CN114943629A - Health management and health care service system and health management method thereof - Google Patents
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Abstract
The invention discloses a health management and health care service system and a health management method thereof.A client mobile terminal is used for maintaining user identity information and acquiring user health index information and investigation information; the health management and health care service system is used for acquiring identity information, health index information and investigation information of a user, performing health evaluation according to the health index information and the investigation information to determine the health risk level of the user, automatically generating a corresponding health intervention scheme, performing health intervention, health tracking guidance and health effect evaluation on the user according to the health intervention scheme, and performing health early warning when abnormal values occur to the health index information of the user; the health manager mobile terminal is used for information maintenance of the health manager and information interaction with the client mobile terminal. According to the invention, health evaluation is carried out through health index information, and on the basis, health managers carry out client health intervention work, so that the health detection and intervention efficiency is improved, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of health management, in particular to a health management and healthcare service system and a health management method.
Background
Since the 21 st century, due to the improvement of the living standard of people, the acceleration of the aging process of population, the change of the living environment of human beings and other factors, with the progress of society and the development of health science, health has already occupied a very important place in the mind of people, and scientific health management and health care services have attracted more and more attention of people. The health management and health care service aims at preventing and controlling the occurrence and development of diseases, reducing medical expenses and improving the quality of life, and aims at providing health education for individuals and groups, improving self-management consciousness and level and continuously improving health risk factors related to life styles of the individuals and the groups through means of health information acquisition, health detection, health assessment, personalized health management schemes, health intervention and the like.
At present, in the field of big health, the development of the health care industry lags behind the public system as a main medical system for a long time. However, with the release of the Chinese white paper for health economy, the important role of the non-medical part in the aspect of health consumption is emphasized. With the continuous development of 5G networks and big data and cloud computing technologies, the big health industry has begun to enter the information-based era.
However, health management and health care services in China are in a starting stage, an integrated and comprehensively coordinated health management and health care service system is not formed, and health monitoring, health file establishment, health assessment, health intervention, tracking guidance and effect assessment cannot be effectively carried out on the health conditions of people.
The existing health assessment method comprises the following steps: collecting various personal health index data through effective means, for example, the health index data comprises blood pressure data, blood sugar data and the like; then, each health index data is sorted and analyzed to realize reasonable judgment of the current health state and the health development trend of the human body.
The main problems of the health assessment method are as follows: when a certain health index is judged, only one detection result of the health index is judged, so that the accuracy of health evaluation is limited, and meanwhile, only objective index evaluation is carried out, and subjective feeling of a life individual is lacked.
The existing health management system only focuses on the front-end data collection or a single health scheme.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a health management and healthcare service system and a health management method aiming at the defects of the prior art, so as to greatly promote the improvement of the service quality and the improvement of the service efficiency on providing more intimate and humanized services for users.
The technical scheme is as follows: the health management and health care service system runs in a cloud server, and is connected with a client mobile terminal and a health manager mobile terminal through a network;
the client mobile terminal is used for maintaining user identity information and acquiring user side health index information and investigation information;
the health management and health care service system is used for acquiring identity information, health index information and investigation information of a user, performing health evaluation according to the health index information and the investigation information to determine a health risk level of the user, automatically generating a corresponding health intervention scheme, performing health intervention, health tracking guidance and health effect evaluation on the user according to the health intervention scheme, and performing health early warning when abnormal values occur to the health index information of the user;
the health manager mobile terminal is used for information maintenance of the health manager, obtaining a health intervention scheme of the user and conducting health tracking guidance on the user.
