Personalized health management system and method based on multi-dimensional health intervention

Abstract

The invention relates to the technical field of life style medical services, in particular to a personalized health management system and method based on multi-dimensional health intervention, and the system comprises a data collection module which is used for obtaining user data; the data processing module is used for sorting, standardizing and fusing the multi-source health data; the intelligent analysis module is used for generating a personalized health intervention scheme; and the user interaction module is used for feeding back health suggestions to the user and collecting user behavior data. The method comprises the following steps: S1, collecting a physical examination report, psychological assessment, lifestyle and health somatosensory self-test data of a user; s2, sorting, standardizing and fusing the data; s3, generating a personalized health intervention scheme; and S4, health suggestions are fed back to the user, a subsequent intervention strategy is optimized, and interaction is optimized by selecting proper movement and loved languages according to character characteristics of the user, so that the execution rate of the user is improved.

Description

Technical Field

[0001] This invention relates to the field of lifestyle medicine service technology, specifically to a personalized health management system and method based on multi-dimensional health intervention. Background Technology

[0002] The formation and development of appropriate health management technologies are the result of the combined effects of multidisciplinary integration, social demand-driven development, and policy support.

[0003] I. Origin and Development

[0004] The concept of health management first emerged in the US insurance industry in the late 1950s, with the initial aim of reducing medical claims costs by systematically managing clients' health risks. In 1929, Blue Cross and Blue Shield Insurance Companies were the first to include health management fees in their insurance coverage, initiating the commercial practice of health management. The enactment of the Health Maintenance Act of 1973 spurred the establishment of models such as Health Maintenance Organizations (HMOs), marking the transition of health management from a concept to a formalized system. By the early 21st century, 70% of the US population enjoyed health management services, forming a mature market system.

[0005] Health management in China started relatively late. The profession of "health manager" was officially established in 2005, and the Chinese Medical Association's Health Management Branch was established in 2007, marking the beginning of industry standardization. With the advancement of "Healthy China 2030," health management has been incorporated into the national medical innovation system and has become an important direction for medical system reform.

[0006] II. Disciplinary Foundations and Knowledge System

[0007] Health management is a typical interdisciplinary field, integrating theories and methods from multiple disciplines:

[0008] 1. Medicine and Public Health: Covering basic medicine (anatomy, physiology), clinical medicine (chronic disease management), and public health (epidemiology, health education), used for health risk assessment and disease prevention.

[0009] 2. Management and Economics: Utilize management tools such as resource allocation and quality control to optimize health service processes, while combining health economics to analyze the input-output benefits of health services.

[0010] 3. Behavioral Science and Psychology: Guiding individuals to change their lifestyles and cope with stress and psychological problems through health belief models, social cognitive theories, etc.

[0011] 4. Information technology: Real-time monitoring and personalized intervention of health data are achieved by leveraging big data analytics, wearable devices, and other technologies.

[0012] Taking the Health Service and Management major at China Pharmaceutical University as an example, its curriculum emphasizes "understanding products, strong management, and familiarity with policies," integrating disciplines such as pharmacy, management, and law to cultivate interdisciplinary talents capable of engaging in health policy research and service design.

[0013] III. Social Background and Policy Drivers

[0014] 1. Disease spectrum and population structure changes: The global burden of chronic diseases is increasing (e.g., there are 290 million cardiovascular disease patients in China) and the aging population is accelerating (it is estimated that the proportion of the population aged 60 and above will exceed 30% by 2035), which is driving health management to shift from treatment to prevention.

[0015] 2. Pressure on healthcare resources: Traditional healthcare models struggle to meet the long-term care needs of chronic diseases, while health management, through early intervention, can reduce healthcare costs by 30%. For example, in the United States, participants in health management programs spend an average of $200 less on healthcare annually than those who do not participate.

[0016] 3. Policy support: China has incorporated health management into the "Healthy China" initiative. In 2019, the "Opinions on Promoting the Development of the Health Service Industry" explicitly encouraged social capital to enter the health management field. By 2023, there were more than 620,000 health management-related enterprises.

