Family doctor service information management method and system and electronic equipment
The family doctor service information management method and system address inefficiencies in paper-based systems by electronically managing health records and doctor evaluations, improving data accuracy and user satisfaction.
Patent Information
- Application Number
- CN202410906947.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-08
- Publication Date
- 2024-12-13
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Traditional family doctor service information management systems rely on paper files, leading to inconsistent information, difficulty in sharing, and inefficient manual processes, which compromise user satisfaction and loyalty due to potential errors and information leakage.
A family doctor service information management method and system that collects and stores electronic health records, evaluates the storage process, uploads medical reports, and scores family doctors based on user feedback to ensure accurate, efficient, and transparent service delivery.
Enhances data management efficiency, reduces errors, improves service quality, and fosters trust between doctors and patients by providing objective evaluations and timely feedback mechanisms.
Smart Images
Figure CN119132485A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of service information management, and in particular to a family doctor service information management method, system and electronic equipment. Background Art
[0002] Family doctor service refers to the provision of continuous, comprehensive, coordinated and accessible health services to individuals or families living at home. With the improvement of people's health awareness and the shortage of medical resources, family doctor services have received more and more attention. With the development of Internet technology and mobile communication technology, people's demand for convenient, efficient and personalized health management services has gradually increased. As a comprehensive health management model, family doctor services need to use information technology to provide better services. Through scientific research and technological innovation, the quality and efficiency of family doctor services can be improved to better meet people's health management needs.
[0003] Nowadays, there are still some shortcomings in the research on a family doctor service information management method, system and electronic equipment. Specifically, the traditional medical information management method is usually paper files, which have problems such as inconsistent information and difficulty in sharing. It also ignores the user's feelings about family doctor services. The information in paper files may be distributed in different places, which is not convenient for integration and unified management. Sometimes the information of the same user may be stored in a scattered manner, resulting in difficulties in information search and use. The sharing and delivery of paper files usually require manual copying or mailing, which is inefficient and prone to the risk of transmission errors or information leakage. Ignoring the user's feelings about family doctor services reduces user satisfaction and loyalty. Summary of the invention
[0004] In view of the deficiencies in the prior art, the present invention provides a family doctor service information management method, system and electronic device, which can effectively solve the problems involved in the above-mentioned background technology.
[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a family doctor service information management method, comprising the following steps: collecting and storing the user's electronic health records, obtaining a data set of the user's electronic health record collection and storage process, and judging whether the user's electronic health record has been successfully collected and stored based on the obtained data set of the user's electronic health record collection and storage process; the family doctor who has made a successful appointment obtains the user's corresponding successfully stored electronic health record, uploads the medical report after diagnosis and treatment, obtains a medical report upload data set, and judges whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set; after the family doctor successfully uploads the medical report, the user is reminded to evaluate the family doctor, obtains a data set of feedback from the user on the family doctor, and based on the obtained data set of feedback from the user on the family doctor, scores the family doctor and records it on the family doctor's personal page.
[0006] As a further method, the user's electronic health records are collected and stored, and a data set of the user's electronic health records collection and storage process is obtained. The specific analysis process is: collect the user's electronic health records, store the collected user's electronic health records, and obtain a data set of the user's electronic health records collection and storage process. The data set of the user's electronic health records collection and storage process specifically includes the completion storage time of the user's electronic health records, the completeness ratio of the user's electronic health records content, and the number of storage authentication times of the user's electronic health records.
[0007] As a further method, based on the obtained user electronic health record collection and storage process data set, it is judged whether the user's electronic health record is collected and stored successfully. The specific analysis process is: based on the obtained user electronic health record collection and storage process data set, a comprehensive analysis is performed to obtain an evaluation value of the user's electronic health record collection and storage process, and the evaluation value of the user's electronic health record collection and storage process is used as an analysis basis for judging whether the user's electronic health record is collected and stored successfully; the evaluation value of the user's electronic health record collection and storage process is compared with a reference evaluation value of the user's electronic health record collection and storage process stored in a database; if the evaluation value of the user's electronic health record collection and storage process is higher than or equal to the reference evaluation value of the user's electronic health record collection and storage process, the user's electronic health record is collected and stored successfully; if the evaluation value of the user's electronic health record collection and storage process is lower than the reference evaluation value of the user's electronic health record collection and storage process, the user's electronic health record is not collected and stored successfully, and needs to be collected and stored again.
[0008] As a further approach, the user's electronic health record collects and stores process evaluation values. The specific analysis process is as follows:
[0009]
[0010] Wherein, δ is the evaluation value of the user's electronic health record collection and storage process, CT is the completion storage time of the user's electronic health record, WZ is the complete content ratio of the user's electronic health record, RN is the number of storage authentications of the user's electronic health record, CT0 is the reference time for the completion storage of the user's electronic health record stored in the database, RN0 is the number of storage authentications of the user's electronic health record stored in the database, μ1 is the compensation factor for the set completion storage time of the user's electronic health record, μ2 is the compensation factor for the set complete content ratio of the user's electronic health record, and μ3 is the compensation factor for the set number of storage authentications of the user's electronic health record.
