A medical intelligent triage method and triage system

Abstract

The present invention relates to a medical intelligent triage method and triage system, the system at least comprising an access terminal, a hospital data terminal and a remote server. The access terminal can guide a patient to log in and / or register to the medical intelligent triage system. The hospital data terminal can store and collect hospital data including the medical resources, geographical location, and building structure of the hospital. The remote server is configured with a medical recommendation unit that recommends a corresponding target hospital and / or target doctor to the patient when the patient uploads his or her condition to the remote server through the access terminal. The patient selects the recommended target hospital and / or target doctor through the access terminal. In response to the patient's selection of the target hospital and / or target doctor, the remote server generates a patient's medical route, and retrieves the structural data of the target doctor and his or her hospital to model a local model corresponding to the patient's indoor medical route.

Description

Technical Field

[0001] The present invention relates to the field of intelligent medical technology, and in particular to an intelligent medical triage method and a triage system. Background Art

[0002] Medical and health care is one of the public services to protect people's livelihood. Due to the imbalance of economic development and geographical barriers, there is still a big difference in the level of public medical services between urban and rural areas in my country. In addition, there may be multiple hospitals in the same area at the same time, and the scale, departments, diagnosis and treatment characteristics and doctor qualifications of each hospital are different. Although some hospitals have realized online appointments, self-service appointments and other functions so that patients can understand the relevant information of the hospital, most patients are not clear about the department corresponding to their own symptoms and often make the wrong appointment. The existing triage system can only provide patients with relevant information about the hospital they belong to based on their diseases, but cannot provide relevant information about other hospitals. In addition, when providing patients with medical routes, only the route from the patient's starting point to the hospital is provided, and it is impossible to evaluate whether the medical plan is reasonable and convenient, and it is impossible to accurately and effectively evaluate and estimate the convenience of transportation for residents to seek medical treatment, and it is impossible to provide effective guidance and prompts for residents' medical routes.

[0003] Therefore, in view of the deficiencies in the prior art, the present invention provides a medical intelligent triage method and system to solve the above-mentioned problems.

[0004] In addition, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making the present invention, but due to space limitations, not all details and contents are listed in detail. However, this does not mean that the present invention does not have the characteristics of these prior arts. On the contrary, the present invention already has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art to the background technology. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a medical intelligent triage system. The medical intelligent triage system at least includes an access terminal, a hospital data terminal and a remote server. The access terminal can guide patients to log in and / or register to the medical intelligent triage system. The hospital data terminal is configured in the relevant hospital and can store and collect hospital data including medical resources, geographical location, and building structure of the hospital. The remote server can data connect several of the access terminals and several of the hospital data terminals. The remote server is configured with a medical recommendation unit that recommends the corresponding target hospital and / or target doctor to the patient when the patient uploads his or her condition to the remote server through the access terminal. The patient selects the recommended target hospital and / or target doctor through the access terminal. In response to the patient's selection of the target hospital and / or target doctor, the remote server generates the patient's medical route, and retrieves the structural data of the target doctor and his or her hospital to model a local model corresponding to the patient's indoor medical route.

[0006] Preferably, the remote server transmits the local model in the form of a video stream to an access terminal used by the patient, thereby providing navigation for the patient's medical consultation.

[0007] Preferably, the medical intelligent triage system starts from the perspective of global resource allocation, and provides the patient with a list of doctors who are capable of diagnosing the disease, and whose hospitals are well ranked and within a moderate distance, based on the patient's symptoms and location. In order to ensure that patients can easily obtain a list of doctors who are capable of diagnosing their diseases through the medical intelligent triage system, the list fully considers the patient's other objective indicators, including the driving distance between the patient and the hospital, the official ranking of the hospital, and the comprehensive capabilities of the hospital. The medical intelligent triage system can divert patients to different hospitals, solving the problem of patients' difficulty in choosing doctors and the uneven allocation of hospital resources. The medical intelligent triage system can adapt doctors who can diagnose and treat the patient's disease according to the patient's condition, thereby avoiding looking for experts for small problems at least within a certain geographical range, causing a run on expert medical resources. For example, when a patient selects a target hospital and / or a target doctor, the remote server determines a visit ranking suggestion related to the patient's condition uploaded by the patient based on the driving distance between the patient's location and the target hospital determined by the access terminal and the predicted waiting time related to the target doctor's visit time given by the hospital data terminal, so that the patient can use the access terminal to select one of the visit routes, wherein the visit ranking suggestion is a selectable list of several visit routes set by the remote server based on the patient's condition uploaded by the patient at least according to the ability weight of the corresponding doctor in the doctor list, so that the patient can use the access terminal to select the corresponding visit route from the selectable list. In response to the selection of the corresponding visit route, the remote server retrieves the structural data of the target doctor and the hospital where he is located to model a local model corresponding to the patient's indoor visit route, and provides at least one suboptimal visit route in combination with the patient's condition uploaded by the patient, wherein the suboptimal visit route is determined and provided by the remote server in consideration of the impact of the patient's condition on the patient's mobility, the distance between the patient and the target hospital, and the predicted waiting time related to the target doctor's visit time.

[0008] According to a preferred embodiment, the medical recommendation unit is configured with a preparation module. The preparation module is configured to: obtain the patient's disease data from the access terminal, and obtain data including doctors who can diagnose the disease, the patient's evaluation of the doctor's ability to diagnose the disease, the hospital's official ranking, and the driving distance between the hospital and the patient from the hospital data terminal.

