, traverse the remaining points of Bn, calculate the time it takes to complete the inspection items from the returned point to the remaining points of Bn, sort them from small to large according to the length of time, return the point with the shortest time, delete the point from Bn and update Bn. When the shortest time is greater than the waiting time of a1, return a null value; S4. Loop S3 until the return point is null, and output the results returned in Bn in order to obtain the items that can be completed in sequence during the waiting time of a1; S5. The remaining points in An are cycled according to steps S2-S4 until all points in An are visited; S6. Sort the points in An and the remaining points in Bn according to step 3; S7. Return all sorted results based on the results obtained in S1-S5.

[0013] According to the above technical solution, the step of returning the recommended route to the user APP includes: Based on the planned route, the recommended route will be returned to the user APP. The user APP will display the location nodes, the estimated travel time between each node, the waiting time in line for each node, and the time consumed for item inspection at each node in order. The route is displayed on each floor plan. Clicking on different sections will display the routes on different floor plans.

[0014] Compared with the prior art, the beneficial effects achieved by the present invention are: (1) By setting up a data acquisition module to obtain the patient's location information and check the project information in a timely manner, the route can be recommended to the patient in real time; (2) By setting up a path planning model, patients can be helped to shorten their waiting time, reduce the waste of medical resources, and improve the hospital’s service level; (3) The recommended route is visualized and more intuitive by setting up a route recommendation module; (4) Protect the patient’s personal information and privacy by setting up a security module; (5) By setting up a system management module that combines big data and the medical industry, it is not only beneficial to improve the service level of the hospital, but also helps to promote the informatization process of the entire medical industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 is a flow chart of the method steps of the present invention; Figure 2 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1: Figure 1 This is a flowchart of a medical platform management method based on big data provided in Embodiment 1 of the present invention. This embodiment can be applied to a scenario of a medical platform based on big data. This method can be executed by a medical platform management system based on big data provided in this embodiment. Figure 1 As shown, the method specifically comprises the following steps: Step 1: Obtain the patient's current location and the location of the examination room where the patient is to be examined; In the embodiment of the present invention, each area on different floors of the hospital is divided into different location nodes. First, the system data is read to obtain the current location of the patient, and then the items that the patient needs to examine are read, and then the locations of the examination rooms for these items are confirmed. The patient's location is obtained by the system reading the outpatient room where the patient is located; For example, after the patient has finished the doctor's consultation, he confirms that he wants to complete the blood routine and electrocardiogram examinations. The system obtains the current location of the patient and the locations of the two examination rooms. If the patient is in outpatient room 1, the system automatically reads the current location as outpatient room 1. After obtaining the patient's location and the examination items required by the patient, the medical platform management system will start planning a recommended route; Step 2: Get the number of people currently waiting in line, estimate the waiting time, and determine whether there are any projects that will take more than half an hour to queue; In the embodiment of the present invention, all the examination items of the patient are first obtained, and according to the obtained examination items, the current number of people in the queue for each item is queried, the current waiting time in the queue is estimated through big data, and it is determined whether there is an examination item whose waiting time exceeds half an hour; For example, the patient's examination items include liver function and B-ultrasound. The current number of people in the queue for these two examination items is queried from the system. The big data estimates the expected waiting time based on the number of people in the queue. Based on the estimated waiting time, it is determined whether there are items with a waiting time of more than half an hour.

[0018] Step 3: If there is no inspection item with a waiting time of more than half an hour, plan the route; In the embodiment of the present invention, when there is no examination item with a queue route of more than half an hour, the medical management platform system will recommend patients to go to the points in sequence for queue examination. The specific steps are as follows: A1. Select the location node where the current patient is located as the starting point; A2. Select a node as the second visited node, calculate the distance from the point to other nodes, and select the node with the closest distance as the next visited node; A3. Select the point selected in step S2 as the starting point, and repeat step S2 until all points have been visited; A4. Calculate the total length of the path; A5. Repeat steps S2 to S4 with different starting points, compare the total lengths of all paths, and select the shortest path as the optimal route; A6. Use big data to calculate the time required for each route. For each selected examination item location node, estimate the time consumed for each route based on the distance between adjacent nodes. According to the hospital process planning and historical data, estimate the average waiting time in the queue at the node, and add this time to the route. Then estimate the total estimated time of the entire route. For example, when the patient's current queuing time for an examination item does not exceed half an hour, the system reads the patient's current outpatient clinic 1 and the examination items the patient needs. The system calculates the shortest path between the location node of outpatient clinic 1 and the location nodes of each examination item, and calculates the time required for the route and the queuing and examination time required for each node, plans the optimal route, and estimates the time spent on each section of the journey and the total estimated time for the entire route.

