Hospital intelligent operation management method, server, medium and product

Abstract

The invention discloses a hospital intelligent operation management method, a server, a medium and a product, and relates to the field of digital medical treatment. The method comprises the following steps: when a target ambulance arrives at an accident scene, obtaining personal information and injury conditions of a patient; determining a target medical equipment condition and a target medicine condition required for maintaining the current vital signs of the patient within the target ambulance driving time; calculating a risk assessment value of the patient under the transportation of the target ambulance configured with different medical devices and medicines; when the risk assessment values are all greater than a preset threshold value, determining a target duration and missing medical supplies of the target ambulance; searching a preset emergency medical warehouse with missing medical supplies and closest to the target ambulance, and determining a position set; and when the target position exists in the position set, sending the target position and the missing medical supplies to the emergency medical warehouse. By implementing the technical scheme, the timeliness of medical treatment of the patient during the transportation of the ambulance is improved.

Description

Technical Field

[0001] This application relates to the field of digital medicine, and in particular to a hospital intelligent operation and management method, server, medium and product. Background Art

[0002] With the rapid development of the medical industry, smart healthcare has become a key means of improving the quality of medical services and optimizing the allocation of medical resources. By introducing advanced information technology, smart hospital operations management is committed to breaking the limitations of traditional medical models, achieving efficient and intelligent medical processes and precise allocation of medical resources, thereby providing patients with higher-quality and more convenient medical services.

[0003] At present, when facing a major accident, emergency rescue is needed or the patient is unable to seek medical treatment on his own, the patient is usually transported to the hospital for treatment by the hospital ambulance.

[0004] However, when an ambulance is transporting the injured to the hospital for treatment, the medical equipment and medicines in the ambulance are fixed and limited. When patients with special medication needs need to be transported or the ambulance is running out of medicines due to long-term operation, medical staff can often only rely on limited existing supplies for emergency treatment, and are unable to accurately meet the patient's treatment needs. As a result, patients face the risk of delayed treatment and difficulty maintaining vital signs during transportation, and may even miss the best time for rescue due to the lack of key medicines and equipment. Summary of the Invention

[0005] This application provides a hospital intelligent operation management method, server, medium and product, which can improve the timeliness of medical treatment for patients while being transported by ambulance.

[0006] In the first aspect, the present application provides a hospital intelligent operation and management method, which includes: when the target ambulance of the hospital arrives at the accident scene, obtaining the patient's historical medical history and injury situation; determining the target medical equipment and target drug situation required to maintain the patient's current vital signs during the driving time of the target ambulance based on the historical medical history and the injury situation; calculating the risk assessment value of the patient under the transportation of the target ambulance equipped with different medical equipment and drugs based on the idle medical equipment and idle drug situation in all preset ambulances, the target medical equipment situation and the target drug situation; when the risk assessment values ​​are all greater than the preset threshold value, determining the target medical equipment situation and the first drug situation corresponding to the lowest risk assessment value. The target time length and the missing medical supplies of the target ambulance are determined, and the target time length is the shortest time length that the first medical equipment condition and the first drug condition can maintain the patient's current vital signs; find the preset emergency medical warehouse with the missing medical supplies that is closest to the target ambulance; based on the target time length, the position of the emergency medical warehouse, the driving path and driving speed of the target ambulance, determine the position set, and the time length for the missing medical supplies delivered by the emergency medical warehouse to arrive at each position in the position set is less than the target time length; when the target position exists in the position set, send the target position and the missing medical supplies to the emergency medical warehouse, and when the target ambulance arrives at the target position, the missing medical supplies delivered by the emergency medical warehouse have arrived at the target position.

[0007] Using the above technical solution, the medical equipment and drugs required to maintain the patient's vital signs during ambulance transportation are determined based on the patient's historical medical history and injury situation. A risk assessment is then conducted based on the supply situation in the ambulance to calculate the probability of the patient being in a dangerous situation during transportation due to insufficient medical supplies. When the risk assessment values ​​are all below the preset threshold, meaning that the patient is very likely to be unable to maintain vital signs due to insufficient medication during transportation, the nearest emergency medical warehouse is located and the appropriate location for handing over medical supplies is calculated to ensure that the missing medical supplies in the ambulance are replenished in the shortest possible time, allowing the patient to obtain medical supplies in a timely manner to maintain their vital signs, avoiding delays in treatment due to insufficient medical supplies, improving the timeliness and effectiveness of medical treatment for patients during ambulance transportation, and also optimizing the allocation and utilization efficiency of hospital medical resources.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the position set is determined based on the target duration, the location of the emergency medical warehouse, the driving path and driving speed of the target ambulance, specifically including: obtaining the terminal position of the target ambulance; planning the driving path with the shortest driving time from the current position to the terminal position of the target ambulance; based on the location of the emergency medical warehouse and the driving path, calculating the predicted duration for the emergency medical warehouse to deliver the missing medical supplies to each location in the target path of the driving path, the target path being the set of locations that the target ambulance can reach within the target duration; when there is a target predicted duration among all predicted durations that is less than the target duration, obtaining the position set in the driving path corresponding to the target predicted duration.

[0009] By adopting the above technical solution, by planning the shortest driving route of the ambulance, combining the location of the emergency medical warehouse with the driving dynamics of the ambulance, calculating the predicted time for the missing medical supplies to be delivered to each location on the driving route, and screening out a set of locations that meet the time requirements, it is ensured that the materials delivered by the emergency medical warehouse can be handed over to the ambulance within the effective time, avoiding handover delays due to unreasonable material distribution routes or time estimation deviations, further improving the timeliness and accuracy of medical material supply, providing more reliable protection for the life safety of patients during ambulance transportation, and at the same time realizing the refined management of medical resource allocation in spatial and temporal dimensions.

[0010] In combination with some embodiments of the first aspect, in some embodiments, obtaining the terminal position of the target ambulance specifically includes: calculating the probability and type of surgery that the patient currently needs to undergo based on the historical medical history and the injury condition; when the probability of the surgery is greater than a preset probability threshold, obtaining the number of surgeries corresponding to the surgery type that the hospital can accept; if the number of surgeries is zero, searching for a target hospital in the preset hospital set that can accept the surgery type; and using the location of the target hospital as the terminal position of the target ambulance.

[0011] The above technical solution combines the patient's medical history and injury history to determine the patient's surgical needs, and dynamically adjusts the ambulance's destination based on the hospital's surgical capacity and the patient's surgical needs. When the hospital is unable to undertake the corresponding surgery, the system quickly locates the target hospital in the preset hospital set, avoiding delays in treatment due to saturated hospital surgical resources. This improves the efficiency of matching emergency resources with patient needs, ensures that patients receive appropriate surgical treatment in a timely manner, optimizes the coordinated scheduling of medical resources within the region, and enhances the flexibility and effectiveness of the hospital's intelligent operations management system in responding to complex emergency scenarios.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining the location set based on the target duration, the location of the emergency medical warehouse, the driving path and driving speed of the target ambulance, the method also includes: when there is no target location in the location set, based on the current location, driving speed and historical energy consumption records of the target ambulance, calculating a first energy consumption set and a second energy consumption set, the first energy consumption set being a set of energy consumption consumed by the target ambulance when receiving the missing medical supplies at each location in the location set, and the second energy consumption set being a set of energy consumption consumed by the target ambulance from each location in the location set to the terminal location; calculating a remaining energy consumption set based on the current energy consumption of the target ambulance and the first energy consumption set; when there is no remaining energy consumption greater than the second energy consumption corresponding to the remaining energy consumption, calculating the receiving time point at which the target ambulance receives the missing medical supplies at each location in the location set; and sending the location corresponding to the earliest receiving time point and the missing medical supplies to the emergency medical warehouse.

