Self-service community eye health screening management system

Abstract

The invention relates to a self-service community eye health screening management system. Specifically, the user end adopts electronic filing, and meanwhile, eye health examination equipment configured at the initial examination end has a data automatic uploading function, so that the information input speed is increased, and the manpower and time cost is reduced; the referral module can automatically judge the specific disease of the user according to the condition of the user and match the best doctor for the user, so that the referral efficiency is improved, and the doctor-seeing experience of the user is optimized; and the pushing module can push the matched matters needing attention according to the user condition. Based on cooperation of ports and modules in the system, the problems of long time consumption of manual input, low referral efficiency, insufficient utilization of medical resources, insufficient science popularization and lack of statistical pain points in traditional eye health screening are solved, and the eye health level in a region can be improved.

Description

Technical Field

[0001] This invention belongs to the field of eye health technology, specifically relating to a self-service community eye health screening and management system. Background Technology

[0002] Eye health screening is a systematic eye examination process designed to detect visual abnormalities, refractive errors (such as myopia, hyperopia, and astigmatism) and potential eye diseases (such as strabismus, amblyopia, and congenital cataracts) at an early stage, and to ensure normal visual function development through timely intervention. Its core objective is to prevent avoidable vision impairment and reduce the incidence of eye diseases such as myopia.

[0003] Traditional eye health screening has its drawbacks:

[0004] 1. Manual data entry is time-consuming, and medical staff have to manually enter data, which consumes a lot of manpower and time.

[0005] 2. Low referral efficiency and insufficient utilization of medical resources: Most people do not have professional eye health knowledge and are unsure how to choose a suitable hospital or doctor for further examination when faced with screening results. Therefore, most choose famous doctors and experts. In addition, eye health screenings are mostly organized by the community, and a large number of people need to go to the hospital for further examination at the same time. The combination of these two factors leads to a shortage of appointments with famous doctors and experts, while there are no appointments available for ordinary doctors. This results in a longer time for all people screened in the same batch to complete the referral, and the medical resources corresponding to ordinary doctors are not fully utilized.

[0006] However, each doctor has different areas of expertise, and each person's eye condition is different. For some minor and complex eye conditions, ordinary doctors are perfectly capable of making a diagnosis and treatment, and there is no need for famous doctors or experts to make a diagnosis and treatment.

[0007] 3. Insufficient public education prevents people from properly learning about scientific knowledge of eye health, correct eye habits, and precautions.

[0008] 4. Lack of statistics: It is impossible to collect data on key indicators such as abnormal examination rate, abnormal referral rate, record-keeping rate, and poor vision rate, resulting in a lack of data support for macro-level decision-making.

[0009] In response, this application proposes a self-service community eye health screening and management system, which aims to address the pain points of traditional eye health screening, such as time-consuming manual data entry, low referral efficiency, insufficient utilization of medical resources, inadequate public education, and lack of statistics, thereby improving the level of eye health in the region. Summary of the Invention

[0010] The purpose of this invention is to solve the problems mentioned in the background section. To achieve this purpose, the specific technical solution is as follows:

[0011] A self-service community eye health screening and management system includes: a user terminal, an initial screening terminal, a referral module, a consultation terminal, a push module, a statistics module, and a server;

[0012] The user terminal includes information input and information display. The user terminal inputs basic user information and uploads it to the server for storage. The user terminal accesses the server to display basic user information, user eye data, and user medical data.

[0013] The initial screening unit includes an eye health examination device, and the eye data obtained by the user after using the eye health examination device is uploaded to the server for storage;

[0014] The referral module is configured on the server. By accessing the server, it obtains user information and their eye data, analyzes and processes the data, and then matches the user with a suitable consultation terminal for consultation.

[0015] After a user receives a diagnosis via the online consultation platform, the platform uploads the user's diagnosis data to the server for storage.

[0016] The push module is configured on the server. By accessing the server, it obtains the user's basic information and medical data, analyzes and processes them, and then pushes matching precaution information to the user's terminal.

