A health management system and method

Abstract

This invention discloses a health management system and method, belonging to the field of health management technology. It addresses the technical problems of ineffective targeted health management for different dietary-related diseases in schools, and the poor tracking, analysis, and optimization of health management programs for different dietary types. The system uses a dietary type information processing set to analyze and combine different aspects of the monitoring status of all target students in each academic year for each dietary type. It utilizes a type-based dining implementation status monitoring sequence to process, calculate, and integrate the implementation effects of dining for each dietary type from different dimensions. Furthermore, it optimizes the subsequent implementation of existing catering service programs for each dietary type, thereby expanding the use of digital monitoring data corresponding to previous dietary types.

Description

Technical Field

[0001] This invention relates to the field of health management technology, specifically to a health management system and method. Background Technology

[0002] A health management system is a comprehensive information technology solution designed to improve health management, disease prevention, and treatment outcomes by collecting, analyzing, and managing the health information of individuals or groups.

[0003] The existing health management system cannot implement targeted dining window settings and meal preparation settings for different dietary-related illnesses in schools. It also cannot track and analyze the recovery status of different dietary-related illnesses, nor can it dynamically optimize the dining window settings and meal preparation settings for different dietary-related illnesses based on the analysis results. As a result, the targeted health management of different dietary-related illnesses in schools is not effective, and the tracking, analysis, and optimization management of health management programs for different dietary-related illnesses is not effective. Summary of the Invention

[0004] The purpose of this invention is to provide a health management system and method to solve the technical problems of poor targeted health management of different dietary-related diseases in schools and poor tracking, analysis and optimization management of the implementation of health management programs for different dietary-related diseases in existing solutions.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] A health management system, comprising:

[0007] The student health data statistics and processing module is used to monitor and statistically analyze the health data and physical examination data of all new students enrolled in the school each year, and to perform privacy processing and classification of the monitored statistical data to obtain a set of dietary type information and upload it to the student dietary health management platform.

[0008] The Student Health Data Diet Supervision Module is used to analyze and combine different aspects of the supervision status processing of all target students in each academic year based on the attention to diet type information processing set, obtain the corresponding type of dining implementation status supervision sequence, and upload it to the student diet health management platform.

[0009] The "Pay Attention to Dining Type Service Evaluation and Management Module" is used to process and calculate the implementation effect of the dining type according to the monitoring sequence of the dining type implementation status. It integrates and analyzes the results of the processing and calculation of different dimensions, and conducts targeted optimization management for the subsequent implementation of the existing catering service plan of the dining type.

[0010] Preferably, the health data and health check-up data of all new students enrolled in the school each year are monitored and statistically analyzed, and students with diseases related to dietary attention are identified, and all students with the same dietary attention type are sorted and combined to obtain dietary attention type combination data.

[0011] The data on dietary type combinations for treating all different dietary diseases are sorted, combined, and made private to obtain a dietary type information processing set.

[0012] Preferably, the total number of target students corresponding to different attention-based diet types is obtained based on the attention-based diet type information processing set, and the dining data of all target students of different attention-based diet types at the target dining window for each academic year are statistically analyzed and processed using a formula. Calculate the dining implementation value JSi corresponding to the target dining window for different target students with different dietary attention types; where i represents different target students with different dietary attention types, i=1, 2, 3, ..., n, and n is a positive integer representing all target students with different dietary attention types; NJi is the total number of times different target students dine at the target dining window each academic year; NJ0i is the total number of times different target students dine at all dining windows each academic year; JS0 is the standard value for dining implementation.

[0013] The calculated dining implementation values ​​are analyzed, and the dining implementation status of the target students belonging to the dietary attention type is classified and labeled according to the analysis results.

[0014] If the dining implementation value is greater than or equal to 0, the dining implementation status of the target student belonging to the dietary attention type will be marked as normal dining implementation status, and the target student will be associated with a dining implementation status identifier with a value of 0.

[0015] Preferably, if the meal implementation value is less than 0, the recovery status of the target students belonging to the attention diet type is traced and verified.

[0016] If the target student has not recovered, mark the student's dining implementation status as abnormal and associate the student with a dining implementation status identifier with a value of 1.

[0017] If the target student has recovered, mark the student's dining implementation status as "dining implementation completed" and associate the student with a dining implementation status identifier with a value of 2.