[0009] According to a preferred embodiment, the medical recommendation unit also includes: a screening module and a first list module. The screening module is configured to: summarize the doctors who can diagnose the patient's disease, obtain the distance between the hospital to which each doctor belongs and the patient's current location, and determine whether the distance is greater than a preset distance. If the distance is greater than the preset distance, the doctor corresponding to the distance is deleted from the summarized doctors. The first list module is configured to: sort the doctors summarized by the screening module from high to low scores based on the patient's evaluation of the doctor's ability to diagnose the disease, and obtain a doctor list.

[0010] According to a preferred embodiment, the medical recommendation unit also includes: a first weight module and a recommendation module. The first weight module is configured to: determine the ability weight of each doctor based on the evaluation of each doctor, determine the first hospital weight of each doctor based on the ranking of the hospital to which each doctor belongs, and determine the driving weight of each doctor based on the distance between the hospital to which each doctor belongs and the patient's current location. The recommendation module is configured to: establish a medical guidance recommendation model based on the ability weight, first hospital weight and driving weight of each doctor in the doctor list, use the medical guidance recommendation model to determine the recommendation index of each doctor, and select the doctor corresponding to the largest recommendation index as the recommended doctor.

[0011] According to a preferred embodiment, the medical recommendation unit further includes: a second list module and a second weight module. The second list module is configured to: sort each doctor in order from high to low in recommendation index to obtain a second doctor list. The second weight module is configured to: for each doctor in the second doctor list, obtain the number of times the hospital to which the current doctor belongs appears in the corresponding hospital set, and calculate the quotient of the number and the total number of hospitals in the hospital set to obtain the second hospital weight. Preferably, the hospital set is a set of hospitals to which doctors whose recommendation index is equal to or less than the current doctor belong.

[0012] According to a preferred embodiment, the recommendation module establishes a target intelligent diagnosis guidance model based on the ability weight, the first hospital weight, the second hospital weight, and the driving distance weight of each doctor in the second doctor list. The recommendation module uses the target intelligent diagnosis guidance model to determine the target recommendation index of each doctor, and selects the doctor corresponding to the largest target recommendation index to obtain the target recommended doctor. The recommendation module sorts the corresponding doctors in descending order according to the target recommendation index to obtain a recommended list of doctors for receiving consultations.

[0013] According to a preferred embodiment, the remote server includes at least a data processing unit, a communication unit, a medical recommendation unit and a modeling unit. The communication unit, the medical recommendation unit and the modeling unit are respectively connected to the data processing unit. The data processing unit uses the communication unit to establish a data transmission channel with the access terminal and the hospital data terminal to obtain data including the patient's disease type, hospital medical resources and hospital building structure. The data processing unit transmits the acquired patient disease type and hospital medical resources to the medical recommendation unit to obtain a recommended doctor. In response to obtaining the recommended doctor, the data processing unit transmits the recommended doctor and the structure of the hospital where he is located to the modeling unit to model a local model corresponding to the patient's indoor medical treatment route.

[0014] According to a preferred embodiment, in response to the patient's selection of a doctor, the remote server generates a navigation route from the patient's current location to the entrance of the hospital where the selected doctor is located and a treatment route after the patient enters the hospital. The remote server generates a corresponding model from the hospital entrance to the department where the selected doctor is located based on the treatment route. The remote server sends the generated navigation route and model to the access terminal used by the patient.

[0015] The present invention also provides a medical intelligent triage method. The medical intelligent triage method at least comprises:

[0016] Guiding the patient to log in and / or register to the medical intelligent triage system using an access terminal;

[0017] Hospital data terminals are deployed in relevant hospitals to store and collect hospital data including the medical resources, geographical location, and building structure of the hospital;

[0018] The remote server can be data-connected to a plurality of the access terminals and a plurality of the hospital data terminals;

[0019] When a patient uploads his or her medical condition to the remote server through an access terminal, the medical recommendation unit configured in the remote server recommends a target hospital and / or target doctor corresponding to the disease to the patient;

[0020] The patient selects the recommended target hospital and / or target doctor through the access terminal;

[0021] In response to the patient's selection of a target hospital and / or a target doctor, the remote server generates a patient's medical route and retrieves the structural data of the target doctor and his hospital to build a local model corresponding to the patient's medical route.

[0022] According to a preferred embodiment, the medical intelligent triage method further includes:

[0023] Select a corresponding doctor list according to the patient's disease, the doctor list includes several doctors and the hospital each doctor belongs to;

[0024] Obtain the evaluation of each doctor in the doctor list, and determine the ability weight of each doctor based on the evaluation of each doctor;

[0025] Get the ranking of the hospital to which each doctor belongs in the doctor list, and determine the first hospital weight of each doctor based on the ranking of the hospital to which each doctor belongs;

[0026] Get the distance between the hospital where each doctor in the doctor list belongs and the patient's current location, and determine the driving weight of each doctor based on the distance;

[0027] A consultation recommendation model is established based on the ability weight, first hospital weight and driving distance weight of each doctor in the doctor list, and the recommendation index of each doctor is determined using the consultation recommendation model, and the doctor with the largest recommendation index is selected as the recommended doctor. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of a first method of a preferred embodiment provided by the present invention;

[0029] Figure 2 is a schematic diagram of a second method of a preferred embodiment provided by the present invention;

[0030] Figure 3 It is a simplified schematic diagram of a medical intelligent triage system according to a preferred embodiment of the present invention;

[0031] Figure 4 is a simplified schematic diagram of a remote server according to a preferred embodiment of the present invention;

[0032] Figure 5 It is a simplified schematic diagram of a medical recommendation unit of a preferred embodiment provided by the present invention.