[0013] With the above technical solution, when the target location does not exist in the location set, it means that the ambulance needs to wait for a period of time at the handover location before obtaining medical supplies. The extra waiting time may cause the ambulance's own energy consumption to be insufficient to drive the vehicle to the destination. At this time, the remaining energy consumption of the ambulance when receiving the supplies is calculated to determine whether the energy consumption is sufficient to continue driving to the destination. If the energy consumption is insufficient, the time points at which each location receives the supplies are calculated, and the location corresponding to the earliest reception time point is selected as the handover point. This ensures that the patient can receive medical supplies as soon as possible to maintain vital signs, providing a longer buffer time for later replacement of the ambulance with sufficient energy to transport the patient to the hospital or for the ambulance to recharge and continue transporting the patient to the hospital.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of sending the location corresponding to the earliest receiving time point and the missing medical supplies to the emergency medical warehouse, the method also includes: determining a first duration based on the target medical equipment status and the target drug status, and the first duration is the shortest duration that the target medical equipment status and the target drug status can maintain the patient's current vital signs; planning a charging path with the shortest driving time for the target ambulance to pass through the charging station to the terminal location; obtaining the charging driving time of the charging path; when the charging driving time is less than the first duration, updating the driving path of the target ambulance.

[0015] This technical solution combines the medical treatment time window with the vehicle's energy supply needs by evaluating the minimum time that target medical equipment and medications can maintain a patient's vital signs and planning the shortest charging route based on the ambulance's charging requirements. If the charging time is less than the minimum time it takes to maintain vital signs, the route is updated promptly to ensure the ambulance can both recharge and reach the hospital within the safe timeframe for maintaining the patient's vital signs, thus avoiding delays in treatment due to insufficient vehicle energy or inappropriate route planning.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining the charging driving time of the charging path, the method further includes: when the charging driving time is greater than the first time, obtaining a set of ambulances that can replace patients or idle ambulances within a preset range of the target ambulance; calculating the arrival time points of each ambulance in the ambulance set at the destination location; when there is a second time between the arrival time point and the current time point that is less than the first time, the ambulance corresponding to the earliest arrival time point is used as a replacement ambulance for the target ambulance, and the replacement ambulance is the ambulance that transports the patient from the target location to the destination location.

[0017] By adopting the above technical solution, when the charging driving time exceeds the shortest time that the patient's vital signs can be maintained, the standby ambulance dispatch mechanism is activated. By screening the ambulances that can replace patients or are idle within a preset range and calculating the time for each vehicle to arrive at the destination, the ambulance that can complete the transfer in the shortest time is given priority as the replacement vehicle, avoiding the risk of the patient missing the best treatment time due to insufficient energy and long charging time of the ambulance. It not only ensures that the patient can be sent to the hospital for treatment in time within the effective time of maintaining vital signs, but also realizes the dynamic allocation and efficient utilization of ambulance resources in the region, thereby improving the success rate and reliability of medical rescue.

[0018] In combination with some embodiments of the first aspect, in some embodiments, when there is a target location in the location set, after the step of sending the target location and the missing medical supplies to the emergency medical warehouse, the method also includes: when the target ambulance transports the patient, obtaining in real time the first medicine taken by the target doctor on the target ambulance; based on the patient's current vital signs data, the historical medical history and the remaining medicines in the target ambulance, determining whether there is a second medicine in the target ambulance with a better therapeutic effect than the first medicine; if so, playing a prompt message through the preset speaker on the target ambulance, and the prompt message is used to prompt the target doctor to determine whether the wrong medicine is taken.

[0019] Using this technical solution, while an ambulance is transporting a patient, doctors' medication use is monitored in real time. This is combined with patient vital sign data, historical medical records, and the remaining medications in the vehicle to determine whether the currently used medication is the most appropriate. If a superior medication is identified, an immediate notification is issued through the vehicle's speakers, preventing doctors from overthinking medication in emergency situations and ensuring that patients receive the most appropriate medication during transport.

[0020] In a second aspect, an embodiment of the present application provides a hospital management server, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the hospital management server to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a hospital management server, the hospital management server executes the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, the present application provides a computer program product, which, when running on a hospital management server, enables the hospital management server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the hospital management server provided in the second aspect, the storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the method provided in this application. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding methods and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. This application calculates the risk assessment value of the patient being in a dangerous situation due to insufficient medical supplies during transportation. When the risk assessment value is lower than the preset threshold, that is, the patient is very likely to be unable to maintain vital signs due to insufficient medicine during transportation, the nearest emergency medical warehouse is located and the appropriate location for handing over medical supplies is calculated to ensure that the missing medical supplies in the ambulance are replenished in the shortest time, so that the patient can obtain medical supplies in time to maintain his or her vital signs, avoid delays in treatment due to insufficient medical supplies, and improve the timeliness and effectiveness of medical treatment for patients during transportation by ambulance.

[0025] 2. When the remaining energy consumption of the ambulance after receiving the supplies is insufficient to supply the vehicle to continue driving to the destination, and the charging driving time of the ambulance exceeds the shortest time that the patient's vital signs can be maintained, the present application selects ambulances that can replace patients or are idle within a preset range, and calculates the time for each vehicle to arrive at the destination, and gives priority to the ambulance that can complete the transfer in the shortest time as the replacement vehicle to complete the remaining transfer distance of the patient, avoiding the risk of the patient missing the best time for treatment due to insufficient energy and long charging time of the ambulance. It not only ensures that the patient can be sent to the hospital for treatment in time within the effective time for maintaining vital signs, but also realizes the dynamic allocation and efficient utilization of ambulance resources in the region, and improves the success rate and reliability of medical rescue.

[0026] 3. This application monitors doctors' medication use in real time and analyzes it based on patient vital signs, medical history, and remaining medications in the vehicle to identify whether the current medication is the most appropriate. If a superior medication is found, an immediate notification is sent through the vehicle's speakers, preventing doctors from oversight in emergency settings and misusing medication, ensuring patients receive the most appropriate medication during transport. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a structural diagram of a system architecture to which the hospital intelligent operation management method in the embodiment of the present application can be applied; Figure 2 This is a flowchart of the hospital smart operation management method in the embodiment of the present application; Figure 3 This is another flowchart of the hospital smart operation management method in the embodiment of the present application; Figure 4 This is an exemplary hardware structure diagram of the hospital management server in the embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of this application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in this application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0030] Figure 1 It is a structural diagram of the system architecture to which the hospital intelligent operation management method in the embodiment of this application can be applied.

[0031] See also Figure 1 ,The hospital smart operation and management system includes medical equipment, smart medicine boxes and hospital management servers.

[0032] The hospital management server, the core component of the system, analyzes and processes data collected by medical devices and smart medicine boxes, and transmits medical supply request information to the emergency medical warehouse. Medical devices, deployed in ambulances, collect vital sign data from patients inside and transmit this data to the hospital management server. Smart medicine boxes, deployed in ambulances, transmit information about the medications in the boxes to the server. The emergency medical warehouse receives medical supply request information from the hospital management server and dispatches medical supplies to the ambulance accordingly.

[0033] Through the above system architecture, the hospital's intelligent operation and management system can send information to the emergency medical warehouse when the medical equipment equipped in the ambulance and the medical drugs in the smart medicine box cannot maintain the patient's vital signs during the ambulance's driving, and call the necessary medical supplies to the ambulance, so that the patient can receive timely treatment and improve the timeliness of medical treatment for patients during ambulance transportation.

[0034] In related technologies, when facing a major accident, emergency rescue is required, or when the patient is unable to seek medical treatment on their own, the patient is usually transported to the hospital for treatment by hospital ambulance. However, during the transportation of the injured to the hospital for treatment, the medical equipment and medicines equipped in the ambulance are fixed and limited. When it is necessary to transport patients with special medication needs or the ambulance is running out of medicine due to long-term operation, medical staff can often only rely on limited existing supplies for emergency treatment, and are unable to accurately meet the patient's treatment needs. As a result, the patient faces the risk of delayed treatment and difficulty maintaining vital signs during transportation, and may even miss the best time for rescue due to the lack of key medicines and equipment.