[0018] By sorting and combining the dining implementation status identifiers associated with all target students for each dietary type, a monitoring sequence of dining implementation status corresponding to each dietary type is obtained.

[0019] Preferably, the monitoring sequence of dining implementation status is traversed, and the total number of normal dining implementations (NZ) with a value of 0, the total number of abnormal dining implementations (NY) with a value of 1, and the total number of completed dining implementations (NJ) with a value of 2 are counted respectively. The total number of normal dining implementations and the total number of abnormal dining implementations are then expressed using the formula... Calculate the implementation validity SX1 of the first dining type corresponding to the attention-based diet type; where YL is the dining implementation abnormality rate corresponding to the attention-based diet type, obtained through the formula... The calculated value is YL′, which represents the standard value of the abnormal dining implementation rate corresponding to the relevant dietary type.

[0020] Preferably, the total number of meals completed is calculated using a formula. Calculate the second dining type implementation validity SX2 corresponding to the relevant attention-based diet type; where BJ is the standard value for the end of the dining implementation corresponding to the relevant attention-based diet type; [a] is the floor function, and the largest integer not exceeding the real number a is called the integer part of a.

[0021] Preferably, the calculated implementation validity of the first and second dining types are sorted and combined to obtain the monitoring sequence of the implementation effect of the dining type corresponding to the respective dietary attention type;

[0022] Data analysis is conducted on the effectiveness monitoring sequence of dining types, and the existing catering service plans of the corresponding dining types are optimized and managed in a targeted manner based on the analysis results.

[0023] Preferably, if SX1≤0 and SX2≥0 in the monitoring sequence of dining type implementation effect, then a valid catering service label is generated, and the existing catering service plan is maintained for the corresponding dietary type.

[0024] If the SX1>0 and SX2≥0 or SX1≤0 and SX2<0 in the monitoring of the dining type, then a valid label for the catering service will be generated, and the existing catering service plan for the corresponding dietary type will be partially upgraded and optimized.

[0025] If SX1 > 0 and SX2 < 0 in the monitoring of dining type effectiveness, an invalid catering service label will be generated, and the existing catering service plan for the corresponding dietary type will be upgraded and optimized as a whole.

[0026] A health management method, comprising:

[0027] The health data and health check-up data of all new students enrolled in the school each year are monitored and statistically analyzed. The monitored and statistical data are then processed for privacy and classified and combined to obtain a set of dietary type information and uploaded to the student dietary health management platform.

[0028] Based on the information processing set of dietary attention types, the monitoring status processing and combination of different aspects are carried out for all target students in each academic year who are paying attention to dietary attention, and the corresponding type of dining implementation status monitoring sequence is obtained and uploaded to the student dietary health management platform.

[0029] Based on the monitoring sequence of dining type implementation status, the effectiveness of the implementation of the dining type under the corresponding dietary precautions is processed and calculated from different dimensions. The results of the processing and calculation from different dimensions are integrated and analyzed, and the existing catering service plan for the corresponding dietary precautions type is optimized and managed in a targeted manner.

[0030] Compared to existing solutions, the beneficial effects achieved by this invention are:

[0031] This invention monitors, statistically analyzes, and processes the health data and physical examination data of all new students enrolled in schools each year to obtain a set of information on dietary types for all students who need to pay attention to their diet. This provides reliable data support for subsequent dietary supervision and analysis of all target students in different dietary categories.

[0032] This invention analyzes and combines different aspects of the monitoring status processing for all target students in each academic year who are paying attention to their diet, based on the information processing set of the diet type. This enables different aspects of the monitoring processing of existing catering service programs for different diet types. At the same time, it can also provide reliable multi-dimensional monitoring and screening data support for subsequent monitoring and analysis of service effects and optimization management, thereby improving the diversity and reliability of monitoring and processing of service effect data for different diet types.

[0033] This invention utilizes a monitoring sequence of dining implementation status to process, calculate, and integrate the effects of different dietary types on the implementation of dining types with different dietary requirements. It also optimizes the subsequent implementation of existing catering service plans for different dietary types. This allows for the expansion and utilization of digital monitoring data corresponding to previous dietary types, and multi-dimensional processing, analysis, and optimization of existing catering service plans for different dietary types. This improves the targeted health management effectiveness for different dietary-related diseases in schools, and enhances the tracking, analysis, and optimization management effectiveness of health management plans for different dietary types. Attached Figure Description

[0034] The invention will now be further described with reference to the accompanying drawings.

