Multi-objective optimized intelligent doctor-seeing guiding method and multi-objective optimized intelligent doctor-seeing guiding system

Abstract

The invention relates to the technical field of medical informatization and intelligent service, in particular to a multi-objective optimized intelligent medical treatment guide method and system. The system integrates a plurality of modules such as position navigation, process guidance, humanistic care, doctor-seeing prompt, propaganda and education, tracking, information input, data analysis and intelligent recommendation, and comprehensively optimizes the doctor-seeing process; through data analysis and intelligent recommendation, the system can provide personalized guidance service according to the specific condition of the patient; meanwhile, in the position navigation module and in the multi-objective optimization solving process, the traditional genetic algorithm is improved, including determining the elitist retention proportion and then carrying out interlace operation, so that the global search capability and the local search capability of the genetic algorithm are better balanced.

Description

Technical Field

[0001] This invention relates to the field of medical information technology and intelligent service technology, and in particular to a multi-objective optimized intelligent medical guidance method and system. Background Technology

[0002] Modern general hospitals typically have a vast physical space, encompassing multiple functional areas such as outpatient buildings, inpatient wards, medical technology buildings, pharmacies, and emergency departments. Different departments may be located on different floors or even in different buildings. Patients are often completely unfamiliar with the hospital layout and cannot quickly locate their target department / examination room using only paper information sheets or verbal inquiries, frequently resulting in them running back and forth to the wrong floors and wasting a significant amount of time searching for their way. Furthermore, the medical process usually involves multiple steps, including registration, triage and check-in, waiting, doctor's consultation, ordering examinations / tests / prescriptions, payment, undergoing examinations, waiting for reports, returning to the doctor for follow-up, and picking up medication / hospitalization. The order of these steps varies depending on the condition and type of examination. Patients often don't know what to do next and can only rely on repeatedly asking the information desk or nurses, sometimes even resulting in repeated queueing due to incorrect ordering.

[0003] In existing technologies, intelligent medical guidance systems have limited integrated functions and cannot meet the needs of patients; in particular, intelligent medical guidance systems have a long waiting time when generating navigation routes for the destination entered by the patient. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a multi-objective optimized intelligent medical guidance method and system to solve the problems existing in the prior art.

[0005] This invention provides a multi-objective optimized intelligent medical guidance method, comprising the following steps: S1: Collect patient information; S2: Provide intelligent medical guidance to the patient based on the patient information; The intelligent medical guidance includes location navigation, process guidance, humanistic care, medical consultation prompts, patient education, and record tracking; The location navigation process is as follows: Sa1: Obtain real-time map data of the hospital; Sa2: Construct the objective function; Sa3: Based on the real-time map data, an improved genetic algorithm is used to solve the objective function to obtain the navigation path; The cross-operation based on elite retention is improved by determining the operating ratio value; the formula for determining the elite ratio is: ; In the formula, p elite(t) represents the proportion of elites in generation t, p elite (t−1) represents the proportion of elites in generation t−1, α, β, and γ are adjustment parameters, and σ fitness (t) represents the standard deviation of individual fitness in the population at generation t, d hamming (t) represents the average Hamming distance between individuals in the population at generation t, d hamming_threshold It is a preset Hamming distance threshold; Sa4: Display the navigation path to the patient.

[0006] Preferably, S1 specifically includes: basic patient information and dynamic key medical information.

[0007] Preferably, the patient's basic information includes identity information, contact information, basic health information, and medical treatment preference information; the identity information includes name, gender, date of birth, and ID card number / medical insurance card number; the contact information includes mobile phone number and emergency contact information; the basic health information includes height, weight, blood type, and allergy history; the medical treatment preference information includes whether the patient is disabled, whether they are an elderly patient, and their language preference. The key dynamic medical information includes location information, registration information, consultation type information, chief complaint and preliminary needs information, and special needs information; the location information is the patient's location; the registration information includes the department, doctor's name / number, and appointment time; the consultation type information includes initial visit / follow-up visit; the chief complaint and preliminary needs information includes the purpose of this medical visit; the special needs information includes whether a wheelchair / stretcher is needed, whether previous examination reports are brought, and whether priority treatment is required.