[0011] As a further method, a medical report upload data set specifically includes the medical report upload network speed, the medical report upload packet loss rate, and the length of time from the successful appointment of the medical report to the upload of the medical report.
[0012] As a further method, based on the obtained medical report upload data set, it is judged whether the family doctor has successfully uploaded the medical report. The specific analysis process is: based on the obtained medical report upload data set, a medical report upload evaluation value is obtained through comprehensive analysis, and the medical report upload evaluation value is used as the analysis basis for judging whether the family doctor has successfully uploaded the medical report; the medical report upload evaluation value is compared with the medical report upload reference evaluation value stored in the database; if the medical report upload evaluation value is higher than or equal to the medical report upload reference evaluation value, the family doctor has successfully uploaded the medical report; if the medical report upload evaluation value is lower than the medical report upload reference evaluation value, the family doctor has not successfully uploaded the medical report and needs to upload it again.
[0013] As a further method, a user feedback data set on family doctors specifically includes the user feedback waiting time for consultation, the number of bytes of positive user feedback evaluations, and the proportion of the number of bytes of positive user feedback evaluations in the total number of evaluation bytes.
[0014] As a further method, based on the obtained data set of user feedback on family doctors, family doctors are scored and recorded in the personal page of the family doctor. The specific analysis process is: based on the obtained data set of user feedback on family doctors, comprehensive analysis is performed to obtain user feedback characteristic values on family doctors, and the user feedback characteristic values on family doctors are used as the analysis basis for scoring family doctors; the user feedback characteristic values on family doctors are compared with the family doctor scores corresponding to the user feedback characteristic values of each user stored in the database to obtain the family doctor scores corresponding to the user feedback characteristic values; the family doctor scores corresponding to the compared user feedback characteristic values on family doctors are recorded in the personal page of the family doctor.
[0015] The second aspect of the present invention provides a family doctor service information management system, including an electronic health record collection and storage module, a family doctor medical report upload module and a family doctor scoring module, wherein: the electronic health record collection and storage module is used to collect and store the user's electronic health record, obtain the user's electronic health record collection and storage process data set, and judge whether the user's electronic health record is successfully collected and stored based on the obtained user's electronic health record collection and storage process data set; the family doctor medical report upload module is used for the family doctor who has made a successful appointment to obtain the user's corresponding successfully stored electronic health record of the user, upload the medical report after diagnosis and treatment, obtain the medical report upload data set, and judge whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set; the family doctor scoring module is used to remind the user to evaluate the family doctor after the family doctor successfully uploads the medical report, obtain the user's feedback data set on the family doctor, and score the family doctor based on the obtained user's feedback data set on the family doctor, and record it to the family doctor's personal page.
[0016] The third aspect of the present invention provides a family doctor service information management electronic device, including a processor and a memory and a network interface connected to the processor, the network interface is connected to a non-volatile memory in a server, and the processor retrieves a computer program from the non-volatile memory through the network interface during operation, and runs the computer program through the memory.
[0017] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides a family doctor service information management method, system and electronic device, and obtains the user's electronic health record collection and storage process data set to determine whether the user's electronic health record is successfully collected and stored. By analyzing the electronic health record collection and storage process data, the efficiency, quality and bottleneck of information collection can be understood, which helps to optimize and improve the information management system and improve the quality and reliability of data. According to the data analysis results, the entire electronic health record collection and storage process can be continuously improved to optimize the process, improve efficiency, and further improve the quality and efficiency of family doctor services. By continuously collecting and analyzing the electronic health record collection and storage process data, a monitoring mechanism can be established to regularly evaluate the system operation, identify problems and correct them in a timely manner, thereby ensuring the stability and reliability of the family doctor service information management system.
[0018] (2) The present invention determines whether a family doctor has successfully uploaded a medical report based on the acquired medical report upload data set, thereby helping to reduce human errors and inaccuracies in information transmission. The electronic record of the medical report can present the user's medical information more clearly and accurately, reduce information omissions and errors, and help family doctors to promptly re-upload medical reports that failed to be uploaded, ensuring that the medical report is viewed by the user in a timely manner, thereby improving the efficiency of medical services.
[0019] (3) The present invention can improve the transparency and credibility of medical services by scoring family doctors and recording them on the family doctor's personal page. Users can easily view other users' evaluations of doctors, thereby trusting and choosing doctors that suit them. They can understand the doctor's service quality by analyzing the scoring data, identify problems and take measures to improve them. Recording family doctor scores can also help build trust and loyalty between doctors and users. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.
[0021] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.
[0022] Figure 2 It is a schematic diagram of system module connection of the present invention.
[0023] Figure 3 Collect images of storage process assessment values for the user's electronic health record as a function of the length of time the user's electronic health record is stored. DETAILED DESCRIPTION
[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.