[0017] IV. Career Development and Market Demand

[0018] The profession of health management is becoming increasingly professionalized globally: the United States requires practitioners to have a master's degree in public health or health management, while China standardizes talent cultivation through national vocational qualification certification (included in the National Occupational Directory in 2017). Employment fields include:

[0019] - Medical institutions: physical examination centers, chronic disease management departments (such as Fuwai Hospital, which incorporates health management into its clinical pathways).

[0020] -Insurance industry: Design health insurance products and provide health risk assessment services.

[0021] - Businesses and communities: Implement projects such as employee health promotion and elderly care.

[0022] -Policy Research: Participation in health policy formulation and health economic analysis.

[0023] There is a significant talent shortage in China's health management market, and graduates with relevant expertise can play a role in emerging fields such as health product development and health data management.

[0024] Traditional health management relies on single physical examination data or wearable devices, lacking multi-dimensional data such as psychological and behavioral data. The suggestions provided by the system do not take into account the user's personality and psychological preferences, resulting in poor compliance, one-sided assessments, and low accuracy. For example, a remote online health management system disclosed in the Chinese Patent Document Database with application number 201610325826.4 only uses remote probe terminals such as Bluetooth blood pressure monitors, Bluetooth body fat analyzers, spirometers, blood glucose meters, and electrocardiogram monitors to monitor physiological indicators and generate dietary, medication, and training suggestions. This is relatively simplistic, does not involve psychological adaptation, and users have a low adherence rate to the matched exercise suggestions, resulting in poor effectiveness. Summary of the Invention

[0025] The purpose of this invention is to provide a personalized health management system and method based on multi-dimensional health intervention to solve the problems mentioned in the background art.

[0026] To achieve the above objectives, the present invention provides the following technical solution: a personalized health management system based on multi-dimensional health intervention, comprising:

[0027] Data acquisition module: used to acquire users' physiological data, psychological assessment data, lifestyle data, and health self-test data;

[0028] Data processing module: used to organize, standardize, and integrate multi-source health data;

[0029] Intelligent analysis module: used to generate personalized health intervention plans;

[0030] User interaction module: Used to provide health advice to users and collect user behavior data.

[0031] Furthermore, the data acquisition module includes:

[0032] Key indicator extraction unit for physical examination reports: used to analyze hospital physical examination reports and extract key physiological indicators;

[0033] Psychological assessment unit: used to analyze personality test and love language test data;

[0034] Lifestyle survey unit: used to collect data on users' eating, exercise, and sleep habits;

[0035] Health Self-Assessment Questionnaire Analysis Unit: Used to analyze the 100 health self-assessment questions filled out by users;

[0036] Cardiovascular disease risk assessment unit: Used to calculate the user's 10-year cardiovascular disease risk score.

[0037] Furthermore, the key indicator extraction unit for the physical examination report includes:

[0038] A multi-format report parser for structuring multi-format medical examination reports;

[0039] A medical entity recognition engine is used to identify the names, values, and units of indicators in reports.

[0040] A dynamic field matching library is used to store indicator aliases and clinically equivalent terms;

[0041] The outlier marking unit automatically marks outlier indicators based on preset thresholds.

[0042] Furthermore, the aforementioned psychological assessment unit includes:

[0043] Personality Test Analysis Submodule: Used to test the user's personality traits;

[0044] The Love Language Recognition Submodule is used to determine the user's emotional needs and preferred interaction methods.

[0045] Psychological-physiological association rule base: Stores the mapping relationship between personality traits and healthy behaviors.

[0046] Furthermore, the health self-assessment questionnaire analysis unit includes:

[0047] Symptom-system mapping algorithm: used to associate self-tested symptoms with corresponding physiological systems;

[0048] Health Radar Chart Generator: Used to visualize the degree of deviation from a user's health status.