[0017] The statistics module is configured on the server. By accessing the server, it obtains basic user information, user eye data, and user medical data that do not involve user privacy, and performs data statistics and display.

[0018] The server also includes a user database, a medical record database, a doctor database, and a precautions database.

[0019] The user database provides basic user information, user eye data, and user medical records, offering data support for the user interface and referral module.

[0020] The case database provides data on normal eyes and classic case information, offering data support for the referral module.

[0021] The doctor database provides basic information about doctors and their areas of expertise, offering data support for the referral module.

[0022] The Notes database provides notes and data support for the push module.

[0023] Furthermore, the user terminal includes mobile terminals and PC terminals, enabling online information input and display.

[0024] Furthermore, the eye health examination equipment is a self-service intelligent device with data uploading function, such as an intelligent LCD vision chart, a self-service screening vision tester, an automatic optometry instrument, and an intelligent refractive screening instrument. The examination process of the above-mentioned intelligent devices is mostly automated or has operation prompts. Therefore, users can conduct self-service eye health examinations, requiring only a small number of medical staff to provide services. There is no need for medical staff to provide one-on-one guidance to users. After completing the eye health examination, the above-mentioned intelligent devices can upload the user's eye data to the server for storage.

[0025] Furthermore, the referral module's analysis and processing steps include:

[0026] S1 accesses the server to obtain basic user information, user eye data, and normal eye data;

[0027] S2 compares the user's eye data with normal eye data to identify any abnormalities in the user's eyes;

[0028] S3 accesses classic case information on the server and compares it with the combination of user's eye abnormalities to determine the user's specific condition.

[0029] Based on the user's specific symptoms, S4 accesses the doctor database to determine the best doctor to consult, and requests the server to push the user's basic information, eye data, and treatment information to the best doctor's consultation terminal.

[0030] Furthermore, the determination of the user's specific ailment is achieved based on a ailment matching score formula and a confidence score calculation formula, wherein,

[0031] Symptom matching score formula:

[0032]

[0033] in,

[0034] Score(D): Candidate symptom score,

[0035] R D The set of necessary abnormalities for candidate symptom D.

[0036] O D The set of optional anomalies for candidate symptom D.

[0037] A: The actual set of user-reported anomalies.

[0038] F D The set of risk factors required for candidate disease D.

[0039] F U : The set of actual risk factors for users

[0040] Ⅱ: Indicator function (1 when satisfied, 0 otherwise),

[0041] α: Required item weight, α = 0.7,

[0042] β: Optional item base weight, β = 0.3,

[0043] γ opt : Optional item amplification factor, γ opt = 1.2,

[0044] δ: Risk factor weight, δ = 0.5;

[0045] [[ID=​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0059] Doctor matching score formula:

[0060]

[0061] in,

[0062] DoctorScore(d): Candidate doctor score

[0063] ω s Professional matching coefficient, ω s =0.4,

[0064] S d Professional matching degree

[0065] ω l : Workload factor, ω l =0.3,

[0066] L d The current number of patients received on a weekday.

[0067] C d The maximum number of patients received on a weekday.

[0068] ω t : Professional title coefficient, ω t =0.2,

[0069] T d Job weight, resident physician T d =0.5, Attending Physician T d =0.7, Associate Chief Physician T d =0.85, Chief Physician T d =1.0,

[0070] ω r Service quality coefficient, ω r =0.1,

[0071] R d Service quality rating;

[0072] Professional matching degree calculation:

[0073]

[0074] in,

[0075] Rank(D): The ranking position of the target disease among the diseases that the doctor specializes in (starting from 0).

[0076] |S d |: The doctor is skilled in a wide range of diseases.

[0077] σ: Correction factor, σ = 0.3;

[0078] Service quality score calculation:

[0079]

[0080] in,

[0081] T p The total score of all questionnaires from the previous quarter's doctor-patient consultation feedback. Individual questionnaire scores range from 0 to 5, with 5 being the highest.