The technical scheme is further improved, the health management and health care service system is further connected with an intelligent health management and health care service store management system and an intelligent health management and health care service platform management system, the intelligent health management and health care service platform management system is used for managing the intelligent health management and health care service stores belonging to the intelligent health management and health care service store on the intelligent health management and health care service store management system is used for managing the users belonging to the intelligent health management and health care service stores and health managers, and the intelligent health management and health care service stores are provided with health management integrated machines for collecting health index information of the users;
the health management and health care service system comprises an organization management module, a user management module, a health evaluation module, a health intervention module, a health early warning module, a health tracking guidance module and a health effect evaluation module;
the institution management module is used for information management of an affiliated intelligent health management and health care service store on the platform and an affiliated health manager on the store;
the user management module is used for acquiring identity information, health index information, investigation information and process information of a health intervention scheme executed by a user;
the health management module is used for managing a health database;
the health evaluation module is used for determining the health risk level of the user according to the identity information, the health index information and the investigation information of the user;
the health intervention module is used for automatically generating a health intervention scheme of the user according to the health risk level of the user;
the health tracking guidance module is used for making a health plan according to a health intervention scheme of the user, and guiding and recording a health execution process of the user;
the health effect evaluation module is used for evaluating the user intervention effect according to the health intervention scheme execution process of the user;
the health early warning module is used for detecting the health indexes of the user, and outputting early warning information to the health manager mobile terminal and the client mobile terminal when the health indexes are abnormal.
The health management method based on the health management system comprises the following steps:
acquiring identity information and health index information of a user;
acquiring survey parameters of a user;
matching and determining a health risk index of the user from a pre-established health management evaluation model according to the health index information and the survey parameters of the user;
acquiring a self-sensing health score of a user;
determining a health dynamic level according to the health risk index and the self-perception health score of the user;
automatically generating a health intervention scheme of the user according to the health dynamic level of the user;
and guiding and recording the health execution process of the user according to the health intervention scheme of the user.
Further, phase data in the health execution process of the user and the latest health index information, survey parameters and self-induction health score of the user are obtained, and the health intervention scheme of the user is updated.
Further, the identity information, the health index information, the survey parameters and the self-induction health score of the user are acquired through a client mobile terminal or a health management all-in-one machine arranged in a store and then transmitted to a cloud server.
Further, the evaluation process of the health dynamic level comprises:
dividing the obtained health index information and survey parameters according to clinical medicine dimension, symptom index dimension, physique and physical ability dimension, health life style dimension, cognition and daily activity ability dimension, health literacy dimension, psychology and social support dimension, respectively calculating the score of each dimension, carrying out standardization processing on the scores, and carrying out weighted calculation on the standardized scores of seven dimensions to obtain a health level comprehensive score;
associating the obtained health index information and investigation parameters with risk factors related to each model based on an overweight/obesity model, a hypertension model, a hyperlipidemia model, a diabetes model, a cardiovascular disease model, a cerebrovascular disease model and a tumor model to obtain a risk score of each model, and carrying out weighted calculation on the risk scores of the seven models to obtain a health risk comprehensive score;
carrying out weighted calculation on the health level comprehensive score and the health risk comprehensive score to obtain a health risk index;
acquiring self-sensing health scores of users, and carrying out weighted calculation on the health risk indexes and the self-sensing health scores to obtain health dynamic indexes;
and acquiring health dynamic indexes of a plurality of time points, and generating a health dynamic level curve with time as an X axis and the health dynamic indexes as a Y axis.
Further, the health index information is acquired through a sensor device with a body parameter measuring function, and the survey parameters and the self-sensing health scores are acquired through a questionnaire survey mode.
Further, risk factors related to the overweight and obesity model, the hypertension model, the hyperlipidemia model, the diabetes model, the cardiovascular disease model, the cerebrovascular disease model and the tumor model are divided into internal factors and external factors;
defining steady state parameters of the model as f, wherein a is an internal factor ratio, b is an external factor ratio, the internal factor ratio is an internal factor score/an internal factor total score, and the external factor ratio is an external factor score/an external factor total score;
when the steady state f is 1, the balance of external factors and internal factors is represented, and the healthy dynamic level tends to be stable; when the steady state f is less than 1, the trend of the healthy dynamic level is upward; when the steady state f is more than 1, the healthy dynamic level trends downwards.
Further, the health index information includes, but is not limited to, height, weight, blood sugar, blood fat, blood pressure, heart rate, body fat rate; the survey parameters include, but are not limited to, gender, age, waist circumference, hip circumference, family history, past medical history, present medical history, smoking, drinking, diet, drinking water, exercise, sleep, environmental, psychological emotional state.
Further, the self-sensing health score of the user is in a robot question-answer interaction mode, the user firstly selects a self-sensing score level, the robot outputs a score interval corresponding to the self-sensing score level, and the user further selects a specific score in the score interval as the self-sensing health score.
