Medical care information integrated management system

Abstract

The invention discloses a medical care information comprehensive management system, relates to the technical field of medical care management, and aims to solve the problem that faster and more accurate medical judgment cannot be performed according to health data of a patient. By confirming the specific attributes of the non-health data, the system can accurately transmit the data to the corresponding medical personnel diagnosis center. The accuracy ensures that the data can be analyzed by medical personnel with relevant specialities, the accuracy and efficiency of diagnosis are improved, whether written diagnosis or home consultation is adopted can be automatically determined, more personalized and appropriate medical services are provided for patients, the satisfaction degree and the treatment effect of the patients are improved, and the patient experience is improved. Intelligent matching is carried out according to the residual capacity of each channel and the transmission quantity of the health data of the patient, it is ensured that the selected channel can meet the data transmission requirement, excessive network resources cannot be wasted, and the operation efficiency of the whole medical care system can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical care management, in particular to a medical care information integrated management system. Background Art

[0002] Healthcare management refers to the process of planning, organizing, directing and controlling the operations, finances, human resources, and service quality of a healthcare institution or healthcare system.

[0003] Patent application with publication number CN114144844A discloses a system and method for reducing the actions required by a patient to advance his or her healthcare, mainly by receiving patient health data about the patient through a health management system; the health management system analyzes the patient health data to determine the healthcare products required by the patient; the health management system determines the specific provider of the healthcare products; the health management system generates a healthcare product ordering interface, which includes information about the healthcare products and a non-ordering control; in response to determining that the non-ordering control is not activated, generates a product order and transmits the product order to a provider system of a specific provider. Although the above solution solves the problem of medical management, the following problems still exist in actual operation: 1. The patient's health data is not monitored and collected through more methods, resulting in inaccurate patient health data.

[0004] 2. After obtaining the patient's health data, the data is not promptly transmitted to medical institutions for professionals to make professional judgments, resulting in misdiagnosis of the patient.

[0005] 3. The patient’s health data is not used for targeted decision-making, resulting in poor treatment results. Summary of the invention

[0006] The purpose of the present invention is to provide a comprehensive management system for medical care information, which can confirm the specific attributes of non-health data, and the system can accurately transmit the data to the corresponding medical personnel diagnosis center. This accuracy ensures that the data can be analyzed by medical personnel with relevant expertise, improves the accuracy and efficiency of diagnosis, and can automatically decide whether to take a written diagnosis or a home consultation, providing patients with more personalized and appropriate medical services, improving patient satisfaction and treatment effects, and intelligently matching according to the remaining capacity of each channel and the transmission volume of the patient's health data to ensure that the selected channel can meet the data transmission requirements without wasting too much network resources, which helps to improve the operating efficiency of the entire medical care system and can solve the problems in the prior art.

[0007] To achieve the above object, the present invention provides the following technical solutions: A comprehensive medical care information management system, comprising: Patient health monitoring units for: Conduct health monitoring and health inquiries on patients, and classify the health data of patients according to the data types of health monitoring and health inquiries. After the classification is completed, unique coding and labeling are performed. After the unique coding and labeling are completed, the health data of patients is obtained; Medical institution docking unit for: Transmit the patient's health data to the connected medical institution. At the same time, the patient's health data is transmitted through the fastest transmission channel; Monitoring data consultation unit, used for: The medical institution receives the patient's health data, monitors and judges the received patient's health data, makes a consultation decision based on the judgment result, generates a health report based on the judgment result and the consultation decision, and transmits the health report to the patient's mobile terminal for display; Health care push unit for: The patient checks his / her health on the mobile terminal according to the generated health report, and the patient conducts online consultation on the mobile terminal according to the health report.

[0008] Preferably, the patient health monitoring unit comprises: Health data acquisition module: Collect health data from patients using smart measuring devices or by regular inquiries from staff; Health data includes blood pressure data, blood sugar data, heart rate data, body temperature data, electrocardiogram data and blood oxygen saturation data; Among them, smart measuring devices include smart blood pressure monitors, smart blood glucose meters, smart watches, smart thermometers and smart ECG monitoring devices; The smart blood pressure monitor collects blood pressure data; the smart blood glucose meter collects blood glucose data; the smart watch collects blood oxygen saturation data and heart rate data; the smart thermometer collects body temperature data; the smart ECG monitoring device collects ECG data; Regular inquiries by staff means that staff will collect data through home visits regularly according to the set time, and staff will wear monitoring equipment by themselves; Smart measuring devices and monitoring equipment worn by staff members collect patients' health data and uniformly mark them as original health data.

[0009] Preferably, the patient health monitoring unit further comprises: Health data classification and labeling module for: Classify the original health data according to the attributes of the data, and uniquely code and label them after classification; The unique code labeling process is: Confirm the coding structure rules of the original health data, wherein the coding structure rules include prefix, timestamp and sequence number; The prefix is ​​a fixed name generated according to the attributes of the original health data classification; the timestamp is the time when the original health data is generated; the sequence number is a number used to distinguish different records of the original health data under the same timestamp; After the coding structure rules are confirmed, the unique code of the original health data is obtained, and the original health data with the unique coding label is marked as the patient's health data.

[0010] Preferably, the medical institution docking unit comprises: Monitoring data import module, used for: Import the patient's health data into the patient's mobile terminal, wherein the data collected by the smart measuring device is transmitted to the patient's mobile terminal via Bluetooth, and the data regularly inquired by the staff is input into the patient's mobile terminal by the staff; The patient's mobile terminal connects signals with the medical institution; After signal docking is completed, preparations for patient health data transmission are made.