[0025] Reference Figure 1 As shown, the first aspect of the present invention provides a family doctor service information management method, including: collecting and storing the user's electronic health record, obtaining a data set of the user's electronic health record collection and storage process, and judging whether the user's electronic health record has been successfully collected and stored based on the obtained data set of the user's electronic health record collection and storage process.
[0026] Specifically, the user's electronic health records are collected and stored, and a data set of the user's electronic health record collection and storage process is obtained. The specific analysis process is: collect the user's electronic health records, store the collected electronic health records of the user, and obtain the user's electronic health record collection and storage process data set. The user's electronic health record collection and storage process data set specifically includes the user's electronic health record completion storage time, the user's electronic health record content completeness ratio, and the user's electronic health record storage authentication times. The completion storage time refers to the total time it takes for the user's electronic health record to complete the storage process in the system. The content completeness ratio refers to the ratio of complete information contained in the user's electronic health record. A complete health record can better provide medical personnel with necessary health information. Improving the content completeness ratio is conducive to improving the quality of medical services. The number of storage authentications refers to the number of times the user's trust in the user's electronic health record is authenticated during the storage authentication process. Storage authentication is usually used to ensure the authenticity and accuracy of health information submitted by the user.
[0027] In a specific embodiment, the longer the storage time of the user's electronic health record is, the more times the user's electronic health record is stored and authenticated. Users with a low content completeness ratio need to spend more effort to complete the information in their health records, which also means that they are more likely to ensure the authenticity and accuracy of the submitted information through storage authentication, thereby increasing the number of storage authentication times.
[0028] Specifically, based on the obtained data set of the user's electronic health record collection and storage process, it is judged whether the user's electronic health record is collected and stored successfully. The specific analysis process is: based on the obtained data set of the user's electronic health record collection and storage process, a comprehensive analysis is performed to obtain an evaluation value of the user's electronic health record collection and storage process, and the evaluation value of the user's electronic health record collection and storage process is used as an analysis basis for judging whether the user's electronic health record is collected and stored successfully; the evaluation value of the user's electronic health record collection and storage process is compared with a reference evaluation value of the user's electronic health record collection and storage process stored in a database; if the evaluation value of the user's electronic health record collection and storage process is higher than or equal to the reference evaluation value of the user's electronic health record collection and storage process, the user's electronic health record is collected and stored successfully; if the evaluation value of the user's electronic health record collection and storage process is lower than the reference evaluation value of the user's electronic health record collection and storage process, the user's electronic health record is not collected and stored successfully and needs to be collected and stored again.
[0029] In a specific embodiment, by using evaluation values for judgment, the objectivity and standardization of judgment can be increased. The evaluation values may be based on a series of indicators and standards, thereby providing a relatively objective measurement standard. The comparison of evaluation values can be automated, thereby improving the efficiency of judgment. Especially in large-scale data sets, automated judgment can save time and labor costs. Comparing the evaluation values with reference evaluation values can provide feedback for continuous improvement. If the evaluation value is lower than the reference evaluation value, it means that there is room for improvement, and the storage process can be adjusted and improved in a targeted manner. Judging whether the storage is successful or not in this way can prompt medical institutions and related personnel to pay more attention to improving data quality. Only when the data quality reaches a certain standard can a higher evaluation value be obtained, which is then considered a successful storage process. A successful storage process means that the health record contains accurate and complete information, which can improve the quality and efficiency of medical services and help doctors make more accurate diagnosis and treatment decisions, thereby improving the user's medical experience and treatment effects.
[0030] In a specific embodiment, by obtaining the user's electronic health record collection and storage process data set, it is determined whether the user's electronic health record is successfully collected and stored. By analyzing the electronic health record collection and storage process data, the efficiency, quality and bottlenecks of information collection can be understood, which helps to optimize and improve the information management system and improve the quality and reliability of data. According to the data analysis results, the entire electronic health record collection and storage process can be continuously improved to optimize the process, improve efficiency, and further improve the quality and efficiency of family doctor services. By continuously collecting and analyzing the electronic health record collection and storage process data, a monitoring mechanism can be established to regularly evaluate the system operation, identify problems and correct them in a timely manner, thereby ensuring the stability and reliability of the family doctor service information management system.
[0031] Specifically, the user's electronic health record collects and stores the process evaluation value, and the specific analysis process is as follows:
[0032]
[0033] Wherein, δ is the evaluation value of the user's electronic health record collection and storage process, CT is the completion storage time of the user's electronic health record, WZ is the complete content ratio of the user's electronic health record, RN is the number of storage authentications of the user's electronic health record, CT0 is the reference time for the completion storage of the user's electronic health record stored in the database, RN0 is the number of storage authentications of the user's electronic health record stored in the database, μ1 is the compensation factor for the set completion storage time of the user's electronic health record, μ2 is the compensation factor for the set complete content ratio of the user's electronic health record, and μ3 is the compensation factor for the set number of storage authentications of the user's electronic health record.