[0082] T: The number of all questionnaires collected from patient feedback during doctor consultations in the previous quarter;

[0083] Final selection rules:

[0084]

[0085] Furthermore, the push module analysis and processing steps include:

[0086] S1 accesses the server's user database to obtain specific symptom information of the user;

[0087] Based on the user's basic information and specific symptom information, S2 requests the server to push the corresponding precautions from the precautions database to the user's client.

[0088] Furthermore, the user terminal, initial examination terminal, consultation terminal, and server use existing, well-known, and commonly used communication methods for data transmission, such as 4G, 5G, Internet, Bluetooth, and wireless LAN. Based on the selected communication method, the user terminal, initial examination terminal, consultation terminal, and server select models with corresponding communication functions or configure corresponding communication modules, communication interfaces, and communication protocols to achieve normal data communication.

[0089] Furthermore, the system also includes a processor, a memory, and a network interface. The processor is connected to the memory and the network interface. The network interface is used to provide data communication functions, the memory is used to store program code and data, and the processor is used to call the program code and data to execute the self-service community eye health screening and management system.

[0090] Compared with the prior art, the beneficial effects of the present invention are:

[0091] (1) Based on the user end and the initial examination end, the user file creation is electronic and the upload of user eye health examination data is automated. Compared with manual file creation and data entry, it takes into account both high efficiency and low cost.

[0092] (2) Based on the referral module, after the user completes the corresponding eye health examination items, the system can analyze the user's possible eye diseases and recommend the best doctor to the user. On the one hand, the user does not need to worry about the choice of doctor, shortening the average time for the user to go to the hospital for referral. On the other hand, the doctor consults patients whose diseases are in the doctor's area of ​​expertise, shortening the average time for the doctor to consult patients. Furthermore, it guides the user and diverts users in the same batch of screenings to different hospitals and doctors, making fuller use of medical resources in the region.

[0093] (3) Based on the push module, targeted precautions can be pushed according to the user's eye health status to protect eye health.

[0094] (4) Based on the statistical module, the competent authorities can clearly understand the eye health status in the region, providing data support for the macro-decision-making of the competent authorities. Attached Figure Description

[0095] Figure 1 This is a schematic diagram of the overall process of the present invention. Detailed Implementation

[0096] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0097] A self-service community eye health screening and management system includes: a user terminal, an initial screening terminal, a referral module, a consultation terminal, a push module, a statistics module, and a server;

[0098] The user terminal includes information input and information display. The user terminal inputs basic user information and uploads it to the server for storage. The user terminal accesses the server to display basic user information, user eye data, and user medical data.

[0099] The initial screening unit includes an eye health examination device, and the eye data obtained by the user after using the eye health examination device is uploaded to the server for storage;

[0100] The referral module is configured on the server. By accessing the server, it obtains user information and their eye data, analyzes and processes the data, and then matches the user with a suitable consultation terminal for consultation.

[0101] After a user receives a diagnosis via the online consultation platform, the platform uploads the user's diagnosis data to the server for storage.

[0102] The push module is configured on the server. By accessing the server, it obtains the user's basic information and medical data, analyzes and processes them, and then pushes matching precaution information to the user's terminal.

[0103] The statistics module is configured on the server. By accessing the server, it obtains basic user information, user eye data, and user medical data that do not involve user privacy, and performs data statistics and display.

[0104] The server also includes a user database, a medical record database, a doctor database, and a precautions database.

[0105] The user database provides basic user information, user eye data, and user medical records, offering data support for the user interface and referral module.

[0106] The case database provides data on normal eyes and classic case information, offering data support for the referral module.

[0107] The doctor database provides basic information about doctors and their areas of expertise, offering data support for the referral module.

[0108] The Notes database provides notes and data support for the push module.

[0109] In a preferred embodiment, the user terminal includes a mobile terminal and a PC terminal, enabling online information input and display.

