Methods and systems for monitoring and mediating eye health.

Abstract

The present invention discloses an eye health monitoring and mediation method and system, which includes acquiring a patient's axial length data using a pre-configured axial length detection module, generating an estimated prescription for the patient based on the axial length data, and storing the axial length data and estimated prescription in a server; in response to the initial storage of axial length data, the server constructs a personal health database for the patient based on the axial length data and estimated prescription, and transmits the estimated prescription to the user terminal; in response to subsequent acquisitions of axial length data, the server generates an axial length change record based on the multiple stored axial length data, stores the axial length change record in the personal health database, and if the axial length change record is greater than a pre-configured threshold, the server sends an alarm message to the user terminal. The present invention establishes a mechanism for tracking a patient's eye health data over the long term by matching medical institutions with health activity locations, effectively improving the benefits of long-term tracking of eye health, and enabling the utilization of available resources such as optometrists and opticians.

Description

Technical Field

[0001] The present invention relates to the technical field of human eye health monitoring, and particularly relates to an eye health monitoring and mediation method, and a system.

Background Art

[0002] In the prior art, the cost of early detection and regular follow-up of myopia is high. The main reason is that patients with poor visual acuity test results, especially minors, need to undergo continuous and multiple examinations at ophthalmic hospitals or clinics, but the number of specialized ophthalmic hospitals and clinics is limited. Taking the data of first-year primary school students in City A as an example, about 20 - 25% of minors become myopic, and by the end of the third year of high school, about 80 - 85% are myopic. Therefore, with the existing number of specialized ophthalmic hospitals and clinics, it is impossible to establish sufficient long-term and regular detection capabilities.

[0003] In addition, in the case of minors, the problem of pseudo-myopia often occurs due to excessive regulation of the ciliary muscle, and it is necessary to use a mydriatic agent to dilate the pupil and then perform an eye examination to determine the refractive power, which takes a very long time (it is necessary to wait for 1 hour to perform an eye examination after dilation). Also, when instilling the mydriatic agent into the eyes, obvious stabbing pain occurs, so the willingness of minors to cooperate decreases, and it is difficult to continuously conduct long-term follow-up.

[0004] On the other hand, continuing with City A as an example, there are currently about 5,000 optometrist clinics and opticians throughout the city, distributed across various areas. These optometrist clinics and opticians primarily sell eyeglass frames and do not offer services related to eye health. As a result, these clinics and opticians have a significant amount of idle time, leading to increased operating costs. Furthermore, professional optometrists are unable to utilize their expertise to provide effective eye health services and assess patients' current conditions and future health needs. Therefore, while optometrist clinics and opticians desire collaboration with specialized ophthalmological medical institutions, there is currently no systematic solution. [Overview of the project]

[0005] In view of the shortcomings of the prior art described above, the present invention proposes a method and system for monitoring and mediating eye health to solve the above technical problems.

[0006] According to the first aspect of this application, (S1) Using axial length detection modules installed at each medical institution and health activity location, patient axial length data is acquired, estimated frequency is generated based on the axial length data, and the axial length data and estimated frequency are stored on a server. (S2) Upon initial storage of axial length data, the server constructs the patient's personal health database based on the axial length data and estimated frequency, and transmits the estimated frequency to the user terminal. Upon subsequent acquisition of axial length data, the server generates an axial length change record based on the multiple stored axial length data, and stores the axial length change record in the personal health database. If the axial length change record exceeds a preset threshold, the server sends an alert message to the user terminal and either matches and schedules a follow-up appointment or provides health consultation. We propose eye health monitoring and mediation methods, including those mentioned above.

[0007] By tracking patient data over the long term on a server and using it as medical reference, if a patient needs eyeglasses after an outpatient visit, medical staff can issue a prescription and refer them to an appropriate health activity center.

[0008] Preferably, the method is (S3) When the user terminal receives a signal indicating that the patient requires a follow-up visit or health activity, the server matches the patient with a medical institution and a location for health activity for the follow-up visit. (S4) Medical institutions and health activity locations store patients' follow-up visit and health activity data on a server, and the server generates follow-up visit and health activity records based on the follow-up visit and health activity data, and stores them in the personal health database along with the follow-up visit and health activity data. It also includes.