[0011] Preferably, the medical institution docking unit further includes: Monitoring data transmission module, used for: When patient health data is transmitted from the patient's mobile terminal to the medical institution, the transmission channel with the fastest transmission speed is automatically selected; Among them, the patient health data is first divided into sections, and the patient health data is divided into several sections of the same length; Calculate the amount of patient health data transmitted based on the paragraph data; There are no fewer than four transmission channels from the patient’s mobile terminal to the medical institution; Confirm the remaining capacity of each transmission channel; A transmission channel whose transmission amount of patient health data is less than the remaining capacity of the channel is selected as the transmission channel for transmitting the patient health data from the mobile terminal to the medical institution.

[0012] Preferably, the monitoring data transmission module includes: A real-time monitoring module, used to monitor in real time the data transmission operation parameters of the patient's health data transmitted from the mobile terminal to the medical institution; The data transmission operation parameters include the amount of other data transmitted in parallel by the transmission channel in the process of transmitting the patient health data, as well as the data transmission rate of the patient health data and the data transmission rate of other data transmitted in parallel in addition to the patient health data; A data volume information extraction module, used to extract the data volume of other data transmitted in parallel with the patient health data corresponding to each unit time during the patient health data transmission process; wherein the unit time is 1s; A first data transmission evaluation coefficient acquisition module, used to obtain a first data transmission evaluation coefficient by combining the data amount of other data transmitted in parallel except for the patient health data corresponding to each unit time during the patient health data transmission process with the data amount of data transmitted per unit time during the patient health data transmission process; The first data transmission evaluation coefficient is obtained by the following formula: Among them, R 01 represents the first data transmission evaluation coefficient; n represents the number of unit times that the patient's health data transmission process has experienced; C 01i represents the amount of patient health data transmitted corresponding to the i-th unit time; C 02i represents the amount of other data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; C yi represents the remaining capacity of the transmission channel corresponding to the i-th unit time; C 02b represents the standard deviation of the amount of other data transmitted in parallel with the patient health data during the n unit time of the patient health data transmission process; C 01b represents the standard deviation of the data volume corresponding to n unit time experienced in the patient health data transmission process; r represents the first adjustment coefficient, and the adjustment coefficient is obtained by the following formula: Wherein, r represents the first adjustment coefficient; n represents the number of unit times that the patient health data transmission process has experienced; C 01i represents the amount of patient health data transmitted corresponding to the i-th unit time; C 02i represents the amount of other data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; C yi represents the remaining capacity of the transmission channel corresponding to the i-th unit time; A first comparison module, configured to compare the first data transmission evaluation coefficient with a preset first coefficient threshold; The quality evaluation module is used to evaluate the data transmission quality of the patient health data by using the data transmission rate of the patient health data and the data transmission rate of other data transmitted in parallel with the patient health data when the first data transmission evaluation coefficient exceeds a preset first coefficient threshold.

[0013] Preferably, the quality evaluation module includes: A first data transmission rate information extraction module is used to extract the data transmission rate corresponding to each unit time during the patient health data transmission process; A second data transmission rate information extraction module is used to extract the data transmission rate per unit time corresponding to other data transmitted in parallel except for the patient health data; A second data transmission evaluation coefficient acquisition module, used to acquire a second data transmission evaluation coefficient by using a data transmission rate of the patient health data and a data transmission rate of other data transmitted in parallel except for the patient health data; The second data transmission evaluation coefficient is obtained by the following formula: Among them, R 02 represents the second data transmission evaluation coefficient; n represents the number of unit times that the patient health data transmission process has experienced; m represents the number of other data transmitted in parallel in addition to the patient health data corresponding to each unit time; V 01i V represents the data transmission rate of the patient's health data corresponding to the i-th unit time; 02ij=1 、V 02ij=2 ,……,V 02ij=m They represent the data transmission rates corresponding to the 1st, 2nd, ...mth data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; V 02ip V represents the average data transmission rate of m other data transmitted in parallel in addition to the patient health data in the i-th unit time; 01bi and V 02bi represents the data transmission rate standard deviation of the patient health data in the i-th unit time and the average value of the data transmission rate standard deviation of m other data transmitted in parallel except for the patient health data; f represents the second adjustment coefficient, and the second adjustment coefficient is obtained by the following formula: Wherein, f represents the second adjustment coefficient; V 01bi V represents the standard deviation of the data transmission rate of the patient's health data per unit time; 02bimax represents the maximum value of the standard deviation of the data transmission rate of m other data transmitted in parallel except for the patient's health data; V 02bimin represents the minimum standard deviation of the data transmission rate of m other data transmitted in parallel except for the patient health data; A second comparison module, used for comparing the second data transmission evaluation coefficient with a preset second coefficient threshold; The abnormality determination and alarm module is used to determine that there is an abnormality in the data transmission of the patient health data and to issue an abnormality alarm when the second data transmission evaluation coefficient exceeds a preset second coefficient threshold.

[0014] Preferably, the monitoring data consultation unit comprises: Health data judgment module, used for: The medical institution receives the patient's health data and makes an abnormality judgment after receiving the patient's health data; Among them, the blood pressure data, blood sugar data, heart rate data, body temperature data, electrocardiogram data and blood oxygen saturation data in the patient's health data are respectively converted into curve data, and the curve health data is obtained after the conversion; Overlap and compare the curve health data with the standard curve data; According to the overlapping comparison results, qualified data, low data and high data are obtained; Among them, when the low data is an overlapping comparison, the healthy data of the curve is lower than the data area of ​​the standard curve data; when the high data is an overlapping comparison, the healthy data of the curve is higher than the data area of ​​the standard curve data; Low data and high data are marked as unhealthy data and stored separately.

