CN114842971A

CN114842971A - Integrated intelligent management system for comprehensive doctor-patient intelligent management and health active management

Info

Publication number: CN114842971A
Application number: CN202210344121.2A
Authority: CN
Inventors: 胡平; 傅烨; 胡芸倩; 胡立诗; 邵炜; 王全江
Original assignee: Shanghai Pung Information Technology Co ltd
Current assignee: Shanghai Pung Information Technology Co ltd
Priority date: 2022-04-02
Filing date: 2022-04-02
Publication date: 2022-08-02

Abstract

The application relates to an integrated intelligent management system for comprehensive doctor-patient intelligent management and health active management, which comprises: the doctor-patient intelligent management system is used for providing doctor-patient interaction conditions based on an intelligent management mode, and intelligently outputting medical treatment pre-treatment/inquiry, doctor-patient follow-up visit and advice management results according to the acquired second user visit information; the lifestyle active management system is used for establishing a behavior characteristic model according to the life characteristics, monitoring the health data of the second user through the behavior characteristic model, and carrying out active intelligent early warning on the health of the second user by combining the feedback result of the doctor-patient intelligent management system; the first user end is used for calling the doctor-patient intelligent management system; and the second user end is used for logging in and calling the doctor-patient intelligent management system or the living mode active management system. The doctor-patient interaction and the user health management are effectively and comprehensively managed, so that integrated intelligent centralized management is achieved among the doctors and patients, and doctor-patient management and user health activities are effectively and intelligently implemented.

Description

Integrated intelligent management system for comprehensive doctor-patient intelligent management and health active management

Technical Field

The utility model relates to an intelligent medical technology field especially relates to an integrated intelligent management system who synthesizes doctor-patient intelligent management and healthy initiative management.

Background

The world health organization emphasizes in the 21 st century challenge report: "medical science of the 21 st century should not continue to be the main field of disease, and should be the main research direction of medicine with human health". The medical mode of the 21 st century is changed from a simple treatment mode to a healthy medical mode such as environmental, social and psychological health. All the factors influencing the health of people are brought into the category, and the medical research is carried out in an all-round, multi-view and three-dimensional way.

The world health organization defines four major health-related factors, of which "lifestyle" accounts for 60%. This factor, which has been the largest, has often been ignored in the past. In recent years, improvement of healthy water and cure of chronic diseases through lifestyle management are widely concerned and practiced by society, but a large amount of information related to lifestyle (eating, drinking, pulling, scattering, sleeping, joy, anger, sadness, happiness and the like) is fragmented, somewhat contradictory, and more importantly, the information lacks of providing overall and effective association and guidance for all kinds of life information. The life quality is improved and the disease is prevented from being cured from the life style, the cost is low for the user, the effect is high, and the extension value is large; the number of people benefiting the country is large, a large number of medical resources are saved, and the method is beneficial to social stability.

Therefore, in the existing medical technology, more doctors and patients are no longer in the relationship between the user and the medical institution, and the attention of the user on health management is gradually paid.

In the field of traditional medical technology, medical platforms or other terminals, such as medical websites or systems, platforms, etc., appearing in the market are all interactive systems between users and medical institutions, etc., and users can establish medical relationships with medical institutions, such as registration, appointment, payment, etc., through the systems or platforms, but the systems or platforms are simple medical procedures, and the procedures such as off-line inquiry and the like are carried on line.

In addition, the user can well manage the body of the user in a full-health way, and the method is an effective method for the user to establish self health and reduce the interaction chance with a medical institution. The world faces the dilemma of an increased incidence of chronic disease and the increased overall medical costs associated therewith; technological advances have led to an increase in medical levels, with an accompanying increase in user and government medical expenses. People are expected to turn this situation back through lifestyle medicine. Obviously, starting from a healthy life style, the 'preventive treatment' is the most economical and practical. But the confusion with lifestyle health management is: people do not want to change their past behavior, and often go irreparably, which is the remorse to begin.

Therefore, for the self health management of the user, the prior art gradually has a health management system platform or APP, etc., and the health value of the user is early warned by recording the life data of the user. However, the technical means of user health management in the prior art is relatively single and crude, and one or more independent health parameters, such as heart rate and blood pressure, can not be monitored and early-warned intelligently, so that health can not be effectively managed comprehensively, actively and intelligently. Meanwhile, a comprehensive management system for user health management and doctor-patient interaction is lacked.

Disclosure of Invention

In order to solve the problems, the application provides an integrated intelligent management system for comprehensive doctor-patient intelligent management and health active management, so that an artificial intelligence technology is adopted, doctor-patient management modes and user health management are effectively integrated and intelligently managed, an integrated intelligent centralized management effect is achieved between medical treatment and user users, a simple treatment mode is changed into a health medical mode such as environment, society and psychology, and an intelligent tool capable of being executed on the ground is provided for doctors and users through omnibearing, multi-view and three-dimensional medical research. In addition, a human body personalized full-health data model is established, and health information with extremely strong personalized relevance can be intelligently obtained through the model; when the information received by people is highly matched with the health condition of people, people are willing to receive related education and gradually form habits, so that the goals of advocating scientific life style by people and improving the soft strength of the health of people are achieved. Meanwhile, the method can drive the quick and effective development of related health industries.