[0033] Reference numerals list

[0034] 100: medical intelligent triage system; 110: access terminal; 120: hospital data terminal; 130: remote server; 131: data processing unit; 132: communication unit; 133: medical recommendation unit; 134: modeling unit; 141: preparation module; 142: screening module; 143: first list module; 144: first weight module; 145: recommendation module; 146: second list module; 147: second weight module. DETAILED DESCRIPTION

[0035] The following is combined with Figures 1 to 5 Provide detailed explanation.

[0036] The medical intelligent triage system and method provided by the present invention generates a doctor list by combining the patient's condition and the medical resources of each hospital, taking into account factors such as the doctor's ability, the hospital's ranking, and the driving distance between the patient and the hospital, thereby realizing personalized medical selection for patients and alleviating the problem of uneven allocation of hospital resources. In response to the patient's selection of a doctor in the doctor list, the medical intelligent triage system can also generate a medical navigation route to guide the patient to seek medical treatment.

[0037] Example 1

[0038] This embodiment provides a medical intelligent triage method. The medical intelligent triage method at least includes:

[0039] Guide the patient to log in and / or register to the medical intelligent triage system 100 using the access terminal 110;

[0040] The hospital data terminal 120 is configured in the relevant hospital, which can store and collect hospital data including the medical resources, geographical location, and building structure of the hospital;

[0041] The remote server 130 can be data-connected to a number of access terminals 110 and a number of hospital data terminals 120;

[0042] When the patient uploads his / her condition to the remote server 130 via the access terminal 110, the medical recommendation unit 133 configured in the remote server 130 recommends a target hospital and / or target doctor corresponding to the disease to the patient;

[0043] The patient selects the recommended target hospital and / or target doctor by accessing the terminal 110;

[0044] In response to the patient's selection of a target hospital and / or a target doctor, the remote server 130 generates a patient's medical route and retrieves the structural data of the target doctor and his hospital to build a local model corresponding to the patient's medical route.

[0045] Preferably, the consultation route may be the patient's movement route from the hospital entrance to the department where the selected doctor is located.

[0046] Preferably, the medical intelligent triage method further includes:

[0047] The remote server 130 transmits the recommended doctor and the recommended attending doctor list to the access terminal 110 used by the patient, so that the patient can select the attending doctor;

[0048] In response to the patient's selection of a doctor, the remote server 130 generates a navigation route from the patient's current location to the entrance of the hospital where the selected doctor works and a route for the patient to see a doctor after entering the hospital;

[0049] The remote server 130 generates a corresponding model from the hospital entrance to the department where the selected doctor is located according to the medical treatment route;

[0050] The remote server 130 sends the generated navigation route and model to the access terminal 110 used by the patient;

[0051] The access terminal 110 provides medical consultation navigation to the patient using the access terminal 110 through voice and / or images, so that the patient can go to the department where the selected doctor is located for consultation.

[0052] Preferably, the model is a local model corresponding to the hospital structure for the patient's travel route modeled by the remote server 130. Preferably, the remote server 130 sends the local model in the form of a video stream to the corresponding access terminal 110 logged into the medical intelligent triage system 100 through the communication unit 132, thereby realizing personal navigation.

[0053] See also Figure 1 Preferably, the medical intelligent triage method comprises the following steps:

[0054] S110, selecting a corresponding doctor list according to the patient's disease, where the doctor list includes a number of doctors and the hospital to which each doctor belongs;

[0055] S120, obtaining the evaluation of each doctor in the doctor list, and determining the ability weight of each doctor according to the evaluation of each doctor;

[0056] S130, obtaining the ranking of the hospital to which each doctor belongs in the doctor list, and determining the first hospital weight of each doctor according to the ranking of the hospital to which each doctor belongs;

[0057] S140, obtaining the distance between the hospital to which each doctor in the doctor list belongs and the patient's current location, and determining the driving weight of each doctor according to the distance;

[0058] S150. Establish a medical consultation recommendation model based on the ability weight, first hospital weight and driving distance weight of each doctor in the doctor list, and use the medical consultation recommendation model to determine the recommendation index of each doctor, and select the doctor with the largest recommendation index as the recommended doctor; specifically, the output value of the medical consultation recommendation model is obtained by multiplying the ability weight, first hospital weight and driving distance weight.

[0059] See also Figure 2 Preferably, the medical intelligent triage method further comprises the following steps:

[0060] S210, sorting each doctor in order of recommendation index from high to low to obtain a second doctor list;

[0061] S220, for each doctor in the second doctor list, obtain the number of times the hospital to which the current doctor belongs appears in the corresponding hospital set, and calculate the quotient of the number and the total number of hospitals in the hospital set to obtain the second hospital weight; wherein the hospital set is a set of hospitals to which doctors with recommendation indexes equal to or less than the current doctor belong;

[0062] S230. Establish a target intelligent diagnosis guidance model based on the ability weight of each doctor in the second doctor list, the weight of the first hospital, the weight of the second hospital, and the driving distance weight, and use the target intelligent diagnosis guidance model to determine the target recommendation index of each doctor, and select the doctor corresponding to the largest target recommendation index to obtain the target recommended doctor; in addition, sort the corresponding doctors in descending order according to the target recommendation index to obtain a recommended list of doctors for receiving patients.