[0035] The hospital intelligent operation and management method in the embodiment of the present application is adopted. By calculating the risk assessment value of the patient being in a dangerous situation due to insufficient medical supplies during transportation, when the risk assessment values ​​are lower than the preset threshold, that is, when the patient is very likely to be unable to maintain vital signs due to insufficient medicine during transportation, the nearest emergency medical warehouse is located and the location of the appropriate handover of medical supplies is calculated to ensure that the missing medical supplies in the ambulance are replenished in the shortest time, so that the patient can obtain medical supplies in time to maintain his or her vital signs, avoid delays in treatment due to insufficient medical supplies, and improve the timeliness and effectiveness of medical treatment for patients during transportation by ambulance.

[0036] The following combination Figure 2 To illustrate the method of the embodiment of the present application.

[0037] See also Figure 2 , which is a flow chart of the hospital intelligent operation and management method in the embodiment of this application.

[0038] S201. When the target ambulance of this hospital arrives at the accident scene, obtain the patient's medical history and injury conditions.

[0039] Among them, the injury conditions include basic vital signs data such as heart rate, blood pressure, respiratory rate, body temperature, injury location and degree of injury, etc.

[0040] Specifically, first, real-time communication is established with the positioning device on the target ambulance to obtain the real-time position of the target ambulance, and then it is compared with the preset coordinates of the accident scene. When the error between the ambulance position and the accident scene coordinates is within the preset threshold range, it is determined that the ambulance has arrived at the accident scene.

[0041] When the target ambulance of this hospital arrives at the scene of the accident, real-time video data is obtained through image acquisition equipment installed in the ambulance door and compartment. Image recognition technology is used to dynamically monitor the people in the real-time video data, and a human feature recognition algorithm is used to determine whether there are patients entering the ambulance.

[0042] When a patient is detected entering a target ambulance, facial recognition technology is used to identify the patient's facial information in the real-time video data and compare the identified facial information with the user information in the preset medical database. If the comparison is successful, the patient's personal information in the medical database is obtained, including name, age, contact information, and historical medical history. If the comparison fails, a prompt is sent to the onboard medical staff through the vehicle terminal. The medical staff can manually enter the patient's name, age, gender, and other information through the touch screen. The information entered by the medical staff is then compared with the user information in the preset medical database. If the comparison is successful, the patient's personal information in the medical database is obtained; if the comparison fails, the information entered by the medical staff is used as the patient's personal information.

[0043] To acquire basic vital signs data, the system communicates with multi-parameter monitors, electrocardiographs and other medical equipment equipped in ambulances to obtain the patient's heart rate, blood pressure, respiratory rate, body temperature and other basic vital signs data in real time, and structures and stores and analyzes these data in time series.

[0044] To determine the location and severity of injury, an image recognition algorithm is first used to scan real-time video data frame by frame. By extracting and analyzing the features of bloodstain color, morphology, and distribution area on different parts of the patient, a first set of injury locations is determined. Then, based on a pre-established database linking accident causes to common injury type sets, a set of common injury types corresponding to the cause of the accident at the scene is searched. The first set of injury locations is cross-matched with the set of common injury types. By comparing the overlap and degree of correlation between the two, high-probability injury locations are selected to generate a second set of injury locations. Next, vital sign parameter data is obtained from the basic vital sign data, corresponding to the preset vital sign parameters associated with each injury location in the second set of injury locations. Based on the deviation between the vital sign parameter data and the preset normal vital sign parameter data and the weight of the preset vital sign parameter corresponding to each injury location, a weighted calculation is performed to determine the severity of injury. The severity of injury for each injury location in the second set of injury locations is determined based on a pre-set table of injury severity values ​​and injury severity correspondences.

[0045] At the same time, a connection is established with the voice collection equipment on the target ambulance to receive real-time voice information from medical staff on-site assessing the patient's injuries. Voice recognition technology is used to convert the voice information into text content, and natural language processing technology is used to extract keywords from the text to identify the injured area and descriptions of the injury severity mentioned. If the description of the injury severity is quantitative, such as "the amount of bleeding is approximately 500ml," the numerical value is compared with the preset normal physiological indicator range and bleeding severity grading standards, and the first injury severity level is determined based on the degree of deviation. If the description of the injury severity is qualitative, such as "confused consciousness," it is mapped to the corresponding injury severity semantic category using a pre-trained text classification model. This model, trained based on a large amount of medical text data, can accurately identify the severity information contained in different qualitative descriptions. Next, based on the quantitative and qualitative description results, the injury severity of each injured area is determined. Finally, the injury locations and severity obtained from the two different methods were cross-validated. For conflicting or inconsistent information, the information obtained using the method with the higher confidence level was selected as the final result, based on the preset confidence level. The cross-validated data were integrated to determine the patient's injury location and severity for each injury site.

[0046] S202. Determine the target medical equipment and target drugs required to maintain the patient's current vital signs within the target ambulance travel time based on the historical medical history and injury situation.

[0047] The target medical device information includes the types of various medical devices, etc. The target drug information includes the types and quantities of various drugs, etc.

[0048] Specifically, we first analyze and integrate historical medical records and injury data. We extract key information from historical medical records, including age, gender, body mass index, long-term medications, and chronic conditions (such as hypertension, diabetes, and heart disease), allergies, and surgical history. We also quantify and structure the basic vital signs (heart rate, blood pressure, respiratory rate, and temperature), injury location, and severity of injury data from injury records. Then, we integrate historical medical record data with injury data to form a complete patient health data set.

[0049] This deep learning-based risk prediction model uses the integrated patient health data set as input and outputs the various conditions that a patient may develop within the target ambulance travel time, along with their corresponding risk probabilities. This model is constructed using a hybrid architecture combining a long short-term memory (LSTM) network and a convolutional neural network (CNN).

[0050] During the model training process, the model is trained using a large amount of patient data collected from the hospital's electronic medical record system and historical emergency records database. The model parameters are continuously adjusted during the training process, allowing the trained model to capture the complex patterns and dynamic changes in patient health data. This patient data covers the patient's historical medical information, injury data, and various conditions and outcomes encountered during ambulance transport.

[0051] The patient health data set is fed into the trained model. The data first enters the Long Short-Term Memory (LSTM) network. The LSTM is capable of processing historical medical information with time series characteristics, such as long-term changes in a patient's vital signs, the onset and frequency of past illnesses, and the chronological order of medication use. Through its unique gating mechanism, it filters and retains long-term information that is important for current predictions, while discarding irrelevant historical data. This process extracts the dynamic temporal characteristics of the patient's health status. This processed information, along with injury data, is then fed into a convolutional neural network (CNN). Through convolutional and pooling layers, the CNN performs feature extraction and dimensionality reduction on the injury data, capturing local features of the injury site and the spatial distribution of vital sign data. This allows it to detect unusual fluctuation patterns in vital sign data. The features extracted by the LSTM and CNN are fused in subsequent layers. The resulting feature vector captures the temporal dynamics of the patient's historical health information and the spatial characteristics of the injury. These feature vectors are then input into the fully connected layer, and after a series of linear transformations and activation function operations, the Softmax activation function is finally used to output various possible conditions (such as cardiac arrest risk, increased bleeding risk, infection risk, etc.) that the patient may develop within the target ambulance driving time and their corresponding probability values.

[0052] For each possible condition identified by the model, the corresponding standard treatment plan is retrieved from a pre-set medical knowledge base to determine the medical equipment and medications required to maintain the patient's vital signs under various conditions. For example, a heart patient with a potential arrhythmia would require a defibrillator, an ECG monitor, and antiarrhythmic medications such as amiodarone.

[0053] Finally, the server will combine the patient's historical medical history to personalize the medical devices and medications obtained, ultimately determining the target medical device and medication profile. If the patient has a history of allergies to a common medication, the server will automatically filter out alternative medications from a pre-set replacement medication table to replace the allergic medication. If the patient has been taking a specific medication for a long time, the server will determine whether any of the obtained medications conflict with the specific medication based on a pre-set medication conflict table, and replace the conflicting medication to avoid adverse reactions.