Further, the self-sensing health score of the user is in a robot question-answer interaction mode, the user firstly selects a self-sensing score grade, the robot outputs a score interval corresponding to the self-sensing score grade, and the user further selects a specific score in the score interval to serve as the self-sensing health score.
Has the advantages that: compared with the prior art, the invention has the advantages that: the health management health service system and the health management method comprehensively solve the problems of six links of front-end health data acquisition, health file establishment, health assessment, health intervention, health tracking guidance and health effect evaluation according to the requirements of health management health service specifications. The Internet technology is used for establishing a health manager expert system, establishing a health management and health care service standardized flow and specification, and replacing part of basic work of health managers by using a computer artificial intelligence technology.
The whole health management and health care service process is full-automatic and real-time, a health manager and a user can interact in two ways, a terminal data acquisition part is provided, a client can finish the terminal questionnaire part, the robot automatically asks questions, and the terminal data acquisition part and the client form good man-machine interaction, so that the health management and health care service specialty is improved, the interest of the client experience is improved, and the time of the health manager is greatly saved, by using the system, the health evaluation can be simultaneously carried out on tens of thousands of clients, the health manager which can only provide health management and health care service one by one originally is liberated from the work of repeated basis, the health manager can have more energy to analyze a health management evaluation model established after the client health information collected by the system, and the health management model is more professionally put into the work of client health intervention, health tracking guidance and health effect evaluation, the efficiency of user function health detection and intervention is improved to the greatest extent, the trouble of human factors is eliminated, and the user experience is improved.
Meanwhile, the intelligent expert system based on cloud computing and big data can not only accept the intellectual contribution of each partner openly, but also can learn and iterate automatically, and does not need to occupy too much manpower to update the algorithm and the knowledge base manually, thereby greatly reducing the maintenance cost.
Drawings
FIG. 1 is a schematic block diagram of a health management healthcare service system of the present invention;
FIG. 2 is a flow chart of the comprehensive health risk assessment of the present invention;
FIG. 3 is a flow chart of the method for comprehensive assessment of health risk according to the present invention for calculating a health dynamic level curve.
Detailed Description
The technical solution of the present invention is described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the embodiments.
As shown in fig. 1, the health management and healthcare service system integrates a client mobile terminal 2, a health manager mobile terminal 3, an intelligent health management and healthcare service store management system 4, and an intelligent health management and healthcare service platform management system 5. The health management and health care service system 1 runs in a cloud server, the cloud server is in communication connection with a client mobile terminal 2, a health manager mobile terminal 3, a smart health management and health care service store management system 4 and a smart health management and health care service platform management system 5, a Bluetooth electronic sphygmomanometer 7 and a Bluetooth body fat scale 8 which are used by the client mobile terminal 2 are used for collecting health index information, and a health management all-in-one machine 6 used by the store terminal is used for collecting health index information.
The health management and health care service system comprises an organization management module 101, a user management module 102, a health management module 103, a health assessment module 104, a health intervention module 105, a health early warning module 106, a health tracking guidance module 107 and a health effect evaluation module 108, wherein:
the organization management module 101 is used for information management of the intelligent health management and health care service store and the health manager on the platform; the user management module 102 is configured to obtain identity information of a user, basic information of the user, a user evaluation report, a health profile of the user, a physical examination report, health data, a health plan, and a follow-up visit record; the health management module 103 is used for acquiring health index information, a disease library, a food material library, an exercise library and risk factor management of a user;
the health evaluation module 104 is configured to determine a health risk level of the user according to the identity information of the user and the health index information of the user;
the health intervention module 105 is used for automatically generating a health intervention scheme of the user according to the health risk level of the user;
the health early warning module 106 is used for detecting health indexes such as user weight, heart rate, blood pressure value, blood sugar value, sleeping condition and the like, when abnormality occurs, a background alarm prompts a health manager to follow up the user in time, and a user mobile terminal can synchronously receive abnormality reminding information;
the health tracking guidance module 107 is used for making a health plan according to the health intervention scheme of the user and guiding and recording the health execution process of the user;
the health effect evaluation module 108 is configured to evaluate a client intervention effect in an execution process of a health intervention scheme according to a user, and is configured to correct a future health management and healthcare service scheme, where the evaluation includes improvement of three (1) indicators: when the self-management is determined to be carried out, indexes including health indexes are formulated; (2) changes in cognition and behavior; (3) change in compliance.