[0063] This embodiment starts from the perspective of global resource allocation, and provides a list of doctors who are capable of diagnosing the patient's disease, have excellent hospital rankings, and are within a moderate distance, based on the patient's symptoms and location. To ensure that the patient can easily obtain a list of doctors who are capable of diagnosing the patient's disease using this method, the list fully considers the patient's other objective indicators, such as the driving distance between the patient and the hospital, the official ranking of the hospital, and the comprehensive capabilities of the hospital.

[0064] The medical intelligent triage method obtains the distance between the hospital to which each doctor belongs and the patient's current location, and determines whether the distance is greater than the preset distance. If the distance is greater than the preset distance, the doctor corresponding to the distance is deleted from the doctor list, thereby eliminating the doctor who is too far away from the patient.

[0065] In the above embodiment, first, a list of doctors corresponding to the disease (i.e., a list of doctors) is obtained according to the patient's disease; the patient's evaluation data on the doctors in the list who diagnose the disease is obtained, and the optimal ranking of the doctors' abilities corresponding to the disease is obtained from the evaluation data (i.e., the ability weight of each doctor is obtained); then, the guidance recommendation model in the present invention is used to fully consider the doctor's ability, hospital ranking, hospital resources, and the driving distance between the patient and the hospital to obtain a recommended list of doctors for receiving the consultation. The algorithm of the guidance recommendation model draws on the idea of ​​the greedy algorithm, reduces the spatial complexity of the algorithm by obtaining the local optimal method, and uses the method of dynamically updating the weights to achieve the purpose of diverting patients to different hospitals. The present invention aims to solve the problem of patients' difficulty in choosing doctors and the uneven distribution of hospital resources. The above embodiment can effectively solve the current phenomenon that large hospitals are crowded with people, while small hospitals with the same ability to diagnose the same disease have very few patients, which is conducive to alleviating the current situation of uneven distribution of medical resources.

[0066] Example 2

[0067] This embodiment is a further improvement on Embodiment 1, and the repeated contents will not be repeated here.

[0068] This embodiment provides a medical intelligent triage system 100. Figure 3 Preferably, the medical intelligent triage system 100 includes at least an access terminal 110, a hospital data terminal 120 and a remote server 130. The access terminal 110 can guide the patient to log in and / or register to the medical intelligent triage system 100. The hospital data terminal 120 is configured in the relevant hospital and can store and collect hospital data including the medical resources, geographical location, and building structure of the hospital. The remote server 130 can data connect several access terminals 110 and several hospital data terminals 120. The remote server 130 is configured to: when the patient uploads his or her own condition to the remote server 130 through the access terminal 110, recommend the target hospital and / or target doctor corresponding to the disease to the patient through the guidance recommendation model. Preferably, the guidance recommendation model is generated by the remote server 130 based on the hospital data of several hospital data terminals 120.

[0069] Preferably, the medical intelligent triage system 100 starts from the perspective of global resource allocation, and provides the patient with a list of doctors who are capable of diagnosing the disease, have excellent hospital rankings, and are within a moderate distance based on the patient's symptoms and location. To ensure that the patient can easily obtain a list of doctors who are capable of diagnosing the disease through the medical intelligent triage system 100, the list fully considers the patient's other objective indicators, including the driving distance between the patient and the hospital, the official ranking of the hospital, and the comprehensive capacity of the hospital. This effectively solves the current phenomenon that large hospitals are crowded with patients, while small hospitals with the same ability to diagnose the same disease have very few patients, which is conducive to alleviating the current situation of uneven distribution of medical resources.

[0070] See also Figure 4 Preferably, the remote server 130 includes at least a data processing unit 131, a communication unit 132, a medical recommendation unit 133 and a modeling unit 134. The communication unit 132, the medical recommendation unit 133 and the modeling unit 134 are respectively connected to the data processing unit 131. The data processing unit 131 uses the communication unit 132 to establish a data transmission channel with the access terminal 110 and the hospital data terminal 120 to obtain data including the patient's disease type, hospital medical resources and hospital building structure. The data processing unit 131 transmits the acquired patient disease type and hospital medical resources to the medical recommendation unit 133 to obtain a recommended doctor. In response to obtaining the recommended doctor, the data processing unit 131 transmits the recommended doctor and the structure of the hospital where he is located to the modeling unit 134 to model a local model corresponding to the patient's indoor medical treatment route.

[0071] The medical recommendation unit 133 may generate a recommended list of attending doctors.

[0072] See also Figure 5 Preferably, the medical recommendation unit 133 may include: a preparation module 141 , a screening module 142 , a first list module 143 , a first weight module 144 , a recommendation module 145 , a second list module 146 , and a second weight module 147 .

[0073] The preparation module 141 is used to obtain the following data: the patient's disease, the doctor who can diagnose the disease, the patient's evaluation of the doctor's ability to diagnose the disease, the official ranking of the hospital, and the driving distance between the hospital and the patient.

[0074] The screening module 142 summarizes the doctors who can diagnose the patient's disease, obtains the distance between the hospital to which each doctor belongs and the patient's current location, and determines whether the distance is greater than a preset distance. If the distance is greater than the preset distance, the doctor corresponding to the distance is deleted from the summarized doctors.

[0075] The first list module 143 sorts the doctors collected by the screening module 142 from high to low scores based on the patient's evaluation of the doctor's ability to diagnose the disease, and obtains a doctor list.