The technical scheme of the application is as follows:

an integrated intelligent management system for integrating doctor-patient intelligent management and health active management, comprising:

the doctor-patient intelligent management system is used for providing doctor-patient interaction conditions based on an intelligent management mode, and intelligently outputting medical treatment pre-treatment/inquiry, doctor-patient follow-up visit and advice management results according to the acquired second user visit information;

the lifestyle active management system is used for establishing a behavior characteristic model according to the life characteristics, monitoring the health data of the second user through the behavior characteristic model, and carrying out active intelligent early warning on the health of the second user by combining the feedback result of the doctor-patient intelligent management system;

the first user side is used for the first user to log in and call the doctor-patient intelligent management system;

and the second user side is used for logging in and calling the doctor-patient intelligent management system or the living mode active management system by the second user.

As an optional embodiment of the present application, optionally, the doctor-patient intelligent management system includes:

the doctor-patient relationship management system is used for authenticating and logging in the user and carrying out intelligent operation and/or intelligent association processing on the instruction information and/or the task input by the second user according to a preset doctor-patient relationship association module;

The intelligent expert decision system is used for making a decision on the instruction information and/or the task input by the second user according to a preset intelligent expert decision rule and outputting a decision result;

and the intelligent control system is used for performing linkage management control on the doctor-patient relationship through the established linkage control rule and realizing the logic execution of each instruction information and/or task.

As an optional embodiment of the present application, optionally, the doctor-patient relationship management system includes:

the pre-waiting module is used for acquiring second user information and establishing a pre-waiting process according to the second user information;

the intelligent inquiry module is used for intelligently inquiring the second user information through the intelligent expert decision system, wherein the intelligent inquiry comprises the following steps: medical and/or lifestyle inquiries;

the doctor-patient follow-up visit module is used for establishing a follow-up visit channel between doctors and patients according to preset follow-up visit selection conditions;

and the medical advice management module is used for issuing medical advice, and performing decision feedback and medical advice reminding on the second user according to the medical advice execution condition fed back by the second user through the intelligent expert decision rule.

As an optional embodiment of the present application, optionally, the order management module comprises:

An order placement module for placing an order to a second user, wherein the order includes: medication and index orders, lifestyle behavior orders, nutrition conditioning order orders, and/or self-evaluation orders;

the intelligent medical advice tracking module is used for acquiring the medical advice execution condition fed back by the second user in real time and intelligently tracking the medical advice execution condition of the second user in real time through the intelligent expert decision rule;

the medical advice comparison module is used for comparing and analyzing the issued medical advice and historical data through the intelligent expert decision rule and intelligently outputting a comparison and analysis result;

and the medical advice adjusting module is used for adjusting the medical advice issued by the second user according to the medical advice execution condition fed back by the second user through the intelligent expert decision rule.

As an optional embodiment of the present application, optionally, the method further includes:

and the medical advice execution feedback module is used for feeding back the execution condition of the second user on the medical advice, feeding back the execution condition to the medical advice management module, and synchronizing the execution condition to the first user side and/or the second user side.

As an optional embodiment of the present application, optionally, the lifestyle initiative management system includes:

The model creating module is used for carrying out model training according to historical data of different behaviors to obtain different behavior characteristic models and establishing a behavior model system according to the different behavior models;

and the behavior model management module is used for judging the behavior type according to the behavior data, calling a specific behavior model in the behavior model system according to a preset model management rule, and actively managing the behavior of the user through the behavior model.

As an optional embodiment of the present application, optionally, the behavior model system includes at least one of the following behavior models:

the nutrition characteristic feature model is used for calculating deviation values of the collected second user nutrition data and feature data of the nutrition preset model, comparing and judging whether the second user nutrition data reach the standard or not, and if the deviation values are larger than a preset threshold value, outputting a nutrition early warning signal;

the motion characteristic model is used for calculating deviation values of the collected second user motion data and the characteristic data of the motion preset model, comparing and judging whether the second user motion data reach the standard or not, and if the deviation values are larger than a preset threshold value, outputting a motion early warning signal;

The eating balance management characteristic model is used for calculating deviation values of the collected eating data of the second user and preset eating data, comparing and judging whether the eating data of the second user reach the standard or not, and if the deviation values are larger than a preset threshold value, outputting an eating early warning signal;

the sleep characteristic feature model is used for calculating deviation values of the collected second user sleep data and feature data of a sleep preset model, comparing and judging whether the second user sleep data reach the standard or not, and if the deviation values are larger than a preset threshold value, outputting a sleep early warning signal;

the excretion characteristic model is used for calculating deviation values of the acquired second user excretion data and the characteristic data of the excretion preset model, comparing and judging whether the second user excretion data reach the standard or not, and outputting an excretion early warning signal if the deviation values are greater than a preset threshold value;

the living characteristic model is used for calculating deviation values of the collected second user living data and the characteristic data of the living preset model, comparing and judging whether the second user living data reach the standard or not, and if the deviation values are larger than a preset threshold value, outputting a living early warning signal;

the emotion management characteristic model is used for calculating deviation values of the collected second user emotion data and preset emotion characteristic data, comparing and judging whether the second user emotion data reach the standard or not, and if the deviation values are larger than a preset threshold value, outputting an emotion early warning signal;