[0035] Figure 1 This is a block diagram of a health management system according to the present invention.

[0036] Figure 2This is a flowchart illustrating the steps involved in data analysis of the calculated dining implementation values ​​in this invention.

[0037] Figure 3 This is a flowchart illustrating the steps of a health management method according to the present invention. Detailed Implementation

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0039] Example 1: Figure 1 As shown, the present invention is a health management system, including a student health data statistical processing module, a student health data dietary supervision module, a dietary type service evaluation and management module, and a student dietary health management platform;

[0040] The student health data statistics and processing module is used to monitor and statistically analyze the health data and physical examination data of all new students enrolled each year. It also performs privacy processing and categorizes the monitored statistical data to obtain a set of dietary type information, which is then uploaded to the student dietary health management platform. Specific steps include:

[0041] The health data and health check-up data of all new students enrolled in the school each year are monitored and statistically analyzed. Students with diseases related to dietary attention are identified, and all students with the same dietary attention type are sorted and combined to obtain dietary attention type combination data.

[0042] It should be noted that the health data of all new students can be obtained through anonymous electronic health questionnaires, and the health examination data can be obtained from the entrance physical examinations of all new students.

[0043] The types of diets to be aware of include those that emphasize a light diet and those that require special dietary requirements.

[0044] Pay attention to a light diet, such as for cardiovascular disease, diabetes, obesity, and digestive system diseases, which require light foods that are low in salt, oil, and fat.

[0045] Pay attention to specific dietary requirements, such as thyroid disease, which necessitates the consumption of foods without iodine.

[0046] However, the existing health management programs for school canteens cannot provide targeted food supply services and optimize service supervision for different types of diseases that require special dietary attention, resulting in poor health management for people with special dietary needs.

[0047] The data on dietary type combinations corresponding to the treatment of all different dietary diseases are sorted, combined, and made private to obtain a dietary type information processing set.

[0048] In particular, privacy processing can be used to digitize the relevant identity information of students with dietary-related illnesses, such as their names and student IDs. Digitization is a conventional technical means, and the specific implementation steps will not be elaborated here.

[0049] In this embodiment of the invention, by monitoring, statistically analyzing, and processing the health data and health check-up data of all new students enrolled in the school each year, a set of information processing data on dietary types for all students who need to pay attention to their diet is obtained. This can provide reliable data support for subsequent dietary supervision and analysis of all target students in different dietary categories.

[0050] The student health data dietary supervision module is used to analyze and combine different aspects of the supervision status processing of all target students in each academic year who are paying attention to dietary types, based on the information processing set of dietary attention types. This results in a corresponding type of dining implementation status supervision sequence, which is then uploaded to the student dietary health management platform. Specific steps include:

[0051] The total number of target students corresponding to different dietary categories is obtained based on the dietary type information processing set. The dining data of all target students of different dietary categories at the target dining windows for each academic year is statistically analyzed. The target dining windows specifically provide a number of foods for different dietary categories of diseases, such as light foods that are low in salt, oil, and fat, as well as foods that do not contain iodized salt. The statistical analysis of dining data is obtained based on the card swiping data of the card reader at the target dining window.

[0052] And through the formula Calculate the dining implementation value JSi corresponding to the target dining window for different target students with different dietary attention types; where i represents different target students with different dietary attention types, i=1, 2, 3, ..., n, and n is a positive integer representing all target students with different dietary attention types; NJi is the total number of times different target students dine at the target dining window each academic year; NJ0i is the total number of times different target students dine at all dining windows each academic year; JS0 is the standard value for dining implementation, which can be determined based on the preliminary test data of the target dining window or based on the individual dining habit data of all target students.

[0053] The dining implementation value is used to periodically process and calculate all dining data of different target students with different dietary attention types in the target dining window, so as to digitally represent the dining implementation status of all target students with different dietary attention types.

[0054] In this embodiment of the invention, by periodically processing and calculating all dining data of different target students with different dietary habits at the target dining window, it is possible to digitally represent the dining status of all target students with different dietary habits, and to provide reliable periodic digital data support for the subsequent regulatory analysis of different aspects of the existing catering service schemes for dietary habits.