[0076] The first weight module 144 determines the ability weight of each doctor according to the evaluation of each doctor, determines the first hospital weight of each doctor according to the ranking of the hospital to which each doctor belongs, and determines the driving weight of each doctor according to the distance between the hospital to which each doctor belongs and the current location of the patient.

[0077] The recommendation module 145 establishes a medical consultation recommendation model according to the ability weight, the first hospital weight and the driving distance weight of each doctor in the doctor list, and determines the recommendation index of each doctor using the medical consultation recommendation model, and selects the doctor corresponding to the largest recommendation index as the recommended doctor. Specifically, the medical consultation recommendation model multiplies the ability weight, the first hospital weight and the driving distance weight to obtain an output value.

[0078] The second list module 146 sorts each doctor in order of recommendation index from high to low to obtain a second doctor list.

[0079] The second weight module 147 obtains the number of times the hospital to which the current doctor belongs appears in the corresponding hospital set for each doctor in the second doctor list, and calculates the quotient of the number and the total number of hospitals in the hospital set to obtain the second hospital weight. The hospital set is a set of hospitals to which doctors with recommendation indexes equal to or less than the current doctor belong.

[0080] The recommendation module 145 establishes a target intelligent diagnosis guidance model based on the ability weight of each doctor in the second doctor list, the weight of the first hospital, the weight of the second hospital, and the driving distance weight. Preferably, the recommendation module 145 uses the target intelligent diagnosis guidance model to determine the target recommendation index of each doctor, and selects the doctor corresponding to the largest target recommendation index to obtain the target recommended doctor. Preferably, the recommendation module 145 sorts the corresponding doctors in descending order according to the target recommendation index to obtain a recommended list of doctors for receiving consultations.

[0081] Many existing doctor recommendation systems only make recommendations based on the doctor's qualifications, which results in overload of patients in large hospitals, patients competing for specialist appointments, and uneven allocation of hospital resources. To solve these problems, this embodiment, when recommending doctors to patients, not only considers the doctor's ability to diagnose diseases, but also considers factors such as the official ranking of the hospital and the driving distance between the patient and the hospital.

[0082] Preferably, the patient's evaluation of the doctor's ability to diagnose the disease can directly reflect the doctor's professional ability level; the hospital's official ranking can reflect the hospital's overall service level; the driving distance between the patient and the hospital directly affects the convenience of the patient receiving treatment. The present invention adopts a guidance recommendation model, and ultimately obtains a doctor recommendation sequence that weighs the above indicators. The specific modeling process follows the following conditions:

[0083] Doctor's ability is derived from the patient's evaluation of the doctor's diagnosis of the disease. The larger the weight of the doctor's ability, the more experience the doctor has in diagnosing the disease, and the higher the patient's satisfaction.

[0084] The hospital weight includes the proportion of hospitals in the doctor ability ranking (corresponding to the second hospital weight mentioned above) and the official ranking of the hospital (corresponding to the first hospital weight mentioned above). Among them, the proportion of hospitals in the doctor ability ranking is calculated by the ratio of the number of hospitals to the number of all hospitals in the list. This ratio is a dynamic update process, because in the ranking process, when a doctor is selected, when selecting the next doctor, the doctor ability ranking after excluding the selected doctor's information is used, and so on, until all doctors are ranked.

[0085] The weight of the first hospital is determined based on the official ranking of the hospital. The official ranking of the hospital can reflect the overall medical service level of the hospital, so the higher the ranking, the greater the corresponding weight should be.

[0086] When patients are choosing doctors, the driving distance between the patient and the hospital is one of the important considerations, which directly affects the patient's choice of doctor. Therefore, this embodiment uses the driving distance between the patient and the hospital as one of the indicators for weighing diversity. The driving distance between the patient and the hospital is determined by the patient's location, and with the patient as the center, all hospitals in the area with a driving distance less than a preset reference value are collected, and sorted by the length of the driving distance, and the intersection is taken with the hospitals in the doctor's ability ranking. The shorter the driving distance between the patient and the hospital, the greater the recommendation should be, and the corresponding weight should also be greater.

[0087] Preferably, the output value of the medical consultation recommendation model can be the product of the weights of each item. The larger the output value, the better the corresponding doctor ranking, that is, the more comprehensively the doctor ranking can consider factors such as doctor ability, hospital ranking, and the driving distance between the patient and the hospital. The purpose of the medical consultation recommendation model is to obtain the doctor ranking corresponding to the maximum output value. The medical consultation recommendation model contains 4 constraints. Condition 1: The driving distance between the patient and the hospital does not exceed the preset value, which is used to limit the driving distance between the patient and the hospital; the other three conditions are used to solve the weight of the doctor's ability, the weight of the hospital, and the weight of the driving distance between the patient and the hospital.

[0088] The medical recommendation unit 133 fully considers factors such as doctor ability, hospital ranking, hospital resource allocation, and driving distance between the hospital and the patient in the process of recommending doctors, thereby achieving personalized medical selection for patients and alleviating the problem of uneven distribution of hospital resources.

[0089] Preferably, the remote server 130 transmits the recommended list of doctors and the recommended list of doctors to the access terminal 110 used by the patient, so that the patient can select the doctor to see. In response to the patient's selection of the doctor to see, the remote server 130 generates a navigation route from the patient's current location to the entrance of the hospital where the selected doctor belongs and a model from the hospital entrance to the department where the selected doctor belongs. The model is a local model corresponding to the hospital structure for the patient's route modeled by the remote server 130.

[0090] Preferably, the remote server 130 sends the local model to the corresponding access terminal 110 logged in to the medical intelligent triage system 100 in the form of a video stream through the communication unit 132. The access terminal 110 is configured to at least be able to navigate the patient based on the target hospital and / or target doctor to assist the patient in finding the target hospital and / or target doctor quickly and accurately. Preferably, the access terminal 110 can be a smart terminal such as a smart phone, a smart bracelet, a tablet computer, etc.

[0091] After receiving the video stream of the corresponding local model, the access terminal 110 carried by the patient can display the local model at any time to provide route navigation for the patient. Preferably, after the patient enters the hospital, especially when the communication signal is interfered, the patient can go to the destination by viewing the navigation video of the access terminal 110.

[0092] Preferably, in response to the patient's determination of the doctor to be seen, the remote server 130 retrieves the plane and three-dimensional data of the hospital building to which the doctor belongs, so as to model a part of the model corresponding to the hospital for the corresponding patient's target location (the department where the doctor is located) and the starting position is located at the entrance of the hospital. Preferably, the remote server 130 can access a public map database, and the local model modeled by the remote server 130 for the patient's target location can be matched with the public map. In response to the determination of the patient's target location, the remote server 130 generates a patient's route to guide the patient to the corresponding department for treatment. Preferably, the patient's route includes a route from the patient's current location to the entrance of the hospital to which the selected doctor belongs and a route from the hospital entrance to the department where the selected doctor is located. Preferably, in the process of the patient moving from his own location to the hospital entrance, the patient can navigate through the navigation function of the access terminal 110. Preferably, when the patient uses the access terminal 110 to navigate to the hospital entrance along the public map, the access terminal 110 switches from public map navigation to video navigation.

[0093] Preferably, the remote server 130 obtains the starting position and viewing direction of the patient by reading the location information of the access terminal 110, and navigates the patient to the hospital entrance based on the starting position and viewing direction of the patient in combination with the public map data. Preferably, the remote server 130 generates a corresponding local model of the route from the hospital entrance to the corresponding department. Preferably, the remote server 130 generates the local model in the following manner. Preferably, the remote server 130 can use the hospital entrance where the patient arrives as the patient's starting position and the direction of entering the hospital as the patient's viewing direction, and at the same time retrieve the plane data and three-dimensional data associated with the corresponding patient's target department and starting position to complete the modeling. Preferably, when the remote server 130 is modeling the virtual model, it can generate a virtual character image in the model that is the same as the patient's starting position and viewing direction.

[0094] When the patient arrives at the hospital entrance according to the navigation route and starts video navigation, the patient's starting position and viewing direction match the corresponding local model. The patient can determine the characteristic reference objects on the navigation path in the navigation model by adjusting the viewing angle of the corresponding virtual character image based on the movement of the virtual character in the virtual model corresponding to his actual position and viewing direction. When moving in the hospital, the patient can view the local model at any time, and can observe the model in all directions by adjusting the viewing direction of the virtual character to compare the architectural features in the virtual environment with the architectural features in the actual environment to determine the route of travel and realize portable navigation. In the process of the patient navigating through the access terminal 110, the access terminal 110 can only receive the navigation video of the virtual model generated by the remote server 130, thereby avoiding the data in the hospital that is not allowed by laws and regulations to be retained on the access terminal 110 worn by the patient due to modeling by the access terminal 110 worn by the patient, thereby reducing the risk of confidential data leakage in the hospital.

[0095] Preferably, when the patient receives the video stream of the local model by accessing the terminal 110, the patient can view the local model at any time, and can adjust the viewing direction of the virtual character to observe the model in all directions, thereby comparing the architectural features in the virtual environment with the architectural features in the actual environment to determine the route of travel.

[0096] Preferably, when the patient enters the hospital building, the personal access terminal 110 is easily disturbed by the building and the communication quality is reduced. If the local model video stream generated by the remote server 130 is still sent to the access terminal 110 when the patient enters the hospital, the integrity and stability of the video stream transmission cannot be ensured. Preferably, when the patient is within the hospital, the patient can navigate by using a self-service machine.

[0097] Preferably, the patient can register and / or log in to the medical intelligent triage system 100 by matching the access terminal 110 with the self-service machine, and then handle the business by operating the self-service machine. Preferably, in addition to smart terminals carried by individuals such as smart phones, smart bracelets, and tablet computers, the access terminal 110 of the present invention can also be a self-service machine configured by each hospital.

[0098] Preferably, when a patient uses a business self-service machine to log in and / or register to the medical intelligent triage system 100, the self-service machine can obtain its own position data through the configured positioning unit, and then obtain the starting position and viewing direction of the corresponding patient by mirroring its own position data, and upload the starting position and viewing direction of the corresponding patient to the remote server 130. The starting position and viewing direction of the corresponding patient are determined in the following manner, that is, the self-service machine uses the positioning unit to perform position detection to determine its own current position and orientation, and after mirroring its own current position and orientation along the display side, determines the viewing direction and positioning of the patient currently using the self-service machine, and determines the starting position and viewing direction of the patient in the corresponding local model based on the viewing direction and positioning of the current patient in combination with the hospital structure data.

[0099] Preferably, the remote server 130 can generate a virtual character image in the generated virtual model. Preferably, when the patient uses the business self-service machine to log in and / or register to the medical intelligent triage system 100, the starting position and viewing direction of the virtual character image are determined in the following manner, that is, the self-service machine determines the viewing direction and positioning of the current patient of the self-service machine according to its own current position and orientation, and provides the viewing direction and positioning to the remote server 130, which determines the starting position and viewing direction of the corresponding virtual character image, so that the starting position and viewing direction of the corresponding virtual character image are the same as the actual position and viewing direction of the current patient of the self-service machine, thereby facilitating the patient to substitute the model into reality.

[0100] The business self-service machine can prompt the patient who logs into the medical intelligent triage system 100 to select his or her personalized virtual character image by providing voice prompts to the patient, and determine the patient's current position and orientation through the business self-service machine's own current position and orientation, and thereby determine the starting position and viewing direction of the virtual character image selected by the patient, thereby ensuring that the position and viewing direction of the virtual character image selected by the patient are consistent with the patient's actual position and viewing direction.

[0101] When the corresponding local model that determines the patient's starting position and viewing direction is displayed to the patient in the form of a video, the patient can determine the characteristic reference objects on the navigation path in the navigation model by adjusting the viewing angle of the corresponding virtual character image based on the movement of the virtual character corresponding to the patient's actual position and viewing direction in the virtual model. When the medical treatment path generated by the patient through the operation of the self-service machine intersects with the medical treatment path of at least another patient, the virtual character image corresponding to the current patient will appear in the navigation video generated by the other patient through the operation of the self-service machine to determine the patient's starting position and viewing direction and sent to the smart device, thereby reflecting the actual flow of people in the corresponding area in the local model.

[0102] It should be noted that the above-mentioned specific embodiments are exemplary, and those skilled in the art can come up with various solutions inspired by the disclosure of the present invention, and these solutions also belong to the disclosure scope of the present invention and fall within the protection scope of the present invention. Those skilled in the art should understand that the present invention specification and its drawings are illustrative and do not constitute a limitation of the claims. The scope of protection of the present invention is defined by the claims and their equivalents. The present invention specification contains multiple inventive concepts, such as "preferably", "according to a preferred embodiment" or "optionally", all of which indicate that the corresponding paragraph discloses an independent concept, and the applicant reserves the right to file a divisional application based on each inventive concept. Throughout the text, the feature guided by "preferably" is only an optional method and should not be understood as a must-have setting. Therefore, the applicant reserves the right to abandon or delete the relevant preferred features at any time.

Claims

1. A medical intelligent triage system, the medical intelligent triage system (100) comprising an access terminal (110), a hospital data terminal (120) and a remote server (130), wherein the access terminal (110) is capable of guiding a patient to log in and / or register to the medical intelligent triage system (100); the hospital data terminal (120) is configured in a relevant hospital and is capable of storing and collecting hospital data including medical resources, geographical location, and building structure of the hospital; the remote server (130) is capable of data connection with a plurality of the access terminals (110) and a plurality of the hospital data terminals (120); It is characterized in that The remote server (130) is provided with a medical recommendation unit (133) for recommending a corresponding target hospital and / or target doctor to the patient when the patient uploads his / her own medical condition to the remote server (130) via the access terminal (110); the patient selects the recommended target hospital and / or target doctor via the access terminal (110); In response to the patient's selection of a target hospital and / or a target doctor, the remote server (130) generates a navigation route from the patient's current location to the entrance of the hospital to which the selected doctor belongs and the patient's medical treatment route after entering the hospital, and retrieves the structural data of the target doctor and the hospital to which he belongs to build a local model corresponding to the patient's indoor medical treatment route, and sends the generated navigation route and model in the form of a video stream to the corresponding access terminal (110) used by the patient to log in to the medical intelligent triage system (100). After receiving the video stream of the corresponding local model, the access terminal (110) carried by the patient provides route navigation for the patient by displaying the local model at any time. The remote server (130) obtains the starting position and viewing direction of the patient by reading the location information of the access terminal (110), and navigates the patient to the hospital entrance according to the starting position and viewing direction of the patient in combination with public map data. The remote server (130) uses the hospital entrance where the patient arrives as the patient's starting position and the direction of entering the hospital as the patient's viewing direction, and simultaneously retrieves the plane data and three-dimensional data associated with the corresponding patient's target department and starting position to complete the modeling. When the remote server (130) is modeling the virtual model, it generates a virtual character image in the model that has the same starting position and viewing direction as the patient. When the patient moves from his / her own location to the hospital entrance, the patient navigates through the navigation function of the access terminal (110). When the patient uses the access terminal (110) to navigate to the hospital entrance along the public map, the access terminal (110) switches from public map navigation to video navigation. When the patient arrives at the hospital entrance according to the navigation route and starts video navigation, the patient's starting position and viewing direction are matched with the corresponding local model. The patient can determine the characteristic reference objects on the navigation route in the navigation model by adjusting the viewing angle of the corresponding virtual character image based on the movement of the virtual character image corresponding to his or her actual position and viewing direction in the virtual model. When moving in the hospital, the patient adjusts the viewing direction of the virtual character image to observe the model in all directions, thereby comparing the architectural features in the virtual environment with the architectural features in the actual environment, so as to determine the route of travel and realize portable navigation. During the process of the patient navigating through the access terminal (110), the access terminal (110) can only receive the navigation video of the virtual model generated by the remote server (130). When the medical treatment path generated by a patient by operating a self-service machine intersects with the medical treatment path of at least another patient, the virtual character image corresponding to the current patient will appear in the navigation video generated by another patient by operating the self-service machine and sent to the access terminal (110) to determine the patient's starting position and viewing direction, thereby reflecting the actual flow of people in the corresponding area in the local model.

2. The intelligent medical triage system according to claim 1, characterized in that: The medical recommendation unit (133) is configured with a preparation module (141); the preparation module (141) is configured to: obtain the patient's disease data from the access terminal (110), and obtain data including doctors who can diagnose the disease, the patient's evaluation of the doctor's ability to diagnose the disease, the hospital's official ranking and the driving distance between the hospital and the patient from the hospital data terminal (120).

3. The intelligent medical triage system according to claim 1, characterized in that: The medical recommendation unit (133) further includes: a screening module (142) and a first list module (143); wherein the screening module (142) is configured to: summarize doctors who can diagnose the patient's disease, obtain the distance between the hospital to which each doctor belongs and the patient's current location, and determine whether the distance is greater than a preset distance. If the distance is greater than the preset distance, the doctor corresponding to the distance is deleted from the summarized doctors; and the first list module (143) is configured to: sort the doctors summarized by the screening module (142) from high to low scores based on the patient's evaluation of the doctor's ability to diagnose the disease, to obtain a doctor list.

4. The intelligent medical triage system according to claim 1, characterized in that: The medical recommendation unit (133) further includes: a first weight module (144) and a recommendation module (145); wherein the first weight module (144) is configured to: determine the ability weight of each doctor according to the evaluation of each doctor, determine the first hospital weight of each doctor according to the ranking of the hospital to which each doctor belongs, and determine the driving weight of each doctor according to the distance between the hospital to which each doctor belongs and the current location of the patient; the recommendation module (145) is configured to: establish a medical guidance recommendation model according to the ability weight, first hospital weight and driving weight of each doctor in the doctor list, determine the recommendation index of each doctor using the medical guidance recommendation model, and select the doctor corresponding to the largest recommendation index as the recommended doctor.

5. The intelligent medical triage system according to claim 4, characterized in that: The medical recommendation unit (133) also includes: a second list module (146) and a second weight module (147); wherein the second list module (146) is configured to: sort each doctor in order from high to low according to the recommendation index to obtain a second doctor list; the second weight module (147) is configured to: for each doctor in the second doctor list, obtain the number of times the hospital to which the current doctor belongs appears in the corresponding hospital set, and calculate the quotient of the number and the total number of hospitals in the hospital set to obtain a second hospital weight; wherein the hospital set is a set of hospitals to which doctors whose recommendation index is equal to or less than the current doctor belong.

6. The intelligent medical triage system according to claim 5, characterized in that: The recommendation module (145) establishes a target intelligent diagnosis guidance model according to the ability weight, the first hospital weight, the second hospital weight and the driving distance weight of each doctor in the second doctor list, and uses the target intelligent diagnosis guidance model to determine the target recommendation index of each doctor, and selects the doctor corresponding to the largest target recommendation index to obtain the target recommended doctor; and the recommendation module (145) sorts the corresponding doctors in descending order according to the target recommendation index to obtain a recommended list of doctors for receiving consultations.

7. The intelligent medical triage system according to claim 1, characterized in that: The remote server (130) includes at least a data processing unit (131), a communication unit (132), a medical recommendation unit (133) and a modeling unit (134); the communication unit (132), the medical recommendation unit (133) and the modeling unit (134) are respectively connected to the data processing unit (131); wherein the data processing unit (131) uses the communication unit (132) to establish a data transmission channel with the access terminal (110) and the hospital data terminal (120) to obtain data including the patient's disease type, hospital medical resources and hospital building structure; wherein the data processing unit (131) transmits the obtained patient disease type and hospital medical resources to the medical recommendation unit (133) to obtain a recommended doctor; in response to obtaining the recommended doctor, the data processing unit (131) transmits the recommended doctor and the structure of the hospital where he is located to the modeling unit (134) to model a local model corresponding to the patient's indoor medical treatment route.

8. A medical intelligent triage method according to the medical intelligent triage system according to any one of claims 1 to 7, characterized in that: The medical intelligent triage method at least comprises: guiding a patient to log in and / or register to the medical intelligent triage system (100) using an access terminal (110); configuring a hospital data terminal (120) in a relevant hospital, capable of storing and collecting hospital data including the medical resources, geographical location, and building structure of the hospital; a remote server (130) capable of data connection between a plurality of the access terminals (110) and a plurality of the hospital data terminals (120); when a patient uploads his or her own condition to the remote server (130) via the access terminal (110), a medical recommendation unit (133) configured in the remote server (130) recommends a target hospital and / or a target doctor corresponding to the disease to the patient; the patient selects the recommended target hospital and / or target doctor via the access terminal (110); in response to the patient's selection of the target hospital and / or target doctor, the remote server (130) generates a patient's medical route, and retrieves the structural data of the target doctor and the hospital to which he or she belongs to model a local model corresponding to the patient's medical route.

9. The medical intelligent triage method according to claim 8, characterized in that: The method also includes: selecting a corresponding doctor list according to the patient's disease; obtaining the evaluation of each doctor in the doctor list, and determining the ability weight of each doctor based on the evaluation of each doctor; obtaining the ranking of the hospital to which each doctor in the doctor list belongs, and determining the first hospital weight of each doctor based on the ranking of the hospital to which each doctor belongs; obtaining the distance between the hospital to which each doctor in the doctor list belongs and the patient's current location, and determining the driving weight of each doctor; establishing a consultation recommendation model based on the ability weight, first hospital weight and driving weight of each doctor in the doctor list to determine the recommendation index of each doctor, and selecting the doctor corresponding to the largest recommendation index as the recommended doctor.

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