[0015] Preferably, the monitoring data consultation unit further includes: Judgment data consultation module, used for: Medical institutions confirm the specific attributes of non-health data; According to the specific attributes of the non-health data, the non-health data is transmitted to the corresponding medical personnel diagnosis center for corresponding diagnosis; Medical personnel make diagnostic decisions based on abnormal thresholds of non-health data; Diagnostic decision-making is based on the degree of abnormality of non-healthy data; When the abnormal thresholds of low and high data in non-health data do not exceed 20%, a written diagnosis will be conducted; when the abnormal thresholds of low and high data in non-health data exceed 20%, a home consultation will be conducted; A health report is generated based on the diagnosis decision results and transmitted to the patient's mobile terminal.

[0016] Preferably, the health care push unit is also used for: The patient checks the health report on the mobile terminal and confirms the final treatment method based on the results; Among them, the purchase of medicines is based on the written diagnosis results, and the consultation time is confirmed based on the results of the home consultation; At the same time, patients can conduct online consultations on mobile terminals based on their health reports.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention provides a comprehensive management system for medical care information. The use of intelligent measuring instruments automates the data collection process, can instantly obtain the patient's health data, reduces manual intervention and waiting time, and improves the efficiency of data collection. By formulating a unified coding structure rule for the original health data, relevant information can be quickly retrieved, greatly improving work efficiency. Through the timestamp and serial number in the coding structure, the generation time and source of the data can be traced, enhancing the security and credibility of the data.

[0018] 2. The present invention provides a comprehensive management system for medical care information, which intelligently matches the remaining capacity of each channel and the transmission volume of the patient's health data to ensure that the selected channel can meet the data transmission requirements without wasting too much network resources. This way of optimizing resource utilization helps to improve the operating efficiency of the entire medical care system, and realizes the remote transmission and sharing of patient health data through the signal connection between the patient's mobile terminal and the medical institution.

[0019] 3. The present invention provides a comprehensive management system for medical care information. By confirming the specific attributes of non-health data, the system can accurately transmit the data to the corresponding medical personnel diagnosis center. This accuracy ensures that the data can be analyzed by medical personnel with relevant expertise, improves the accuracy and efficiency of diagnosis, and can automatically decide whether to take a written diagnosis or a home consultation, providing patients with more personalized and appropriate medical services. This customized processing method improves patient satisfaction and treatment effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a comprehensive management unit for medical care information of the present invention; Figure 2 It is a schematic diagram of the integrated management process of medical care information of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] In order to solve the problem that the existing technology does not monitor and collect the patient's health data through more methods, resulting in inaccurate patient health data, please refer to Figure 1 and Figure 2, this embodiment provides the following technical solutions: A comprehensive medical care information management system, comprising: Patient health monitoring units for: Conduct health monitoring and health inquiries on patients, and classify the health data of patients according to the data types of health monitoring and health inquiries. After the classification is completed, unique coding and labeling are performed. After the unique coding and labeling are completed, the health data of patients is obtained; Medical institution docking unit for: Transmit the patient's health data to the connected medical institution. At the same time, the patient's health data is transmitted through the fastest transmission channel; Monitoring data consultation unit, used for: The medical institution receives the patient's health data, monitors and judges the received patient's health data, makes a consultation decision based on the judgment result, generates a health report based on the judgment result and the consultation decision, and transmits the health report to the patient's mobile terminal for display; Health care push unit for: The patient checks his / her health on the mobile terminal according to the generated health report, and the patient conducts online consultation on the mobile terminal according to the health report.

[0023] Specifically, the patient health monitoring unit can trace the generation time and source of the data, enhancing the security and credibility of the data; the medical institution docking unit can connect the patient's mobile terminal with the signal of the medical institution, realizing the remote transmission and sharing of the patient's health data; the monitoring data consultation unit ensures that the data can be analyzed by medical personnel with relevant expertise, improving the accuracy and efficiency of diagnosis; and the health care push unit allows patients to view health reports in detail, including diagnostic results, examination data, etc., which helps to have a more comprehensive understanding of their health status.

[0024] Patient health monitoring unit, including: Health data acquisition module: Collect health data from patients using smart measuring devices or by regular inquiries from staff; Health data includes blood pressure data, blood sugar data, heart rate data, body temperature data, electrocardiogram data and blood oxygen saturation data; Among them, smart measuring devices include smart blood pressure monitors, smart blood glucose meters, smart watches, smart thermometers and smart ECG monitoring devices; The smart blood pressure monitor collects blood pressure data; the smart blood glucose meter collects blood glucose data; the smart watch collects blood oxygen saturation data and heart rate data; the smart thermometer collects body temperature data; the smart ECG monitoring device collects ECG data; Regular inquiries by staff means that staff will collect data through home visits regularly according to the set time, and staff will wear monitoring equipment by themselves; Smart measuring devices and monitoring equipment worn by staff members collect patients' health data and uniformly mark them as original health data.