[0009] If a patient requires further follow-up appointments or health activities, the server matches the patient with appropriate medical institutions and health activity locations, and either matches and schedules follow-up appointments or health activities, or provides health consultations. The data on these follow-up appointments and health activities is uploaded to the server, and a record of these activities is generated. By matching health activity locations with medical institutions for follow-up appointments, it is possible to link specialized medical institutions with non-specialized health activity locations, thereby preventing non-specialized health activity locations such as opticians and optometrists from having excessive downtime, and to better support the tracking of patients' eye health status.

[0010] Preferably, the estimated frequency in step S1 is obtained by matching based on a preset axial length measurement conversion library, and the data in the preset axial length measurement conversion library is obtained by learning using a multiple regression analysis model.

[0011] More preferably, step S1 further includes obtaining the patient's age, corneal horizontal curvature, corneal vertical curvature, anterior chamber measurement depth, and lens thickness.

[0012] More preferably, the procedure for constructing a multiple regression analysis model is: (S101) Input parameters that make the frequency predictable into the model, and construct the model using the least squares method. In the JPEG2026519993000002.jpg15170(S102) model, a basic model test is performed on the squared difference, and then the parameters are narrowed down using stepwise regression. Based on the interpretability of the parameters and the reduction in the number of parameters, the parameters are selected and the model is constructed. (S103) Using the variance expansion coefficient to determine whether or not the model is collinear, Includes.

[0013] Preferably, the method is

[0014] (S5) The server further includes calculating eye development indices based on axial length data and axial length change records, as well as calculating health behavior scores based on estimated prescriptions, and storing the health behavior scores and eye development indices in a personal health database. By integrating health data such as axial length data, axial length change records, and estimated prescriptions and calculating them as the patient's eye development indices and health behavior scores, patients can more intuitively check their own health status. At the same time, the patient's health behavior scores can be synchronized with a health database of a group or family of relatives, friends, or specific individuals, so that the patient's relatives, friends, or specific individuals can help track the patient's vision status and establish a mutual health tracking mechanism.

[0015] More preferably, the method for calculating the eye development index includes comparing axial length data and axial length change records with a big data nomogram to determine the patient's eye development index, which is a percentile of the patient's axial length for the same age group.

[0016] More preferably, the method for calculating health behavior scores includes increasing or decreasing the score based on changes in estimated frequencies, increasing the score when the hyperopic refractive power increases or the myopic refractive power decreases, and decreasing the score when the hyperopic refractive power decreases or the myopic refractive power increases.

[0017] More preferably, step S5 further includes establishing a patient's eye health change and tracking model based on axial length data, axial length change records, follow-up data, and health activity data. Establishing eye health change and tracking models for various patients further realizes the establishment of medical big data on the eye health of human children.

[0018] According to the second aspect of this application, An axial length detection module used to acquire patient axial length data, installed in medical institutions and health activity locations, comprising at least one axial length detection module including at least one axial length detection device including a non-contact optical axial length measuring instrument, A server that includes a member module for inputting and storing axial length data and building a patient's personal health database based on the axial length data, and a matching module for matching patients with medical institutions and health activity locations. A user terminal that communicates with a server and is used by patients to receive alarm messages from the server and retrieve data from a personal health database, and in response to the user terminal receiving a signal that the patient needs a follow-up visit or health activity, the matching module includes a user terminal that matches the patient with a medical institution and a health activity location. We propose an eye health monitoring and mediation system.

[0019] Axial length detection modules installed at each medical institution and health activity location acquire patients' axial length data, which is then entered into a member module on the server by the relevant staff. The member module builds a patient-specific personal health database based on the axial length data, and also generates axial length change records based on the patient's multiple recorded axial length data. If the axial length change record exceeds a preset threshold, the matching module automatically sends an alert message to the user terminal, matching and booking a medical institution or providing relevant consultation to the patient. At the same time, the patient's long-term tracking data of axial length can be used as medical reference, and if the patient needs eyeglasses after an outpatient visit, medical staff can issue a prescription for eyeglasses and refer them to an appropriate health activity location. Simultaneously, by acquiring the patient's axial length data using a non-contact optical axial length measuring device, patient discomfort during the detection process is avoided. [Effects of the Invention]