[0055] The calculated dining implementation values ​​are analyzed, and the dining implementation status of the target students belonging to the dietary attention type is classified and labeled according to the analysis results.

[0056] like Figure 2 As shown, if the dining implementation value is greater than or equal to 0, the dining implementation status of the target student belonging to the dietary attention type will be marked as normal dining implementation status, and the target student will be associated with a dining implementation status identifier with a value of 0.

[0057] If the implementation value of the meal is less than 0, the recovery status of the target students of the corresponding dietary type will be traced and verified, which can be done through an anonymous electronic health questionnaire.

[0058] It is important to note that when the dining implementation status of a target student is abnormal, it is necessary to further trace, verify, and classify the types of abnormal dining implementation. This can effectively improve the accuracy and reliability of the monitoring and analysis of the service effects of existing catering service programs for different types of dietary needs.

[0059] If the target student has not recovered, mark the student's dining implementation status as abnormal and associate the student with a dining implementation status identifier with a value of 1.

[0060] If the target student has recovered, mark the student's dining implementation status as "dining implementation completed" and associate the student with a dining implementation status identifier with a value of 2.

[0061] Among them, the target student has recovered, indicating that the corresponding dining data has no value for the monitoring and analysis of the negative effects of the existing catering service program for the corresponding dietary type.

[0062] By sorting and combining the dining implementation status identifiers associated with all target students for each type of dietary attention, a monitoring sequence of dining implementation status corresponding to each type of dietary attention is obtained.

[0063] In this embodiment of the invention, the monitoring status processing and combination of all target students in each academic year for the "pay attention to diet" category are carried out in different aspects based on the information processing set of the "pay attention to diet" category. This enables different aspects of the monitoring processing of existing catering service plans for different "pay attention to diet" categories. At the same time, it can also provide reliable multi-dimensional monitoring and screening data support for subsequent monitoring and analysis of service effects and optimization management in different aspects, thereby improving the diversity and reliability of monitoring and processing of service effect data for different "pay attention to diet" categories.

[0064] The "Pay Attention to Dining Type Service Evaluation and Management Module" is used to process and calculate the implementation effect of the "Pay Attention to Dining Type" service from different dimensions based on the monitoring sequence of the dining type's implementation status. It then integrates and analyzes the results of these calculations and provides targeted optimization management for the subsequent implementation of existing catering service plans for the "Pay Attention to Dining Type." Specific steps include:

[0065] The system iterates through the monitoring sequence of dining implementation status for each type, and separately counts the total number of normal dining implementations (NZ) with a value of 0, the total number of abnormal dining implementations (NY) with a value of 1, and the total number of completed dining implementations (NJ) with a value of 2. The total number of normal dining implementations and the total number of abnormal dining implementations are then expressed using the formula... Calculate the implementation validity SX1 of the first dining type corresponding to the attention-based diet type; where YL is the dining implementation abnormality rate corresponding to the attention-based diet type, obtained through the formula... The calculated value of YL′ represents the standard value of the abnormal dining implementation rate corresponding to the relevant dietary type. This value can be determined based on the design requirements data corresponding to the relevant dietary type, or it can be determined based on the previous test data corresponding to the relevant dietary type.

[0066] Among them, the first type of dining implementation validity is used to process and calculate different regulatory data after the implementation of the existing catering service plan for the corresponding type of attention-based diet from the perspective of abnormal dining implementation, so as to digitally represent the abnormal dining implementation effect.

[0067] And, the total number of meals completed will be calculated using the formula. Calculate the implementation validity of the second dining type corresponding to the relevant dietary type SX2; where BJ is the standard value for the end of the dining implementation corresponding to the relevant dietary type, which can be determined based on the existing health recovery cycle data corresponding to the relevant dietary type; [a] is the floor function, and the largest integer not exceeding the real number a is called the integer part of a;

[0068] Among them, the second type of dining implementation validity is used to process and calculate different regulatory data after the implementation of the existing catering service program of the corresponding dietary attention type from the perspective of normal dining implementation, so as to digitally represent the normal dining implementation effect.

[0069] The calculated implementation validity of the first and second dining types are sorted and combined to obtain the monitoring sequence of the implementation effect of the dining type corresponding to the dietary attention type.