[0054] S203. Based on the idle medical equipment and idle medicine status in all preset ambulances, the target medical equipment status and the target medicine status, calculate the risk assessment value of the patient when being transported by the target ambulance equipped with different medical equipment and medicines.

[0055] Specifically, the system first obtains the available medical equipment and available medicine status within the hospital's pre-set ambulances within the preset range of the target ambulance. It also obtains the current medical equipment and medicine status within the target ambulance. This preset range can be dynamically adjusted based on factors such as the ambulance's speed and road conditions to ensure rapid deployment of available resources. The real-time location of each of the hospital's ambulances is first obtained. Pre-set ambulances whose real-time locations are within the preset range of the target ambulance's real-time location are selected. The target medical equipment and target medicine status of each pre-set ambulance are then obtained. Next, the preset basic medical equipment and the real-time medicine status of each pre-set ambulance and the target ambulance are obtained, along with the real-time medicine status of the smart medicine box. The target medical equipment and target medicine corresponding to each pre-set ambulance are then removed from the preset basic medical equipment and real-time medicine status of each pre-set ambulance, resulting in the available medical equipment and medicine status of each pre-set ambulance.

[0056] This smart medicine box, equipped with a high-precision weight sensor, RFID recognition module, and temperature and humidity monitoring device, can sense the use and replenishment of medicines in real time, accurately tracking the inventory quantity, expiration date, and storage environment of each box. When medicines are taken or replenished, the weight sensor calculates the weight change and automatically updates the inventory quantity based on the preset single-box weight data. The RFID recognition module scans the electronic label on the medicine packaging to obtain detailed information such as the drug name, specification, production date, and expiration date.

[0057] Next, the risk probability of each condition that the patient may develop during the ambulance's travel time is multiplied by the corresponding preset risk degree coefficient to obtain a risk weighted value for each condition.

[0058] A first risk assessment value is calculated based on the current medical equipment and medication status of the target ambulance. For each condition that a patient may develop while the target ambulance is in operation, the target medical equipment and medication required for that condition are obtained. These target medical equipment and medications are compared with the target ambulance's current medical equipment and medications to determine missing medical equipment and medications. Then, based on a preset replacement medication table and a replacement medical equipment table, the devices and medications that can be replaced within the current medical equipment and medications are determined, and the replaceable medical equipment and medications from the missing medical equipment and medications are deleted. Next, a preset risk aggravation coefficient for the missing medical equipment and medication for treating that condition is obtained. The risk weight corresponding to that condition is multiplied by the risk aggravation coefficient to obtain an adjusted risk value. Finally, the adjusted risk values ​​for all conditions are summed to obtain a first risk assessment value. The medical equipment and medication status corresponding to the first risk assessment value are the current medical equipment and medication status of the target ambulance.

[0059] Based on the current medical equipment and drug status of the target ambulance, and the idle medical equipment and drug status in the preset ambulance, a second risk assessment value is calculated. For each missing medical device and drug corresponding to the condition determined in the calculation of the first risk assessment value, the medical devices and drugs that are identical or replaceable with the missing medical devices and drugs in the idle medical devices and drugs in the preset ambulance are determined. Then, the identical or replaceable medical devices and drugs in the missing medical devices and drugs are deleted, and the identical or replaceable medical devices and drugs are added to the preset medical equipment status and preset drug status. Next, the preset risk aggravation coefficient of the missing medical devices and drugs for treating the condition is obtained. The risk weighted value corresponding to the condition is multiplied by the risk aggravation coefficient to obtain an adjusted risk value. Finally, the adjusted risk values ​​of all conditions are added to obtain a second risk assessment value. The medical device status and drug status corresponding to the second risk assessment value are the preset medical device status and preset drug status.

[0060] S204. When all risk assessment values ​​are greater than the preset threshold, the target duration and the missing medical supplies of the target ambulance are determined based on the first medical equipment status and the first drug status corresponding to the lowest risk assessment value.

[0061] The target duration is the minimum time that the primary medical equipment and primary drug conditions can maintain the patient's current vital signs. Medical supplies include medical equipment and drugs.

[0062] Specifically, when the minimum risk assessment values ​​are all greater than a preset threshold, the first medical device status and the first drug status corresponding to the minimum risk assessment value are obtained, and the first medical device and the first drug in the target medical device and the target drug are deleted to obtain the missing medical device and the missing drug of the target ambulance.

[0063] At the same time, based on the risk probabilities of missing medical devices, missing medications, and various medical conditions, the minimum duration that the first medical device condition and the first medication condition can maintain the patient's current vital signs is determined. First, a set of medical conditions corresponding to the missing medical devices and missing medications is obtained, and a set of target conditions whose risk probabilities exceed a preset threshold are screened out from the condition set. Then, for each target condition, the target medical device and target medication corresponding to the target condition are obtained. Second medical devices and second medications that are identical to or interchangeable with the target medical device and target medication are screened out from the current medical devices and current medications. Next, a preset condition library corresponding to the target condition is obtained. The range of durations for maintaining the vital signs corresponding to the second medical device and second medication in the condition library is searched. Finally, based on the obtained duration ranges for each target condition, the shortest duration is selected as the minimum duration (i.e., the target duration) that the first medical device condition and the first medication condition can maintain the patient's current vital signs.

[0064] S205: Search for a preset emergency medical warehouse with missing medical supplies that is closest to the target ambulance.

[0065] Specifically, the server first obtains the real-time location of the target ambulance. Next, it obtains detailed information about all pre-stored emergency medical warehouses, including the location of each warehouse and the inventory of stored medical supplies. Next, based on the missing medical supplies and the inventory of each emergency medical warehouse, it selects a set of second emergency medical warehouses whose inventory contains the missing medical supplies. Next, it calculates the distance between each warehouse in the second set and the target ambulance. This can be done using commonly used distance calculation algorithms in geographic information systems (GIS), such as the Haversine formula, which accurately calculates the spherical distance between two points on the Earth's surface based on their latitude and longitude coordinates. Using this formula, the server determines the actual distance between each candidate warehouse and the target ambulance. Finally, the calculated distances between each warehouse in the second set and the target ambulance are sorted from closest to farthest. After sorting, the closest pre-stored emergency medical warehouse is selected as the final result.

[0066] S206: Determine a location set based on the target duration, the location of the emergency medical warehouse, the driving path and driving speed of the target ambulance.

[0067] Among them, the time it takes for the missing medical supplies delivered by the emergency medical warehouse to arrive at each location in the location set is less than the target time.

[0068] Specifically, the target ambulance's final destination is first obtained. A communication connection is established with the target ambulance's onboard navigation system to obtain the target ambulance's final destination. Typically, the final destination is the location of the hospital.

[0069] Next, the target ambulance plans a route that minimizes travel time from its current location to its final destination. This module uses a built-in route planning module, combined with real-time traffic data, road conditions, and historical traffic information, to employ a route planning algorithm (such as the A* algorithm or the Dijkstra algorithm) to create a route that minimizes travel time from the target ambulance's current location to its final destination. This route consists of a series of consecutive geographic coordinate points.

[0070] Next, based on the location and driving route of the emergency medical warehouse, the predicted time it takes for the emergency medical warehouse to deliver the missing medical supplies to each location in the target path of the driving route is calculated. The target path is the set of locations that the target ambulance can reach within the target time. First, taking the current location of the target ambulance as the starting point, the driving distance that the target ambulance can travel within the target time is calculated based on the driving speed of the target ambulance. The distance information between each location point in the driving path and the current location of the target ambulance is obtained, and the location points with a distance less than or equal to the driving distance are filtered out, and these location points are combined into the target path. For each location point in the target path, the location of the emergency medical warehouse is used as the starting point, and the delivery time is calculated based on the preset material delivery method (such as ambulance delivery, drone transportation, etc.) and its corresponding speed information. If an ambulance is used for delivery, real-time traffic data and congestion along the delivery route are combined to estimate driving speeds at different road sections, thereby calculating the delivery time from the emergency medical warehouse to the desired location. If a drone is used for delivery, factors such as the drone's flight speed, endurance, and the presence of obstacles along the flight route are considered to calculate the flight time from the emergency medical warehouse to the desired location, thus determining the delivery time. This delivery time is then added to the preset supply preparation time to determine the estimated delivery time for the emergency medical warehouse to deliver the missing medical supplies to each location along the route.