[0020] Compared to the prior art, the beneficial effects of this invention are as follows:

[0021] In the eye health monitoring and mediation method and system proposed in this application, a pre-configured axial length detection module at medical institutions and health activity locations (e.g., orthoptics clinics, opticians) acquires patients' axial length data and stores it on a server. The server's member module establishes a personal health database dedicated to each patient, and different medical institutions (specialized ophthalmology hospitals, clinics) and health activity locations (e.g., orthoptics clinics, opticians) can synchronize and acquire data from the patient's personal health database using the member module. At the same time, orthoptics clinics and opticians, being numerous and widely distributed, can conveniently support regular and long-term axial length measurements for patients, thus avoiding excessive idle time for non-specialized health activity locations such as opticians and optometrists. Simultaneously, the axial length detection module is equipped with a preset axial length measurement conversion library, and by matching the patient's axial length data with this library, a more accurate estimated power can be obtained. If a patient's axial length change record is excessive, the matching module automatically issues an alert message, matches and books an appointment with a medical institution for the patient, or provides relevant consultation. The long-term tracking data of the patient's axial length can also be used as medical reference. If the patient needs eyeglasses after an outpatient visit, medical staff can issue a prescription for eyeglasses and refer them to an appropriate health activity center.

[0022] Patient follow-up visit data and health activity data are stored in a synchronized personal health database, making it convenient for staff at the next medical institution or health activity location to retrieve the patient's historical health data. This invention, in a modular form, links medical institutions (specialized ophthalmology hospitals, clinics), health activity locations (orthoptics clinics, opticians, etc.), related staff, and patients. By combining this with the patient's eye health data provided by the server, ophthalmologists can query prescriptions as needed, such as to make eyeglasses, and the server can match them with an appropriate health activity location (orthoptics clinic, optician, etc.), effectively utilizing the available resources of existing orthoptics clinics and opticians.

Brief Description of the Drawings

[0023] The drawings are included to further understand the embodiments, and the drawings are incorporated herein and form a part of this specification. The drawings illustrate the embodiments and are used in conjunction with the description to interpret the principles of the present invention. Other embodiments and many of the expected advantages of the embodiments will be readily recognized as they will be better understood by referring to the following detailed description. Other features, objects, and advantages of the present application will become more apparent by referring to the detailed description of the non-limiting embodiments with reference to the accompanying drawings. [Figure 1] It is a flowchart of a method for eye health monitoring and mediation according to an embodiment of the present invention. [Figure 2] It is a schematic diagram of a multiple regression analysis model according to an embodiment of the present invention. [Figure 3] It is a system configuration diagram of an eye health monitoring and mediation system according to an embodiment of the present invention. [Figure 4] It is a flowchart of a patient entering an eye health monitoring and mediation system according to an embodiment of the present invention.

Modes for Carrying Out the Invention

[0024] Hereinafter, the present application will be described in more detail with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are merely for interpreting the related invention and do not limit the present invention. Also, for the convenience of description, only the parts related to such an invention are shown in the drawings.

[0025] Unless there is a contradiction, the embodiments in the present application and the features in the embodiments can be combined with each other. Hereinafter, the present application will be described in detail in conjunction with the embodiments while referring to the drawings.

[0026] According to a first aspect of the present application, a method for eye health monitoring and mediation is proposed. FIG. 1 shows a flowchart of a method for eye health monitoring and mediation according to an embodiment of the present invention. As shown in the figure, this method (S1) Using axial length detection modules installed at each medical institution and health activity location, patient axial length data is acquired, estimated frequency is generated based on the axial length data, and the axial length data and estimated frequency are stored on a server. (S2) Upon initial storage of axial length data, the server constructs the patient's personal health database based on the axial length data and estimated frequency, and the server transmits the estimated frequency to the user terminal. Upon obtaining axial length data for the second time or later, the server generates an axial length change record based on the multiple stored axial length data, stores the axial length change record in the personal health database, and, if the axial length change record is greater than a preset threshold, the server sends an alert message to the user terminal and matches and schedules follow-up appointments / health activities or provides health consultations. The server of this application can match and book appointments with medical institutions or provide related consultations, and at the same time, it can use long-term tracking data of the patient's axial length as medical reference. If the patient needs eyeglasses after an outpatient visit, medical staff can issue a prescription for eyeglasses and refer them to an appropriate health activity location.

[0027] In this application, there are two methods for setting a threshold. The first method is triggered when the change in the patient's axial length data over the years exceeds 10% of the original nomogram. For example, if the axial length data was originally at the 50th percentile and reached the 60th percentile within one year after several measurements, the threshold alarm is triggered. The second method is also triggered when, after several measurements of the patient's axial length, it is found that the change in the patient's axial length exceeds the physiological range of change expected for that age.

[0028] This method acquires real-time axial length data from a patient using a pre-configured axial length detection module and matches it with an estimated frequency corresponding to the patient using a preset axial length conversion library. When a patient undergoes detection using the axial length detection module for the first time, the server builds a patient-specific personal health database based on the axial length data and uses it to store subsequent health data of the patient (including, but not limited to, axial length data, axial length change records, health activity data, health activity records, follow-up visit data, follow-up visit records, eye development indicators, health behavior scores, etc.). When a patient undergoes detection using the axial length detection module for the second time or later, the server generates axial length change records based on the axial length data that has been stored multiple times. If a patient's axial length data changes beyond a threshold, the server automatically sends an alert message to the user terminal, promptly urging the patient to seek further medical attention. The server also matches and schedules appointments with medical institutions or provides relevant consultations. Simultaneously, the long-term tracking data of the patient's axial length can be used as medical reference. If the patient requires eyeglasses after an outpatient visit, medical staff can issue a prescription and refer them to an appropriate health activity center. By providing reference tracking data, this system connects specialized medical institutions (specialized ophthalmology hospitals, clinics, etc.) and health activity centers (orthoptics clinics, opticians, etc.), making full use of available resources at health activity centers and enabling better long-term tracking of patients' eye health.

[0029] In a specific embodiment, the method further includes: (S3) When the user terminal receives a signal indicating that the patient requires a follow-up visit or health activity, the server matches the patient with a medical institution and a location for health activity for the follow-up visit. (S4) The medical institution / health activity location stores the patient's follow-up visit / health activity data on a server, and the server generates follow-up visit / health activity records based on the follow-up visit / health activity data and stores them in the personal health database along with the follow-up visit / health activity data.

[0030] By tracking patient data over the long term on a server and using it as medical reference, if a patient needs eyeglasses after an outpatient visit, medical staff can issue a prescription and refer them to an appropriate health activity center.

[0031] If a patient requires further consultation or health activity, the server matches the patient with the appropriate medical institution or health activity location. This consultation and health activity data (including prescriptions, inquiry / referral data, etc.) is uploaded to the server, and a consultation / health activity record is generated. By accumulating examination data at health activity locations (orthoptics clinics, opticians, etc.), coordinating with consultation medical institutions, and making referrals / inquiries for subsequent eyeglass manufacturing activities, it is possible to link specialized medical institutions with health activity locations, fully utilize available resources such as opticians and optometry clinics, and track the patient's eye health in a better and longer-term manner.

[0032] In a specific example, the estimated frequency in step S1 can be obtained by matching with a preset axial length measurement conversion library, and in the future, it can be compared and corrected with data published in medical journals. Here, the data for the preset axial length measurement conversion library is obtained by training using a multiple regression analysis model, and step S1 further includes, but is not limited to, obtaining the patient's age, corneal horizontal curvature, corneal vertical curvature, anterior chamber measurement depth, and lens thickness. The multiple regression analysis model is a predictive model used in statistics and is suitable for analyzing the influence of multiple predictive parameters (such as axial length, age, corneal horizontal curvature, corneal vertical curvature, anterior chamber measurement depth, and lens thickness) on the response parameter (estimated frequency). In order to predict the optometric frequency and explain it with other parameters, parameters such as the patient's axial length, age, corneal horizontal curvature, corneal vertical curvature, anterior chamber measurement depth, and lens thickness are input into the model for training, and the model is constructed using the least squares method. The least squares method is used to construct the model. The straight line that takes the minimum value of L is considered the constructed regression model. After taking the minimum value, this line best fits the prediction line for the data. In the regression model, model learning and prediction are performed using data such as eye examination power, axial length, age, corneal horizontal curvature, corneal vertical curvature, anterior chamber measurement depth, and lens thickness, collected after the patient's pupils have been sufficiently dilated.

[0033] The specific steps for building the model are as follows: (S101) Parameters that are considered to be predictable for the degree of incidence (axial length of the eye, age, horizontal curvature of the cornea, vertical curvature of the cornea, measurement depth of the anterior chamber, thickness of the lens, etc.) are input into the model, and the model is constructed using the least squares method. In the (S102) model, basic model tests such as normality tests are performed on the squared difference. Then, stepwise regression is used to narrow down the parameters, and based on the interpretability of the parameters and the reduction in the number of parameters, parameters such as Age (age), AL (axial length), K1 (horizontal curvature of the cornea), K2 (vertical curvature of the cornea), ACD (measurement depth of the anterior chamber), and LT (thickness of the lens) are selected to construct the model. (S103) The variance expansion factor (VIF) is used to determine whether or not the model is collinear, thereby avoiding the impact of collinearity on the interpretability and predictive power of the parameters within the model.

[0034] As an example, let's look at Figure 2. As shown in the figure, the regression model is as follows: X=102.559+(-2.7982)*AL+0.1219*Age+(-0.5879)*K1+(-0.2723)*K2+2.7685*ACD+(-3.4206)*LT+ε Here, ε represents the random error of the model, X is the estimated frequency, AL is the axial length of the eye, Age is age, K1 is the horizontal curvature of the cornea, K2 is the vertical curvature of the cornea, ACD is the measurement depth of the anterior chamber, and LT is the thickness of the lens.

[0035] The slope of AL is -2.7982, meaning that for every 1 unit (1 mm) increase in AL, the degree of myopia increases by 2.7982 diopters. The ACD slope is 2.7685, meaning that for every 1 unit (1 mm) increase in ACD, the degree of myopia decreases by 2.7685 diopters. Similar results are obtained for other parameters.

[0036] The final adjusted R-squared index is 0.9167. This means that the model can interpret 91.7% of the changes in optometric power, and that the parameters within the model can interpret approximately 91.7% of the changes in optometric power.

[0037] In a specific example, the method is: (S5) The server further includes calculating an eye development index based on axial length data and axial length change records, calculating a health behavior score based on the estimated frequency, and storing the health behavior score and eye development index in the personal health database. By integrating health data such as axial length data, axial length change records, and estimated prescription, and calculating them as an indicator of the patient's eye development and a health behavior score, patients can more intuitively understand their own health status. At the same time, the patient's health behavior score can be synchronized with a health database of relatives, friends, or a specific group or family, allowing relatives, friends, or specific individuals to support tracking the patient's visual condition and establish a mutual health tracking mechanism.

[0038] In a specific example, the method for calculating the eye development index includes comparing axial length data and axial length change records with a big data nomogram to determine the patient's eye development index, which is the percentile of the patient's axial length for their age group. For example, if the patient's axial length data is 50% of that of their age group, the eye development index will be 50%.

[0039] In a specific example, the method for calculating health behavior scores includes increasing or decreasing the score based on changes in estimated refractive power, increasing the score when hyperopic refractive power increases or myopic refractive power decreases, and decreasing the score when hyperopic refractive power decreases or myopic refractive power increases. For example, if the patient's refractive power is +0.50D, the health behavior score will be +50, and if the refractive power changes to -0.25D, the health behavior score will change to -25. At the same time, it is possible to determine whether the patient's visual acuity is stable or changing abnormally based on the trend of changes in the patient's health behavior score.

[0040] In a specific embodiment, step S5 further includes establishing a patient's eye health change and tracking model based on axial length data, axial length change records, follow-up examination data, and health activity data. By establishing eye health change and tracking models for various patients, the establishment of medical big data on the eye health of human children is further realized.

[0041] In specific implementations, the health activity locations matched by the server include, but are not limited to, health activities such as eyeglass manufacturing (fine-tuning of prescription by an orthoptist and detection of binocular visual acuity balance). Furthermore, the targets of server matching include, but are not limited to, patients, medical institutions (specialized ophthalmology hospitals, clinics, etc.), health activity locations (opticians, eye examination clinics, etc.), specialists (ophthalmologists, orthoptists, etc.), eyeglass manufacturers, etc.

[0042] In a specific embodiment, data from the patient's personal health database is displayed on the user's terminal in the form of an application. When a patient performs detection using an axial length detection module and builds their personal health database, the application associates it with the patient's app account and displays health data such as the patient's health behavior score and eye development indicators within the app in the form of a balance and health score, similar to the concept of an eye health bank. Patients can then continuously and regularly visit the medical institutions and health activity locations matched by this method. Measurements are taken at these medical institutions and health activity locations (including, but not limited to, specialized ophthalmology hospitals or clinics, and health activity locations with a wider distribution and closer proximity, such as orthoptics clinics and opticians, that are equipped with axial length detection modules). The axial length data obtained from the measurements is synchronized and uploaded to the patient's personal health database, and the patient can view all of their eye health data at any time via their app account.

[0043] In a specific implementation, if a patient's axial length data changes too significantly, the app automatically assists with scheduling follow-up appointments and referrals in the form of online reservations and notifications. Patients can also actively use the app to find nearby medical institutions with available appointments. The patient's long-term axial length data is synchronized with medical institutions for reference. If a patient needs eyeglasses after an outpatient visit, ophthalmic medical staff can issue a prescription or refer the patient to a health activity location within the app for reference by specialist staff at the health activity location. The app may also display to the patient whether certain characteristic data of the health activity location (such as distance from home, availability of lenses and eyeglass frames that meet the needs, and availability of special defocus eyeglasses or orthokeratology lenses) meets the patient's actual needs. This meets the patient's eyeglasses needs, provides a health activity location with long-term connectivity, performs regular axial length detection, and achieves the effects of long-term and regular follow-up examinations, prescription reduction, and health promotion.

[0044] In a specific implementation, the app includes an evaluation mechanism for health activity locations. During the process of patients undergoing long-term, regular eye length measurements or getting eyeglasses made, the app can be used to evaluate the service experience at each health activity location, track patient activity, and establish the sharing and public accessibility of activity data and evaluations. Simultaneously, the server may be instructed to provide a more appropriate health activity location matching mechanism, depending on the format of evaluation sharing (e.g., community sharing). The evaluation mechanism can optimize the professional literacy and service attitude of staff in health activity settings, and simultaneously, based on the evaluation results, it can develop training courses for staff and regular corrective instruction for the axial length detection module. Courses and instruction can be delivered in the form of online educational videos, audio, and image captions, but are not limited to these formats.

[0045] A second aspect of this application proposes an eye health monitoring and mediation system. Figure 3 shows a system block diagram of an eye health monitoring and mediation system according to an embodiment of the present invention. As shown in the figure, the system is An axial length detection module 201 used to acquire patient axial length data and installed in a medical institution 20 and a health activity location 40, comprising at least one axial length detection module 201 including at least one axial length detection device including a non-contact optical axial length measuring instrument, A server 10 includes a member module 101 for inputting and storing axial length data and building a patient's personal health database based on the axial length data, and a matching module 102 for matching patients with medical institutions 20 and health activity locations 40. A user terminal 30 communicates with a server 10 and is used by the patient to receive alarm messages from the server 10 and retrieve data from a personal health database. The matching module, in response to the user terminal 30 receiving a signal that the patient needs a follow-up visit or health activity, matches the patient with a medical institution 20 and a health activity location 40.

[0046] The axial length detection device of the present invention includes, but is not limited to, a non-contact optical axial length measuring instrument. It is possible to avoid patient discomfort during the detection process and quickly acquire patient axial length data by non-contact means without using means that require contact with the patient's eye, such as pupil dilators. By installing axial length detection modules in each medical institution 20 and health activity location 40, patient axial length data is acquired. Medical institutions 20 include, but are not limited to, specialized ophthalmology hospitals and clinics. Health activity locations 40 include, but are not limited to, opticians and optometrist clinics. Each axial length detection module 201 in one medical institution 20 or health activity location 40 includes at least one axial length detection device, and the staff of the medical institution 20 or health activity location 40 acquire the patient's axial length data using the axial length detection device and manually input and store the patient's axial length data using the member module 101. When a patient acquires axial length data for the first time, the member module 101 builds the patient's personal health database based on the axial length data. The data stored in the personal health database includes, but is not limited to, the patient's axial length data, axial length change records, health activity data, health activity records, follow-up visit data, and follow-up visit records. If a patient's record of axial length change exceeds a preset threshold, the matching module 102 can automatically send an alert message to the user terminal 30, prompting the patient to participate in health activities and follow up with appointments in a timely manner. The message can also encourage the patient to reduce their use of 3C products, to regularly use pupil-dilating agents as directed by a doctor, to regularly use restrictive glasses or contact lenses, and to schedule follow-up appointments. The patient can also access the server 10 via the user terminal 30 and proactively match the matching module 102 with the appropriate health activity location 40 and medical institution 20. Health activities include, but are not limited to, eye examinations, eyeglass fitting, and eye health consultations offered at the health activity location 40.

[0047] Figure 4 shows a flowchart illustrating an embodiment of the present invention in which a patient enters the eye health monitoring and mediation system. As shown in the figure, when a patient enters a medical institution 20 or health activity location 40 for the first time, an eye examination is performed using the device to detect axial length data. The axial length detection module 201 directly outputs the patient's real-time axial length data, and the estimated frequency can be matched using a preset axial length measurement conversion library pre-configured within the axial length detection module. Simultaneously with the patient receiving the axial length data report on-site, the staff inputs the patient's axial length data into the member module 101. When a patient undergoes detection using the system for the first time, the member module 101 builds a personal health database for the patient based on the axial length data. When a patient undergoes detection using the system for the second time or later, the input axial length data is automatically stored in the patient's personal health database. When a patient accesses the server 10 via a user terminal 30, they may directly search their own personal health database data using the member module 101, or they may use the matching module 102 to match them with a medical institution 20 and health activity location 40 to revisit. When a patient completes a follow-up visit or health activity, the medical institution 20 and health activity location 40 store the patient's follow-up visit and health activity data in a personal health database. If the patient has a need for general or special eyeglasses (for example, if defocus eyeglasses are needed), the matching module 102 matches the patient with a suitable health activity location 40 (for example, an optician, orthoptics clinic) according to their needs, enabling them to perform health activities such as eyeglasses.

[0048] In the eye health monitoring and mediation method and system proposed in this application, a pre-configured axial length detection module 201 at a specialized medical institution 20 and a health activity location 40 acquires the patient's axial length data and stores it in a server 10. The server 10's member module 101 establishes a personal health database dedicated to the patient, and different medical institutions 20 and health activity locations 40 can synchronize and acquire data from the patient's personal health database. This avoids excessive idle resources at health activity locations 40 such as optometrists and opticians. At the same time, the axial length detection module 201 is equipped with a preset axial length measurement conversion library, and by matching the patient's axial length data with this library, a more accurate estimated prescription can be obtained. If the patient's axial length change record is excessive, the matching module 102 can automatically send an alarm message and match and recommend an appropriate medical institution 20 to the patient for booking. Furthermore, follow-up visit data is stored in the patient's personal health database in synchronization. Furthermore, if a patient needs eyeglasses, the matching module 102 can match and recommend an appropriate health activity location 40 and book health activities such as eyeglasses. Prescription or inquiry data is also synchronized and stored in the patient's personal health database so that the staff of the medical institution 20 and health activity location 40 can retrieve the patient's historical health data at the next visit or health activity.

[0049] The above description is merely a description of preferred embodiments and the technical principles employed in the present application. A person skilled in the art will understand that the scope of the present invention is not limited to technical solutions formed by specific combinations of the above technical features, but also includes other technical solutions formed by arbitrarily combining the above technical features or their equivalents, as long as they do not deviate from the concept of the present invention. For example, technical solutions formed by substituting the above features with technical features having similar functions disclosed in the present application (but not limited to these) may be included. [Explanation of symbols]

[0050] 10 servers, 101 member modules, 102 matching modules, 20 medical institutions, 201 axial length detection modules, 30 user terminals, 40 health activity locations.

Claims

1. (S1) An axial length detection module installed at each medical institution / health activity location acquires the patient's axial length data, generates an estimated frequency for the patient based on the axial length data, and stores the axial length data and the estimated frequency in a server. (S2) In response to the initial storage of the axial length data, the server constructs the patient's personal health database based on the axial length data and the estimated frequency, and the server transmits the estimated frequency to the user terminal. In response to the acquisition of the axial length data for the second time or later, the server generates an axial length change record based on the axial length data stored multiple times, stores the axial length change record in the personal health database, and, if the axial length change record is greater than a preset threshold, the server sends an alert message to the user terminal and matches and schedules a follow-up appointment or provides health consultation. A method for monitoring and mediating eye health, characterized by the following features.

2. (S3) In response to the user terminal receiving a signal indicating that the patient requires a follow-up visit or health activity, the server matches the patient with a medical institution and a health activity location for the follow-up visit. (S4) The medical institution / health activity location stores the patient's follow-up visit / health activity data in the server, and the server generates a follow-up visit / health activity record based on the follow-up visit / health activity data and stores it in the personal health database together with the follow-up visit / health activity data. The eye health monitoring and mediation method according to feature 1.

3. The estimated frequency in step S1 is obtained by prediction based on a preset axial length measurement conversion library, and the data in the preset axial length measurement conversion library is obtained by learning using a multiple regression analysis model. The eye health monitoring and mediation method according to feature 1.

4. Step S1 further includes obtaining the patient's age, corneal horizontal curvature, corneal vertical curvature, anterior chamber measurement depth, and lens thickness. The eye health monitoring and mediation method according to feature 3.

5. The procedure for constructing the aforementioned multiple regression analysis model is as follows: (S101) Input parameters that make the frequency predictable into the model, and construct the model using the least squares method. (S102) In the model, a basic model test is performed on the squared difference, and then the parameters are narrowed down using stepwise regression. Based on the interpretability of the parameters and the reduction in the number of parameters, the parameters are selected and the model is constructed. (S103) Includes determining whether or not the model is collinear using a variance expansion coefficient. The eye health monitoring and mediation method according to feature 3.

6. (S5) The server further includes calculating an eye development index based on the axial length data and the axial length change record, calculating a health behavior score based on the estimated frequency, and storing the health behavior score and the eye development index in the personal health database. The eye health monitoring and mediation method according to feature 2.

7. The method for calculating the aforementioned eye development index includes comparing the axial length data and the axial length change record with a big data nomogram to determine the patient's eye development index, which is the percentile of the patient's axial length for the same age group. The eye health monitoring and mediation method according to feature 6.

8. The method for calculating the health behavior score includes increasing or decreasing the score based on the change in the estimated frequency, increasing the score if the patient's hyperopic refractive power increases or myopic refractive power decreases, and decreasing the score if the hyperopic refractive power decreases or myopic refractive power increases. The eye health monitoring and mediation method according to feature 6.

9. Step S5 further includes establishing a model of changes in the patient's eye health and tracking based on the axial length data, the axial length change record, and the follow-up visit and health activity data. The eye health monitoring and mediation method according to feature 6.

10. An axial length detection module used to acquire patient axial length data, installed in medical institutions and health activity locations, comprising at least one axial length detection module including at least one axial length detection device including a non-contact optical axial length measuring instrument, A server including a member module for inputting and storing the axial length data and for constructing the patient's personal health database based on the axial length data, and a matching module for matching the patient with the medical institution and health activity location, A user terminal that communicates with the server and is used by the patient to receive alarm messages from the server and search for data in the personal health database, wherein when the user terminal receives a signal indicating that the patient needs a follow-up visit or health activity, the matching module matches the patient with the medical institution and health activity location, and the user terminal and including An eye health monitoring and mediation system characterized by the following features.

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