[0049] Furthermore, the intelligent analysis module includes:

[0050] Physiological-Psychological Characteristic Cross-Analysis Engine: Used to calculate the correlation between physiological indicators and psychological characteristics;

[0051] Nutritional needs analysis submodule: Generates personalized diet and specific nutrient intake recommendations based on metabolic data;

[0052] Exercise plan generation submodule: Recommends suitable exercises based on the user's physical health and personality traits;

[0053] Emotional support optimization submodule: Adjust intervention strategies based on love language type.

[0054] A health management method, applied to a personalized health management system based on multi-dimensional health intervention, includes the following steps:

[0055] S1. Collect users' physical examination reports, psychological assessments, lifestyle data, and self-test data on their health and physical sensations;

[0056] S2. Organize, standardize, and integrate the data;

[0057] S3. Generate personalized health intervention plans through the intelligent analysis module;

[0058] S4. Provide users with health advice and optimize subsequent intervention strategies.

[0059] A health management method, wherein S3 includes:

[0060] Assess cardiovascular disease risk levels and prioritize management efforts;

[0061] Optimize intervention methods by combining personality traits and love language types;

[0062] The health plan is dynamically adjusted based on user feedback.

[0063] Compared with the prior art, the beneficial effects of the present invention are: the personalized health management system and method based on multi-dimensional health intervention selects appropriate exercises based on user personality traits, optimizes interaction with the language of love, improves user execution rate, and can provide feedback and suggestions based on the user's own situation to optimize subsequent intervention strategies, making it more scientific, reasonable and effective. Attached Figure Description

[0064] Figure 1 This is a system block diagram of the present invention;

[0065] Figure 2 This is a system block diagram of the data acquisition module of the present invention;

[0066] Figure 3 This is a system block diagram of the intelligent analysis module of the present invention.

[0067] The diagram shows: 1. Data Acquisition Module; 11. Key Indicator Extraction Unit for Physical Examination Reports; 111. Multi-Format Report Parser; 112. Medical Entity Recognition Engine; 113. Dynamic Field Matching Library; 114. Outlier Marking Unit; 12. Psychological Assessment Unit; 121. Personality Test Analysis Submodule; 122. Love Language Recognition Submodule; 123. Psychological-Physiological Association Rule Library; 13. Personality Test Analysis Submodule; 14. Psychological-Physiological Association Rule Library; 141. Symptom-System Mapping Algorithm; 142. Health Radar Chart Generator; 15. Cardiovascular Disease Risk Assessment Unit; 2. Data Processing Module; 3. Intelligent Analysis Module; 31. Physiological-Psychological Feature Cross-Analysis Engine; 311. Dynamic Weight Calculation Unit; 312. Association Rule Library; 313. Conflict Arbitration Unit; 32. Nutritional Needs Analysis Submodule; 33. Exercise Program Generation Submodule; 34. Emotional Support Optimization Submodule; 4. User Interaction Module. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] See also Figure 1-3 One embodiment of the present invention provides: a personalized health management system based on multi-dimensional health intervention, comprising:

[0070] Data acquisition module 1: Used to acquire users' physiological data, psychological assessment data, lifestyle data, and health self-test data;

[0071] Data acquisition module 1 includes:

[0072] Unit 11 for extracting key physiological indicators from hospital physical examination reports: used to analyze hospital physical examination reports and extract key physiological indicators;

[0073] The key indicator extraction unit for physical examination reports includes 11: a multi-format report parser 111, used for structured processing of multi-format physical examination reports; a medical entity recognition engine 112, used to identify the indicator names, values ​​and units in the report; a dynamic field matching library 113, used to store indicator aliases and clinically equivalent terms; and an outlier marking unit 114, which automatically marks abnormal indicators according to preset thresholds.