[0025] Health data classification and labeling module for: Classify the original health data according to the attributes of the data, and uniquely code and label them after classification; The unique code labeling process is: Confirm the coding structure rules of the original health data, wherein the coding structure rules include prefix, timestamp and sequence number; The prefix is ​​a fixed name generated according to the attributes of the original health data classification; the timestamp is the time when the original health data is generated; the sequence number is a number used to distinguish different records of the original health data under the same timestamp; After the coding structure rules are confirmed, the unique code of the original health data is obtained, and the original health data with the unique coding label is marked as the patient's health data.

[0026] Specifically, the health data acquisition module is used to monitor the health data of patients. The use of smart meters automates the data collection process, can obtain the health data of patients in real time, reduces manual intervention and waiting time, and improves the efficiency of data collection. The real-time monitoring function (such as the continuous monitoring of blood oxygen saturation and heart rate by smart watches) helps to timely discover abnormal health conditions of patients, and wins precious time for timely intervention and treatment. Smart meters usually have a convenient operation interface and a simple use process, which can be easily used by patients or their families, reducing the threshold for use. After the original health data is collected, it can be further analyzed and mined through the comprehensive management system of medical and health information, providing doctors with key information such as trend analysis and abnormal warning of patients' health status. The monitored data is further analyzed and processed through the health data classification and labeling module, and the standardization and normalization of data is achieved by formulating a unified coding structure rule for the original health data. This not only facilitates the storage, retrieval and management of data, but also improves the consistency and comparability of data, laying a solid foundation for subsequent data analysis and mining. The unique coding label enables each patient's health data to be quickly and accurately located. When you need to query or analyze the health data of a specific patient, you can quickly retrieve relevant information through the code, which greatly improves work efficiency. Through the timestamp and serial number in the coding structure, you can trace the generation time and source of the data, which enhances the security and credibility of the data. At the same time, the unique code also reduces the risk of data tampering or misuse.

[0027] In order to solve the problem in the prior art that after obtaining the patient's health data, the data is not promptly transmitted to the medical institution for professionals to make professional judgments, thus causing the patient to be misdiagnosed, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: Medical institution docking unit, including: Monitoring data import module, used for: Import the patient's health data into the patient's mobile terminal, wherein the data collected by the smart measuring device is transmitted to the patient's mobile terminal via Bluetooth, and the data regularly inquired by the staff is input into the patient's mobile terminal by the staff; The patient's mobile terminal connects signals with the medical institution; After signal docking is completed, preparations for patient health data transmission are made.

[0028] Monitoring data transmission module, used for: When patient health data is transmitted from the patient's mobile terminal to the medical institution, the transmission channel with the fastest transmission speed is automatically selected; Among them, the patient health data is first divided into sections, and the patient health data is divided into several sections of the same length; Calculate the amount of patient health data transmitted based on the paragraph data; There are no fewer than four transmission channels from the patient’s mobile terminal to the medical institution; Confirm the remaining capacity of each transmission channel; A transmission channel whose transmission amount of patient health data is less than the remaining capacity of the channel is selected as the transmission channel for transmitting the patient health data from the mobile terminal to the medical institution.

[0029] Specifically, by automatically selecting the channel with the fastest transmission speed, it can ensure that the patient's health data can be transmitted from the patient's mobile terminal to the medical institution at the fastest speed. This method of dynamically selecting the optimal channel reduces the delay of data transmission, allowing medical institutions to obtain the patient's latest health data more quickly, so that they can make diagnosis or treatment decisions more quickly. Among multiple available channels, the system intelligently matches the remaining capacity of each channel and the transmission volume of the patient's health data to ensure that the selected channel can meet the data transmission requirements without wasting too many network resources. This method of optimizing resource utilization helps to improve the operating efficiency of the entire healthcare system. Dividing the patient's health data into several sections of the same length and transmitting them one by one can effectively reduce the risk of data loss or damage caused by transmission interruptions or errors. Even if a problem occurs in the data of a certain section during transmission, only the section can be retransmitted without retransmitting the entire data packet, thereby ensuring the integrity and accuracy of the data. Through the signal docking between the patient's mobile terminal and the medical institution, the remote transmission and sharing of the patient's health data is realized. This provides strong support for new medical service models such as telemedicine and remote consultation, so that patients can enjoy high-quality medical services even in remote areas.

[0030] Specifically, the monitoring data transmission module includes: A real-time monitoring module, used to monitor in real time the data transmission operation parameters of the patient's health data transmitted from the mobile terminal to the medical institution; The data transmission operation parameters include the amount of other data transmitted in parallel by the transmission channel in the process of transmitting the patient health data, as well as the data transmission rate of the patient health data and the data transmission rate of other data transmitted in parallel in addition to the patient health data; A data volume information extraction module, used to extract the data volume of other data transmitted in parallel with the patient health data corresponding to each unit time during the patient health data transmission process; wherein the unit time is 1s; A first data transmission evaluation coefficient acquisition module, used to obtain a first data transmission evaluation coefficient by combining the data amount of other data transmitted in parallel except for the patient health data corresponding to each unit time during the patient health data transmission process with the data amount of data transmitted per unit time during the patient health data transmission process; The first data transmission evaluation coefficient is obtained by the following formula: Among them, R 01 represents the first data transmission evaluation coefficient; n represents the number of unit times that the patient's health data transmission process has experienced; C01i represents the amount of patient health data transmitted corresponding to the i-th unit time; C 02i represents the amount of other data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; C yi represents the remaining capacity of the transmission channel corresponding to the i-th unit time; C 02b represents the standard deviation of the amount of other data transmitted in parallel with the patient health data during the n unit time of the patient health data transmission process; C 01b represents the standard deviation of the data volume corresponding to n unit time experienced in the patient health data transmission process; r represents the first adjustment coefficient, and the adjustment coefficient is obtained by the following formula: Wherein, r represents the first adjustment coefficient; n represents the number of unit times that the patient health data transmission process has experienced; C 01i represents the amount of patient health data transmitted corresponding to the i-th unit time; C 02i represents the amount of other data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; C yi represents the remaining capacity of the transmission channel corresponding to the i-th unit time; A first comparison module, configured to compare the first data transmission evaluation coefficient with a preset first coefficient threshold; The quality evaluation module is used to evaluate the data transmission quality of the patient health data by using the data transmission rate of the patient health data and the data transmission rate of other data transmitted in parallel with the patient health data when the first data transmission evaluation coefficient exceeds a preset first coefficient threshold.