[0019] Step 4: When there are inspection items with a waiting time of more than half an hour, plan the route; In the embodiment of the present invention, when there are examination items with a waiting time of more than half an hour, the medical management platform will recommend that the patient first go to the examination item that takes a long time to get a number, use the waiting time to go to other examination items, and then return for the examination. The specific steps are as follows: S1. Traverse all points and return the points An{a1,...an} for the inspection items whose waiting time exceeds half an hour, and return the points Bn{b1,...,bn} for the inspection items whose waiting time is within half an hour; S2. Select the point with the longest queue time in An, traverse the Bn points, calculate the time it takes to start from this node, complete the inspection items at Bn and return to this node, sort them from small to large according to the length of time, return to the point with the shortest time, delete the point from Bn and update Bn; S3. Starting from the returned point, traverse the remaining points of Bn, calculate the time it takes to complete the inspection items from the returned point to the remaining points of Bn, sort them from small to large according to the length of time, return the point with the shortest time, delete the point from Bn and update Bn. When the shortest time is greater than the waiting time of a1, return a null value; S4. Loop S3 until the return point is null, and output the results returned in Bn in order to obtain the items that can be completed in sequence during the waiting time of a1; S5. The remaining points in An are cycled according to steps S2-S4 until all points in An are visited; S6. Sort the points in An and the remaining points in Bn according to step 3; S7. Return all sorted results based on the results obtained in S1-S5; In this step, the total time to complete the project from a node in An to a node in Bn is the sum of the travel time from a node in An to a point in Bn, the queuing waiting time at the point in Bn, the time spent on the inspection project at the point in Bn, and the travel time from the point in Bn back to point A; the results returned during the calculation process for the inspection items that exceed half an hour in this step are 5 minutes deducted from the original time, giving the system a 5-minute prediction deviation; this step uses big data to estimate the time required for the journey, the queuing waiting time, and the completion time of the inspection items combined with the algorithm to recommend routes, so that patients can maximize the use of the longer queuing waiting time and complete other inspection items as much as possible within this time, thereby achieving the purpose of saving time.

[0020] For example, after visiting outpatient clinic 1, the patient confirms that the examination items he needs include electrocardiogram, blood routine test, and B-ultrasound. The system estimates based on big data that the current waiting time for these items is 5 minutes, 7 minutes, and 35 minutes, respectively. The final recommended route is: 1) Go to the B-ultrasound examination room from outpatient department 1 to get a number. The estimated journey time is 5 minutes; 2) Go from the B-ultrasound examination room to the electrocardiogram examination room to get a number and queue up for the examination. The estimated journey time is 5 minutes, the waiting time in the queue is 5 minutes, and the examination takes 2 minutes; 3) Go from the ECG examination room to the blood routine examination room to get a number and queue up for examination. The estimated journey time is 3 minutes, the waiting time in the queue is 7 minutes, and the examination time is 2 minutes; 4) The estimated journey time from the routine blood test room to the B-ultrasound test room is 5 minutes.

[0021] Step 5: Return the recommended route to the user's APP.

[0022] In the embodiment of the present invention, the recommended route is returned to the user APP according to the planned route. The user APP displays each location node, the estimated time between each node, the waiting time for each node, and the time consumed for each node project inspection in order. The route is displayed in a floor plan of each layer. Clicking on different sections will display the routes on different floor plans. For example, after visiting outpatient clinic 1, the patient confirms that the examination items required are electrocardiogram and blood routine examination. The system recommends the optimal route from outpatient clinic 1 to the electrocardiogram examination room and blood routine examination room based on the patient's location and the examination items required by the patient, including the route, estimated travel time, estimated waiting time, and estimated time consumption for the examination items.

[0023] Embodiment 2: Embodiment 2 of the present invention provides a medical platform management system based on big data. Figure 2 The schematic diagram of the module composition of the medical platform management system based on big data provided in the second embodiment of the present invention is as follows: Figure 2 As shown, the system includes: Data collection module, used to collect data on patient location, items to be examined, and number of people waiting in line; A data processing module, used for processing the collected data; The path planning module is used to plan the optimal path according to the patient's current location, the location of the examination room for the item to be examined, and the queue situation; Route recommendation module, used to return the planned optimal route to the user APP, providing navigation and prompt functions; A data storage module is used to store the collected data and processed data for subsequent use and analysis; Security module, used to protect the patient's personal information and privacy security; System management module, used for system operation and management.

[0024] In some embodiments of the present invention, the path planning module includes: Point data unit, used to provide location nodes for path planning; A path planning algorithm unit is used to determine the optimal path by calculating the distance and time consumption between nodes in the map data; The path optimizer unit is used to optimize the planned path.

[0025] In some embodiments of the present invention, the data storage module includes: A database unit for storing various data used in the system; Data warehouse unit, used to store large amounts of historical data; A data backup unit is used to back up data regularly.