[0110] In a preferred embodiment, the eye health examination equipment is a self-service intelligent device with data uploading function, such as an intelligent LCD vision chart, a self-service screening vision tester, an automatic optometer, or an intelligent refractive screening instrument. The examination process of the above-mentioned intelligent devices is mostly automated or has operation prompts, so users can conduct self-service eye health examinations. Only a small number of medical staff are needed to provide services, and there is no need for medical staff to provide one-on-one guidance to users. After completing the eye health examination, the above-mentioned intelligent devices can upload the user's eye data to the server for storage.

[0111] In a preferred embodiment, the steps of the referral module analysis and processing include:

[0112] S1 accesses the server to obtain basic user information, user eye data, and normal eye data;

[0113] S2 compares the user's eye data with normal eye data to identify any abnormalities in the user's eyes;

[0114] S3 accesses classic case information on the server and compares it with the combination of user's eye abnormalities to determine the user's specific condition.

[0115] Based on the user's specific symptoms, S4 accesses the doctor database to determine the best doctor to consult, and requests the server to push the user's basic information, eye data, and treatment information to the best doctor's consultation terminal.

[0116] In a preferred embodiment, the determination of the user's specific ailment is achieved based on a ailment matching score formula and a confidence score calculation formula, wherein,

[0117] Symptom matching score formula:

[0118]

[0119] in,

[0120] Score(D): Candidate symptom score,

[0121] R D The set of necessary abnormalities for candidate symptom D.

[0122] O D The set of optional anomalies for candidate symptom D.

[0123] A: The actual set of user-reported anomalies.

[0124] F D The set of risk factors required for candidate disease D.

[0125] F U : The set of actual risk factors for users

[0126] II: Indicator function (1 if satisfied, 0 otherwise),

[0127] α: Weight of required items, α = 0.7

[0128] β: Optional base weight, β = 0.3

[0129] γ opt Optional amplification factor, γ opt =1.2,

[0130] δ: Risk factor weight, δ = 0.5;

[0131] Confidence level calculation formula:

[0132]

[0133] in,

[0134] TopScore: The highest score matching the disease.

[0135] Δ: Smoothing constant, Δ = 5

[0136] ΔScore: The difference between the highest and second-highest scores.

[0137] β gap : Competition discount coefficient, β gap = 0.2,

[0138] K: Slope of the competition curve, K = 2,

[0139] t: Competition threshold, t = 1.5,

[0140] 0.85 < Confidence ≤ 0.99, High confidence result, the auditor directly determines the specific disease of the user,

[0141] 0.7 ≤ Confidence ≤ 0.85, Medium confidence result, the auditor individually reviews and determines the specific disease of the user,

[0142] Confidence < 0.7, Low confidence result, the auditor reviews by multiple people to determine the specific disease of the user;

[0143] Specifically, based on the disease matching score formula, the highest score candidate disease and the second highest score candidate disease are obtained, and then the credibility of the highest score candidate disease is verified through the confidence calculation formula. According to the verification result, the auditor directly determines the specific disease of the user, or individually reviews and determines the disease of the user, or reviews by multiple people to determine the disease of the user.

[0144] In the preferred case, the determination of the best doctor for consultation is realized based on the doctor matching score formula on the premise of determining the specific disease of the user, where,

[0145] Doctor matching score formula:

[0146]

[0147] Where,

[0148] DoctorScore(d): Candidate doctor score,

[0149] ω s : Professional matching degree coefficient, ω s = 0.4,

[0150] S d : Professional matching degree,

[0151] ω l : Workload coefficient, ω l = 0.3,

[0152] L d : Current number of patients received on the working day,

[0153] C d : Maximum number of patients received on the working day,

[0154] ω t : Professional title coefficient, ω t =0.2,

[0155] T d Job weight, resident physician T d =0.5, Attending Physician T d =0.7, Associate Chief Physician T d =0.85, Chief Physician T d =1.0,

[0156] ω r Service quality coefficient, ω r =0.1,

[0157] R d Service quality rating;

[0158] Professional matching degree calculation:

[0159]

[0160] in,

[0161] Rank(D): The ranking position of the target disease among the diseases that the doctor specializes in (starting from 0).