The invention also provides a 2+1 health management method, and the explanation of terms related to the method is shown in the table 1:
TABLE 1 noun explanation of health management method
According to the health management method provided by the invention, health index information is obtained through the measurement of the sensor equipment, and health assessment is carried out by combining survey parameters (the health index information and the survey parameters can reach 378 risk factor information at most) input by questionnaires of a client mobile terminal and a store terminal. The health indicator information may be: health record data of physical examination mechanism physical examination data, intelligent wearing equipment, intelligent all-in-one machine equipment, user app. Specifically, the health index information and survey parameters selected by the invention include sex, height, weight, age, family history, past medical history, present medical history, blood sugar, blood fat, blood pressure, waist circumference, hip circumference, heart rate, blood oxygen saturation, glycated hemoglobin, homocysteine, uric acid, triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein, carotid plaque, brain CT result, cardiac function classification, smoking, drinking, diet, drinking water, exercise, sleep, environment, psychological emotional state and the like, and comprehensively reflect 7 dimensions for health assessment: clinical medicine dimension, symptom index dimension, constitution and physical ability dimension, healthy lifestyle dimension, cognitive and daily activity ability dimension, health literacy dimension, psychological and social support dimension. And (3) adopting a formula f (1-sigma score/sigma topic total score) × 100% in each mode, carrying out data standardization, mapping each dimensionality score to the same interval, calculating each dimensionality score, and calculating the comprehensive score of the health level according to weighting.
The health assessment model may include objective measurement indicators such as height, weight, blood pressure, blood sugar, etc., and subjective indicators such as symptom expression, mood, physical activity, etc., which cannot be directly measured. Using the health level composite score to evaluate the health condition of the user, seven dimensions have respective weights, for example, a clinical medicine dimension, a symptom index dimension may have a higher weight under the application of evaluating the risk of the user suffering from a disease; psychological and social support dimensions may have higher weights under the application of assessing the user's mental state; in an application of encouraging a user to exercise actively and live healthily, the physical and physical dimensions and the healthy lifestyle dimensions may have higher weights. The invention is not limited to this, and any other evaluation model can be used for calculation, and the inventor selects the model through the research and analysis of a large amount of data, not only considers the main diseases which bring great adverse effects to the human mouth health and the life expectancy, but also selects a model with better applicability according to the physical characteristics of the Chinese.
The health assessment model gives a series of risk factors and their Relative Risk (RR) based on the health index information and survey parameters. In the invention, the relative risk degree is converted into a risk score, and the risk exposure rate (p value) of risk factor population is combined to evaluate the individual suffering risk of a certain disease; then, the risk of disease, which can be based on 7 diseases, including overweight, obesity, diabetes, hypertension, hyperlipidemia, cardiovascular disease, cerebrovascular disease, tumors, obtained using a synthetic analysis method; and then carrying out standardization and calculating a comprehensive score.
In addition, the method can also be based on Internet health big data, perform multi-index comprehensive evaluation, present in a quantitative form, and operate in a social e-commerce mode, so that the individual health responsibility is stimulated, health risks of individual users are guided in an intervention manner by providing health management and health care services, follow-up is continued, and the health behaviors of the individual users are improved.
The health assessment model runs in a server, the server is in communication connection with a client mobile terminal, a health administrator client terminal and a health management all-in-one machine, and a flow chart of the health risk comprehensive assessment method is shown in fig. 2. The health risk comprehensive assessment method 100 includes:
and 140, calculating a health level comprehensive score, namely a weighted sum of the scores of the clinical medicine dimension, the functional symptom dimension, the physique and physical ability dimension, the health life style dimension, the cognition and daily activity ability dimension, the health literacy dimension and the psychological and social support dimension.