[0071] Finally, all the calculated predicted durations are compared with the target durations, and the location points with predicted durations less than the target duration are screened out. The locations in the driving path corresponding to these location points are integrated into a location set, and the time it takes for the missing medical supplies delivered by the emergency medical warehouse to arrive at each location in the location set is less than the target duration.

[0072] S207: When the target location exists in the location set, the target location and the missing medical supplies are sent to the emergency medical warehouse.

[0073] Among them, when the target ambulance arrives at the target location, the missing medical supplies delivered by the emergency medical warehouse have already arrived at the target location.

[0074] Specifically, for each location in the set, the target ambulance's current location, speed, and route are calculated using a geographic information system (GIS) distance calculation formula to determine the required travel time. During this calculation, the server accesses real-time traffic data and dynamically adjusts the ambulance's speed along different road sections according to pre-set rules.

[0075] The ambulance travel time for each location is then compared against the previously calculated estimated time it would take for the emergency medical depot to deliver the missing medical supplies to that location. During this comparison, a set of target locations with predicted travel times less than or equal to the travel time is obtained, and the target location closest to the target ambulance is selected from this set.

[0076] Finally, a communication connection is established with the emergency medical warehouse, and the target location and missing medical supplies information are sent to the emergency medical warehouse through the built-in communication module. After receiving the information, the emergency medical warehouse dispatches the missing medical supplies to the target location.

[0077] In an embodiment of the present application, the medical equipment and medications required to maintain the patient's vital signs during ambulance transportation are determined based on the patient's medical history and injury status. A risk assessment is then conducted in conjunction with the availability of supplies in the ambulance to determine the probability of the patient being in a dangerous situation during transportation due to insufficient medical supplies. When the risk assessment values ​​are all below a preset threshold, meaning that the patient is highly likely to be unable to maintain vital signs due to insufficient medication during transportation, the nearest emergency medical warehouse is located and the appropriate location for handing over medical supplies is calculated to ensure that the missing medical supplies in the ambulance are replenished in the shortest possible time. This allows the patient to obtain medical supplies in a timely manner to maintain their vital signs, avoiding delays in treatment due to insufficient medical supplies. This improves the timeliness and effectiveness of medical treatment for patients during ambulance transportation, while also optimizing the allocation and utilization efficiency of hospital medical resources.

[0078] The following combination Figure 3 To further illustrate the method of the embodiment of the present application.

[0079] See also Figure 3 , which is another flow chart of the hospital intelligent operation and management method in the embodiment of this application.

[0080] S301. When the target ambulance of this hospital arrives at the accident scene, obtain the patient's medical history and injury conditions.

[0081] S302. Determine the target medical equipment and target drugs required to maintain the patient's current vital signs within the target ambulance travel time based on the historical medical history and injury situation.

[0082] S303. Based on the idle medical equipment and idle medicine status in all preset ambulances, the target medical equipment status and the target medicine status, calculate the risk assessment value of the patient when being transported by the target ambulance equipped with different medical equipment and medicines.

[0083] S304. When all risk assessment values ​​are greater than the preset threshold, the target duration and the missing medical supplies of the target ambulance are determined based on the first medical equipment status and the first drug status corresponding to the lowest risk assessment value.

[0084] S305: Search for a preset emergency medical warehouse with missing medical supplies that is closest to the target ambulance.

[0085] Steps S301-S305 and Figure 2 Steps S201 to S205 in the illustrated embodiment are similar, and the descriptions of steps S201 to S205 may be referred to, and will not be repeated here.

[0086] S306. Calculate the probability and type of surgery that the patient currently needs based on the historical medical history and injury conditions.

[0087] Specifically, the deep learning risk prediction model in step S303 outputs various possible conditions and their associated risk probabilities for the patient within the target ambulance travel time. The required surgery type is determined by combining the association rules between different conditions and surgical types in the pre-set medical knowledge base. For each surgical type, the corresponding risk probability is used as the initial surgical probability for that type of surgery.

[0088] The patient's current vital sign data is then compared and analyzed with the baseline vital sign standards required for each type of surgery. If certain vital signs do not meet the standards, the initial surgery probability corresponding to that type of surgery is reduced according to pre-set adjustment rules to obtain the final surgery probability.

[0089] S307: When the probability of surgery is greater than a preset probability threshold, obtain the number of surgeries that the hospital can accept and that correspond to the surgery type.

[0090] Specifically, when there is a surgery probability greater than a preset probability threshold among all surgery probabilities, the surgery type corresponding to the surgery probability greater than the preset probability threshold is obtained.

[0091] Next, the hospital determines the types of surgeries it can accept and the corresponding number of surgeries. First, a communication connection is established with the hospital's information management system, from which data such as the usage status of each operating room within the hospital, information on currently ongoing surgeries, and scheduled surgeries for the future are extracted. By analyzing this data, the hospital determines the available operating rooms at the current time and for the future, as well as the types of surgeries they correspond to. Based on the available operating rooms and the types of surgeries they correspond to, the hospital calculates the initial types of surgeries it can accept and the initial number of surgeries it can accept. Then, for each initial type of surgery, the hospital obtains information on the number of available surgeons, anesthesiologists, and auxiliary medical staff for each type of surgery, based on the preset tables of available surgeons, anesthesiologists, and auxiliary medical staff. Based on the preset standard numbers of surgeons, anesthesiologists, and auxiliary medical staff for each type of surgery, the hospital determines the second number of surgeries of that type that the currently available surgeons can perform. Finally, the smaller of the initial and second numbers of surgeries is selected as the number of surgeries of that type that the hospital can accept.

[0092] Finally, based on the obtained surgical types that the hospital can accept and their corresponding surgical quantities, find the surgical quantity corresponding to the type of surgery that the patient needs to undergo.

[0093] S308. If the number of surgeries is zero, search for a target hospital in the preset hospital set that can accept the type of surgery.

[0094] Specifically, if the number of surgeries is zero, the real-time location of the target ambulance is obtained. With the real-time location of the target ambulance as the center, according to a pre-set distance range (such as a radius of 30 kilometers, which can be dynamically adjusted according to actual traffic conditions, ambulance speed, patient severity, and other factors), all hospitals within this range are screened out from the hospital database to form the first hospital set.

[0095] Next, for each hospital in the first hospital set, the system retrieves its medical service information database, which contains information about the hospital's departmental settings, available surgical procedures, and specialized medical equipment. The system then compares the patient's desired surgical procedure with the available surgical procedures at each hospital, selecting hospitals capable of performing that type of procedure and creating a predefined hospital set.

[0096] The server then establishes a communication connection with each hospital in the preset hospital set through a pre-set communication interface. A data packet containing the patient's surgery type, medical history, and injury details is sent to each hospital. Once this data is sent, a timer wait mechanism is activated to receive feedback from each hospital within a preset time period. If a hospital reports that it is able to accept the patient and perform the surgery, that hospital is designated as the target hospital. If all hospitals report that they are unable to accept the patient, the patient is treated at the designated hospital along the original route.

[0097] S309: The location of the target hospital is used as the final location of the target ambulance.

[0098] The control command is sent to the navigation system of the target ambulance. After receiving the command, the navigation system displays the driving route with the destination location as the target hospital.

[0099] S310: Plan a driving route with the shortest driving time for the target ambulance from the current position to the destination position.

[0100] S311. Based on the location and driving route of the emergency medical warehouse, calculate the predicted time for the emergency medical warehouse to deliver the missing medical supplies to each location in the target path of the driving route.