[0026] In some embodiments of the present invention, the system management module includes: User management unit, used for user account creation, deletion, modification and permission management; Network management unit, used for setting up and maintaining network topology, network resources and access control.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0028] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A medical platform management method based on big data, characterized by: The method comprises: Step 1: Obtain the patient's current location and the location of the examination room where the patient is to be examined; Step 2: Get the number of people currently waiting in line, estimate the waiting time, and determine whether there are any projects that will take more than half an hour to queue; Step 3: If there is no inspection item with a waiting time of more than half an hour, plan the route; Step 4: When there are inspection items with a waiting time of more than half an hour, plan the route; Step 5: Return the recommended route to the user's APP.

2. The medical platform management method based on big data according to claim 1, characterized in that: The step of obtaining the patient's current location and the location of the examination room for the patient's pending examination item includes: The various areas on different floors of the hospital are divided into different location nodes. First, the system data is read to obtain the patient's current location, and then the items that the patient needs to examine are read. After that, the locations of the examination rooms for these items are confirmed. The patient's location is obtained by reading the patient's outpatient department through the system.

3. The medical platform management method based on big data according to claim 1, characterized in that: The steps of obtaining the current number of people waiting in line, estimating the waiting time in line, and determining whether there is an item whose waiting time exceeds half an hour include: First, obtain all the examination items of the patient. According to the obtained examination items, query the current number of people queuing for each item, estimate the current waiting time through big data, and determine whether there are examination items whose waiting time exceeds half an hour.

4. The medical platform management method based on big data according to claim 1, characterized in that: When there is no inspection item with a waiting time exceeding half an hour, the step of planning a route includes: A1. Select the location node where the current patient is located as the starting point; A2. Select a node as the second visited node, calculate the distance from the point to other nodes, and select the node with the closest distance as the next visited node; A3. Select the point selected in step S2 as the starting point, and repeat step S2 until all points have been visited; A4. Calculate the total length of the path; A5. Repeat steps S2 to S4 with different starting points, compare the total lengths of all paths, and select the shortest path as the optimal route; A6. Use big data to calculate the time required for each route. For each selected examination item location node, estimate the time consumed for each section of the journey based on the distance between adjacent nodes. Based on the hospital process planning and historical data, estimate the average waiting time in line at the node, and add this time to the route. Later, estimate the total estimated time for the entire route.

5. The medical platform management system based on big data according to claim 1, characterized in that: When there is an inspection item with a waiting time of more than half an hour, the step of planning a route includes: S1. Traverse all points and return the points An{a1,...an} for the inspection items whose waiting time exceeds half an hour, and return the points Bn{b1,...,bn} for the inspection items whose waiting time is within half an hour; S2. Select the point with the longest queue time in An, traverse the Bn points, calculate the time it takes to start from this node, complete the inspection items at Bn and return to this node, sort them from small to large according to the length of time, return to the point with the shortest time, delete the point from Bn and update Bn; S3. Starting from the returned point, traverse the remaining points of Bn, calculate the time it takes to complete the inspection items from the returned point to the remaining points of Bn, sort them from small to large according to the length of time, return the point with the shortest time, delete the point from Bn and update Bn. When the shortest time is greater than the waiting time of a1, return a null value; S4. Loop S3 until the return point is null, and output the results returned in Bn in order to obtain the items that can be completed in sequence during the waiting time of a1; S5. The remaining points in An are cycled according to steps S2-S4 until all points in An are visited; S6. Sort the points in An and the remaining points in Bn according to step 3; S7. Return all sorted results based on the results obtained in S1-S5.

6. The medical platform management method based on big data according to claim 1, characterized in that: The step of returning the recommended route to the user APP includes: Based on the planned route, the recommended route will be returned to the user APP. The user APP will display the location nodes, the estimated travel time between each node, the waiting time in line for each node, and the time consumed for item inspection at each node in order. The route is displayed on each floor plan. Clicking on different sections will display the routes on different floor plans.

7. A medical platform management system based on big data, characterized by: The system comprises: Data collection module, used to collect data on patient location, items to be examined, and number of people waiting in line; A data processing module, used for processing the collected data; The path planning module is used to plan the optimal path according to the patient's current location, the location of the examination room for the item to be examined, and the queue situation; Route recommendation module, used to return the planned optimal route to the user APP, providing navigation and prompt functions; A data storage module is used to store the collected data and processed data for subsequent use and analysis; Security module, used to protect the patient's personal information and privacy security; System management module, used for system operation and management.

8. The big data-based medical platform management system according to claim 7, characterized in that: The path planning module includes: Point data unit, used to provide location nodes for path planning; A path planning algorithm unit is used to determine the optimal path by calculating the distance and time consumption between nodes in the map data; The path optimizer unit is used to optimize the planned path.

9. The medical platform management system based on big data according to claim 8, characterized in that: The data storage module comprises: A database unit for storing various data used in the system; Data warehouse unit, used to store large amounts of historical data; A data backup unit is used to back up data regularly.

10. The medical platform management system based on big data according to claim 9, characterized in that: The system management module includes: User management unit, used for user account creation, deletion, modification and permission management; Network management unit, used for setting up and maintaining network topology, network resources and access control.

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