And the somatosensory management characteristic model is used for calculating a deviation value of the collected second user somatosensory data and preset somatosensory characteristic data, comparing and judging whether the second user somatosensory data reach the standard or not, and outputting a somatosensory early warning signal if the deviation value is greater than a preset threshold value.

As an optional implementation of the present application, optionally, the lifestyle initiative management system further includes:

the data acquisition module is used for acquiring and sending behavior data which influences human health in life behaviors according to preset acquisition conditions;

the intelligent algorithm module is used for acquiring the behavior data, calculating a deviation value of the behavior data according to a preset algorithm and outputting the deviation value;

and the active early warning module is used for feeding back the behavior data of which the deviation value is greater than a preset threshold value through a pre-constructed behavior model system and actively reminding the user of the behavior through the intelligent expert decision system.

As an optional implementation of the present application, optionally, the active warning module is further configured to:

and acquiring a sending instruction of a second user, and sending the behavior data of which the deviation value is greater than a preset threshold value to the intelligent inquiry module according to the sending instruction.

and the display module is used for sending and displaying the behavior data of which the deviation value is greater than the preset threshold value to the first user end and/or the second user end according to a pre-constructed display condition.

The invention has the technical effects that:

the application provides an integrated intelligent management system who synthesizes doctor-patient intelligent management and healthy initiative management includes: a doctor-patient intelligent management system and a living mode active management system; the medical institution logs in and calls the doctor-patient intelligent management system through the first user terminal; and logging in and calling the doctor-patient intelligent management system or the living mode active management system by an individual or a patient through a second user terminal. Through effective comprehensive and intelligent management of doctor-patient interaction and second user health management, integrated intelligent centralized management is achieved among doctors and patients, and doctor-patient management and user health activities are effectively and intelligently implemented.

By adopting the artificial intelligence technology, the medical management mode and the user health management are effectively integrated and intelligently managed, so that the medical treatment and the user are intensively managed, the simple treatment mode is changed into the environmental, social, psychological and other health medical modes, and the medical research is carried out in an all-round, multi-view and three-dimensional way, so that an intelligent tool capable of being executed on the ground is provided for the medical personnel and the user. In addition, a human body personalized full-health data model is established, and health information with extremely strong personalized relevance can be intelligently obtained through the model; when the information received by people is highly matched with the health condition of people, people are willing to receive related education and gradually form habits, so that the goals of advocating scientific life style by people and improving the soft strength of the health of people are achieved. Meanwhile, the method can drive the quick and effective development of related health industries.

Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a schematic diagram showing the components of the application system of the present invention;

FIG. 2 shows a schematic system of the present invention for the composition of a doctor-patient intelligent management system;

FIG. 3 is a schematic diagram showing the components of the order management module of the present invention;

FIG. 4 is a schematic diagram illustrating the components of the lifestyle proactive management system of the present invention;

FIG. 5 is a schematic diagram illustrating the components of the lifestyle initiative management system according to another aspect of the present invention;

fig. 6 shows a radar chart of a motion behavior model in an embodiment of the invention.

Detailed Description

Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.

The medical treatment and second user health management system adopts an artificial intelligence technology to effectively and comprehensively and intelligently manage a medical treatment mode and second user health management, so that the medical treatment and second user centralized management is changed into an environmental, social, psychological and other health medical mode from a simple treatment mode.

The patient or the individual user (the second user for short) and the medical institution or the doctor (the first user for short) can be in integrated online docking for doctor-patient management and individual health management simultaneously through the system platform.

As shown in fig. 1, an integrated intelligent management system for integrated doctor-patient intelligent management and health active management is disclosed, which includes:

The lifestyle active management system is used for establishing a behavior characteristic model according to living characteristics, monitoring the health data of a second user through the behavior characteristic model, and performing active intelligent early warning on the health of the second user by combining the feedback result of the doctor-patient intelligent management system;

In this embodiment, the first user side is a terminal where a medical institution or a doctor or an administrator logs in the system, and may be an APP such as a doctor or a manager, or another login terminal. Doctors and administrators can log in the system through the first user side and call the doctor-patient intelligent management system to handle doctor-patient management relations between patients or individuals, namely the second users.

Similarly, the second user side is a terminal for logging in the system by the patient or the individual user, that is, the second user side, and may be a web page, an individual user side, an applet, or the like. The second user can call the doctor-patient intelligent management system of the system through login to carry out doctor-patient interaction relations such as intelligent pre-diagnosis and inquiry, and can call the living mode active management system to carry out online management on the self health state.