FIG. 3 is a flow chart of a method for comprehensive assessment of health risk, comprising the steps of:
in steps 200 and 201, health index information and survey parameters are acquired. The health indicator information may be measured by various biosensors, such as a blood pressure sensor, a blood lipid sensor, a blood glucose sensor, a blood oxygen sensor, a heart rate sensor, and the like. Survey parameters may be input from the terminal device, for example, a survey questionnaire is presented on the terminal device, and completed by the user. The health index information and the survey parameters may be transmitted to a server via a network for calculation of a health risk composite score. Here, the health index information includes, but is not limited to, height, weight, blood sugar, blood fat, blood pressure, heart rate, and body fat rate, and the survey parameters include, but are not limited to, gender, age, waist circumference, hip circumference, family history, past medical history, present medical history, smoking, drinking, diet, drinking, exercise, sleep, environment, and psychological emotional state. Those skilled in the art will appreciate that these parameters and combinations with each other and operations are used to determine or judge whether the relevant condition of health risk is met, whereby the health condition of the user can be evaluated.
Step 211-.
Step 221- & gt227, calculating a risk score for each disease using the overweight | obesity model 221, the hypertension model 222, the hyperlipidemia model 223, the diabetes model 224, the cardiovascular disease model 225, the cerebrovascular disease model 226 and the tumor model 227 according to the 378 kinds of risk factor information included in the 7 dimensions obtained in step 211- & gt217.
And step 232, acquiring self-sensing health scores of the target individuals through robot question-answer interaction. The health self-induction score grade is five: 1-20 for "poor", 21-40 for "poor", 41-60 for "normal", 61-80 for "good", 81-100 for "good"; the target individual selects the grade first, and then carries out subjective scoring on the health condition of the target individual according to the grade. The self-induction health score is 1-100 points from low to high; score 1 represents worst and 100 represents best. Examples are as follows: firstly, selecting a self-induction grading grade as 'better' for a target individual, and prompting a specific grading interval as '61-80' by a system terminal robot; secondly, selecting '75' as a self-induction health score of a target individual; and thirdly, the system obtains a final result, and the self-infection health score of the target individual is 75.
And 241, obtaining the health dynamic index of the final target individual according to the results of the steps 231 and 232 and a specific algorithm, and performing multiple evaluation comparison to obtain the health dynamic index of the target individual, wherein in an XY coordinate axis, an X axis is a time axis, a Y axis is the health dynamic index, and the results of multiple evaluations of the target individual form a health dynamic horizontal curve.
According to the present embodiment, each disease model contains risk factors, and therefore, only the positive correspondence of the Relative Risk (RR) to the risk score in the 2+1 health assessment model is retained. That is, only risk factors having a relative risk degree greater than 1 are considered. Converting to obtain a risk score according to the risk grade of the relative risk RR, and classifying the hypertension group into low-risk, medium-risk and high-risk classifications according to the risk score; the hypertension susceptible population is divided into low risk population, middle risk population and high risk population according to the score. The crowd without triggering the related risk items is non-hypertension susceptible crowd and belongs to hypertension slight risk crowd. The 2+1 health assessment module screens key populations for hypertension, primarily because these populations have a higher chance of developing hypertension. This is not to say that hypertension is necessarily expected for people at high risk. However, it is helpful for the health manager to be able to find the trace of hypertension at the earliest stage by accurately determining the important population (high risk population) through the tool and outputting the screening result as a report to advise the population to receive hypertension screening regularly. Hypertension has a greater chance of success with health interventions when found early.
Taking a hypertension model as an example, the hypertension model comprises 19 risk factors, the assigning range of the model is 0-25 points, and the risk factors are divided into internal causes and external causes according to different action points on individual health, wherein 10 internal causes and 9 external causes are included. The higher the individual score, the higher the risk of hypertension. The details of the model's individual risk factor level assignments are shown in Table 2.
TABLE 2 hypertension model
| Risk factors (internal cause) | Assignment of value | Risk factors (external cause) | Assignment of value |
| Family history of hypertension | Is-1, no-0 | Insufficient intake of vegetables | Is-1, no-0 |
| Age (more than or equal to 45 years old) | Is-1, no-0 | Insufficient intake of fruit | Is-1, no-0 |
| Gender (Male) | Is-1, no-0 | Lack of exercise | Is-1, no-0 |
| Isolated systolic hypertension | Is-1, no-0 | Noise (S) | Is-1, no-0 |
| High blood pressure level 1 | Is-2, is-0 | Insufficient drinking water | Is-1, no-0 |
| Hypertension of grade 2 | Is-3, no-0 | Drinking wine | Is-1, no-0 |
| Hypertension of 3 grades | Is-4, is not-0 | Passive smoking | Is-1, no-0 |
| Overweight | obesity symptoms | Is-1, no-0 | Smoking | Is-1, no-0 |
| Triglyceride excess | Is-1, no-0 | High salt diet | Is-1, no-0 |
| High density lipoprotein hypoplasia | Is-1, no-0 |
The questionnaire designed for the self-perceived health dimension and its risk factors are detailed in table 3.