[0034] It should be explained that the above-mentioned evaluation value of the user's electronic health record collection and storage process is calculated through the storage time of the user's electronic health record, the completeness ratio of the user's electronic health record content, and the number of storage authentication times of the user's electronic health record. By considering multiple indicators such as storage time, completeness of health record content and number of storage authentications, the storage status of the user's health record can be comprehensively evaluated. Not only is it concerned with whether the health record is stored, but it is also possible to understand the quality and authentication status of the health record and improve the accuracy of the evaluation. The length of storage time, the completeness ratio of the health record content and the number of storage authentications can all reflect the degree of importance the user places on his or her own health record. By evaluating these indicators, it is possible to understand the degree of attention the user pays to the health record, which helps to improve the user's awareness of health management. Using the storage status of the user's health record as an evaluation standard can motivate users to more actively manage their personal health data. Users are expected to improve the evaluation value by continuously improving and authenticating their health records, thereby forming good health record management habits. By evaluating the storage status of the user's health record, a reference basis can be provided for health services, which is useful for extracting user health information from it and providing users with personalized health services. Health service providers who provide advice, prevention, diagnosis and treatment support, these evaluation values can help them better understand the health status of users and provide more accurate services. By recording the start and end time of the user's electronic health record storage in the system, the storage time can be simply calculated. By evaluating the completion of various information in the user's electronic health record, the content completeness ratio can be calculated. By recording the number of times the user authenticates the electronic health record, the number of storage authentications can be directly obtained. The reference time for completing the storage of the user's electronic health record stored in the database and the reference standard for the number of storage authentications of the user's electronic health record stored in the database are extracted from the database. According to the relevant rules and standards set by the system, the compensation ratio or weighting coefficient of different factors is set as the compensation factor.
[0035] like Figure 3As shown, this is an image of the change in the evaluation value of the user's electronic health record collection and storage process as the user's electronic health record is completed and stored. The x-axis represents the time it takes to complete the storage of the user's electronic health record, and the y-axis represents the evaluation value of the user's electronic health record collection and storage process. This can help intuitively understand how the time it takes to complete the storage of the user's electronic health record affects the evaluation value of the user's electronic health record collection and storage process. The longer the time it takes to complete the storage of the user's electronic health record, the smaller the evaluation value of the user's electronic health record collection and storage process, indicating that the collection and storage status of the user's electronic health record is worse. As the time it takes to complete the storage of the user's electronic health record increases, its impact on the evaluation value of the user's electronic health record collection and storage process gradually weakens, and eventually It is stabilized at a lower value, and the completeness ratio of the user's electronic health record content is set to 0.8, the number of storage authentication times of the user's electronic health record is set to 2, the reference time for the completion of the storage of the user's electronic health record stored in the database is set to 60, the number of storage authentication limits of the user's electronic health record stored in the database is set to 4, the compensation factor for the completion of the storage time of the user's electronic health record is set to 0.3, the compensation factor for the completeness ratio of the user's electronic health record content is set to 0.3, the compensation factor for the number of storage authentication times of the user's electronic health record is set to 0.4, and only the size of the completion storage time of the user's electronic health record is changed. The example values of the completion storage time of the user's electronic health record are as follows:
[0036] Table 1: Example values of the time required to complete the storage of the user's electronic health record in the evaluation value of the user's electronic health record collection and storage process
[0037]
[0038] It should be noted that, as shown in the table, the greater the completeness ratio of the user's electronic health record content, the greater the evaluation value of the user's electronic health record collection and storage process, indicating that the collection and storage status of the user's electronic health record is better, and the user's electronic health record completion storage time is set to 29 unchanged, the user's electronic health record storage authentication times are set to 2 unchanged, the user's electronic health record storage completion reference time stored in the database is set to 60 unchanged, the user's electronic health record storage authentication limit times stored in the database is set to 4 unchanged, the user's electronic health record completion storage time is set to 0.3 unchanged, the user's electronic health record content completeness ratio is set to 0.3 unchanged, the user's electronic health record storage authentication times are set to 0.4 unchanged, only the size of the user's electronic health record content completeness ratio is changed, and the example values of the user's electronic health record content completeness ratio are as follows:
[0039] Table 2: Example values of the completeness ratio of the user's electronic health record content in the evaluation value of the user's electronic health record collection and storage process
[0040]
[0041] The family doctor who has made a successful appointment obtains the electronic health record of the user that has been successfully stored, uploads the medical report after diagnosis and treatment, obtains the medical report upload data set, and determines whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set.