[0070] Unlike existing technical solutions that only analyze the effects of health service implementation based on a single dimension or aspect, resulting in poor reliability and comprehensiveness, this invention provides reliable multidimensional data support for subsequent data analysis by processing and combining data from different aspects and dimensions. This improves the diversity and reliability of the analysis of the effects of existing health service implementations.

[0071] Data analysis is conducted on the effectiveness monitoring sequence of dining types, and the existing catering service plans of the corresponding dining types are optimized and managed in a targeted manner based on the analysis results;

[0072] If SX1≤0 and SX2≥0 in the monitoring sequence of dining type implementation effect, then a valid catering service label is generated, and the existing catering service plan is maintained for the corresponding dietary type.

[0073] If the monitoring results for the dining type show SX1 > 0 and SX2 ≥ 0, or SX1 ≤ 0 and SX2 < 0, then a valid label for the catering service will be generated, and the existing catering service plan for the corresponding dining type will be partially upgraded and optimized. The partial upgrade and optimization can specifically involve upgrading and optimizing the taste of the existing dining dishes.

[0074] If SX1 > 0 and SX2 < 0 in the monitoring of dining type effectiveness, an invalid catering service label will be generated, and the existing catering service plan for the corresponding dining type will be upgraded and optimized as a whole. The overall upgrade and optimization can specifically upgrade and optimize the existing dining food taste, dining queue, dining environment, dining feedback, etc.

[0075] In this embodiment of the invention, the implementation status monitoring sequence of dining by type is used to process, calculate, and integrate the implementation effect of the dining type of the corresponding dietary precaution type from different dimensions, and to carry out targeted optimization management of the subsequent implementation of the existing catering service plan of the corresponding dietary precaution type. This realizes the expansion and utilization of the digital monitoring data corresponding to the previous dietary precaution type, and the multi-dimensional processing, analysis, and optimization management of the existing catering service plan of the dietary precaution type. This improves the targeted health management effect of different dietary precaution diseases in schools, and the tracking, analysis, and optimization management effect of the implementation of health management plans for different dietary precaution types.

[0076] Example 2: Figure 3 As shown, a health management method includes:

[0077] The health data and health check-up data of all new students enrolled in the school each year are monitored and statistically analyzed. The monitored and statistical data are then processed for privacy and classified and combined to obtain a set of dietary type information and uploaded to the student dietary health management platform.

[0078] Based on the information processing set of dietary attention types, the monitoring status processing and combination of different aspects are carried out for all target students in each academic year who are paying attention to dietary attention, and the corresponding type of dining implementation status monitoring sequence is obtained and uploaded to the student dietary health management platform.

[0079] Based on the monitoring sequence of dining type implementation status, the effectiveness of the implementation of the dining type under the corresponding dietary precautions is processed and calculated from different dimensions. The results of the processing and calculation from different dimensions are integrated and analyzed, and the existing catering service plan for the corresponding dietary precautions type is optimized and managed in a targeted manner.

[0080] Furthermore, the formulas mentioned above are all numerical calculations obtained by removing dimensions and using simulation software to obtain a formula that is closest to the real situation, based on the collection of a large amount of data.

[0081] In the several embodiments provided by this invention, it should be understood that the disclosed system can be implemented in other ways. For example, the embodiments of the invention described above are merely illustrative; for example, the division of modules is only a logical functional division, and there may be other division methods in actual implementation.