[0101] The target path is the set of locations that the target ambulance can reach within the target duration.

[0102] S312: When there is a target predicted duration that is shorter than the target duration among all predicted durations, obtain a set of positions in the driving path corresponding to the target predicted duration.

[0103] S313. When the target location exists in the location set, the target location and the missing medical supplies are sent to the emergency medical warehouse.

[0104] Steps S310-S313 and Figure 2 Steps S206 and S207 in the illustrated embodiment are similar, and reference may be made to the description of steps S206 and S207 , which will not be repeated here.

[0105] S314. When the target location does not exist in the location set, calculate the first energy consumption set and the second energy consumption set based on the current location, driving speed, and historical energy consumption records of the target ambulance.

[0106] Among them, the first energy consumption set is the set of energy consumption consumed by the target ambulance when receiving missing medical supplies at each location in the location set, and the second energy consumption set is the set of energy consumption consumed by the target ambulance from each location in the location set to the terminal location.

[0107] Specifically, the energy consumption of the target ambulance during its current driving process is first obtained. The energy storage status of the storage devices (such as built-in batteries) of each running medical device (such as a multi-parameter monitor, etc.) that relies on its own storage device function is obtained, including information such as the remaining power percentage and the remaining power value. Combined with the real-time power consumption data of each medical device, the formula "continuous working time = remaining power / real-time power" is used to calculate the continuous working time of each medical device when it relies solely on the storage device for power. At the same time, the historical energy consumption records of the target ambulance under different driving conditions (such as different road conditions, different speeds, different loads, etc.) and different medical equipment usage combinations are retrieved from the historical energy consumption database.

[0108] Next, the first energy consumption set is calculated. Data mining and machine learning algorithms are first used to match data such as the current ambulance's speed, road conditions (e.g., urban roads, highways, rural roads), and the usage status of onboard medical equipment (which equipment is currently operating and how it obtains energy) with historical energy consumption records. This process selects the historical energy consumption data sample that most closely resembles the current scenario. Based on this matched historical data and the distance information from the target ambulance's current location to each location in the location set, a preset energy consumption calculation model (this mathematical formula accounts for factors such as vehicle mechanical efficiency, wind resistance, and tire friction) is used to calculate the initial energy consumption of each location in the target ambulance's arrival location set. If the target ambulance's travel time at a location in the location set exceeds the available operating time of the medical equipment, the energy consumption required per unit time for the medical equipment to switch to the ambulance's energy supply is calculated. The initial energy consumption is added to the product of the difference between the available operating time and the travel time and the energy consumption required per unit time.

[0109] Based on the previously calculated driving time of the target ambulance to each location in the location set and the predicted time for the emergency medical warehouse to deliver the missing medical supplies to the corresponding location, the waiting time of the ambulance waiting for the medicine to arrive at each location is calculated. According to the continuous working time of the medical equipment, it is determined whether each medical equipment has a predicted time period in which it needs to switch to the ambulance to provide energy. If so, the difference between the predicted time and the continuous working time corresponding to the medical equipment is calculated, and the difference is multiplied by the energy consumption of the ambulance required for the medical equipment to switch to the ambulance to provide energy per unit time, and the waiting energy consumption is added to the product of the preset basic energy consumption and the waiting time to obtain the waiting energy consumption.

[0110] The initial energy consumption corresponding to each position is added to the corresponding waiting energy consumption to obtain the set of energy consumption consumed by the target ambulance when receiving the missing medical supplies at each position in the position set.

[0111] Next, the second energy consumption set is calculated. First, the preset energy acquisition targets for each medical device in the missing medical supplies are obtained. For missing devices whose energy acquisition targets are ambulances, the energy consumption required by the ambulance per unit time for each device is obtained. Next, the first path from each location in the location set to the destination is obtained. Based on the target ambulance's current location, travel speed, and the first path, the first travel time required for the target ambulance to reach the destination from each location in the location set is calculated using the distance calculation formula of the geographic information system. When calculating the energy consumption (i.e., the second energy consumption) consumed by the target ambulance from each location in the location set to the destination, an energy consumption calculation model is first used to calculate the base travel energy consumption based on factors such as the ambulance's first path, road conditions, and speed. The energy consumption of the missing device during this travel period is then added to the base travel energy consumption to obtain the second energy consumption corresponding to each location, forming the second energy consumption set. The energy consumption of the missing device is equal to the first travel time multiplied by the energy consumption required by the ambulance per unit time for that device.

[0112] S315: Calculate a remaining energy consumption set based on the current energy consumption of the target ambulance and the first energy consumption set.

[0113] Establish a communication connection with the onboard system of the target ambulance, obtain the current energy consumption of the target ambulance, subtract each first energy consumption of the first energy consumption set from the current energy consumption, and calculate the remaining energy consumption set.

[0114] S316. When there is no remaining energy consumption greater than the second energy consumption corresponding to the remaining energy consumption, calculate the receiving time point of the target ambulance receiving the missing medical supplies at each location in the location set.

[0115] Specifically, the remaining energy consumption corresponding to each location in the location set is compared with the corresponding second energy consumption. If the remaining energy consumption at each location is less than the second energy consumption, it is determined that there is no remaining energy consumption greater than the second energy consumption corresponding to the remaining energy consumption. At this time, the predicted duration for each location is added to the current time point to obtain the time point at which the target ambulance received the missing medical supplies at each location in the location set.

[0116] S317. Send the location corresponding to the earliest receiving time point and the missing medical supplies to the emergency medical warehouse.

[0117] Establish a communication connection with the emergency medical warehouse and send the location corresponding to the earliest receipt time and missing medical supplies information to the emergency medical warehouse through the built-in communication module. After receiving the information, the emergency medical warehouse dispatches the missing medical supplies to the location corresponding to the earliest receipt time.

[0118] In some embodiments, if the remaining energy consumption corresponding to the location at the earliest receiving time is negative, a second location set is selected in which the remaining energy consumption corresponding to each location in the location set is not negative. The second location corresponding to the earliest receiving time among all receiving time points corresponding to the second location set is selected. This second location and the missing medical supplies are sent to the emergency medical warehouse.

[0119] S318. Determine the first duration based on the target medical device and target drug conditions.

[0120] Among them, the first duration is the shortest duration that the target medical equipment conditions and target drug conditions can maintain the patient's current vital signs.

[0121] Specifically, a set of conditions that may occur during the travel of a target ambulance and have a risk probability higher than a preset threshold is obtained. Then, for each condition in the condition set, the corresponding target medical device and target drug are obtained. Next, a preset condition library corresponding to each condition is obtained. The range of durations for maintaining vital signs corresponding to the target medical device and target drug in the condition library is searched. Finally, based on the obtained duration ranges for each condition, the shortest duration is selected as the minimum duration (i.e., the first duration) that the target medical device and target drug can maintain the patient's current vital signs.

[0122] S319. Plan a charging route with the shortest driving time for the target ambulance to pass through the charging station and reach the destination.

[0123] Specifically, the target ambulance's current location, destination location, and the location of all charging stations within a preset distance from the target ambulance are first obtained. The preset distance is calculated based on the target ambulance's remaining energy consumption when receiving the missing medical supplies at the location corresponding to the earliest receiving time, and the preset maximum energy consumption per unit distance traveled by the target ambulance.

[0124] Next, the built-in path planning algorithm (such as the improved A* algorithm or Dijkstra algorithm) is called to perform path planning with the target ambulance starting from the current location, passing through at least one charging station and reaching the destination with the shortest total driving time as the optimization goal. During the planning process, the driving path is divided into three stages: from the current location to the charging station, charging at the charging station, and from the charging station to the destination, and the time is calculated for each stage. For the calculation of the driving time from the current location to the charging station, the path distance calculation function of the geographic information system (GIS) is used in combination with the road speed limit information and the driving speed of the target ambulance to calculate the first driving time of each feasible route. When calculating the driving time from the charging station to the destination, the above method is also used to calculate the second driving time from the charging station to the destination. For the charging time at the charging station, if the preset energy acquisition method of the target ambulance includes refueling at a gas station, the preset first charging time is obtained as the charging time; if the preset energy acquisition method of the target ambulance only includes charging at a charging pile, the preset second charging time is obtained as the charging time, and the second charging time is greater than the first time.