[0074] Psychological Assessment Unit 12: Used to analyze personality test and love language test data;

[0075] Psychological assessment unit 12 includes:

[0076] Personality Test Analysis Submodule 121: Tests users' personality traits through questionnaires, specifically categorized into lively, powerful, perfectionist, and peaceful types;

[0077] The test questionnaire is shown in the table below:

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084] Among them, S represents the lively type, C represents the strong type, M represents the perfectionist type, and P represents the peaceful type. By counting the number of SCMPs, the user's personality type is determined, and a suitable exercise program is matched for the user.

[0085] Love Language Recognition Submodule 122: Determines users' preferred emotional interaction methods through questionnaires;

[0086] The test questionnaire is shown in the table below:

[0087]

[0088]

[0089] Among them, A: verbal affirmation, B: time spent together (careful moments), C: giving and receiving gifts, D: service behavior, and E: physical contact, the user's preferred emotional interaction method is determined based on the number of A, B, C, D, and E.

[0090] Psychological-physiological association rule base 123: Stores the mapping relationship between personality traits and healthy behaviors.

[0091] Lifestyle Survey Unit 13: Used to collect data on users' eating, exercise, and sleep habits;

[0092] Health Self-Assessment Questionnaire Analysis Unit 14: Used to analyze the 100 questions in the health self-assessment completed by users;

[0093] Health self-assessment questionnaire analysis unit 14 includes:

[0094] Symptom-System Mapping Algorithm 141: Used to associate self-tested symptoms with corresponding physiological systems;

[0095] Health Radar Chart Generator 142: Used to visualize the degree of deviation of a user's health status.

[0096] The following table contains 100 questions for a health self-test:

[0097]

[0098]

[0099] Cardiovascular Disease Risk Assessment Unit 15: Used to calculate the user's 10-year cardiovascular disease risk score. The 10-year cardiovascular disease risk score is shown in the table below:

[0100]

[0101]

[0102] Based on the user's self-test results, a total score of 40 or above indicates high risk, 20-39 indicates medium risk, and below 10 indicates low risk. Personalized intervention plans can be generated based on the user's self-test score. For example, health education (such as salt control guidelines) can be provided for low risk, customized exercise plans can be provided for medium risk, and nutritionist meal replacements and smoking cessation supervision can be provided for high risk.

[0103] Data processing module 2: Used to organize, standardize, and integrate multi-source health data.

[0104] Intelligent Analysis Module 3: Used to generate personalized health intervention plans;

[0105] The intelligent analysis module 3 includes:

[0106] Physiological-Psychological Feature Cross-Analysis Engine 31: Used to adjust the weights of physiological and psychological data based on the user's current state, store verified physiological-psychological association rules, and handle data inconsistencies.

[0107] Nutritional Needs Analysis Submodule 32: Generate personalized diet and specific nutrient intake recommendations based on metabolic data;

[0108] Exercise program generation submodule 33: Recommends suitable exercises based on the user's physical health and personality traits;

[0109] Emotional support optimization submodule 34: Adjusting intervention strategies based on love language type.

[0110] Recommend suitable exercise types and intervention strategies based on user personality types. See the table below for specific correspondences:

[0111]

[0112] User interaction module 4: Used to provide users with health advice and collect user behavior data.

[0113] Based on the same inventive concept, this invention also proposes a health management method, applied to a personalized health management system based on multi-dimensional health intervention, comprising the following steps:

[0114] S1. Collect users' physical examination reports, psychological assessments, lifestyle data, and self-test data on their health and physical sensations;

[0115] S2. Organize, standardize, and integrate the data;

[0116] S3. Generate personalized health intervention plans through the intelligent analysis module, specifically including:

[0117] Assess cardiovascular disease risk levels and prioritize management efforts;

[0118] Optimize intervention methods by combining personality traits and love language types;

[0119] The health plan is dynamically adjusted based on user feedback.

[0120] S4. Provide users with health advice and optimize subsequent intervention strategies.

[0121] For example, if a high-pressure user prefers "service behavior" but the system detects a high-pressure state, psychological intervention and quick and convenient strategies can be used to help the customer reduce stress and provide a good user experience.