[0162] |S d |: The doctor is skilled in a wide range of diseases.

[0163] σ: Correction factor, σ = 0.3;

[0164] Service quality score calculation:

[0165]

[0166] in,

[0167] T p The total score of all questionnaires from the previous quarter's doctor-patient consultation feedback. Individual questionnaire scores range from 0 to 5, with 5 being the highest.

[0168] T: The number of all questionnaires collected from patient feedback during doctor consultations in the previous quarter;

[0169] Final selection rules:

[0170]

[0171] In a preferred embodiment, the push module analysis and processing steps include:

[0172] S1 accesses the server's user database to obtain specific symptom information of the user;

[0173] Based on the user's basic information and specific symptom information, S2 requests the server to push the corresponding precautions from the precautions database to the user's client.

[0174] In a preferred embodiment, the user terminal, the initial examination terminal, the consultation terminal, and the server use existing, well-known, and commonly used communication methods for data transmission, such as 4G, 5G, the Internet, Bluetooth, and wireless LAN. Based on the selected communication method, the user terminal, the initial examination terminal, the consultation terminal, and the server select models with corresponding communication functions, or configure corresponding communication modules, communication interfaces, and communication protocols to achieve normal data communication.

[0175] In a preferred embodiment, the system also includes a processor, a memory, and a network interface. The processor is connected to the memory and the network interface. The network interface is used to provide data communication functions, the memory is used to store program code and data, and the processor is used to call the program code and data to execute the self-service community eye health screening and management system.

[0176] Obviously, the above embodiments of this application are merely examples for clear illustration and are not intended to limit the implementation of the application. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of the claims of this application.

Claims

1. A self-service community eye health screening and management system, characterized in that, Including: A client, a preliminary examination terminal, a referral module, a consultation terminal, a push module, a statistics module, and a server; The client includes information input and information display. The client inputs the basic information of the user and uploads it to the server for storage. The client accesses the server to display the basic information of the user, the eye data of the user, and the diagnosis and treatment data of the user; The preliminary examination terminal includes eye health examination equipment. The eye data obtained by the user after using the eye health examination equipment is uploaded to the server for storage; The referral module is configured on the server. By accessing the server, it obtains the user information and their eye data, and after analysis and processing, it matches a suitable consultation terminal for the user to conduct a consultation; After the user undergoes diagnosis and treatment by the consultation terminal, the consultation terminal uploads the user's diagnosis and treatment data to the server for storage; The push module is configured on the server. By accessing the server, it obtains the basic information of the user and the user's diagnosis and treatment data, and after analysis and processing, it pushes the matching attention information to the client; The statistics module is configured on the server. By accessing the server, it obtains the basic information of the user, the eye data of the user, and the diagnosis and treatment data of the user that do not involve user privacy, and conducts data statistics and display; The server also includes a user database, a case database, a doctor database, and a notice database. The user database provides the basic information of the user, the eye data of the user, and the diagnosis and treatment information of the user, providing data support for the client and the referral module. The case database provides normal eye data and classic case information, providing data support for the referral module. The doctor database provides the basic information of the doctor and the fields of expertise, providing data support for the referral module. The notice database provides notices, providing data support for the push module.

2. The self-service community eye health screening and management system according to claim 1, characterized in that: The client includes a mobile terminal and a PC terminal, and conducts information input and information display online.