[0008] Preferably, in Sa2, the targets for generating the navigation route include: Shortest path length: Select the shortest path from the current location to the destination to reduce the patient's walking distance; Minimum waiting time: Select the department or examination room with the shortest current waiting time to reduce patient waiting time; Choose the least busy department or examination room to reduce the time patients spend in the department; Highest priority: For emergency patients, prioritize the route to ensure timely medical attention.

[0009] Preferably, the expression for the objective function is: ; In the formula, d(x) represents the path length, t(x) represents the waiting time, b(x) represents the department's busyness level, p(x) represents the priority, and w1, w2, w3, w4 are weight coefficients.

[0010] Preferably, the process guidance is as follows: the intelligent medical guidance system is synchronized with the hospital's medical order system in real time to obtain the patient's medical order information; based on the medical order, the intelligent medical guidance system automatically reminds the patient of the next step; and the process sequence is optimized by analyzing the patient's medical process.

[0011] Preferably, the process of the humanistic care is as follows: monitoring the patient's emotional state through the patient's behavioral data; automatically pushing psychological counseling content based on the emotional state; and providing online psychological counseling function so that the patient can communicate with a psychologist at any time.

[0012] Preferably, the process of the medical appointment prompt is as follows: real-time monitoring of the queuing situation in each department and examination room, and notification to patients through the intelligent medical appointment guidance system; based on the queuing situation, estimating the patient's waiting time and reasonably arranging the patient's waiting time; for emergency patients, the intelligent medical appointment guidance system automatically adjusts the priority.

[0013] Preferably, the patient education process is as follows: establishing a basic knowledge base of diseases, examinations, nursing care, and medication; recommending educational content based on the patient's condition and history; providing a question-and-answer function, where the intelligent medical guidance system automatically answers questions asked by the patient. The record tracking process is as follows: record the patient's historical medical records, including the condition, examination results, and treatment plan; analyze the data to sort out the patient's disease progression and provide reference for doctors; based on the disease progression, the intelligent medical guidance system automatically reminds the patient of follow-up visits and examinations.

[0014] According to another aspect of the present invention, a multi-objective optimized intelligent medical treatment guidance system is provided, the system employing the above-described multi-objective optimized intelligent medical treatment guidance method, the system comprising: The patient information collection module is used to collect patient information; Location navigation module to help patients find their destination; Process guidance module: It contains details of each step of the medical treatment process, links with the medical order system, and guides patients to the next step according to the medical order; Humanistic care module: Providing emotional support and psychological comfort to patients; Medical appointment reminder module: Provides patients with medical appointment queue reminders and helps them rationally arrange their medical appointment process; Education module: Provides informational and educational materials to patients; Record Tracking Module: Used to record patients' historical medical records, analyze the data to track the patient's disease progression and provide reference for doctors; automatically remind patients of follow-up visits and examinations based on disease progression.

[0015] The present invention has the following technical effects: This invention integrates multiple modules such as location navigation, process guidance, humanistic care, consultation prompts, education, tracking, information entry, data analysis, and intelligent recommendation to comprehensively optimize the medical process. Through data analysis and intelligent recommendation, the system can provide personalized guidance services based on the patient's specific situation. At the same time, in the location navigation module, the traditional genetic algorithm is improved in the multi-objective optimization solution process, including determining the proportion of elites to be retained and then performing crossover operations to better balance the global search capability and local search capability of the genetic algorithm. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a multi-objective optimized intelligent medical guidance method provided in an embodiment of the present invention; Figure 2 This is a flowchart of the location navigation process provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0019] Example 1 Figure 1 A flowchart of a multi-objective optimization intelligent medical guidance method is shown, such as... Figure 1 As shown, a multi-objective optimized intelligent medical guidance method includes the following steps: S1: Collect patient information; S1 specifically includes: basic patient information and dynamic key medical information.

[0020] The patient's basic information includes identity information, contact information, basic health information, and medical treatment preference information. The identity information includes name, gender, date of birth, and ID card number / medical insurance card number. The contact information includes mobile phone number and emergency contact information. The basic health information includes height, weight, blood type, and allergy history. The medical treatment preference information includes whether the patient is disabled, whether the patient is elderly, and language preference.