[0042] Furthermore, the medical report upload data set specifically includes the network speed for medical report upload, the packet loss rate for medical report upload, and the length of time from successful appointment to medical report upload. The network speed for medical report upload refers to the transmission speed of the medical report when it is uploaded to the network. A fast network speed means that the medical report can be transmitted to the target location faster, which helps to improve the real-time and accuracy of medical information. A slower network speed may cause transmission delays, affecting the timeliness and availability of medical information. The packet loss rate for medical report upload indicates the proportion of data packets lost in the process of uploading medical reports. A high packet loss rate may cause incomplete or erroneous data transmission, affecting the integrity and accuracy of medical information. A lower packet loss rate helps to ensure the integrity and accuracy of medical reports. The length of time from successful appointment to medical report upload refers to the length of time from the user's successful appointment for medical services to the completion of medical report upload. This length of time reflects the efficiency and response speed of medical services. Shortening this period of time can improve user satisfaction and the efficiency of medical services, and also help with timely diagnosis and treatment.
[0043] In a specific embodiment, the speed of the network will directly affect the efficiency and speed of data transmission. Generally speaking, the faster the network speed, the lower the packet loss rate and the more stable the data transmission. If the network speed is slow, data packets may be lost, increasing the packet loss rate, thereby affecting the integrity and accuracy of the medical report. A high packet loss rate means that data may be lost or errors may occur during the data transmission process, which may require data to be retransmitted, thereby increasing the upload time. A high packet loss rate will extend the data transmission time and affect the overall time length from the successful appointment to the completion of the upload of the medical report. A fast network speed can usually shorten the data transmission time, thereby shortening the time length from the successful appointment to the completion of the upload of the medical report. A fast network speed helps to improve data transmission efficiency, reduce waiting time, and improve the response speed of medical services.
[0044] Specifically, based on the obtained medical report upload data set, it is determined whether the family doctor has successfully uploaded the medical report. The specific analysis process is: based on the obtained medical report upload data set, a medical report upload evaluation value is obtained through comprehensive analysis, and the medical report upload evaluation value is used as the analysis basis for determining whether the family doctor has successfully uploaded the medical report; the medical report upload evaluation value is compared with the medical report upload reference evaluation value stored in the database; if the medical report upload evaluation value is higher than or equal to the medical report upload reference evaluation value, the family doctor has successfully uploaded the medical report; if the medical report upload evaluation value is lower than the medical report upload reference evaluation value, the family doctor has not successfully uploaded the medical report and needs to upload it again.
[0045] It should be explained that the above comparison of evaluation values can automatically determine whether the medical report is successfully uploaded, thereby improving the efficiency of judgment. Especially in large-scale medical report uploading, automated judgment can save time and labor costs. The evaluation value may be based on a series of indicators and standards, which provides a relatively standardized and consistent judgment standard, which helps to ensure that all family doctors' uploading behaviors are subject to similar evaluation standards. Comparing the evaluation value with the reference evaluation value can provide feedback for continuous improvement. If the evaluation value is lower than the reference evaluation value, it means that the medical report upload process may need to be adjusted or improved to increase the success rate. Successfully uploaded medical reports can make medical data more accessible, which is crucial for medical staff, users and other medical institutions. It can obtain and share key medical information more quickly, thereby improving the quality and efficiency of medical services. Timely uploading of medical reports can help medical staff obtain the latest information from users more quickly, thereby better guiding medical decisions and treatment plans, and improving users' treatment effects and medical experience.
[0046] It should be explained that the above-mentioned judgment on whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set can help reduce human errors and inaccuracies in information transmission. The electronic record of the medical report can present the user's medical information more clearly and accurately, reduce information omissions and errors, and help family doctors to re-upload medical reports that failed to be uploaded in a timely manner, ensure that the medical report is viewed by the user in a timely manner, and improve the efficiency of medical services.
[0047] It should be explained that the above medical report uploads the evaluation value, and the specific analysis process is as follows:
[0048]
[0049] In the formula, γ is the evaluation value of medical report upload, WS is the network speed for medical report upload, DK is the packet loss rate for medical report upload, SC is the time length from successful appointment to medical report upload, WS0 is the reference network speed for medical report upload stored in the database, SC0 is the defined time length from successful appointment to medical report upload stored in the database, σ1 is the compensation factor for the set network speed for medical report upload, σ2 is the compensation factor for the set packet loss rate for medical report upload, σ3 is the compensation factor for the set time length from successful appointment to medical report upload, and e is a natural constant.
[0050] It needs to be explained that the above-mentioned medical report upload evaluation value is calculated through the network speed of medical report upload, the packet loss rate of medical report upload, and the length of time from the successful appointment to the upload of the medical report. Through the calculation of the evaluation value, the key indicators of medical report upload, such as network speed, packet loss rate and upload time length, can be monitored, so as to evaluate the efficiency and performance of the entire upload process. Through the analysis of the evaluation value, problems and bottlenecks in data upload can be discovered in time, and targeted optimization and improvement can be carried out to improve the upload speed and quality of medical reports. It can also help monitor problems such as packet loss rate during data transmission, ensure the security and accuracy of medical report data transmission, and reduce the risk of data loss or errors. Medical institutions and service providers can optimize medical service processes, improve medical report upload efficiency, reduce waiting time, and provide patients with a faster, more convenient and high-quality medical service experience. It can also improve data management efficiency and Utilizing value can help medical institutions better utilize and share medical information and improve the overall level of medical services. Network monitoring tools or speed test websites can be used to test the network speed of medical report uploads. These tools can provide real-time network speed data to help evaluate the speed of data upload. Network monitoring tools or network diagnostic tools can help monitor packet loss rates. These tools can provide information about packet loss rates during data transmission to help evaluate the stability of data transmission. By recording the timestamp of medical report uploads, the length of time required from successful appointment to completion of upload can be calculated. The medical reports stored in the database can be queried or exported from the database with reference to the upload network speed and time length to obtain historical data and reference values for medical report uploads. The compensation factors for the network speed, packet loss rate and time length of medical report uploads are set according to actual conditions and needs, and can be adjusted through system settings or configuration files.
[0051] After the family doctor successfully uploads the medical report, the user is reminded to evaluate the family doctor and obtain the user's feedback data set on the family doctor. Based on the obtained user's feedback data set on the family doctor, the family doctor is scored and recorded in the family doctor's personal page.
[0052] Specifically, the user feedback data set on family doctors includes the user feedback waiting time for medical treatment, the number of bytes of positive user feedback evaluations, and the proportion of the number of bytes of positive user feedback evaluations in the total number of evaluation bytes. The user feedback waiting time for medical treatment refers to the waiting time of the user during the medical treatment process, and is the user's subjective evaluation of the waiting time. This indicator can reflect the reasonable use of user time by medical institutions or family doctors during the service process, as well as service efficiency and user satisfaction. The number of bytes of positive user feedback evaluations refers to the positive and positive words or words used by users in their feedback evaluations. This indicator can reflect the user's satisfaction with medical services and the proportion of positive evaluations. The proportion of the number of bytes of positive user feedback evaluations in the total number of evaluation bytes refers to the proportion of users' positive evaluations in the total evaluations. This proportion can help medical institutions or family doctors understand the user's overall satisfaction with medical services and the weight of positive evaluations in the overall evaluation, so as to better improve and optimize the quality of medical services.
[0053] It needs to be explained that the above-mentioned long waiting time for medical treatment may lead to user dissatisfaction, thereby reducing the possibility of positive evaluation. Usually, when the waiting time for medical treatment is shorter, users are more likely to give positive evaluations. The proportion of positive evaluation words in the total evaluation words can reflect the user's overall satisfaction with the medical service. If the proportion of positive evaluation words is high, it means that the user is satisfied with the medical service. If the proportion of positive evaluation words is low, it may indicate that the user has more negative comments on the medical service. The waiting time for medical treatment may affect the user's overall evaluation. Long waiting time may lead to user dissatisfaction, thereby reducing the proportion of positive evaluation words in the total evaluation words. On the contrary, a shorter waiting time will usually make users more inclined to give positive evaluations, thereby increasing the proportion of positive evaluation words in the total evaluation words.
[0054] Furthermore, based on the obtained data set of user feedback on family doctors, family doctors are scored and recorded in the personal page of the family doctor. The specific analysis process is: based on the obtained data set of user feedback on family doctors, comprehensive analysis is performed to obtain user feedback characteristic values on family doctors, and the user feedback characteristic values on family doctors are used as the analysis basis for scoring family doctors; the user feedback characteristic values on family doctors are compared with the family doctor scores corresponding to the user feedback characteristic values of each user stored in the database to obtain the family doctor scores corresponding to the user feedback characteristic values; the family doctor scores corresponding to the compared user feedback characteristic values on family doctors are recorded in the personal page of the family doctor.
[0055] It needs to be explained that the above-mentioned feedback characteristic values based on users' feedback on family doctors can achieve targeted scoring. By comprehensively analyzing various indicators of user feedback, the service quality of family doctors can be more comprehensively evaluated, making the scoring more personalized and substantial. The user feedback data is imported into the scoring process to avoid the influence of subjective factors on the scoring. Based on objective data analysis, the service quality of family doctors can be evaluated more objectively, and the accuracy and credibility of the scoring can be improved. By comprehensively analyzing the user's feedback characteristic values and recording them on the family doctor's personal page according to the scoring results, important feedback information can be provided to medical institutions. Family doctors can understand users' evaluation of their services based on the scoring results, identify problems and make timely improvements, thereby improving the quality of medical services. Recording the scores corresponding to users' feedback characteristic values on family doctors on the doctor's personal page can provide users with a reference. Users can understand other users' evaluation of their family doctors by viewing the doctor's personal page, and then choose a suitable doctor for treatment, thereby enhancing the doctor-patient trust relationship.
[0056] It needs to be explained that the above-mentioned scoring of family doctors and recording it on the family doctor's personal page can improve the transparency and credibility of medical services. Users can easily view other users' evaluations of doctors, so that they can trust them more and choose doctors that suit them. They can understand the doctor's service quality by analyzing the scoring data, identify problems and take measures to improve them. Recording family doctors' scores can also help build trust and loyalty between doctors and users.
[0057] It should be explained that the specific analysis process of the above-mentioned user feedback characteristic values to the family doctor is as follows:
[0058]
[0059] In the formula, ω is the characteristic value of user feedback on family doctors, DT is the user feedback waiting time for medical treatment, HJ is the number of bytes of positive feedback from users, HB is the proportion of the number of bytes of positive feedback from users in the total number of evaluation bytes, DT0 is the user feedback waiting time for medical treatment permission stored in the database, HJ0 is the number of bytes of positive feedback from users stored in the database, τ1 is the compensation factor for the set user feedback waiting time for medical treatment, τ2 is the compensation factor for the set number of bytes of positive feedback from users, and τ3 is the compensation factor for the set proportion of the number of bytes of positive feedback from users in the total number of evaluation bytes.
[0060] It should be explained that the above-mentioned user feedback characteristic values on family doctors are calculated through user feedback on waiting time for consultation, the number of bytes of positive user feedback evaluations, and the proportion of the number of bytes of positive user feedback evaluations in the total number of evaluation bytes. Family doctors can promptly understand patients' evaluations of waiting time for consultation and service quality, which helps to timely adjust service processes and improve service quality. User feedback characteristic values provide objective evaluation indicators, which can quantify patients' satisfaction and dissatisfaction with family doctor services and help doctors better understand patients' needs and expectations. By paying attention to indicators such as waiting time for consultation and the number of bytes of positive user feedback in user feedback characteristic values, family doctors can improve services in a targeted manner, enhance patients' consultation experience, and increase patient satisfaction. Actively paying attention to and utilizing user feedback characteristic values can help family doctors improve their reputation and credibility, establish a good medical service brand image, and attract more When patients choose to see a doctor, user feedback characteristic values provide data support, which helps family doctors make decisions based on objective data, optimize service processes, improve service quality, and achieve continuous improvement. User feedback on waiting time for medical treatment is obtained through questionnaires filled out by users, online surveys or system records. The number of bytes of positive comments in user feedback evaluations counts the number of positive words used by users in the evaluation, and the proportion of the number of positive comments in the total number of comments is used to calculate the ratio of the number of positive comments to the total number of comments. The user feedback waiting time data and the number of words defined as positive comments in the user feedback evaluations stored in the database are queried or exported from the database. The compensation factor for the user feedback waiting time for medical treatment, the compensation factor for the number of positive comments in the user feedback evaluation, and the compensation factor for the proportion of the number of positive comments in the user feedback evaluation bytes in the total number of comments are obtained according to the values specified in the system settings or configuration files.
[0061] Reference Figure 2 As shown, the second aspect of the present invention provides a family doctor service information management system, including an electronic health record collection and storage module, a family doctor medical report upload module and a family doctor scoring module, wherein: the electronic health record collection and storage module is used to collect and store the user's electronic health record, obtain the user's electronic health record collection and storage process data set, and judge whether the user's electronic health record is successfully collected and stored based on the obtained user's electronic health record collection and storage process data set; the family doctor medical report upload module is used for the family doctor who has made a successful appointment to obtain the user's corresponding successfully stored electronic health record of the user, upload the medical report after diagnosis and treatment, obtain the medical report upload data set, and judge whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set; the family doctor scoring module is used to remind the user to evaluate the family doctor after the family doctor successfully uploads the medical report, obtain the user's feedback data set on the family doctor, and score the family doctor based on the obtained user's feedback data set on the family doctor, and record it to the family doctor's personal page.
[0062] The third aspect of the present invention provides a family doctor service information management electronic device, including a processor and a memory and a network interface connected to the processor, the network interface is connected to a non-volatile memory in a server, and the processor retrieves a computer program from the non-volatile memory through the network interface during operation, and runs the computer program through the memory.
[0063] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.
Claims
1. A family doctor service information management method, characterized in that: The following steps are involved: Collect and store the user's electronic health record, obtain a data set of the user's electronic health record collection and storage process, and determine whether the user's electronic health record is successfully collected and stored based on the obtained data set of the user's electronic health record collection and storage process; The family doctor who has made a successful appointment obtains the electronic health record of the user that has been successfully stored, uploads the medical report after diagnosis and treatment, obtains the medical report upload data set, and determines whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set; After the family doctor successfully uploads the medical report, the user is reminded to evaluate the family doctor and obtain the user's feedback data set on the family doctor. Based on the obtained user's feedback data set on the family doctor, the family doctor is scored and recorded in the family doctor's personal page.
2. A family doctor service information management method according to claim 1, characterized in that: The electronic health records of the user are collected and stored, and a data set of the collection and storage process of the electronic health records of the user is obtained. The specific analysis process is as follows: Collect the user's electronic health records, store the collected user's electronic health records, and obtain the user's electronic health record collection and storage process data set. The user's electronic health record collection and storage process data set specifically includes the user's electronic health record completion storage duration, the user's electronic health record content completeness ratio, and the user's electronic health record storage authentication times.