A doctor-patient intelligent management system is mainly used for a first user to participate under the request of a second user.

Firstly, a second user needs to log in the system through a second user end, can log in the system through an Oldham code or an account number and the like, and is guided according to a guide function module of the doctor-patient intelligent management system, so that a doctor-patient relationship is generated between the second user and the first user. For example, when waiting for a doctor, the patient can enter a waiting questionnaire of a filling department after selecting initial diagnosis or follow-up diagnosis by scanning the two-dimensional code of the code waiting area. On this page, the patient can also see the doctor list and details of the waiting department, which is a reference for future medical inquiry. After the waiting questionnaire is finished, the waiting doctor can wait for the number calling in the waiting area. Or the doctor can scan the code when seeing a doctor face to face, or scan the doctor's mobile phone two-dimensional code to establish an online follow-up relationship.

And secondly, the medical end can receive the treatment information from the second user for analysis and judgment, give a suggestion, and intelligently output data such as medical pre-treatment/inquiry, doctor-patient follow-up and advice management results and the like through an expert system of the system according to the obtained treatment information of the second user.

Finally, through the doctor-patient intelligent management system, the intelligent inquiry treatment can be realized for general diseases, and the intelligent inquiry treatment not only relates to common symptom conditions, but also relates to life style behavior inquiry treatment, including nutrition and health conditions, sleeping, excretion, activity, emotion and the like. The inquiry results can be transmitted to the patient in an advice mode, and doctors can adjust the advice in time according to the results of the patient executing the advice tracking management, especially the lifestyle behavior advice and the nutrition conditioning advice. The intelligent expert decision rule enables the patient to follow the symptoms and health changes of the medical advice to form various trend graphs for the doctor and the patient to look up.

The lifestyle behavior medical advice can be combined with a lifestyle active management system to carry out reference and real-time monitoring on life health data of a patient user. Through the medical advice management function, the patient needs to participate deeply, autonomous full-health management and life style health autonomous management can be realized on the small program, and the doctor end can synchronously receive related information according to the medical advice execution condition clicked by the patient on the small program.

By combining the information data of the doctor-patient intelligent management system, the patient can intelligently control the health state of the living behavior through the living mode active management system of the system. The lifestyle active management system establishes different behavior health models according to the living habits of the users and by combining different behavior historical data or reference standards, can be used for monitoring the health data of a second user, namely a patient or an individual according to the behavior characteristic models established according to the living characteristics, and actively and intelligently warns the health of the second user by combining the feedback result of the doctor-patient intelligent management system.

The application functions of the doctor-patient intelligent management system and the lifestyle active management system in the system will be described in detail below, so that the interaction relationship between the patient (or individual), i.e. the second user, and the medical institution (or doctor), i.e. the first user, can be conveniently understood.

As shown in fig. 2, as an optional embodiment of the present application, optionally, the doctor-patient intelligent management system includes:

the doctor-patient relationship management system is used for authenticating and logging in the user and carrying out intelligent operation and/or intelligent association processing on the instruction information and/or the task input by the second user according to a preset doctor-patient relationship association module; the doctor-patient relationship management system is mainly used for authenticating and logging in a first user or a second user logged in the system according to the authority set by the system, and acquiring different process nodes according to different set authorities so as to execute different operation processes on different nodes. The system is provided with doctor-patient relationship association modules with different functions, and the doctor-patient relationship association modules are used for building and processing the doctor-patient relationship between the first user and the second user (specifically, a flow and the association modules can be set according to requirements). The second user inputs information instructions and execution tasks of the process nodes through the second user side, intelligent operation and/or intelligent association processing are/is carried out through a default or custom set algorithm and the like, and node process processing of doctor-patient management is achieved. The various processes and modules and algorithm settings described above are not specifically defined or limited herein.

the system is provided with an intelligent expert decision system, through the expert decision system, measures such as the situation of executing medical orders of a patient, medical orders issued by a doctor, adjustment of the medical orders and characteristics including various aspects of life style behavior and health are modeled and operated, and correlation characteristics can be intelligently output, so that the doctor is helped to realize that the doctor needs to use a philosophy mode to find out regular things from the regular things and see changes, and the rules according to the philosophy, the summary rules, the individuality and the commonality are found. And the intelligent expert decision system analyzes the medical information input by the patient through a preset decision algorithm and flow, and further analyzes and obtains a specific execution result for making decisions on instruction information and/or tasks input by the second user according to the medical expert decision algorithm. Therefore, the intelligent expert decision rules comprise intelligent decision rules for diagnosis and treatment information of patients and intelligent decision rules for life style behavior health, and the intelligent expert decision rules of the integrated intelligent management system for comprehensive doctor-patient intelligent management and active health management are comprehensively set by weighting and setting the weights of the intelligent decision rules and the life style behavior health. For example, the weight of the intelligent decision rule for the patient diagnosis and treatment information is set to 0.7, and the weight of the intelligent decision rule for the living style behavior health is set to 0.3, so that the attention on the patient diagnosis and treatment information can be emphasized. The intelligent expert decision system can adopt a deep learning model for training, train historical data of different aspects to obtain a decision model, and configure the intelligent expert decision rule so as to comprehensively decide information of different aspects.