TABLE 3 self-inductance health Scoring questionnaire
Compared with the prior art, the health management health service system and the health management method provided by the invention are determined according to the identity information of the user and the health index information of the user by acquiring the identity information and the health index information of the user. The health risk level of the user automatically generates a health guidance scheme of the user according to the health risk level of the user, records the health execution process of the user according to the health guidance scheme of the user, timely adjusts the health guidance scheme of the user, can formulate different health guidance schemes aiming at different crowds, timely and effectively prevents, evaluates and intervenes chronic diseases, and evaluates execution effects.
As noted above, while the present invention has been shown and described with reference to certain preferred embodiments, it is not to be construed as limited to the invention itself. Various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A health management and health care service system runs in a cloud server and is characterized in that: the health management and health care service system is connected with a client mobile terminal and a health manager mobile terminal through a network;
the client mobile terminal is used for maintaining user identity information and acquiring user side health index information and investigation information;
the health management and health care service system is used for acquiring identity information, health index information and investigation information of a user, performing health evaluation according to the health index information and the investigation information to determine a health risk level of the user, automatically generating a corresponding health intervention scheme, performing health intervention, health tracking guidance and health effect evaluation on the user according to the health intervention scheme, and performing health early warning when abnormal values occur to the health index information of the user;
the health manager mobile terminal is used for information maintenance of the health manager, obtaining a health intervention scheme of the user and conducting health tracking guidance on the user.
2. The health management healthcare service system according to claim 1, wherein: the health management and health care service system is further connected with an intelligent health management and health care service store management system and an intelligent health management and health care service platform management system, the intelligent health management and health care service platform management system is used for managing the intelligent health management and health care service stores belonging to the intelligent health management and health care service store on the platform, the intelligent health management and health care service store management system is used for managing the users and health managers belonging to the intelligent health management and health care service store, and the intelligent health management and health care service store is provided with a health management integrated machine for collecting health index information of the users;
the health management and health care service system comprises an organization management module, a user management module, a health evaluation module, a health intervention module, a health early warning module, a health tracking guidance module and a health effect evaluation module;
the institution management module is used for information management of an intelligent health management and health care service store on the platform and a health manager on the store;
the user management module is used for acquiring identity information, health index information, investigation information and process information of a health intervention scheme executed by a user;
the health management module is used for managing a health database;
the health evaluation module is used for determining the health risk level of the user according to the identity information, the health index information and the investigation information of the user;
the health intervention module is used for automatically generating a health intervention scheme of the user according to the health risk level of the user;
the health tracking guidance module is used for making a health plan according to a health intervention scheme of the user, and guiding and recording a health execution process of the user;
the health effect evaluation module is used for evaluating the user intervention effect according to the health intervention scheme execution process of the user;
the health early warning module is used for detecting the health indexes of the user, and outputting early warning information to the health manager mobile terminal and the client mobile terminal when the health indexes are abnormal.
3. A health management method, comprising the steps of:
acquiring identity information and health index information of a user;
acquiring survey parameters of a user;
matching and determining the health risk index of the user from a pre-established health management evaluation model according to the health index information and the investigation parameters of the user;
acquiring a self-sensing health score of a user;
determining a health dynamic level according to the health risk index and the self-perception health score of the user;
automatically generating a health intervention scheme of the user according to the health dynamic level of the user;
and guiding and recording the health execution process of the user according to the health intervention scheme of the user.
4. The health management method according to claim 3, further comprising: and acquiring phase data in the health execution process of the user, the latest health index information, survey parameters and self-induction health scores of the user, and updating the health intervention scheme of the user.