[0082] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0084] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A health management system, characterized in that, include: The student health data statistics and processing module is used to monitor and statistically analyze the health data and physical examination data of all new students enrolled in the school each year, and to perform privacy processing and classification of the monitored statistical data to obtain a set of dietary type information and upload it to the student dietary health management platform. The Student Health Data Diet Supervision Module is used to analyze and combine different aspects of the supervision status processing of all target students in each academic year based on the attention to diet type information processing set, obtain the corresponding type of dining implementation status supervision sequence, and upload it to the student diet health management platform. If the calculated dining implementation value is less than 0, the recovery status of the target students belonging to the dietary attention type will be traced and verified. If the target student has not recovered, mark the student's dining implementation status as abnormal and associate the student with a dining implementation status identifier with a value of 1. If the target student has recovered, mark the student's dining implementation status as "dining implementation completed" and associate the student with a dining implementation status identifier with a value of 2. By sorting and combining the dining implementation status identifiers associated with all target students for each type of dietary attention, a monitoring sequence of dining implementation status corresponding to each type of dietary attention is obtained. The "Pay Attention to Dining Type Service Evaluation and Management Module" is used to process and calculate the implementation effect of the dining type according to the monitoring sequence of the dining type implementation status, and integrate and analyze the results of the processing and calculation of different dimensions. It also conducts targeted optimization management for the subsequent implementation of the existing catering service plan for the dining type. The process involves iterating through the monitoring sequence of dining implementation status for each type, and separately counting the total number of normal dining implementations (NZ) with a value of 0, the total number of abnormal dining implementations (NY) with a value of 1, and the total number of completed dining implementations (NJ) with a value of 2. The total number of normal and abnormal dining implementations is then calculated using a formula. Calculate the implementation validity SX1 of the first dining type corresponding to the attention-based diet type; where YL is the dining implementation abnormality rate corresponding to the attention-based diet type, obtained through the formula... Calculated; The standard value for the abnormality rate of meals corresponding to the relevant dietary type; The total number of meals completed is calculated using the formula. Calculate the second dining type implementation validity SX2 corresponding to the relevant attention-based diet type; where BJ is the standard value for the end of the dining implementation corresponding to the relevant attention-based diet type; [a] is the floor function, and the largest integer not exceeding the real number a is called the integer part of a.

2. The health management system according to claim 1, characterized in that, The health data and health check-up data of all new students enrolled in the school each year are monitored and statistically analyzed. Students with diseases related to dietary attention are identified, and all students with the same dietary attention type are sorted and combined to obtain dietary attention type combination data. The data on dietary type combinations for treating all different dietary diseases are sorted, combined, and made private to obtain a dietary type information processing set.

3. A health management system according to claim 2, characterized in that, Based on the information processing set of attentional diet types, the total number of target students corresponding to different attentional diet types is obtained. Then, the dining data of all target students of different attentional diet types at the target dining windows for each academic year is statistically analyzed, and the results are processed using a formula. Calculate the dining implementation value JSi corresponding to the target dining window for different target students with different dietary attention types; where i represents different target students with different dietary attention types, i=1, 2, 3, ..., n, and n is a positive integer representing all target students with different dietary attention types; NJi is the total number of times different target students dine at the target dining window each academic year; NJ0i is the total number of times different target students dine at all dining windows each academic year; JS0 is the standard value for dining implementation. The calculated dining implementation values ​​are analyzed, and the dining implementation status of the target students belonging to the dietary attention type is classified and labeled according to the analysis results. If the dining implementation value is greater than or equal to 0, the dining implementation status of the target student belonging to the dietary attention type will be marked as normal dining implementation status, and the target student will be associated with a dining implementation status identifier with a value of 0.

4. A health management system according to claim 1, characterized in that, The calculated implementation validity of the first and second dining types are sorted and combined to obtain the monitoring sequence of the implementation effect of the dining type corresponding to the dietary attention type. Data analysis is conducted on the effectiveness monitoring sequence of dining types, and the existing catering service plans of the corresponding dining types are optimized and managed in a targeted manner based on the analysis results.

5. A health management system according to claim 4, characterized in that, If the SX1>0 and SX2≥0 or SX1≤0 and SX2<0 in the monitoring of the dining type, then a valid label for the catering service will be generated, and the existing catering service plan for the corresponding dietary type will be partially upgraded and optimized. If SX1 > 0 and SX2 < 0 in the monitoring of dining type effectiveness, an invalid catering service label will be generated, and the existing catering service plan for the corresponding dietary type will be upgraded and optimized as a whole.

6. A health management method, employing a health management system as described in any one of claims 1-5, characterized in that, include: The health data and health check-up data of all new students enrolled in the school each year are monitored and statistically analyzed. The monitored and statistical data are then processed for privacy and classified and combined to obtain a set of dietary type information and uploaded to the student dietary health management platform. Based on the information processing set of dietary attention types, the monitoring status processing and combination of different aspects are carried out for all target students in each academic year who are paying attention to dietary attention, and the corresponding type of dining implementation status monitoring sequence is obtained and uploaded to the student dietary health management platform. Based on the monitoring sequence of dining type implementation status, the effectiveness of the implementation of the dining type under the corresponding dietary precautions is processed and calculated from different dimensions. The results of the processing and calculation from different dimensions are integrated and analyzed, and the existing catering service plan for the corresponding dietary precautions type is optimized and managed in a targeted manner.

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