The intelligent control system is the core of the system and is configured with logic execution rules of all nodes and linkage control rules of node communication. In the doctor-patient relationship process, the flow management and the information communication among all the nodes are controlled by an intelligent control system. The intelligent control system serves as a control center, and not only needs to process the logic scheduling of the application functions of the doctor-patient intelligent management system and the living mode active management system, but also needs to process the instruction information and the conversation of the second user and the first user. The intelligent control system can be implemented by a single chip microcomputer or a control chip and the like, and can be set according to project and condition requirements.

the second user can input information through the second user side to establish a pre-waiting process. Specifically, the patient establishes a pre-waiting diagnosis through code scanning, and the pre-waiting diagnosis is divided into two parts:

1, is the patient's advance completion of personal information, including a complete description of the sensation of symptoms, with days in it; a duration; degree; the intervention that has been taken; the effect of the prognosis of dryness; family medical history; personal history of previous medical history, etc.; also included are personal lifestyle characteristics (including diet, sleep, excretion, activity, mood, etc.) information.

2, help doctors quickly understand the current state of illness and life style behavior characteristic performance related to the illness. With special features to be emphasized, such as allergy history, the expert system will intelligently alert the physician to special attention. Different departments, different diseases and different stages of the diseases have different particularly sensitive information needing special attention, and the system can be flexibly configured, and an expert system provides a window for doctors to add the medicine independently. And with the same characteristic, the doctor only needs to add the medicine once, and then the expert system can intelligently provide the doctor for use. And providing doctor adding, deleting, modifying and checking services. Therefore, the inquiry time can be greatly reduced, and the disease course information of the patient can be accurately known. Meanwhile, the condition that the course of the disease is unknown for a moment is avoided. Provides doctors with more accurate treatment schemes for patients and provides intelligent assistants.

When waiting for a doctor, the patient can enter a waiting questionnaire of a filling department after selecting initial diagnosis or follow-up diagnosis through the two-dimensional code of the code scanning waiting area. On the page, the patient can also see the doctor list and the details of the waiting department, and the reference is provided for future doctor-seeking inquiry. After the waiting questionnaire is finished, the waiting doctor can wait for the number calling in the waiting area.

according to the second user information input during the pre-waiting diagnosis, the basic body health data and the disease symptoms of the patient can be known. Through the intelligent expert decision-making system, the intelligent inquiry of general diseases can be intelligently realized on the obtained basic body health data and diseases of the patient. The intelligent inquiry relates to the inquiry of life style behaviors besides the common symptom conditions, and comprises nutrition health conditions, sleep, excretion, activities, emotions and the like, and can provide advice suggestions for a life style active management system and healthy life behavior suggestions for patient users. In this embodiment, for a special disease, a special inquiry needs to be added, and a special inquiry sub-module is further built in the expert decision module of the intelligent expert decision system, so that the special inquiry is gradually intelligentized.

the doctor-patient follow-up visit aims at: the online intelligent follow-up visit is established between the patient and the medical institution, the workload of the doctor and the patient for the current follow-up visit can be reduced, the doctor can be helped to know the change reason of the patient symptoms more accurately and completely, and a more accurate treatment scheme is provided. Sometimes, after lifestyle behavior changes, symptoms are alleviated without the need for more medications to reduce government drug expenses. Meanwhile, the health management system helps patients to improve the consciousness of self life style behavior health management, reduces the pain of diseases and reduces the drug cost. A healthy life of better quality is obtained. Therefore, a follow-up channel can be established between the doctors and the patients according to preset follow-up selection conditions, on-line follow-up between the patients and medical institutions or doctors is realized, and intelligent living behavior health management is brought to the patients (individual users). The follow-up selection conditions are preset, a follow-up module can be set in the system according to attributes such as user groups, selection permission can be set, and a follow-up flow is established according to the selection permission of the first user or the second user. Therefore, all patients do not need to establish follow-up visits, and the selection is given to doctors, and the doctors can judge and add patients; there may be a patient request, approved by a physician.

And the medical advice management module is mainly used for processing and forwarding medical advice such as medical advice issued by the intelligent expert decision rule to the second user. Meanwhile, the execution situation of the order by the second user and the health state data of the second user need to be collected. After the intelligent expert decision rule gives suggestions according to the basic information of the patient, the medical advice management module collects the suggestions and medical advice of the doctor on the patient together and sends the suggestions and the medical advice to the second user, and the second user is subjected to decision feedback and medical advice reminding.

The order management module will be described in detail below.