[0122] Based on the same inventive concept, this invention also proposes an intervention method that, after reading a user's "Personality Analysis" and "The Five Love Languages," achieves health management through psychological and behavioral intervention.

[0123] The effectiveness verification data for this embodiment is shown in the table below:

[0124] Combination type Exercise adherence rate (3 months) User satisfaction Lively type + physical contact 89％ 4.9 / 5 Strength-based + service behavior 93％ 4.7 / 5 Perfectionist + Careful Moments 99％ 5.0 / 5 Peaceful type + verbal affirmation 98％ 4.8 / 5

[0125] Choosing the right type of exercise and interaction method based on user personality traits can effectively improve users' exercise persistence and satisfaction.

[0126] 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 invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A personalized health management system based on multi-dimensional health intervention, characterized in that, include: Data acquisition module: used to acquire users' physiological data, psychological assessment data, lifestyle data, and health self-test data; Data processing module: used to organize, standardize, and integrate multi-source health data; Intelligent analysis module: used to generate personalized health intervention plans; User interaction module: Used to provide health advice to users and collect user behavior data.

2. The personalized health management system based on multi-dimensional health intervention according to claim 1, characterized in that, The data acquisition module includes: Key indicator extraction unit for physical examination reports: used to analyze hospital physical examination reports and extract key physiological indicators; Psychological assessment unit: used to analyze personality test and love language test data; Lifestyle survey unit: used to collect data on users' eating, exercise, and sleep habits; Health Self-Assessment Questionnaire Analysis Unit: Used to analyze the 100 health self-assessment questions filled out by users; Cardiovascular disease risk assessment unit: Used to calculate the user's 10-year cardiovascular disease risk score.

3. A personalized health management system based on multi-dimensional health intervention according to claim 2, characterized in that, The key indicator extraction unit in the physical examination report includes: A multi-format report parser for structuring multi-format medical examination reports; A medical entity recognition engine is used to identify the names, values, and units of indicators in reports. A dynamic field matching library is used to store indicator aliases and clinically equivalent terms; The outlier marking unit automatically marks outlier indicators based on preset thresholds.

4. A personalized health management system based on multi-dimensional health intervention according to claim 2, characterized in that, The aforementioned psychological assessment unit includes: Personality Test Analysis Submodule: Used to test the user's personality traits; The Love Language Recognition Submodule is used to determine the user's emotional needs and preferred interaction methods. Psychological-physiological association rule base: Stores the mapping relationship between personality traits and healthy behaviors.

5. A personalized health management system based on multi-dimensional health intervention according to claim 2, characterized in that, The aforementioned health self-assessment questionnaire analysis unit includes: Symptom-system mapping algorithm: used to associate self-tested symptoms with corresponding physiological systems; Health Radar Chart Generator: Used to visualize the degree of deviation from a user's health status.

6. A personalized health management system based on multi-dimensional health intervention according to claim 1, characterized in that, The intelligent analysis module includes: Physiological-Psychological Characteristic Cross-Analysis Engine: Used to calculate the correlation between physiological indicators and psychological characteristics; Nutritional needs analysis submodule: Generates personalized diet and specific nutrient intake recommendations based on metabolic data; Exercise plan generation submodule: Recommends suitable exercises based on the user's physical health and personality traits; Emotional support optimization submodule: Adjust intervention strategies based on love language type.

7. A health management method, applied to a personalized health management system based on multi-dimensional health intervention as described in any one of claims 1-6, characterized in that, Includes the following steps: S1. Collect users' physical examination reports, psychological assessments, lifestyle data, and self-test data on their health and physical sensations; S2. Organize, standardize, and integrate the data; S3. Generate personalized health intervention plans through the intelligent analysis module; S4. Provide users with health advice and optimize subsequent intervention strategies.

8. A health management method according to claim 7, characterized in that, S3 includes: Assess cardiovascular disease risk levels and prioritize management efforts; Optimize intervention methods by combining personality traits and love language types; The health plan is dynamically adjusted based on user feedback.

Images