[0125] Then, all possible path combinations passing through the charging station are traversed and calculated, and the durations calculated in the three stages of each path combination are added together to obtain the total driving duration of the path combination.

[0126] Finally, the total driving time of all path combinations is compared, and the path with the shortest total driving time is screened out, which is determined as the charging path with the shortest driving time for the target ambulance to pass through the charging station and reach the terminal location.

[0127] S320: Obtain the charging driving time of the charging route.

[0128] The shortest total driving time calculated in step S318 is obtained as the charging driving time of the charging path.

[0129] S321: When the charging driving time is less than the first time, update the driving path of the target ambulance.

[0130] When the charging driving time is less than the first time, a communication connection is established with the onboard navigation system of the target ambulance, and the charging route is sent to the onboard navigation system or a description of the charging route is played to the driver through the onboard speaker.

[0131] S322: When the charging driving time is greater than the first time, obtain a set of ambulances within a preset range of the target ambulance that can replace patients or are idle.

[0132] Specifically, the system first obtains a set of ambulances within the preset range of the target ambulance. Then, the pre-recorded personnel information and patient injury status of each ambulance in the set are obtained. If the ambulance's personnel information does not include a patient or the patient's basic vital signs data is within the preset vital signs data range, the ambulance is determined to be a patient-replaceable or idle ambulance. The number of patient-replaceable or idle ambulances is counted to obtain a set of patient-replaceable or idle ambulances.

[0133] S323. Calculate the arrival time of each ambulance in the ambulance set at the destination location.

[0134] Specifically, a second route is first planned for each ambulance in the set, minimizing the travel time from its current location to the location corresponding to the earliest arrival time. The built-in route planning module then utilizes a route planning algorithm (such as A* or Dijkstra) based on real-time traffic data, road conditions, and historical traffic information to plan a second route with the shortest travel distance from the target ambulance's current location to its destination.

[0135] Then, the second travel time for each ambulance in the ambulance set to reach the location corresponding to the earliest reception time point is calculated. The second travel time is calculated based on the current location, travel speed, and second travel path of the target ambulance using the distance calculation formula of the geographic information system.

[0136] For each ambulance in the ambulance set, if the second travel time is less than the travel time of the target ambulance to the location corresponding to the earliest reception time, a determination is made as to whether the sum of the travel time and the preset patient transfer time is less than the predicted time for the location corresponding to the earliest reception time. If so, the predicted time is added to the second travel time corresponding to the location corresponding to the earliest reception time, calculated in S313, to obtain the target total travel time. If not, the sum of the travel time and the preset patient transfer time is added to the second travel time to obtain the target total travel time.

[0137] Based on the maximum energy consumption of the ambulance within the preset unit time and the target total driving time of each ambulance, the target energy consumption of each ambulance is calculated. The current energy consumption of each ambulance is obtained. If the current energy consumption of the ambulance is less than the corresponding target energy consumption, the first energy consumption consumed by the ambulance when receiving the missing medical supplies and the patient on the target ambulance at the location corresponding to the earliest receiving time point and the second energy consumption consumed from the location corresponding to the earliest receiving time point to the terminal location are calculated first, and then the difference between the current energy consumption of the ambulance and the first energy consumption is calculated to obtain the remaining energy consumption. If the remaining energy consumption is less than the second energy consumption, the charging path is planned and the charging driving time is obtained. The implementation steps of the above specific method can refer to the above steps S314-S316 and S319-S320. After obtaining the charging driving time, the target total driving time is updated. Determine whether the sum of the driving time and the preset patient transfer time is less than the predicted time of the location corresponding to the earliest receiving time point. If so, the predicted time is added to the charging driving time to obtain the target total driving time; if not, the sum of the driving time and the preset patient transfer time is added to the charging driving time to obtain the target total driving time.

[0138] Finally, the current time point is added to the target total driving time of each ambulance to obtain the arrival time point of each ambulance in the ambulance set at the destination location.

[0139] S324. When the second duration between the arrival time point and the current time point is less than the first duration, the ambulance corresponding to the earliest arrival time point is used as a replacement ambulance for the target ambulance.

[0140] The replacement ambulance is an ambulance that transports the patient from the target location to the terminal location.

[0141] Specifically, the second duration between each arrival time point and the current time point is calculated. If the second duration is less than the first duration, the ambulance corresponding to the earliest arrival time point is selected as the replacement ambulance for the target ambulance, and a dispatch message is sent to the replacement ambulance. After receiving the dispatch message, the replacement ambulance travels to the location corresponding to the earliest arrival time point, picks up the patient from the target ambulance, and completes the subsequent transportation.

[0142] S325. When the target ambulance is transporting the patient, obtain in real time the first medicine taken by the target doctor on the target ambulance.

[0143] Specifically, a real-time communication connection is first established with the smart medicine box on the target ambulance to ensure that various data information fed back by the smart medicine box can be obtained.

[0144] When the target doctor in the target ambulance takes the first medication from the smart medicine box, the RFID recognition module in the smart medicine box automatically scans the electronic tag on the packaging of the removed medication. After the scan is completed, the obtained detailed information such as the name, strength, production date, and expiration date of the first medication is transmitted to the server.

[0145] S326: Determine whether there is a second drug in the target ambulance that has a better therapeutic effect than the first drug.

[0146] Based on the patient's current vital sign data, historical medical history, and the remaining medications in the target ambulance, a determination is made as to whether a second medication with a better therapeutic effect than the first medication is available in the target ambulance. If so, step S327 is executed; if not, step S325 is executed.

[0147] Specifically, the patient's basic vital signs data such as heart rate, blood pressure, respiratory rate, body temperature, etc. are first obtained, key indicators such as heart rate, blood pressure, blood oxygen saturation, body temperature, etc. are extracted, and compared with the preset normal physiological indicator range to screen out abnormal indicator data of vital signs.

[0148] Next, the system obtains the remaining medications in the target ambulance and, through real-time communication with the smart medicine box, retrieves the medication list. For each medication on the list, it retrieves data on abnormal indicators, contraindications, and other data applicable to the medication from a pre-set medical knowledge base.

[0149] For the first drug, the abnormal indicator data applicable to the first drug is matched with the patient's current abnormal indicator data to determine whether the drug can treat the patient's current condition. At the same time, the patient's historical medical records are checked to see if there are any contraindications or allergies related to the first drug. If the first drug does not completely match the patient's condition, or there are contraindications for use, continue to determine whether there is a more suitable second drug. The abnormal indicator data applicable to each drug in the drug list is matched with the patient's current abnormal indicator data. If there is a drug with a matching degree exceeding the preset threshold and the patient does not have any contraindications for use, it is determined that there is a second drug that is more suitable for the patient's current physical condition than the first drug.

[0150] S327. Play the prompt information through the preset speaker on the target ambulance.

[0151] If there is a second drug that is more suitable for the patient's current physical condition than the first drug, a control command is sent to a preset speaker on the target ambulance. After receiving the command, the speaker plays a prompt message to prompt the target doctor to confirm whether the wrong drug has been taken.

[0152] In the embodiments of the present application, the patient's surgical needs are determined based on their medical history and injury status. The final destination of the ambulance is dynamically adjusted based on the hospital's surgical capacity and the patient's surgical needs. This prevents delays in treatment due to saturation of hospital surgical resources and improves the efficiency of matching emergency resources with patient needs. Furthermore, if the remaining energy consumption of the ambulance after receiving supplies is insufficient to power the vehicle to the final destination, and the ambulance's charging time exceeds the minimum duration for which the patient's vital signs can be maintained, the system selects ambulances within a preset range that can transfer patients or are idle, calculates the time it takes for each vehicle to arrive at the destination, and prioritizes the ambulance that can complete the transfer in the shortest time as a replacement vehicle to complete the remaining patient's journey. This avoids the risk of the patient missing the optimal treatment time due to insufficient ambulance energy and excessive charging time. This ensures that the patient can be delivered to the hospital for treatment in a timely manner within the effective time for maintaining vital signs, and achieves dynamic allocation and efficient utilization of ambulance resources in the region, thereby improving the success rate and reliability of medical rescue.