As an optional embodiment of the present application, as shown in fig. 3, optionally, the order management module includes:

an order placement module for placing an order to a second user, wherein the doctor can place the order to the user including: medication and index orders, lifestyle behavior orders, nutrition conditioning order orders, and/or self-evaluation orders, therefore, the orders include orders for patients with their own symptoms and diseases and orders for active management of patients' personal health. The patient can receive the medical orders through the second user side, such as on the small program, and can take medicine and adjust the life style according to the medical orders, so that the aim of self health management is fulfilled.

The intelligent medical advice tracking module is used for acquiring the medical advice execution condition fed back by the second user in real time and intelligently tracking the medical advice execution condition of the second user in real time through the intelligent expert decision rule; the patient receives the medical advice that the doctor assigned, needs to carry out the medical advice every day, and intelligent expert's decision rule can evaluate the degree of completion of patient's execution situation every day, and the doctor can look over the evaluation to the execution situation by a key.

The execution of the medical order by the patient is determined by calculating the deviation value, and the calculation method may be separately set for the deviation value as needed, and the specific embodiment is not limited. When the execution deviation value of the patient is larger than the preset value, such as 30%, the intelligent decision system automatically starts to send out a reminding mechanism, wherein the reminding mechanism comprises passive reminding (reminding by a trumpet) or active reminding (particularly reminding for the patient to check the completion condition of the small program), and the doctor can synchronously receive the information. Active or passive reminding is required, and doctors and users can set choices by themselves.

The medical advice comparison module is used for comparing and analyzing the issued medical advice and historical data through the intelligent expert decision rule and intelligently outputting a comparison and analysis result; the doctor's advice that intelligence expert decision rule will be assigned the doctor, the doctor's advice that other doctors of administrative or technical offices assigned, including all kinds of historical doctor's advice, can carry out comprehensive intelligence and compare, the comparison result, and the doctor can look into by one key. The user-defined single-dimension and multi-dimension comparison can be carried out. The patient can inquire the individual medical advice for comparison, and the doctor can inquire the group and individual medical advice for comparison.

And the medical advice adjusting module is used for adjusting the medical advice issued by the second user according to the medical advice execution condition fed back by the second user through the intelligent expert decision rule. The doctor can adjust 4 types of medical advice in time according to the result of patient's execution medical advice tracking management, especially lifestyle behavior medical advice and nutrition conditioning meal medical advice. The intelligent expert decision rule enables the patient to follow the symptoms and health changes of the medical advice to form various trend graphs for the doctor and the patient to look up.

and the medical order execution feedback module is used for feeding back the execution condition of a second user on the medical order, feeding back the execution condition to the medical order management module, and synchronizing the execution condition to the first user side and/or the second user side.

The medical advice execution feedback module is mainly realized by a second user on a second user terminal such as an applet, the patient uploads the execution condition of the medical advice on the applet to the doctor-patient intelligent management system of the system, wherein the execution condition of the medical advice comprises the execution of 4 types of medical advice: intelligent tracking management of the medical advice, effect comparison of the medical advice, evaluation of personal somatosensory effect and adjustment management of the medical advice. The patient can realize autonomous full-health management and life style health autonomous management on the small program; and the doctor end can synchronously receive the related information according to the order execution condition clicked by the patient on the small program.

The confusion with lifestyle health management is that: people do not want to change their past behavior, and often go irreparably, which is the remorse to begin. The information detected by the instrument is that the body has formed a focus or formed an abnormal signal, and before the focus or the abnormal signal is formed, the instrument is difficult to detect, but the body of the instrument has abnormal feeling, may be transient and is often ignored by the instrument.

The intelligent system highly pays attention to the body feeling abnormal movement information of an individual, provides the point drops which are convenient for recording the living state of the individual, and the intelligent algorithm system helps to find out the slight abnormal movement and remind in time, so that the focus can be killed in a reversible stage.

The intelligent system finds that the subtle transactions accumulate to a certain value through an expert decision making system, (different groups can make different threshold values), and the intelligent system can automatically remind the user of the change of the individual and provide a trend chart of the development and change of detailed symptoms. And outputting suggestions and guidance for personalized lifestyle adjustment. People find the change in advance, so that the people pay attention in advance and adjust the past unhealthy life style in time. Improving the nutrition intake ratio, ensuring sleep, reducing stress, relaxing emotion, etc., and controlling the focus before the focus is formed. Realizing the autonomous preventive treatment of the disease.

Meanwhile, the invention solves the problem that the health information of a plurality of individuals is discrete, single-point and discontinuous at present, and can be associated through a modeling technology. Provides direct perception evaluation of an individual's body, and provides methods and intelligent systems for instituting health interventions that treat the body as a unified whole. Help people to understand the changes of their bodies and to converse with their bodies. Technical support is made for realizing that the best doctor is the doctor and the first person responsible for the health of the doctor, and an intelligent tool is provided.

Through the intelligent system, when people clearly, conveniently and quantifiably see that the health life style medicine is adopted, the low-cost, non-invasive and harmless intervention means has the value, and the benefit brought to self health by scientifically managing the individual life style can actively use the practiced tool.