3. A family doctor service information management method according to claim 2, characterized in that: The process of determining whether the user's electronic health record is successfully collected and stored based on the obtained user's electronic health record collection and storage process data set is as follows: Based on the obtained data set of the user's electronic health record collection and storage process, a comprehensive analysis is performed to obtain an evaluation value of the user's electronic health record collection and storage process, and the evaluation value of the user's electronic health record collection and storage process is used as an analysis basis for judging whether the user's electronic health record is successfully collected and stored; Compare the evaluation value of the user's electronic health record collection and storage process with the reference evaluation value of the user's electronic health record collection and storage process stored in the database; If the evaluation value of the user's electronic health record collection and storage process is higher than or equal to the reference evaluation value of the user's electronic health record collection and storage process, the user's electronic health record collection and storage is successful; If the evaluation value of the user's electronic health record collection and storage process is lower than the reference evaluation value of the user's electronic health record collection and storage process, the user's electronic health record has not been collected and stored successfully and needs to be collected and stored again.
4. A family doctor service information management method according to claim 3, characterized in that: The user's electronic health record collects and stores the process evaluation value, and the specific analysis process is as follows: Wherein, δ is the evaluation value of the user's electronic health record collection and storage process, CT is the completion storage time of the user's electronic health record, WZ is the complete content ratio of the user's electronic health record, RN is the number of storage authentications of the user's electronic health record, CT0 is the reference time for the completion storage of the user's electronic health record stored in the database, RN0 is the number of storage authentications of the user's electronic health record stored in the database, μ1 is the compensation factor for the set completion storage time of the user's electronic health record, μ2 is the compensation factor for the set complete content ratio of the user's electronic health record, and μ3 is the compensation factor for the set number of storage authentications of the user's electronic health record.
5. A family doctor service information management method according to claim 1, characterized in that: The medical report upload data set specifically includes the medical report upload network speed, the medical report upload packet loss rate, and the length of time from the successful appointment of the medical report to the upload of the medical report.
6. A family doctor service information management method according to claim 5, characterized in that: Based on the obtained medical report upload data set, it is determined whether the family doctor has successfully uploaded the medical report. The specific analysis process is as follows: Based on the obtained medical report upload data set, a comprehensive analysis is performed to obtain a medical report upload evaluation value, which is used as an analysis basis for determining whether the family doctor has successfully uploaded the medical report; comparing the medical report uploaded evaluation value with the medical report uploaded reference evaluation value stored in the database; If the medical report upload assessment value is higher than or equal to the medical report upload reference assessment value, the family doctor successfully uploads the medical report; If the evaluation value uploaded in the medical report is lower than the reference evaluation value uploaded in the medical report, the family doctor has not successfully uploaded the medical report and needs to upload it again.
7. A family doctor service information management method according to claim 1, characterized in that: The user feedback data set on family doctors specifically includes the waiting time for consultation reported by users, the number of bytes of favorable evaluations reported by users, and the proportion of the number of bytes of favorable evaluations reported by users in the total number of bytes of evaluations.
8. A family doctor service information management method according to claim 7, characterized in that: Based on the obtained user feedback data set on family doctors, the family doctors are scored and recorded on the family doctor's personal page. The specific analysis process is as follows: Based on the obtained user feedback data set on family doctors, a comprehensive analysis is performed to obtain the user feedback feature values on family doctors, which are used as the analysis basis for scoring family doctors; Compare the user's feedback characteristic value on the family doctor with the family doctor score corresponding to each user's feedback characteristic value on the family doctor stored in the database to obtain the family doctor score corresponding to the user's feedback characteristic value on the family doctor; The family doctor score corresponding to the user's feedback characteristic value on the family doctor obtained by comparison is recorded in the family doctor's personal page.
9. A family doctor service information management system, characterized in that: A family doctor service information management method for any one of claims 1 to 8, comprising an electronic health record collection and storage module, a family doctor medical report upload module and a family doctor scoring module, wherein: The electronic health record collection and storage module is used to collect and store the user's electronic health record, obtain the user's electronic health record collection and storage process data set, and determine whether the user's electronic health record is successfully collected and stored based on the obtained user's electronic health record collection and storage process data set; The family doctor medical report upload module is used for the family doctor who has made a successful appointment to obtain the user's corresponding electronic health record that has been successfully stored, upload the medical report after diagnosis and treatment, obtain the medical report upload data set, and determine whether the family doctor has successfully uploaded the medical report based on the obtained medical report upload data set; The family doctor scoring module is used to remind users to evaluate their family doctors after they successfully upload medical reports, obtain user feedback data sets on family doctors, score family doctors based on the obtained user feedback data sets on family doctors, and record the scores on the family doctors' personal page.
10. An electronic device for managing family doctor service information, characterized in that: A family doctor service information management method as described in any one of claims 1 to 8, comprising a processor and a memory and a network interface connected to the processor, wherein the network interface is connected to a non-volatile memory in a server, and the processor retrieves a computer program from the non-volatile memory through the network interface during operation, and runs the computer program through the memory.