[0031] The technical effect of the above technical solution is: through the real-time monitoring module, it is possible to track in real time various operating parameters of the data transmission process of the patient's health data from the mobile terminal to the medical institution, including the amount of other data transmitted in parallel, the data transmission rate of the patient's health data, etc., which provides a detailed data basis for the subsequent data transmission quality evaluation. With the help of the first data transmission evaluation coefficient acquisition module and the first comparison module, the first data transmission evaluation coefficient can be calculated using the real-time collected data, and compared with the preset threshold, so as to achieve an accurate evaluation of the data transmission quality.

[0032] The first adjustment coefficient in the technical solution is obtained by a complex calculation formula, which takes into account multiple factors such as the amount of data per unit time during the patient's health data transmission process, the amount of data of other data transmitted in parallel, and the remaining capacity of the transmission channel, so that the evaluation coefficient can dynamically adapt to different data transmission scenarios and conditions. This dynamic adaptability helps to improve the accuracy and applicability of the evaluation and can more accurately reflect the actual situation during the data transmission process. When the first data transmission evaluation coefficient exceeds the preset first coefficient threshold, the quality evaluation module will immediately intervene to evaluate the data transmission quality of the patient's health data using the data transmission rate of the patient's health data and the data transmission rate of other data transmitted in parallel. This evaluation method not only takes into account the rate of data transmission, but also takes into account the possible impact of other data transmitted in parallel on the data transmission quality, so as to more comprehensively and accurately evaluate the quality of data transmission. Through this technical solution, problems in the data transmission process, such as decreased transmission rate, channel congestion caused by excessive data volume, etc., can be discovered in time, thereby providing strong support for optimizing the data transmission process. Medical institutions can adjust the data transmission strategy according to the evaluation results, such as increasing channel capacity, optimizing data transmission algorithms, etc., to improve the efficiency and quality of data transmission. At the same time, the application of this technical solution helps to improve the management level of patient health data, ensure the accurate and timely transmission of data, and provide reliable data support for clinical decision-making and scientific research analysis of medical institutions. In addition, by optimizing the data transmission process, it can also reduce the error rate and loss rate in the data transmission process, and improve the integrity and availability of patient health data.

[0033] In summary, this technical solution effectively improves the efficiency and quality of patient health data transmission by real-time monitoring of data transmission operating parameters, dynamic calculation of evaluation coefficients, efficient evaluation of data transmission quality, and optimization of data transmission processes, providing medical institutions with more reliable and accurate data support.

[0034] Specifically, the quality evaluation module includes: A first data transmission rate information extraction module is used to extract the data transmission rate corresponding to each unit time during the patient health data transmission process; A second data transmission rate information extraction module is used to extract the data transmission rate per unit time corresponding to other data transmitted in parallel except for the patient health data; A second data transmission evaluation coefficient acquisition module, used to acquire a second data transmission evaluation coefficient by using a data transmission rate of the patient health data and a data transmission rate of other data transmitted in parallel except for the patient health data; The second data transmission evaluation coefficient is obtained by the following formula: Among them, R 02 represents the second data transmission evaluation coefficient; n represents the number of unit times that the patient health data transmission process has experienced; m represents the number of other data transmitted in parallel in addition to the patient health data corresponding to each unit time; V 01i V represents the data transmission rate of the patient's health data corresponding to the i-th unit time; 02ij=1 、V 02ij=2 ,……,V 02ij=m They represent the data transmission rates corresponding to the 1st, 2nd, ...mth data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; V 02ip V represents the average data transmission rate of m other data transmitted in parallel in addition to the patient health data in the i-th unit time; 01bi and V 02bi represents the data transmission rate standard deviation of the patient health data in the i-th unit time and the average value of the data transmission rate standard deviation of m other data transmitted in parallel except for the patient health data; f represents the second adjustment coefficient, and the second adjustment coefficient is obtained by the following formula: Wherein, f represents the second adjustment coefficient; V 01bi V represents the standard deviation of the data transmission rate of the patient's health data per unit time; 02bimax represents the maximum value of the standard deviation of the data transmission rate of m other data transmitted in parallel except for the patient's health data; V 02bimin represents the minimum standard deviation of the data transmission rate of m other data transmitted in parallel except for the patient health data; A second comparison module, used for comparing the second data transmission evaluation coefficient with a preset second coefficient threshold; The abnormality determination and alarm module is used to determine that there is an abnormality in the data transmission of the patient health data and to issue an abnormality alarm when the second data transmission evaluation coefficient exceeds a preset second coefficient threshold.

[0035] The technical effect of the above technical solution is: through the first data transmission rate information extraction module and the second data transmission rate information extraction module, the data transmission rate of the patient's health data and other data transmitted in parallel in each unit time can be extracted respectively, which provides accurate data support for the subsequent data transmission evaluation. The second data transmission evaluation coefficient acquisition module uses the data transmission rate of the patient's health data and other data transmitted in parallel, combined with other relevant parameters (such as data transmission rate standard deviation, average value, etc.), and obtains the second data transmission evaluation coefficient through a complex calculation formula. This coefficient not only takes into account the rate of data transmission, but also takes into account the stability and volatility of the rate, so that the quality of data transmission can be evaluated more comprehensively and accurately. The calculation formula of the second adjustment coefficient takes into account the maximum and minimum values ​​of the standard deviation of the data transmission rate of the patient's health data and the standard deviation of the data transmission rate of other data transmitted in parallel, which enables the evaluation coefficient to dynamically adapt to different data transmission scenarios and conditions, thereby improving the accuracy and applicability of the evaluation.

[0036] When the second data transmission evaluation coefficient exceeds the preset second coefficient threshold, the abnormality determination and alarm module will immediately determine that there is an abnormality in the data transmission and issue an alarm. This helps to promptly discover and solve problems that may arise during data transmission, ensuring accurate and timely transmission of data. Through this technical solution, medical institutions can more accurately grasp the actual situation of data transmission, and optimize the data transmission process according to the evaluation results, such as adjusting the data transmission rate, optimizing the data transmission algorithm, etc., to improve the efficiency and quality of data transmission. The application of this technical solution helps to improve the management level of patient health data and ensure the integrity, accuracy and availability of data. This helps medical institutions better use patient health data for clinical decision-making and scientific research analysis, and improve the quality and efficiency of medical services.

[0037] In summary, this technical solution effectively improves the efficiency and quality of patient health data transmission through detailed data transmission rate monitoring, comprehensive data transmission quality evaluation, introduction of dynamic adjustment coefficients, timely abnormality judgment and alarm, and optimization of data transmission processes and strategies, providing medical institutions with more reliable and accurate data support.

[0038] In order to solve the problem that the existing technology does not use the patient's health data for targeted decision-making, resulting in poor treatment results, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: Monitoring data consultation unit, including: Health data judgment module, used for: The medical institution receives the patient's health data and makes an abnormality judgment after receiving the patient's health data; Among them, the blood pressure data, blood sugar data, heart rate data, body temperature data, electrocardiogram data and blood oxygen saturation data in the patient's health data are respectively converted into curve data, and the curve health data is obtained after the conversion; Overlap and compare the curve health data with the standard curve data; According to the overlapping comparison results, qualified data, low data and high data are obtained; Among them, when the low data is an overlapping comparison, the healthy data of the curve is lower than the data area of ​​the standard curve data; when the high data is an overlapping comparison, the healthy data of the curve is higher than the data area of ​​the standard curve data; Low data and high data are marked as unhealthy data and stored separately.

[0039] Judgment data consultation module, used for: Medical institutions confirm the specific attributes of non-health data; According to the specific attributes of the non-health data, the non-health data is transmitted to the corresponding medical personnel diagnosis center for corresponding diagnosis; Medical personnel make diagnostic decisions based on abnormal thresholds of non-health data; Diagnostic decision-making is based on the degree of abnormality of non-healthy data; When the abnormal thresholds of low and high data in non-health data do not exceed 20%, a written diagnosis will be conducted; when the abnormal thresholds of low and high data in non-health data exceed 20%, a home consultation will be conducted; A health report is generated based on the diagnosis decision results and transmitted to the patient's mobile terminal.

[0040] Specifically, by converting the patient's key health indicators such as blood pressure, blood sugar, heart rate, body temperature, electrocardiogram and blood oxygen saturation into curve data and overlapping and comparing them with the standard curve, it can more intuitively and accurately reflect whether the patient's health status is within the normal range. Compared with a single numerical judgment, this curve comparison-based method can better capture the subtle changes and trends of health data, thereby providing a more accurate health assessment. By comparing the patient's health data with the standard curve in real time or regularly, the system can promptly detect abnormal data (low data or high data) and mark it as non-healthy data for separate storage. This helps medical personnel to obtain early warning information in a timely manner, intervene in possible health problems of patients at an early stage, avoid deterioration of the disease, and improve treatment effects. Since the standard curves for different patients and different stages of the disease may be different, the solution allows the standard curve to be set or adjusted according to the patient's specific situation, thereby achieving personalized health management. This helps to provide patients with more accurate and effective medical advice and care plans. By confirming the specific attributes of non-healthy data, the system can accurately transmit data to the corresponding medical personnel diagnosis center. This precision ensures that the data can be analyzed by medical personnel with relevant expertise, improving the accuracy and efficiency of diagnosis. The entire process from data confirmation and transmission to diagnostic decision-making is automated or semi-automated, greatly reducing the time and possible errors of manual operations, and improving the processing speed and efficiency of health care services. According to the abnormality of non-health data (such as the abnormal threshold of low data and high data), the system can automatically decide whether to take a written diagnosis or home consultation, providing patients with more personalized and appropriate medical services. This customized processing method improves patient satisfaction and treatment effects. When non-health data is abnormal, especially when the abnormal threshold exceeds the preset standard, the system can quickly trigger the corresponding response mechanism (such as home consultation), ensuring that the problem can be solved in a timely manner and reducing the risk of worsening of the disease. The introduction of home consultation promotes the application of telemedicine services, allowing patients to obtain professional medical services without going to the hospital in person, which is of great significance, especially for patients with limited mobility or in remote areas.

[0041] Health care push unit, also used for: The patient checks the health report on the mobile terminal and confirms the final treatment method based on the results; Among them, the purchase of medicines is based on the written diagnosis results, and the consultation time is confirmed based on the results of the home consultation; At the same time, patients can conduct online consultations on mobile terminals based on their health reports.

[0042] Specifically, patients are no longer restricted by location and time, and can view their health reports through mobile terminals anytime and anywhere, which greatly improves the convenience of medical treatment. Patients can immediately make preliminary treatment decisions based on health reports, such as whether to purchase specific medications or confirm consultation times, thereby speeding up the diagnosis and treatment process. Patients can view health reports in detail, including diagnostic results, examination data, etc., which helps to understand their health status more comprehensively. By viewing health reports and conducting online consultations, patients can more actively participate in their own treatment process and improve treatment satisfaction and compliance.

[0043] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0044] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A medical care information integrated management system, characterized in that: include: Patient health monitoring units for: Conduct health monitoring and health inquiries on patients, and classify the health data of patients according to the data types of health monitoring and health inquiries. After the classification is completed, unique coding and labeling are performed. After the unique coding and labeling are completed, the health data of patients is obtained; Medical institution docking unit, used for: Transmit the patient's health data to the connected medical institution. At the same time, the patient's health data is transmitted through the fastest transmission channel; Monitoring data consultation unit, used for: The medical institution receives the patient's health data, monitors and judges the received patient's health data, makes a consultation decision based on the judgment result, generates a health report based on the judgment result and the consultation decision, and transmits the health report to the patient's mobile terminal for display; Health care push unit for: The patient checks his / her health on the mobile terminal according to the generated health report, and the patient conducts online consultation on the mobile terminal according to the health report.

2. A medical care information integrated management system according to claim 1, characterized in that: The patient health monitoring unit comprises: Health data acquisition module: Collect health data from patients using smart measuring devices or by regular inquiries from staff; Health data includes blood pressure data, blood sugar data, heart rate data, body temperature data, electrocardiogram data and blood oxygen saturation data; Among them, smart measuring devices include smart blood pressure monitors, smart blood glucose meters, smart watches, smart thermometers and smart ECG monitoring devices; The smart blood pressure monitor collects blood pressure data; the smart blood glucose meter collects blood glucose data; the smart watch collects blood oxygen saturation data and heart rate data; the smart thermometer collects body temperature data; the smart ECG monitoring device collects ECG data; Regular inquiries by staff means that staff will collect data through home visits regularly according to the set time, and staff will wear monitoring equipment by themselves; Smart measuring devices and monitoring equipment worn by staff members collect patients' health data and uniformly mark them as original health data.

3. A medical care information integrated management system according to claim 2, characterized in that: The patient health monitoring unit further comprises: Health data classification and labeling module for: Classify the original health data according to the attributes of the data, and uniquely code and label them after classification; The unique code labeling process is: Confirm the coding structure rules of the original health data, wherein the coding structure rules include prefix, timestamp and sequence number; The prefix is ​​a fixed name generated according to the attributes of the original health data classification; the timestamp is the time when the original health data was generated; the sequence number is a number used to distinguish different records of the original health data under the same timestamp; After the coding structure rules are confirmed, the unique code of the original health data is obtained, and the original health data with the unique coding label is marked as the patient's health data.

4. A medical care information integrated management system according to claim 3, characterized in that: The medical institution docking unit comprises: Monitoring data import module, used for: Import the patient's health data into the patient's mobile terminal, wherein the data collected by the smart measuring device is transmitted to the patient's mobile terminal via Bluetooth, and the data regularly inquired by the staff is input into the patient's mobile terminal by the staff; The patient's mobile terminal connects signals with the medical institution; After signal docking is completed, preparations for patient health data transmission are made.

5. A medical care information integrated management system according to claim 4, characterized in that: The medical institution docking unit further includes: Monitoring data transmission module, used for: When patient health data is transmitted from the patient's mobile terminal to the medical institution, the transmission channel with the fastest transmission speed is automatically selected; Among them, the patient health data is first divided into sections, and the patient health data is divided into several sections of the same length; Calculate the amount of patient health data transmitted based on the paragraph data; There are no fewer than four transmission channels from the patient’s mobile terminal to the medical institution; Confirm the remaining capacity of each transmission channel; A transmission channel whose transmission amount of patient health data is less than the remaining capacity of the channel is selected as the transmission channel for transmitting the patient health data from the mobile terminal to the medical institution.