People experience no short-cut for health and are accumulated in the intravenous drip at ordinary times as all magnificent achievements. Microsclerism-starting from microsclerism, is an effective way to help people do it from drip. The system comprises a method for converting the micro habits of people into habits and is integrated into a personalized model algorithm.

The method is a continuous and endless research and iteration process, and for individuals, an individual characteristic model system is abstracted and generalized from a group, and is continuously iterated and corrected to obtain an intelligent continuous close-fitting health suggestion guidance until a life system is finished. For the group, the individual provides feature sample support for the group, researches are classified according to various needs, services are provided, and continuous iterative correction research can be supported, which is endless.

The design rules of each behavior model of the active lifestyle management system are as follows (except for the nutritional characteristic model): the life style behavior health basic model is obtained by correcting data of thousands of professional crowd queues according to 10 standards related to health made by the world health organization, sub-health evaluation standards published by the discussion of Chinese sub-health academy and relevant factors, and the combination of the traditional Chinese medicine technology, preventive medicine, functional medicine, botany, nutriology, psychology, human mechanics and the like. The model is divided into 5 levels and comprises 8 dimensions, and the established standard of the deviation value threshold value is different according to the physical condition stage and the disease condition stage of an individual. When the deviation reaches the set standard, the system will automatically report out a yellow light and a red light, and the aim is to draw attention. The lifestyle habits are adjusted in time to achieve the health goal, and the automatic reminding mechanism of the system can be set by self.

As shown in fig. 4, as an optional embodiment of the present application, optionally, the lifestyle active management system includes:

The active management system for the life style mainly establishes data models of all behaviors through marble data of different user groups such as patients and different behavior standards. Through the intelligent algorithm module, the data model of the personalized life style is realized, unique characteristics, individual, group commonalities and personalized relations of individuals can be displayed, and life style suggestions suitable for personal characteristics can be intelligently provided.

Firstly, a relation model system of influence of living behaviors such as exercise, sleep, excretion and the like on human health needs to be constructed on a living style active management system. This process is continuous and continuously perfects the application system. The behavior model is obtained by deep training of different learning models through historical data of different behaviors and behavior health standard data, for example, motion historical data and motion standard data of a user are collected and trained to obtain a motion characteristic model, and then motion data (such as a patient executing a medical advice process) of a second user is monitored through the motion characteristic model to actively perform early warning.

Second, different behavior models need to be managed. The behavior model management module is used for setting different behavior model comparison and management rules aiming at different behavior types, calling the matched behavior model according to the behavior type and actively managing the behavior data of the behavior type, including calculation, early warning, display and the like of a behavior deviation value.

Once the intelligent system finds that these subtle variations accumulate to a certain value, the system will automatically alert the user to this change in the individual, revealing a trend graph of the change in detail. And give suggestions and guidance for personalized lifestyle adjustments. People find the change in advance, attach importance to the change in advance, and adjust the past unhealthy life style. Improving nutrition intake ratio, ensuring sleep, relaxing emotion, and controlling focus before formation. Therefore, the autonomous preventive treatment of the diseases is realized.

This example symbolically presents several feature models of different behaviors. In each of the following models, the present embodiment is not limited to the acquisition modes, devices, and the like of different behaviors, as long as corresponding behavior data can be acquired. And processing and algorithmic processing of the behavior data, which is not limited herein.

In addition, the preset model referred to by each model, the data of the preset model and the characteristic data can be set according to the industry standard or the self condition of the patient, and the setting is not limited in this place.

For example, the "motion characteristic feature model" is a feature data of a motion preset model, which is calculated by referring to an established personal motion history feature model, in which the historical data of a patient person is collected from several dimensions: time of onset of personal exercise (childhood, adult, middle aged, elderly); personal sports hobby programs (track and field, balls, yoga, cycling, indoor exercise, others); the length of the individual's historical exercise (1 hour, 2 hours, 3 hours, and more); whether to participate in the competitive game (presence, absence); whether there is injury (presence, absence) during exercise; and so on. The personal motion historical characteristic model outputs characteristic data of various dimensions, and establishes a personal motion characteristic model as a motion characteristic model according to the characteristic data of various dimensions. The motion characteristic feature model can be established together with the health standard of personal motion by referring to medical standards.

As shown in fig. 4, as an optional embodiment of the present application, optionally, the behavior model system includes at least one of the following behavior models:

Through the different behavior models, the health of the second user can be actively managed. The method is characterized in that a personal exclusive health data model is formed by collecting the slight change of the body in daily life, and the abnormal change of the health state is prompted by a scientific quantitative method according to the principle of comparing the body with the past body, so that the disease is prevented and treated. Once the intelligent system finds that these subtle variations accumulate to a certain value, the system will automatically alert the user to this change in the individual, revealing a trend graph of the change in detail. And give suggestions and guidance for personalized lifestyle adjustments.