[0021] The dynamic medical information includes location information, registration information, consultation type information, chief complaint and preliminary needs information, and special needs information; the location information is the patient's location; the registration information includes the department, doctor's name / number, and appointment time; if it is on-site registration, the department and doctor of the currently successfully registered are recorded; the consultation type information includes initial visit / follow-up visit; the chief complaint and preliminary needs information includes the purpose of this medical visit; the special needs information includes whether a wheelchair / stretcher is needed, whether previous examination reports are brought, and whether priority treatment is required.

[0022] S2: Provide intelligent medical guidance to the patient based on the patient information; The intelligent medical guidance includes location navigation, process guidance, humanistic care, medical consultation prompts, patient education, and record tracking. Among them, such as Figure 2 As shown, the location navigation process is as follows: Sa1: Obtain real-time map data of the hospital; The process involves obtaining a floor plan of the hospital and detailed information on key locations such as departments, examination rooms, and pharmacies through the hospital's information system (HIS); converting the map data into a format that the navigation system can process, which is a graph structure of nodes and edges, where each node represents a key location and each edge represents a path between two nodes; the real-time map data also includes queuing information for each department.

[0023] Sa2: Construct the objective function; The objectives of the navigation route generation include: Shortest path length: Select the shortest path from the current location to the destination to reduce the patient's walking distance; Minimum waiting time: Select the department or examination room with the shortest current waiting time to reduce patient waiting time; Choose the least busy department or examination room to reduce the time patients spend in the department; Highest priority: For emergency patients, prioritize the route to ensure timely medical attention.

[0024] Based on the above objectives, a multi-objective optimization objective function is constructed that comprehensively considers path length, waiting time, departmental workload, and priority. The expression of the objective function is as follows: ; In the formula, d(x) represents the path length, t(x) represents the waiting time, b(x) represents the department's busyness level, p(x) represents the priority, and w1, w2, w3, w4 are weight coefficients.

[0025] Sa3: Based on the real-time map data, an improved genetic algorithm is used to solve the objective function to obtain the navigation path; In existing technologies, a fixed ratio of elites is generally used for crossover operations. However, a fixed ratio may weaken the search ability of the genetic algorithm and increase patient waiting time. This step improves the crossover operation based on elite preservation to better balance the algorithm's global search ability and local search ability.

[0026] Specifically, after each generation of the population is generated, the elitist ratio is adjusted based on the population's fitness distribution and diversity. This involves calculating the standard deviation of the fitness of individuals in the population. A larger standard deviation indicates greater differences in fitness among individuals, in which case the elitist ratio can be appropriately reduced to increase population diversity and prevent premature convergence to a local optimum. Conversely, a smaller standard deviation indicates more similar fitness among individuals, in which case the elitist ratio can be appropriately increased to accelerate algorithm convergence. The average Hamming distance between individuals in the population is used to measure population diversity. A larger average Hamming distance indicates higher population diversity, in which case the elitist ratio can be appropriately reduced; conversely, a smaller average Hamming distance indicates lower population diversity, in which case the elitist ratio can be appropriately increased.

[0027] The formula for determining the elite ratio is: ; In the formula, p elite (t) represents the proportion of elites in generation t, p elite (t−1) represents the proportion of elites in generation t−1, α, β, and γ are adjustment parameters, and σ fitness (t) represents the standard deviation of individual fitness in the population at generation t, d hamming (t) represents the average Hamming distance between individuals in the population at generation t, d hamming_threshold It is a preset Hamming distance threshold.

[0028] Sa4: Display the navigation path to the patient.

[0029] This invention improves upon traditional genetic algorithms by determining the proportion of elites to be retained and then performing a crossover operation, thereby better balancing the global and local search capabilities of the genetic algorithm.

[0030] The process described is as follows: the intelligent medical guidance system is synchronized with the hospital's medical order system in real time to obtain the patient's medical order information. Based on the medical order, the intelligent medical guidance system automatically reminds the patient of the next step, such as examination, medication pickup, and follow-up visit. By analyzing the patient's medical process, the process sequence is optimized to reduce unnecessary waiting time.

[0031] The humanistic care process involves: monitoring the patient's emotional state through behavioral data; automatically pushing psychological counseling content based on the emotional state; and providing online psychological counseling functions so that patients can communicate with psychologists at any time.

