A hospital appointment registration assistance method for multiple age groups

Abstract

The present invention discloses a hospital appointment registration assistance method for multiple age groups, which belongs to the field of medical services, including: receiving appointment request information; matching user age information by age group to obtain age group characteristic values; performing correlation analysis to obtain department correlation; dividing the request registration timestamp by time zone to obtain a request time zone sequence; traversing the request time zone sequence, sorting from large to small based on department correlation, and obtaining the user call sequence; sending the user call sequence to the hospital registration management end, the requesting doctor, and the user end. This application solves the technical problem that the hospital appointment registration system in the prior art fails to fully consider the differences in user needs of different age groups, resulting in low accuracy and efficiency of appointment registration and poor user experience, and achieves the technical effect of providing personalized department recommendations and intelligent registration sequence arrangements based on user characteristics, improving the accuracy and efficiency of hospital appointment registration, and improving the user's medical experience.

Description

Technical Field

[0001] The present invention relates to the field of medical services, and in particular to a hospital reservation and registration assistance method for multiple age groups. Background Art

[0002] At present, hospital appointment registration adopts the principle of first come first served, and patients are arranged to register and see a doctor in the order of appointment time. However, the existing hospital appointment registration often adopts unified standards and processes, ignoring the differences in medical needs of patients of different age groups, and failing to fully consider the specific needs of patients of different age groups, resulting in low accuracy and efficiency of appointment registration, and medical resources are not used reasonably. In addition, the existing hospital appointment registration is only based on the department selected by the patient, failing to fully consider the correlation between different patients and departments, reducing the patient's medical experience. Summary of the invention

[0003] This application provides a hospital appointment registration assistance method for multiple age groups, aiming to solve the technical problem that the hospital appointment registration system in the prior art fails to fully consider the differences in the needs of users of different age groups, resulting in low appointment registration accuracy and efficiency and poor user experience.

[0004] The present application discloses a hospital reservation registration assistance method for multiple age groups, comprising: receiving reservation request information, wherein the reservation request information includes user age information, user gender information, requested department information, requested registration timestamp and requested doctor identity information; performing age group matching on the user age information to obtain age group feature values; performing correlation analysis on the requested department information based on the age group feature values ​​and the user gender information to obtain department correlation; performing time zone division on the requested registration timestamp to obtain a requested time zone sequence; traversing the requested time zone sequence, sorting from large to small based on department correlation, to obtain a user call order; sending the user call order to the hospital registration management end, and after confirmation, sending it to the requested doctor based on the requested doctor identity information, and generating registration success information to feed back to the user end.

[0005] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0006] Due to the adoption of receiving appointment request information, which includes user age information, user gender information, requested department information, requested registration timestamp and requested doctor identity information, by collecting the user's detailed appointment information, a data basis is provided for subsequent personalized registration; the user's age information is matched to the age group, the age group characteristic value is obtained, and the users are divided into different age groups according to their age, which is helpful for providing differentiated registration services according to the characteristics of the age group in the future; according to the age group characteristic value and the user's gender information, the requested department information is analyzed for correlation, the department correlation is obtained, and the accuracy of registration sorting is improved; the requested registration timestamp is divided into time zones to obtain the requested time zone sequence, which is helpful for reasonably arranging the order of visits in the same time zone in the subsequent links and improving the registration efficiency; the requested time zone sequence is traversed, Based on the order from largest to smallest department relevance, the user calling order is obtained. In each time zone, the user's department relevance is prioritized to obtain a personalized medical treatment order, taking into account the dual factors of time and demand; the user calling order is sent to the hospital registration management end, and after confirmation, it is sent to the requesting doctor based on the requesting doctor's identity information, and at the same time, the registration success information is generated and fed back to the user end, realizing a technical solution for intelligent and personalized appointment registration, which solves the technical problem that the hospital appointment registration system in the prior art fails to fully consider the differences in user needs of different age groups, resulting in low accuracy and efficiency of appointment registration and poor user experience, and achieves the technical effect of providing personalized department recommendations and intelligent registration order arrangement according to user characteristics, improving the accuracy and efficiency of hospital appointment registration, and improving user medical experience.

[0007] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flowchart of a hospital appointment registration assistance method for multiple age groups is provided for the embodiment of the present application;

[0009] Figure 2 A flow chart of obtaining department relevance in a hospital appointment registration assistance method for multiple age groups is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0010] The overall idea of ​​the technical solution provided by this application is as follows:

[0011] The embodiment of the present application provides a hospital appointment registration assistance method for multiple age groups. First, an appointment request message containing information such as the user's age, gender, requested department, registration time, and doctor is received. Then, age group matching is performed according to the user's age information to obtain age group characteristic values. On this basis, the requested department is analyzed for correlation in combination with the age group characteristic values ​​and the user's gender information to obtain the department correlation degree. At the same time, the registration time is divided into time zones to obtain a requested time zone sequence. Next, within each time zone, users are sorted according to the department correlation degree to obtain a personalized user call number sequence. Afterwards, the user call number sequence is sent to the hospital management end and the doctor end, and the registration success information is fed back to the user end to complete the appointment registration.

[0012] Through the hospital appointment registration assistance method for multiple age groups, the problems of different medical needs of patients of different age groups and insufficient relevance of department recommendations are effectively solved, the accuracy and efficiency of appointment registration are improved, and the user's medical experience is improved.

[0013] After introducing the basic principles of the present application, the non-limiting implementation methods of the present application will be specifically introduced below in conjunction with the drawings in the specification.

[0014] like Figure 1 As shown, the embodiment of the present application provides a hospital appointment registration assistance method for multiple age groups, the method comprising:

[0015] S1: receiving an appointment request message, wherein the appointment request message includes user age information, user gender information, requested department information, requested registration timestamp, and requested doctor identity information.

[0016] Specifically, first, a request receiving module for receiving appointment request information is set. When a user submits an appointment request through a terminal device such as a mobile phone, tablet computer, PC, etc., the request receiving module obtains the information submitted by the user to form an appointment request information. Among them, the appointment request information includes information of multiple dimensions such as user age information, user gender information, requested department information, requested registration timestamp, and requested doctor identity information. This information is actively filled in by the user when submitting an appointment request, and can also be automatically generated based on the user's historical medical records or registration information. The user's age information represents the age data of the user requesting an appointment; the user's gender information represents the gender of the user requesting an appointment; the requested department information represents the hospital department that the user expects to make an appointment with; the requested registration timestamp represents the time when the user expects to see the doctor; and the requested doctor identity information represents the doctor that the user expects to make an appointment with.

[0017] By receiving appointment request information, we can realize the reception of personalized appointment registration requests submitted by different users, laying the foundation for the subsequent intelligent and precise hospital appointment registration processing.

[0018] S2: Perform age group matching on the user's age information to obtain age group feature values.

[0019] Specifically, after obtaining the reservation request information containing the user's age information, the user's age information is matched with the preset age group to obtain the age group characteristic value that represents the user's age characteristics. The preset age group is divided according to the actual situation and medical experience of the hospital. For example, users of different age groups are divided into multiple age groups such as infants, teenagers, young and middle-aged people, middle-aged and elderly people, and the elderly, and each age group corresponds to a specific age range.

[0020] After obtaining the user age information of a certain user, the specific age value in the user age information is compared with the age interval of the preset age group to determine which age group the user belongs to. Then, the corresponding age group characteristic value is generated according to the determination result. For example, the age group characteristic value is represented by a numerical value, and different numerical values ​​correspond to different age groups.

[0021] By obtaining age-group characteristic values, the user's age information is converted into digital features suitable for computer processing, which is used to analyze the preferences of users of different age groups for hospital departments, thereby providing users with personalized registration arrangements.

[0022] S3: Perform a correlation analysis on the requested department information according to the age group characteristic value and the user gender information to obtain a department correlation degree.

[0023] Specifically, first, according to the requested department information submitted by the user, the records related to the department are searched in the historical registration data, including the age and gender characteristics of users who have been treated in the department in the past. Next, the frequency information of users of different age groups and genders who have been treated in the department is extracted from these historical records, that is, the number of times users of each age group and male and female users have been treated in the department is counted, and the proportion of each of the total number of visits to the department is calculated. Then, the age group characteristic value and gender information of the current user are compared with the above statistical results to find the proportion of the frequency of visits corresponding to the age group and gender of the current user. The two proportions are added to obtain a value indicating the degree of matching between the current user and the department as the department association degree. Among them, the value range of the department association degree is 0 to 1. The higher the value, the more consistent the age and gender characteristics of the current user are with the characteristics of the historical patients in the department, which means that the department may be more suitable for the current user to go to the department for treatment.

[0024] By obtaining the correlation value between the requested department and the current user, a basis is provided for the subsequent steps of registration sorting.

[0025] S4: Divide the request registration timestamp into time zones to obtain a request time zone sequence.

[0026] Specifically, first, according to the actual working hours and registration arrangements of the hospital, 24 hours a day is divided into several time zones. Each time zone corresponds to a specific time interval, for example, 8 am to 10 am is divided into one time zone, 10 am to 12 pm can be divided into another time zone, and so on. Among them, the hospital can flexibly adjust the time zone division scheme according to its own scheduling rules, peak visit periods and other factors. For example, for peak hours in the morning and evening, a smaller time zone interval is used to arrange registration more finely; for time periods with relatively few visits, a larger time zone interval can be used to simplify time zone management. After determining the time zone division scheme, the registration timestamp in the user request is compared with the time interval of each time zone to find the time zone corresponding to the timestamp, and generate a time zone identifier as the time zone attribute of the request. Next, the time zone attributes of all requests are arranged in sequence according to the submission time of the requests to form a request time zone sequence.

[0027] Through the above processing, the classification and abstract representation of the user's requested consultation time can be achieved. Mapping the specific time point into a discrete time zone identifier is conducive to the subsequent batch registration management.

[0028] S5: Traverse the requested time zone sequence, sort from large to small based on the department relevance, and obtain the user calling order.

[0029] Specifically, the request time zone sequence represents the time distribution of user registration requests, and the department relevance reflects the degree of matching between the requested department and the user's characteristics. The request time zone sequence and department relevance are used to generate the final sorting result for registration requests in each time zone, and the user call order in each time zone is obtained.

[0030] First, traverse each time zone in the request time zone sequence. For the currently traversed time zone, collect all the registration requests belonging to the time zone and extract the corresponding department relevance. Then, sort the registration requests in the time zone in descending order according to the numerical value of the department relevance. The higher the department relevance, the higher the matching degree between the requested department and the user's age and gender characteristics, and should be given a higher priority, so it is higher in the sorting. After sorting, the user call number order in the current time zone is obtained, which determines the order in which the user registration requests in the time zone are processed. The requests in the front will get the number source first and arrange the medical treatment. Next, continue to traverse the next time zone in the request time zone sequence, and repeat the above sorting process until all time zones in the sequence have been processed. Finally, the user call number order in each time zone is obtained. These orders are summarized together to form the complete sorting result of the entire registration request pool.

[0031] By combining the two factors of time dimension and user characteristics and sorting by time zone, we can maximize the matching optimization between registration requests and hospital departments while meeting time constraints, thereby improving the efficiency of medical resource utilization and user satisfaction.

[0032] S6: The user's calling order is sent to the hospital registration management terminal, and after confirmation, it is sent to the requesting doctor based on the identity information of the requesting doctor, and at the same time, the registration success information is generated and fed back to the user terminal.

[0033] Specifically, after obtaining the user calling number sequence, the user calling number sequence is sent to the relevant parties to complete the appointment registration.

[0034] First, the generated user call sequence is sent to the hospital registration management terminal. Hospital managers can view and verify the sorting results through the hospital registration management terminal interface and handle abnormal situations. After the hospital manager confirms that the user call sequence is correct, the appointment request of each user is sent to the corresponding doctor according to the identity information of the requested doctor. The doctor can view the appointment status of the day or the future on his work platform. At the same time, according to the user call sequence, the user terminal of each successful appointment user is sent feedback information of successful registration, including the user's queue number, expected consultation time, consultation location, precautions and other details, so that the user can prepare for the consultation. Among them, the feedback information is sent to the user through SMS, WeChat, APP push and other methods to ensure the timeliness and arrival rate of the information. In addition, users can also check their appointment status and queue progress at any time through the user terminal to understand the latest situation.

[0035] By fully publishing and synchronizing appointment results to hospitals, doctors and patients, delays and errors in information transmission can be reduced, the coordination and consistency of the appointment process can be improved, and information symmetry and consistent actions among all parties can be ensured, thereby improving patients' medical experience.

[0036] Furthermore, the embodiment of the present application also includes:

[0037] According to the requested department information, an age group division function is obtained, wherein the age group division function includes a first age interval number to an Mth age interval number; the user age information is traversed, distributed to the first age interval number to the Mth age interval number, to obtain the age group characteristic value.

[0038] In a feasible implementation, when obtaining the age layer characteristic value, first, according to the requested department information submitted by the user, a preset age layer division function is obtained. The age layer division function defines a set of continuous age intervals, each interval corresponds to an age layer, and these age layers are identified by numbering, from the first age interval number to the Mth age interval number, where M is the total number of age layers. Different request departments correspond to different age layer division schemes. For example, the age layer division of pediatrics is more refined, and the age layer division of geriatrics may have a wider span.

[0039] After obtaining the age group division function, the user's actual age information is processed. The age information submitted by the user is traversed, and it is compared with each age interval defined in the age group division function to find out the interval to which the age belongs. Then, the number of the interval is extracted as the age group characteristic value of the user. For example, suppose the age group division function divides 0-10 years old into the first age group, 10-20 years old into the second age group, and so on. If the user is 25 years old, it falls within the interval of the third age group (20-30 years old), so the user's age group characteristic value is 3.

[0040] By obtaining the age-level characteristic values, the user's original age information is normalized and discretized, and the continuous age values ​​are mapped to the age-level categories, which simplifies the subsequent analysis and calculation, and also protects the user's privacy to a certain extent. Different departments use different division granularities and boundaries to adapt to the age distribution characteristics of their patient groups and improve the pertinence and effectiveness of subsequent registration matching.

[0041] Furthermore, the embodiment of the present application also includes:

[0042] According to the requested department information, several evaluation nodes for information isolation are activated, and several initial age-layer division functions are received; interval comprehensive statistics are performed on the several initial age-layer division functions to obtain the first division age node up to the Nth division age node; neighborhood hierarchical clustering fusion is performed based on the first division age node up to the Nth division age node to generate the age-layer division function.

[0043] In a preferred embodiment, in order to generate corresponding age group division functions for different departments. First, according to the requested department information, several preset evaluation nodes are activated. Among them, these evaluation nodes correspond to different age group division schemes, maintain an initial age group division function, and represent a possible age group boundary division method. These evaluation nodes are independent of each other and isolate information from each other. Among them, different evaluation nodes give differentiated age group division suggestions based on different prior knowledge, statistical laws or expert experience. By activating multiple evaluation nodes in parallel, it is possible to collect division opinions extensively and avoid the limitations of a single division standard.

[0044] After obtaining the initial age division function of each evaluation node, these initial age division functions are comprehensively analyzed and processed. Specifically, the boundaries of the age intervals in the initial division functions of each age layer are summarized and counted, and the boundary points with higher frequency and greater overlap are extracted to form a set of candidate age division nodes. These division nodes are numbered in order from small to large in age, and an ordered sequence from the first division age node to the Nth division age node is obtained. By analyzing the intersection and union of different schemes, the key turning points of the age distribution can be identified, reflecting the differences in medical needs of different age groups, thereby extracting division boundaries with strong consensus from multiple initial age division functions, laying the foundation for the generation of age division functions.

[0045] After obtaining the first age-division node to the Nth age-division node, the neighboring hierarchical clustering method is used to gradually merge the adjacent age-division nodes. The age span between adjacent nodes is calculated. If the span is small, the adjacent nodes are merged into one node; if the span is large, the original segmentation is retained. Through bottom-up hierarchical clustering, the number and distribution of division nodes are gradually simplified to obtain a hierarchical age interval division structure, and an age layer division function is generated, which includes the starting boundaries and numbers of each age interval finally determined.

[0046] By selectively merging and refining multiple initial age-stratification functions, a generated age-stratification function that takes into account both commonalities and characteristics is obtained. This function is used as the age-stratification standard to better reflect the age distribution pattern of patient groups in different departments.

[0047] Furthermore, the embodiment of the present application also includes:

[0048] From the first age division node to the Nth age division node, obtain the kth age division node and the k+1th age division node which are neighbors of each other, and calculate the age deviation; when the age deviation is greater than or equal to the age deviation threshold, calculate the aggregation number of the kth age division node and the aggregation number of the k+1th age division node, and calculate the aggregation sum value; compare the aggregation number of the kth age division node and the aggregation number of the k+1th age division node with the aggregation sum value respectively to obtain the weight distribution result; calculate the weighted mean of the kth age division node and the k+1th age division node according to the weight distribution result to obtain the age node update result; when the first age division node to the Nth age division node are completely traversed, construct the age layer division function according to the age node update result.

[0049] In a preferred embodiment, when performing neighborhood hierarchical clustering fusion according to the first age-dividing node to the Nth age-dividing node, first, starting from the first age-dividing node, scan to the Nth age-dividing node in sequence to find each pair of adjacent nodes. For the kth age-dividing node and the k+1th age-dividing node currently traversed, calculate the age difference between adjacent nodes to obtain an age deviation value, which is used to measure the distance between the two nodes in the age dimension. After obtaining the age deviation value, determine whether the deviation value exceeds a preset age deviation threshold. If the age deviation value is greater than or equal to the age deviation threshold, it means that the age span between the two nodes is large and represents different age groups. At this time, calculate the aggregation quantity of the kth age-dividing node and the k+1th age-dividing node, that is, the number of samples or the number of people in the age interval represented by each of the two nodes. Then, add the two aggregation quantities to obtain an aggregation sum value, which represents the overall scale covered by the two nodes.

[0050] After obtaining the number of aggregations and the aggregated sum, the proportion of the number of aggregations of the k-th age-dividing node and the number of aggregations of the k+1-th age-dividing node to the aggregated sum is calculated respectively to obtain the weight distribution result, which reflects the relative importance or contribution of the two nodes in the merged new node. Next, using the weight distribution result, the age values ​​of the k-th age-dividing node and the k+1-th age-dividing node are weighted averaged to obtain the age node update result, which represents the age value of the merged new node and can better represent the overall characteristics of the merged age group. Subsequently, the next pair of adjacent nodes is traversed and the above calculation process is repeated. When all adjacent node pairs from the first age-dividing node to the N-th age-dividing node are processed, all the previously obtained age node update results are summarized and arranged in order from small to large age to form an orderly age layer division scheme. Each updated age node corresponds to the starting boundary of an age interval, and the interval between two adjacent nodes constitutes a complete age layer. By numbering these age layers, a complete age layer division function is obtained.

[0051] Through bottom-up hierarchical clustering fusion, the age-layer division granularity and boundaries are adaptively adjusted according to the actual characteristics of age distribution. By introducing the comparison of age deviation thresholds, overly detailed or overly extensive division results can be effectively avoided. At the same time, by calculating the aggregation number and weight of adjacent nodes, the sample distribution and importance of different age groups can be fully considered when merging nodes, so that the generated age-layer division function can more accurately and reasonably reflect the actual population characteristics.

[0052] Furthermore, the embodiment of the present application also includes:

[0053] When the kth division age node and the k+1th division age node include the first division age node, the age node update result is generated based on the first division age node; when the kth division age node and the k+1th division age node include the Nth division age node, the age node update result is generated based on the Nth division age node.

[0054] In a preferred embodiment, when calculating the aggregated number of adjacent k-th age-dividing nodes and k+1-th age-dividing nodes, if the currently processed node pair includes the first age-dividing node, that is, k=1. In this case, the first age-dividing node has no predecessor node, and the aggregated number cannot be calculated and compared with the previous node. In order to handle this boundary case, the first age-dividing node is directly output as the age node update result. If the currently processed node pair includes the N-th age-dividing node, that is, k=N-1. In this case, the N-th age-dividing node has no successor node, and the aggregated number cannot be calculated and compared with the next node, and the N-th age-dividing node is directly output as the age node update result.

[0055] By dealing with the boundary conditions of age division, calculation anomalies or logical errors caused by the lack of predecessor or successor nodes can be avoided, and the continuity and completeness of the age division function can be ensured.

[0056] Further, such as Figure 2 As shown, the embodiment of the present application also includes:

[0057] Obtain the preset time zone registration record information of the requested department information, wherein the preset time zone registration record information includes age group record characteristic values ​​and recorded user gender; based on the age group record characteristic values ​​and the recorded user gender, calculate the registration frequency characteristics of the age group characteristic values ​​and the user gender information in the preset time zone registration record information; calculate the ratio of the registration frequency characteristics to the sum of the registration frequencies of the preset time zone registration record information, and set it as the department association degree.

[0058] In a feasible implementation, when obtaining the department relevance, first, obtain the preset time zone registration record information related to the requested department information. These record information contains historical registration data within a specific time period of the department, and each record includes the age group record characteristic value and gender information of the patient. By analyzing these historical data, the distribution of users of different age groups and genders visiting the department can be understood, providing a basis for subsequent correlation calculations. After obtaining the preset time zone registration record information, these record information are statistically analyzed. Specifically, based on the age group record characteristic value and the recorded user gender, the number of registration records with the same age group and gender as the current user in the preset time zone is calculated as the registration frequency feature of the user in the department, reflecting the popularity and activity of people with similar characteristics to the current user in visiting the department, and serving as an important indicator to measure the degree of matching between the user and the department.

[0059] After obtaining the registration frequency characteristics, calculate the department relevance. Specifically, divide the registration frequency characteristics by the total registration frequency of the department in the preset time zone to obtain a normalized ratio as the department relevance. Among them, the value range of the department relevance is 0 to 1. The higher the value, the more consistent the current user's age and gender characteristics are with the historical distribution of the department's patients, which means that the current user's choice of this department for treatment is more reasonable and necessary.

[0060] By quantifying the department correlation index, comprehensively considering the user's age and gender characteristics, and correlating them with the department's historical medical data, we can obtain an evaluation result that reflects the degree of match between the user and the department, providing an important reference for subsequent registration sorting and scheduling, and helping hospitals provide registration services to users more intelligently and accurately.

[0061] Furthermore, the embodiment of the present application also includes:

[0062] Obtain a time zone division step; perform time zone division according to the request registration timestamp based on the time zone division step to obtain a time zone division result; arrange the time zone division results in time sequence to generate the request time zone sequence.

[0063] In a feasible implementation, in order to divide the registration request timestamp into time zones, a request time zone sequence is obtained. First, a preset time zone division step is obtained, which represents the time span of each time zone when the registration timestamp is divided into time zones. For example, if the time zone division step is set to 1 hour, then each time zone represents a time range of one hour. Among them, the selection of the time zone division step is adjusted according to the actual work arrangements and medical treatment rules of the hospital. At the same time, the time zone division step is not fixed, and the time zone division step can be dynamically adjusted according to different time periods and different departments to adapt to the actual registration needs and resource allocation. For example, during the peak period of medical treatment, a smaller step value is selected to divide the time zone more finely and improve the flexibility of registration scheduling; during the trough period of medical treatment, a larger step value is selected to reduce the number of time zones and reduce the complexity of calculation and management.

[0064] After obtaining the time zone division step, the request registration timestamp is divided into time zones based on the step. The registration timestamps are grouped according to the step size, and each group corresponds to a time zone, so that the continuous timestamps are converted into discrete time zone identifiers to obtain the time zone division results, which is convenient for subsequent scheduling. After the time zone division is completed, the time zone division results are further processed. The divided time zone identifiers are arranged in chronological order to generate an ordered request time zone sequence. Each item in the sequence represents a specific time zone, and multiple requests may be divided into the same time zone. By generating a request time zone sequence, the distribution and changes of registration requests in the time dimension can be clearly displayed, providing important decision-making basis for subsequent registration scheduling.

[0065] By introducing the time zone division step, the continuous timestamps can be discretized and the registration requests can be classified and organized according to time characteristics. This not only simplifies the calculation and comparison in the time dimension and improves efficiency, but also can dynamically adapt to the registration needs in different scenarios by adjusting the step size, which is very flexible.

[0066] Furthermore, the time zone division step is less than or equal to 24 hours.

[0067] In a feasible implementation, the time zone division step should be less than or equal to 24 hours, which means that when the registration timestamp is divided into time zones, the time span of each time zone cannot exceed one day, so as to ensure that the granularity of the time zone division is not too coarse, so as not to affect the precision and flexibility of registration scheduling. If the time zone division step is too large, such as a few days or even a few weeks, then each time zone will contain a large number of registration requests, which will not only increase the complexity of registration management, but also cause registration requests in certain time periods to be too concentrated, while other time periods are relatively idle, resulting in a waste of medical resources and prolonged patient waiting time.

[0068] By limiting the time zone division step to within 24 hours, the granularity of each time zone will not exceed one day, which is more consistent with the daily work rhythm of the hospital and the patient's treatment habits. On this basis, the division of time zones can be further refined according to actual needs, such as dividing by morning, afternoon, evening and other time periods, or dividing by every few hours to meet the characteristics of different departments and diseases.

[0069] In summary, the hospital appointment registration assistance method for multiple age groups provided by the embodiment of the present application has the following technical effects:

[0070] Receive the reservation request information, which includes the user's age information, user's gender information, requested department information, requested registration timestamp and requested doctor's identity information, providing the necessary data basis for subsequent personalized registration. Perform age-level matching on the user's age information to obtain the age-level feature value, laying the foundation for providing differentiated reservation registration services in the future. According to the age-level feature value and user's gender information, perform correlation analysis on the requested department information to obtain the department's correlation. Perform time zone division on the requested registration timestamp to obtain the requested time zone sequence, providing a time dimension distinction standard for the sorting and calling of users in the same time zone. Traverse the requested time zone sequence, sort from large to small based on the department's correlation, obtain the user's calling order, considering both the user's demand for the department and the order of registration time, and improving the rationality of the sorting. Send the user's calling order to the hospital's registration management end, and after confirmation, send it to the requesting doctor based on the requesting doctor's identity information, and generate registration success information to feedback to the user end to complete the reservation registration, improve the accuracy and efficiency of the hospital's reservation registration, and improve the user's medical experience.

[0071] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0072] Furthermore, the first or second mentioned above may not only represent an order relationship, but may also represent a specific concept, and / or refer to multiple elements that can be selected individually or in full. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these changes and variations.

Claims

1. A hospital appointment registration assistance method for multiple age groups, characterized in that: include: Receiving an appointment request message, wherein the appointment request message includes user age information, user gender information, requested department information, requested registration timestamp, and requested doctor identity information; Performing age group matching on the user's age information to obtain age group feature values; According to the age group characteristic value and the user gender information, a correlation analysis is performed on the requested department information to obtain a department correlation degree; Dividing the request registration timestamp into time zones to obtain a request time zone sequence; Traversing the requested time zone sequence, sorting the departments from large to small based on their relevance, and obtaining the user calling order; The order of the user's calling number is sent to the hospital registration management terminal, and after confirmation, it is sent to the requesting doctor based on the identity information of the requesting doctor, and at the same time, a registration success message is generated and fed back to the user terminal; Performing age group matching on the user age information to obtain age group feature values ​​includes: According to the requested department information, an age group division function is obtained, wherein the age group division function includes a first age interval number to an Mth age interval number; Traversing the user age information, distributing to the first age interval number up to the Mth age interval number, and obtaining the age layer characteristic value; According to the age group characteristic value and the user gender information, a correlation analysis is performed on the requested department information to obtain a department correlation degree, including: Obtaining the preset time zone registration record information of the requested department information, wherein the preset time zone registration record information includes an age group record feature value and a record user gender; Based on the age group record characteristic value and the recorded user gender, the registration frequency characteristics of the age group characteristic value and the user gender information in the registration record information in the preset time zone are counted; Calculate the ratio of the registration frequency feature to the total registration frequency of the registration record information in the preset time zone, and set it as the department association degree; According to the requested department information, an age group division function is obtained, including: According to the requested department information, several evaluation nodes for information isolation are activated, and several initial age-group division functions are received; Performing interval comprehensive statistics on the initial division functions of the plurality of age layers to obtain the first division age node to the Nth division age node; Performing neighborhood hierarchical clustering fusion according to the first age division node to the Nth age division node to generate the age layer division function; Performing neighborhood hierarchical clustering fusion according to the first age division node to the Nth age division node to generate the age layer division function includes: From the first age division node to the Nth age division node, obtain the kth age division node and the k+1th age division node which are neighbors of each other, and calculate the age deviation; When the age deviation is greater than or equal to the age deviation threshold, the aggregation number of the k-th division age node and the aggregation number of the k+1-th division age node are calculated, and the aggregation sum value is calculated; Compare the k-th age node aggregation number and the k+1-th age node aggregation number with the aggregation sum value to obtain a weight distribution result; Calculate the weighted mean of the k-th divided age node and the k+1-th divided age node according to the weight distribution result to obtain an age node update result; When the first age division node to the Nth age division node are completely traversed, the age layer division function is constructed according to the age node update result; When the age deviation is greater than or equal to the age deviation threshold, the aggregate number of the k-th division age node and the aggregate number of the k+1-th division age node are calculated, and the aggregate sum value is calculated, including: When the kth division age node and the k+1th division age node include the first division age node, generating the age node update result based on the first division age node; When the kth divided age node and the k+1th divided age node include the Nth divided age node, the age node update result is generated based on the Nth divided age node.

2. The method according to claim 1, characterized in that The request registration timestamp is divided into time zones to obtain a request time zone sequence, including: Get the time zone division step; Perform time zone division based on the time zone division step and the request registration timestamp to obtain a time zone division result; Arrange the time zone division results in time sequence to generate the requested time zone sequence.

3. The method according to claim 2, characterized in that The time zone division step is less than or equal to 24 hours.

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