3. The self-service community eye health screening and management system according to claim 1, characterized in that: The steps of analysis and processing by the referral module include: S1 Access the server to obtain the basic information of the user, the eye data of the user, and the normal eye data; S2 Compare the user's eye data with the normal eye data to determine the abnormal items of the user's eyes; S3 Access the classic case information of the server, and based on the combination of the user's eye abnormal items, determine the specific disease of the user; S4 Based on the specific disease of the user, access the doctor database to determine the best doctor for consultation, and request the server to push the basic information of the user, the eye data of the user, and the diagnosis and treatment information of the user to the consultation terminal of the best doctor for consultation.

4. The self-service community eye health screening and management system according to claim 3, characterized in that: The determination of the specific disease of the user is realized based on the disease matching score formula and the confidence calculation formula. Among them, Disease matching score formula: Among them, Score(D): Candidate disease score, R D The set of necessary abnormalities for candidate symptom D. O D The set of optional anomalies for candidate symptom D. A: Set of actual abnormal items of the user, F D The set of risk factors required for candidate disease D. F U : The set of actual risk factors for users Ⅱ: Indicator function (1 when satisfied, otherwise 0), α: Weight of required items, α = 0.7, β: Basic weight of optional items, β = 0.3, γ opt Optional amplification factor, γ opt =1.2, δ: Weight of risk factors, δ = 0.5; Confidence calculation formula: Among them, TopScore: Highest disease matching score, Δ: Smoothing constant, Δ = 5, ΔScore: Difference between the highest score and the second highest score, β gap Competition discount factor, β gap =0.2, K: Slope of the competition curve, K = 2, t: Competition threshold, t = 1.5, 0.85 < Confidence ≤ 0.99, high-confidence result, the auditor directly determines the specific disease of the user. 0.7 ≤ Confidence ≤ 0.85, The result indicates that the auditor has individually reviewed and confirmed the user's specific symptoms. Confidence < 0.7, low confidence result, multiple auditors review to confirm the user's specific symptoms; Specifically, the highest-scoring candidate disease and the second-highest-scoring candidate disease are obtained based on the disease matching score formula. Then, the credibility of the highest-scoring candidate disease is verified by the confidence calculation formula. Based on the verification results, the auditor may directly determine the user's specific disease, or a single person may review and determine the user's disease, or multiple people may review and determine the user's disease.

5. The self-service community eye health screening and management system according to claim 3, characterized in that: The determination of the best doctor for consultation is achieved based on a doctor matching score formula, assuming the user's specific symptoms are identified. Doctor matching score formula: in, DoctorScore(d): Candidate doctor score ω s Professional matching coefficient, ω s =0.4, S d Professional matching degree ω l : Workload factor, ω l =0.3, L d The current number of patients received on a weekday. C d The maximum number of patients received on a weekday. ω t : Professional title coefficient, ω t =0.2, T d Job weight, resident physician T d =0.5, Attending Physician T d =0.7, Associate Chief Physician T d =0.85, Chief Physician T d =1.0, ω r Service quality coefficient, ω r =0.1, R d Service quality rating; Professional matching degree calculation: in, Rank(D): The ranking position of the target disease among the diseases that the doctor specializes in (starting from 0). |S d |: The doctor is skilled in a wide range of diseases. σ: Correction factor, σ = 0.3; Service quality score calculation: in, T p The total score of all questionnaires from the previous quarter's doctor-patient feedback surveys. Individual questionnaire scores range from 0 to 5, with 5 being the highest. T: The number of all questionnaires collected from patient feedback during doctor consultations in the previous quarter; Final selection rules:

6. The self-service community eye health screening and management system according to claim 1, characterized in that: The steps of the push module analysis and processing include: S1 accesses the server's user database to obtain specific symptom information of the user; Based on the user's basic information and specific symptom information, S2 requests the server to push the corresponding precautions from the precautions database to the user's client.

7. The self-service community eye health screening and management system according to any one of claims 1 to 6, characterized in that: The system also includes a processor, memory, and a network interface. The processor is connected to the memory and the network interface. The network interface is used to provide data communication functions, the memory is used to store program code and data, and the processor is used to call the program code and data to execute the self-service community eye health screening and management system.

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