[0032] The behavioral data includes walking speed, dwell time, etc.

[0033] The process for providing medical consultation is as follows: real-time monitoring of queuing in various departments and examination rooms, and notification to patients through an intelligent medical guidance system; estimation of patient waiting time based on queuing conditions, and reasonable arrangement of patient waiting time; for emergency patients, the intelligent medical guidance system automatically adjusts priorities to ensure timely medical treatment.

[0034] The patient education process includes: establishing a basic knowledge base on diseases, examinations, nursing care, and medication, and providing rich educational content; recommending relevant educational content based on the patient's condition and history; and providing a question-and-answer function so that patients can ask questions at any time, and the intelligent medical guidance system will automatically answer common questions.

[0035] The record tracking process is as follows: record the patient's historical medical records, including the condition, examination results, treatment plan, etc.; analyze the data to sort out the patient's disease progress and provide reference for doctors; based on the disease progress, the intelligent medical guidance system automatically reminds the patient of follow-up visits, examinations, and other matters.

[0036] This invention integrates multiple modules such as location navigation, process guidance, humanistic care, appointment reminders, health education, tracking, information entry, data analysis, and intelligent recommendation to comprehensively optimize the medical process. Through data analysis and intelligent recommendation, the system can provide personalized guidance services based on the patient's specific situation. Furthermore, in the location navigation module, the traditional genetic algorithm is improved during the multi-objective optimization process. This includes determining the proportion of elites retained and then performing a crossover operation to better balance the global and local search capabilities of the genetic algorithm, thereby reducing patient waiting time.

[0037] Example 2 This invention also provides a multi-objective optimized intelligent medical treatment guidance system, which adopts a multi-objective optimized intelligent medical treatment guidance method according to Embodiment 1. The system includes: The patient information collection module is used to collect patient information; Location navigation module to help patients find their destination; Process guidance module: It contains details of each step of the medical treatment process, links with the medical order system, and guides patients to the next step according to the medical order; Humanistic care module: Providing emotional support and psychological comfort to patients; Medical appointment reminder module: Provides patients with medical appointment queue reminders and helps them rationally arrange their medical appointment process; Education module: Provides informational and educational materials to patients; Record Tracking Module: Used to record patients' historical medical records, analyze the data to track the patient's disease progression and provide reference for doctors; automatically remind patients of follow-up visits and examinations based on disease progression.

[0038] Example 3 The present invention also provides an electronic device, including one or more processors and a memory.

[0039] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0040] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor may execute the program instructions to implement a multi-objective optimized intelligent medical guidance method and / or other desired functions as described in any embodiment of this application. Various contents such as initial extrinsic parameters and thresholds may also be stored in the computer-readable storage medium.

[0041] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to implement the function of a multi-objective optimized intelligent medical guidance method provided in any embodiment of this application.

[0042] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0043] Furthermore, embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to implement a multi-objective optimized intelligent medical guidance method provided in any embodiment of this application.

[0044] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A multi-objective optimization intelligent medical seeking guidance method, characterized in that, The method comprises the following steps: S1: collecting patient information; S2: intelligently guiding the patient to see a doctor according to the patient information; The intelligent guidance to see a doctor comprises position navigation, process guidance, humanistic care, medical visit prompt, patient education and record tracking; The process of the position navigation is as follows: Sa1: obtaining real-time map data of the hospital; Sa2: constructing a target function; Sa3: solving the target function by using an improved genetic algorithm according to the real-time map data to obtain a navigation path; The elite retention-based crossover operation is improved by determining an operation ratio value; and a formula for determining the elite ratio is as follows: ； where p elite (t) denotes the elite ratio of the tth generation, p elite (t−1) denotes the elite ratio of the (t−1)th generation, α, β, γ are adjustment parameters, σ fitness (t) is the standard deviation of the individual fitness in the tth generation, d hamming (t) is the average Hamming distance between individuals in the tth generation, d hamming_threshold is a preset Hamming distance threshold value; Sa4: displaying the navigation path to the patient.

2. The intelligent guidance method to see a doctor according to claim 1, wherein: The S1 specifically comprises collecting patient basic information and dynamic medical visit key information.

3. The intelligent guidance method to see a doctor according to claim 2, wherein: The patient basic information comprises identity information, contact information, basic health information and medical visit preference information; the identity information comprises name, gender, date of birth, ID number and medical insurance card number; the contact information comprises mobile phone number and emergency contact information; the basic health information comprises height, weight, blood type and allergy history; and the medical visit preference information comprises whether the patient is a disabled person, an elderly patient and language preference; The dynamic medical visit key information comprises position information, registration information, medical visit type information, chief complaint and preliminary demand information and special demand information; the position information is the position information of the patient; the registration information comprises registered department, doctor name / number and appointment time period; the medical visit type information comprises initial diagnosis and follow-up visit; the chief complaint and preliminary demand information comprises the purpose of the current medical visit; and the special demand information comprises whether a wheelchair / stretcher is needed, whether previous examination reports are carried, and whether priority treatment is needed.

4. The intelligent guidance method to see a doctor according to claim 1, wherein: In the Sa2, the target of the navigation path generation comprises: Shortest path length: selecting the shortest path from the current position to the destination to reduce the patient's walking distance; Minimum waiting time: selecting the department or examination room with the least waiting time to reduce the patient's waiting time; Lowest department busy degree: selecting the department or examination room with the lowest busy degree to reduce the patient's stay time in the department; Highest priority: for emergency patients, the path is selected in priority to ensure timely medical treatment.

5. The intelligent guidance method to see a doctor according to claim 4, wherein: The expression of the target function is as follows: ； In the formula, d(x) represents the path length, t(x) represents the waiting time, b(x) represents the department busy degree, p(x) represents the priority, and w1, w2, w3 and w4 are weight coefficients.

6. The intelligent guidance method to see a doctor according to claim 1, wherein: The process of the flow guide is that the intelligent medical guide system is synchronized with the medical order system of the hospital in real time, the medical order information of the patient is acquired, and the intelligent medical guide system automatically reminds the patient of the next operation according to the medical order; the process order is optimized by analyzing the medical process of the patient.

7. The intelligent medical guide method of multi-objective optimization according to claim 1, characterized in that: The process of the humanistic care is that the emotional state of the patient is monitored through the behavior data of the patient; the intelligent medical guide system automatically pushes the psychological counseling content according to the emotional state; and the online psychological counseling function is provided, so that the patient can communicate with the psychologist at any time.

8. The intelligent medical guide method of multi-objective optimization according to claim 1, characterized in that: The process of the medical appointment is that the queuing situation of each department and examination room is monitored in real time, and the patient is informed through the intelligent medical guide system; the waiting time of the patient is estimated according to the queuing situation, and the waiting time of the patient is reasonably arranged; for the emergency patient, the intelligent medical guide system automatically adjusts the priority.

9. The intelligent medical guide method of multi-objective optimization according to claim 1, characterized in that: The process of the patient education is that the basic knowledge base of disease, examination, nursing and medication is established; the propaganda and education content is recommended according to the patient's condition and historical record; the question and answer function is provided, and the patient asks questions, and the intelligent medical guide system automatically answers the questions; The process of the record tracking is that the historical medical record of the patient is recorded, including the condition, examination result and treatment plan; the disease progress of the patient is sorted out through data analysis, and the reference for the doctor is provided; According to the disease progress, the intelligent medical guide system automatically reminds the patient of the reexamination and examination matters.

10. A multi-objective optimization intelligent medical seeking guidance system, characterized in that, The system adopts the intelligent medical guide method of multi-objective optimization according to any one of claims 1-9, and the system comprises: A patient information acquisition module for acquiring patient information; A position navigation module for assisting the patient to find the destination; A process guide module: linked with the medical order system, guiding the patient according to the medical order; A humanistic care module: for emotional counseling and psychological comfort of the patient; A medical appointment prompt module: for providing the patient with medical appointment queuing prompt and reasonably arranging the medical appointment process; An education module: for providing propaganda and education for the patient; A record tracking module: for recording the historical medical record of the patient, sorting out the disease progress of the patient through data analysis, providing reference for the doctor, and automatically reminding the patient of the reexamination and examination matters according to the disease progress.

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