5. The health management method according to claim 3, wherein: the identity information, the health index information, the survey parameters and the self-induction health score of the user are acquired through a client mobile terminal or a health management all-in-one machine arranged in a store and then transmitted to a cloud server.
6. The health management method according to claim 5, wherein: the evaluation process of the health dynamic level comprises the following steps:
dividing the obtained health index information and survey parameters according to clinical medicine dimension, symptom index dimension, physique and physical ability dimension, health life style dimension, cognition and daily activity ability dimension, health literacy dimension, psychology and social support dimension, respectively calculating the score of each dimension, carrying out standardization processing on the scores, and carrying out weighted calculation on the standardized scores of seven dimensions to obtain a health level comprehensive score;
associating the obtained health index information and investigation parameters with risk factors related to each model based on an overweight/obesity model, a hypertension model, a hyperlipidemia model, a diabetes model, a cardiovascular disease model, a cerebrovascular disease model and a tumor model to obtain a risk score of each model, and carrying out weighted calculation on the risk scores of the seven models to obtain a health risk comprehensive score;
carrying out weighted calculation on the health level comprehensive score and the health risk comprehensive score to obtain a health risk index;
acquiring self-sensing health scores of users, and carrying out weighted calculation on the health risk indexes and the self-sensing health scores to obtain health dynamic indexes;
and acquiring health dynamic indexes of a plurality of time points, and generating a health dynamic level curve with time as an X axis and the health dynamic indexes as a Y axis.
7. The health management method according to claim 5, wherein: the health index information is acquired through sensor equipment with a body parameter measuring function, and the survey parameters and the self-sensing health scores are acquired through a questionnaire survey mode.
8. The health management method according to claim 5, wherein: risk factors related to the overweight and obesity model, the hypertension model, the hyperlipidemia model, the diabetes model, the cardiovascular disease model, the cerebrovascular disease model and the tumor model are divided into internal factors and external factors;
defining steady state parameters of the model as f, f = b/a, wherein a is an internal cause ratio, b is an external cause ratio, the internal cause ratio = internal cause score/internal cause total score, and the external cause ratio = external cause score/external cause total score;
when the steady state f =1, the exogenous and endogenous factors are balanced, and the healthy dynamic level tends to be stable; when the steady state f is less than 1, the trend of the healthy dynamic level is upward; when the steady state f is more than 1, the healthy dynamic level trends downwards.
9. The health management method according to claim 5, wherein: the health index information includes, but is not limited to, height, weight, blood glucose, blood lipid, blood pressure, heart rate, body fat rate; the survey parameters include, but are not limited to, gender, age, waist circumference, hip circumference, family history, past medical history, present medical history, smoking, drinking, diet, drinking water, exercise, sleep, environmental, psychological emotional state.
10. The health management method according to claim 5, wherein: the self-sensing health score of the user is in a robot question-answer interaction mode, the user firstly selects a self-sensing score grade, the robot outputs a score interval corresponding to the self-sensing score grade, and the user further selects a specific score in the score interval as the self-sensing health score.
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| CN115394394A (en) * | 2022-10-27 | 2022-11-25 | 曹县人民医院 | Resident health service reservation method and system based on big data processing technology |
| CN117079818A (en) * | 2023-08-30 | 2023-11-17 | 首都医科大学附属北京世纪坛医院 | Comprehensive evaluation method, system, equipment and medium for climacteric female health |
| CN118297428A (en) * | 2024-04-18 | 2024-07-05 | 湖南汽车工程职业学院 | Health education investigation evaluation method and equipment based on Android platform |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115394394A (en) * | 2022-10-27 | 2022-11-25 | 曹县人民医院 | Resident health service reservation method and system based on big data processing technology |
| CN115394394B (en) * | 2022-10-27 | 2023-04-07 | 曹县人民医院 | Resident health service reservation method and system based on big data processing technology |
| CN117079818A (en) * | 2023-08-30 | 2023-11-17 | 首都医科大学附属北京世纪坛医院 | Comprehensive evaluation method, system, equipment and medium for climacteric female health |
| CN118297428A (en) * | 2024-04-18 | 2024-07-05 | 湖南汽车工程职业学院 | Health education investigation evaluation method and equipment based on Android platform |
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