6. A medical care information integrated management system according to claim 5, characterized in that: Monitoring data transmission module, including: A real-time monitoring module, used to monitor in real time the data transmission operation parameters of the patient's health data transmitted from the mobile terminal to the medical institution; The data transmission operation parameters include the amount of other data transmitted in parallel by the transmission channel in the process of transmitting the patient health data, as well as the data transmission rate of the patient health data and the data transmission rate of other data transmitted in parallel in addition to the patient health data; A data volume information extraction module, used to extract the data volume of other data transmitted in parallel with the patient health data corresponding to each unit time during the patient health data transmission process; wherein the unit time is 1s; A first data transmission evaluation coefficient acquisition module, used to obtain a first data transmission evaluation coefficient by combining the data amount of other data transmitted in parallel except for the patient health data corresponding to each unit time during the patient health data transmission process with the data amount of data transmitted per unit time during the patient health data transmission process; The first data transmission evaluation coefficient is obtained by the following formula: Among them, R 01 represents the first data transmission evaluation coefficient; n represents the number of unit times that the patient's health data transmission process has experienced; C 01i represents the amount of patient health data transmitted corresponding to the i-th unit time; C 02i represents the amount of other data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; C yi represents the remaining capacity of the transmission channel corresponding to the i-th unit time; C 02b represents the standard deviation of the amount of other data transmitted in parallel with the patient health data during the n unit time of the patient health data transmission process; C 01b represents the standard deviation of the data volume corresponding to n unit time experienced in the patient health data transmission process; r represents the first adjustment coefficient, and the adjustment coefficient is obtained by the following formula: Wherein, r represents the first adjustment coefficient; n represents the number of unit times that the patient health data transmission process has experienced; C 01i represents the amount of patient health data transmitted corresponding to the i-th unit time; C 02i represents the amount of other data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; C yi represents the remaining capacity of the transmission channel corresponding to the i-th unit time; A first comparison module, configured to compare the first data transmission evaluation coefficient with a preset first coefficient threshold; The quality evaluation module is used to evaluate the data transmission quality of the patient health data by using the data transmission rate of the patient health data and the data transmission rate of other data transmitted in parallel with the patient health data when the first data transmission evaluation coefficient exceeds a preset first coefficient threshold.

7. A medical care information integrated management system according to claim 6, characterized in that: The quality evaluation module comprises: A first data transmission rate information extraction module is used to extract the data transmission rate corresponding to each unit time during the patient health data transmission process; A second data transmission rate information extraction module is used to extract the data transmission rate per unit time corresponding to other data transmitted in parallel except for the patient health data; A second data transmission evaluation coefficient acquisition module, used to acquire a second data transmission evaluation coefficient by using a data transmission rate of the patient health data and a data transmission rate of other data transmitted in parallel except for the patient health data; The second data transmission evaluation coefficient is obtained by the following formula: Among them, R 02 represents the second data transmission evaluation coefficient; n represents the number of unit times that the patient health data transmission process has experienced; m represents the number of other data transmitted in parallel in addition to the patient health data corresponding to each unit time; V 01i V represents the data transmission rate of the patient's health data corresponding to the i-th unit time; 02ij=1 、V 02ij=2 ,……,V 02ij=m They represent the data transmission rates corresponding to the 1st, 2nd, ...mth data transmitted in parallel in addition to the patient health data corresponding to the i-th unit time; V 02ip V represents the average data transmission rate of m other data transmitted in parallel in addition to the patient health data in the i-th unit time; 01bi and V 02bi represents the data transmission rate standard deviation of the patient health data in the i-th unit time and the average value of the data transmission rate standard deviation of m other data transmitted in parallel except for the patient health data; f represents the second adjustment coefficient, and the second adjustment coefficient is obtained by the following formula: Wherein, f represents the second adjustment coefficient; V 01bi V represents the standard deviation of the data transmission rate of the patient's health data per unit time; 02bimax represents the maximum value of the standard deviation of the data transmission rate of m other data transmitted in parallel except for the patient's health data; V 02bimin represents the minimum standard deviation of the data transmission rate of m other data transmitted in parallel except for the patient health data; A second comparison module, used for comparing the second data transmission evaluation coefficient with a preset second coefficient threshold; The abnormality determination and alarm module is used to determine that there is an abnormality in the data transmission of the patient health data and to issue an abnormality alarm when the second data transmission evaluation coefficient exceeds a preset second coefficient threshold.

8. A medical care information integrated management system according to claim 5, characterized in that: The monitoring data consultation unit comprises: Health data judgment module, used for: The medical institution receives the patient's health data and makes an abnormality judgment after receiving the patient's health data; Among them, the blood pressure data, blood sugar data, heart rate data, body temperature data, electrocardiogram data and blood oxygen saturation data in the patient's health data are respectively converted into curve data, and the curve health data is obtained after the conversion; Overlap and compare the curve health data with the standard curve data; According to the overlapping comparison results, qualified data, low data and high data are obtained; Among them, when the low data is an overlapping comparison, the healthy data of the curve is lower than the data area of ​​the standard curve data; when the high data is an overlapping comparison, the healthy data of the curve is higher than the data area of ​​the standard curve data; Low data and high data are marked as unhealthy data and stored separately.

9. A medical care information integrated management system according to claim 8, characterized in that: The monitoring data consultation unit further includes: Judgment data consultation module, used for: Medical institutions confirm the specific attributes of non-health data; According to the specific attributes of the non-health data, the non-health data is transmitted to the corresponding medical personnel diagnosis center for corresponding diagnosis; Medical personnel make diagnostic decisions based on abnormal thresholds of non-health data; Diagnostic decision-making is based on the degree of abnormality of non-healthy data; When the abnormal thresholds of low and high data in non-health data do not exceed 20%, a written diagnosis will be conducted; when the abnormal thresholds of low and high data in non-health data exceed 20%, a home consultation will be conducted; A health report is generated based on the diagnosis decision results and transmitted to the patient's mobile terminal.

10. A medical care information integrated management system according to claim 9, characterized in that: The health care push unit is also used for: The patient checks the health report on the mobile terminal and confirms the final treatment method based on the results; Among them, the purchase of medicines is based on the written diagnosis results, and the consultation time is confirmed based on the results of the home consultation; At the same time, patients can conduct online consultations on mobile terminals based on their health reports.

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