[0153] The above describes the hospital intelligent operation and management method in the embodiment of the present application. Below, in combination with the above-mentioned hospital intelligent operation and management method, the hospital management server in the embodiment of the present application is described in detail.

[0154] See also Figure 4 , is a schematic diagram of an exemplary hardware structure of a hospital management server in an embodiment of the present application.

[0155] In some embodiments, the hospital management server 400 includes a computer device, which can be a terminal device. The computer device includes a processor 401, memory 402, a communication module 403, an input device 404, and an output device 405, all connected via a system bus. The processor 401 of the computer device provides computing and control capabilities. The memory 402 of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage medium. The database is used to store data. The communication module 403 of the computer device is used to transmit patient vital sign data, ambulance image data, and the status of medications in the smart medicine box to the server, as well as to send medical supply information to the emergency medical warehouse. The input device 404 of the computer device is used to receive patient vital sign data, image data, and medication status. The output device 405 of the computer device is used to display ambulance dispatch information, etc. When executed by the processor 401, the computer program implements the hospital intelligent operation and management method in the embodiments of the present application.

[0156] Those skilled in the art will understand that Figure 4The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0157] In some embodiments of the present application, a computer-readable storage medium is provided, including instructions. When the instructions are executed on the hospital management server 400, the hospital management server 400 can execute the hospital intelligent operation management method in the embodiments of the present application.

[0158] In some embodiments of the present application, a computer program product is also provided. When the computer program product runs on the hospital management server 400, the hospital management server 400 executes the hospital intelligent operation management method in the embodiments of the present application.

[0159] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0160] As used in the above embodiments, the term “when” may be interpreted to mean “if” or “after” or “in response to determining that” or “in response to detecting that”, depending on the context. Similarly, the phrases “upon determining that” or “if (stated condition or event) is detected” may be interpreted to mean “if determining that” or “in response to determining that” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0161] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be magnetic media (e.g., floppy disk, hard disk, tape), optical media (e.g., DVD), or semiconductor media (e.g., solid-state drive).

[0162] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A hospital intelligent operation management method, characterized in that: include: When the hospital's target ambulance arrives at the accident scene, obtain the patient's medical history and injuries; Determine, based on the historical medical history and the injury condition, the target medical equipment and target medications required to maintain the patient's current vital signs within the target ambulance travel time; Calculating a risk assessment value of the patient under transportation by the target ambulance equipped with different medical equipment and drugs based on the idle medical equipment and idle drugs in all preset ambulances, the target medical equipment, and the target drugs; When the risk assessment values ​​are all greater than a preset threshold, a target duration and the missing medical supplies of the target ambulance are determined based on the first medical equipment status and the first drug status corresponding to the lowest risk assessment value. The target duration is the shortest duration that the first medical equipment status and the first drug status can maintain the patient's current vital signs. Searching for a preset emergency medical warehouse closest to the target ambulance that has the missing medical supplies; Determine a set of locations based on the target duration, the location of the emergency medical warehouse, the travel path and travel speed of the target ambulance, and the time it takes for the missing medical supplies delivered by the emergency medical warehouse to arrive at each location in the set of locations is less than the target duration; When a target location exists in the location set, the target location and the missing medical supplies are sent to the emergency medical warehouse. When the target ambulance arrives at the target location, the missing medical supplies dispatched by the emergency medical warehouse have arrived at the target location.

2. The method according to claim 1, characterized in that The determining of the location set based on the target duration, the location of the emergency medical cabin, and the driving path and speed of the target ambulance specifically includes: Obtaining the final location of the target ambulance; Planning a travel route with the shortest travel time for the target ambulance from the current location to the destination location; Based on the location of the emergency medical warehouse and the driving route, calculating a predicted time for the emergency medical warehouse to deliver the missing medical supplies to each location along a target path along the driving route, where the target path is a set of locations that the target ambulance can reach within the target time; When there is a target predicted duration that is shorter than the target duration among all predicted durations, a position set in the driving path corresponding to the target predicted duration is obtained.

3. The method according to claim 2, characterized in that The obtaining of the terminal position of the target ambulance specifically includes: Calculating the probability and type of surgery that the patient currently needs to undergo based on the historical medical history and the injury condition; When the probability of the operation is greater than a preset probability threshold, obtaining the number of operations corresponding to the operation type that the hospital can accept; If the number of surgeries is zero, search for a target hospital in the preset hospital set that can accept the type of surgery; The location of the target hospital is used as the final location of the target ambulance.

4. The method according to claim 1, wherein After the step of determining a location set based on the target duration, the location of the emergency medical cabin, and the driving path and speed of the target ambulance, the method further includes: When the target location does not exist in the location set, a first energy consumption set and a second energy consumption set are calculated based on the current location, driving speed, and historical energy consumption records of the target ambulance, wherein the first energy consumption set is a set of energy consumption consumed by the target ambulance when receiving the missing medical supplies at each location in the location set, and the second energy consumption set is a set of energy consumption consumed by the target ambulance from each location in the location set to the final location; Calculating a remaining energy consumption set based on the current energy consumption of the target ambulance and the first energy consumption set; When there is no remaining energy consumption greater than a second energy consumption corresponding to the remaining energy consumption, calculating a receiving time point at which the target ambulance receives the missing medical supplies at each location in the location set; The location corresponding to the earliest receiving time point and the missing medical supplies are sent to the emergency medical warehouse.

5. The method according to claim 4, characterized in that After the step of sending the location corresponding to the earliest receiving time point and the missing medical supplies to the emergency medical warehouse, the method further includes: Determining a first duration based on the target medical device status and the target drug status, where the first duration is the shortest duration during which the target medical device status and the target drug status can maintain the patient's current vital signs; Planning a charging route with the shortest driving time for the target ambulance to pass through the charging station to the destination; Obtaining a charging driving time for the charging route; When the charging driving time is less than the first time, the driving path of the target ambulance is updated.

6. The method according to claim 5, characterized in that After the step of obtaining the charging driving time of the charging path, the method further includes: When the charging driving time is greater than the first time, obtaining a set of ambulances within a preset range of the target ambulance that can replace patients or are idle; Calculating the arrival time of each ambulance in the ambulance set at the destination location; When there is a second time length between the arrival time point and the current time point that is less than the first time length, the ambulance corresponding to the earliest arrival time point will be used as a replacement ambulance for the target ambulance, and the replacement ambulance is the ambulance that transports the patient from the target location to the terminal location.

7. The method according to claim 1, characterized in that After the step of sending the target location and the missing medical supplies to the emergency medical warehouse when the target location exists in the location set, the method further includes: When the target ambulance transports the patient, obtaining in real time a first medicine taken by a target doctor on the target ambulance; Determining whether there is a second drug in the target ambulance that has a better therapeutic effect than the first drug based on the patient's current vital sign data, the historical medical history, and the remaining drugs in the target ambulance; If so, a prompt message is played through a preset speaker on the target ambulance, and the prompt message is used to prompt the target doctor to determine whether the wrong medicine is taken.

8. A hospital management server, characterized in that: include: one or more processors and memory; The memory is coupled to the one or more processors, and is used to store computer program codes, where the computer program codes include computer instructions. The one or more processors call the computer instructions to enable the hospital management server to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium storing computer instructions, characterized in that: When the computer instructions are executed on the hospital management server, the hospital management server is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a hospital management server, the hospital management server is enabled to execute the method according to any one of claims 1 to 7.

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