As shown in fig. 5, as an optional embodiment of the present application, optionally, the lifestyle active management system further includes:

The active life style management system firstly needs to collect different behavior data of a second user, collects the behavior data corresponding to each model through a data collection module, and obtains depth data for calculation through data processing. And the acquisition mode and the processing mode of different behavior data are not limited in this place. For example, the exercise data can be collected by counting steps, calculating the heartbeat frequency and the heartbeat rate through a WeChat applet and the like, can be collected directly through the WeChat applet, and can also be collected through other electronic equipment.

And the intelligent algorithm module is a behavior deviation value calculation module for the depth data through a preset deviation value algorithm.

The calculation method of the deviation value of each behavior may be set according to different behavior types, and is not limited here. The deviation value can be calculated by adopting a unified standard, and also can be calculated by adopting different deviation value algorithms. For example, each behavior model is individually configured with a deviation value algorithm matched with the behavior model, and the type of behavior data is individually calculated. After the behavior data is collected, a behavior model matched with the behavior type can be scheduled according to the attribute of the behavior data, namely the behavior type, and then the deviation value of the behavior data can be calculated by calling a deviation value preset algorithm matched with the type of the behavior model.

After the deviation value is calculated, the deviation value is compared with a preset deviation value threshold value, for example, whether the movement deviation value exceeds 30% or not, when the movement deviation value changes from ordinary behavior and the deviation value is greater than 30%, the intelligent expert decision system can automatically prompt an alarm to call attention of a second user and adjust the state in time.

After the active early warning module finds that certain behavior data exceeds the standard, the second user is reminded of paying attention to the second user at the second user end, and the second user selects whether the data exceeding the standard is sent to a medical institution (doctor) associated with the second user or not, namely the first user. Through sending the instruction, and will the behavior data that the deviance is greater than preset threshold value send to intelligence inquiry module, this moment first user end can receive this second user's data that exceeds standard, corresponds adopts expert system to carry out intelligence and assigns the doctor's advice to reach the second user.

The display module can display different behavior data, deviation value data and early warning conditions in real time and send the behavior data, the deviation value data and the early warning conditions to the first user side and/or the second user side. Therefore, the patient can see whether behavior early warning data of different behaviors of the patient reach the standard or exceed the standard in real time on the small program of the patient. Synchronously, a doctor or an intelligent expert decision system can also see the health state of the patient, and the expert decision system actively gives orders to the patient to realize the active management of the health state. And the display module displays the data of different models according to the set display dimension.

In this embodiment, the display module and the data display mode are not limited.

As a preferred mode of the present application, in this embodiment, the data of different dimensions output by each model is displayed by using a radar map.

Fig. 6 is a schematic diagram showing the motion behavior data by radar mapping. As can be seen from the figure, the motion behavior characteristics of the second user are displayed from the dimensions of motion feeling after motion, motion duration, motion intensity and the like. When a certain radar area is exceeded, the radar image of the dimension is subjected to pre-tightening display images such as color marks.

It should be noted that, although the above is described as an example, those skilled in the art can understand that the present disclosure should not be limited thereto. In fact, the user can set flexibly according to the actual application scenario, as long as the technical function of the present application can be realized according to the above technical method.

The modules or steps of the invention described above can be implemented by a general purpose computing device, they can be centralized on a single computing device or distributed over a network of multiple computing devices, and they can alternatively be implemented by program code executable by a computing device, so that they can be stored in a storage device and executed by a computing device, or they can be separately fabricated into various integrated circuit modules, or multiple modules or steps thereof can be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.

Those skilled in the art will appreciate that the control program for implementing the modules in the method of the above embodiments may be implemented by a computer program instructing associated hardware, and the program may be stored in a computer readable storage medium, and when executed, the program may control the modules.

Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. The utility model provides an integrated intelligent management system who synthesizes doctor-patient intelligent management and healthy initiative management which characterized in that includes:

2. The integrated intelligent management system for integrated doctor-patient intelligent management and health initiative management of claim 1, wherein the doctor-patient intelligent management system comprises:

3. The integrated intelligent management system for integrated doctor-patient intelligent management and health initiative management of claim 2, wherein the doctor-patient relationship management system comprises:

4. The integrated intelligent management system for integrated doctor-patient intelligent management and health initiative management of claim 3, wherein the medical order management module comprises:

5. The integrated intelligent management system for integrated physician-patient intelligent management and health initiative management of claim 4, further comprising:

6. The integrated intelligent management system for integrated physician-patient intelligent management and health initiative management of any one of claims 1-5, wherein the lifestyle initiative management system comprises:

7. The integrated intelligent management system for integrated physician-patient intelligent management and active health management as claimed in claim 6, wherein the behavior model system comprises at least one of the following behavior models:

8. The integrated intelligent management system for integrated physician-patient intelligent management and health initiative management of claim 6, wherein the lifestyle initiative management system further comprises:

9. The integrated intelligent management system for integrated physician-patient intelligent management and health initiative management of claim 8, wherein the initiative pre-warning module is further configured to:

10. The integrated intelligent management system control system for integrated physician-patient intelligent management and active health management as claimed in claim 8, wherein the active lifestyle management system further comprises: