CN113470774A - Chronic disease archive management system based on big data - Google Patents
Chronic disease archive management system based on big data Download PDFInfo
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- 208000017667 Chronic Disease Diseases 0.000 title claims abstract description 107
- 238000007726 management method Methods 0.000 claims abstract description 63
- 238000013500 data storage Methods 0.000 claims abstract description 8
- 201000010099 disease Diseases 0.000 claims description 51
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 51
- 208000024891 symptom Diseases 0.000 claims description 12
- 238000012544 monitoring process Methods 0.000 claims description 11
- 238000003745 diagnosis Methods 0.000 claims description 9
- 239000003814 drug Substances 0.000 claims description 6
- 229940079593 drug Drugs 0.000 claims description 5
- 238000000034 method Methods 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 4
- 238000012216 screening Methods 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims 3
- 230000000694 effects Effects 0.000 description 7
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- 238000007405 data analysis Methods 0.000 description 5
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- 239000008103 glucose Substances 0.000 description 5
- 241000282414 Homo sapiens Species 0.000 description 3
- 206010020772 Hypertension Diseases 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 230000036772 blood pressure Effects 0.000 description 2
- 230000001684 chronic effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 230000009897 systematic effect Effects 0.000 description 2
- 208000032928 Dyslipidaemia Diseases 0.000 description 1
- 208000017170 Lipid metabolism disease Diseases 0.000 description 1
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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Abstract
The chronic disease archive management system based on big data comprises a data acquisition module, a structured information module, an individualized information module and a data storage module; the data acquisition module acquires user information to the chronic disease file management system; the structured information module interactively acquires user structured information according to system requirements; the personalized information module comprises an information configurable module, and the chronic disease file management system determines the content of the information configurable module according to the acquired target structured information of the user; the information acquired by the chronic disease file management system can be stored in the chronic disease file management system through the data storage module. Therefore, the user can record the self chronic disease condition through the chronic disease file management system, the chronic disease can be effectively tracked conveniently, and the doctor can refer to the chronic disease conveniently when the doctor visits the doctor.
Description
Technical Field
The invention relates to the technical field of health management, in particular to a health management system for chronic disease management.
Background
According to statistics, Chinese chronic disease (chronic disease) patients approach 3 hundred million people. Chronic diseases become the first killer of human health, and chronic diseases including hypertension, diabetes, dyslipidemia and the like seriously threaten health.
Medical interventions today are often event-oriented, in particular, patients suffering from heart attacks and other catastrophic events, and then sent to hospitals where doctors diagnose the patients and provide treatment options, such as surgery, medication, etc. Admittedly, event-oriented medical intervention is important, but chronic diseases gradually become serious events for medical intervention, are limited by medical resources, can only be treated through short-term hospitalization or outpatient treatment, and are difficult to cure radically, and doctors can only obtain physiological data of patients during treatment, so that the actual degree of illness of patients with chronic diseases is estimated wrongly. Thus, there is a need for a chronic health management system for patients with chronic diseases.
Meanwhile, after treatment, patients with chronic diseases are often annihilated by a large amount of information provided by hospitals, and then few or no follow-up visits are obtained, so that the recovery of the chronic diseases is greatly influenced.
Disclosure of Invention
The invention aims to provide a chronic disease archive management system based on big data.
On the first hand, the chronic disease archive management system based on big data comprises a data acquisition module, a structured information module, an individualized information module and a data storage module; the data acquisition module acquires user information to the chronic disease file management system; the structured information module interactively acquires user structured information according to system requirements; the personalized information module comprises an information configurable module, and the chronic disease file management system determines the content of the information configurable module according to the acquired target structured information of the user; the information acquired by the chronic disease file management system can be stored in the chronic disease file management system through the data storage module. Therefore, the user can record the self chronic disease condition through the chronic disease file management system, the chronic disease can be effectively tracked conveniently, and the doctor can refer to the chronic disease conveniently when the doctor visits the doctor.
With reference to the first aspect, in a first possible embodiment of the first aspect, the target structured information includes names of two or more chronic diseases. In this embodiment, the chronic disease file management system can simultaneously record and analyze a plurality of diseases, and since a plurality of chronic diseases have a certain relationship, the chronic diseases are separately recorded and managed, which often has the influence of considering each other, so the embodiment simultaneously records and analyzes a plurality of diseases, manages the chronic diseases in a systematic manner, and has a better management effect on the chronic diseases.
With reference to the first aspect, in a second possible embodiment of the first aspect, the personalized information module includes an information fixing module, and the information fixing module includes a lifestyle. Chronic diseases are often caused by lifestyle or lifestyle habits, so it is necessary to record and analyze lifestyle habits at the time of management of the chronic diseases. In this embodiment, by recording the lifestyle, a better effect on management of chronic diseases is achieved.
With reference to the first embodiment of the first aspect, in a third possible embodiment of the first aspect, the information configurable module includes disease information, family history, test examinations, medication information, symptom information, and the like. In this embodiment, the chronic disease file management system sets file information including family history according to the fact that some chronic diseases have heritage and other factors, and simultaneously, clinical information such as disease information, examination, medication information, symptom information and the like is taken as important information for chronic disease management together with the family history.
With reference to the first embodiment of the first aspect, in a fourth possible embodiment of the first aspect, the information configurable module sets a single disease constraint rule, the single disease constraint rule determines a necessary information type of the information configurable module, different chronic diseases correspond to different single disease constraint rules, and the information type of the information configurable module is determined by integrating respective single disease constraint rules of the various diseases according to the number of the disease types and the disease types in the target structured information. In the embodiment, different single disease constraint rules are set for different chronic diseases, and the information type of the information configurable module is determined by combining the number of diseases and the disease type in the target structured information, so that the system management for multiple chronic diseases is realized.
With reference to the first aspect, in a fifth possible embodiment of the first aspect, the data acquisition module includes an automatic acquisition mode, and in the automatic acquisition mode, the data acquisition module is in signal connection with the home monitoring instrument, and the home monitoring instrument automatically uploads the data to the data acquisition module after acquiring data of the user. In the embodiment, the data is automatically uploaded to the chronic disease archive management system, so that the accuracy and convenience of data acquisition are better.
In a sixth possible embodiment of the first aspect, in combination with the first aspect or any one of the first to fifth embodiments of the first aspect, the personalized information module comprises a diagnosis library, a test examination library, a symptom library. In the embodiment, the diagnosis library, the inspection library and the symptom library are arranged, so that the characteristics of convenience in big data analysis and the like are achieved.
In a seventh possible embodiment of the first aspect in combination with the sixth embodiment of the first aspect, the data of the diagnosis library, the examination library, the symptom library may be supplemented. In this embodiment, the data can be supplemented, which provides help for the reliability of chronic disease diagnosis and chronic disease monitoring, and is also beneficial for the data analysis of the chronic disease condition and the targeted planning of the improvement scheme of the chronic disease treatment.
With reference to the fourth embodiment of the first aspect, in an eighth possible embodiment of the first aspect, the system includes a control end, the control end may adjust the constraint rule of a single disease type, the control end adjusts the constraint rule of the single disease type based on a single disease control method obtained by big data screening, the control end includes an intelligent model unit, the intelligent model unit generates a corresponding artificial intelligence model according to visit data of a doctor corresponding to each chronic disease, and determines the constraint rule of the single disease type according to information screened by the artificial intelligence model. In the embodiment, the control end is arranged, so that the single-disease constraint rule can be continuously improved according to the clinic data in the chronic disease archive management system, meanwhile, new medical discovery or clinical data are introduced in advance through medical technology improvement, once the slow disease archive management system is entered, the control end can adjust the single-disease constraint rule at a proper time, and therefore a better chronic disease management effect is achieved.
With reference to the eighth embodiment of the first aspect, in a ninth possible embodiment of the first aspect, the data processing system includes a feedback module, the feedback module may perform big data analysis according to the real patient entry information, and transmit the feedback opinion to the control end, and the control end adjusts the state judgment threshold. In this embodiment, the feedback module can feed back to the control end according to the specific effect of chronic disease management, and the control end adjusts the state judgment threshold value to realize better chronic disease management.
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Fig. 1 is a system configuration diagram of a big data-based chronic disease archive management system.
Detailed Description
Specific embodiments will now be described in detail with reference to the accompanying drawings. It should be noted that "chronic disease" and "chronic disease" are the same meaning herein.
Fig. 1 is a system configuration diagram illustrating a big data-based chronic disease archive management system.
The chronic disease archive management system shown in fig. 1 comprises a data acquisition module, a structured information module, an individualized information module, a data storage module, a feedback module and a control terminal.
The data acquisition module acquires user information to the chronic disease file management system. The data acquisition module includes the automatic acquisition mode, and under the automatic acquisition mode, the data acquisition module links to each other with house monitoring instrument signal, and house monitoring instrument is after acquireing user's data, and the automatic upload reaches the data acquisition module. The data are automatically uploaded to a chronic disease archive management system, and the data acquisition accuracy and convenience are better.
The information acquired by the chronic disease file management system can be stored in the chronic disease file management system through the data storage module.
The structured information module interactively acquires the structured information of the user according to the system requirement. The structured information includes chronic disease category information related to the user, and the chronic disease category information related to the user is target structured information.
The personalized information module comprises an information configurable module and an information fixed module, and the information fixed module comprises a life style. The chronic diseases are caused by life styles or life habits in many times, so that the life habits need to be recorded and analyzed during chronic disease management, and a better effect on the chronic disease management is achieved.
The information configurable module includes disease information, family history, test examinations, medication information, symptom information, and the like. The information configurable module sets a single disease type constraint rule, and the single disease type constraint rule determines the necessary information type of the information configurable module. For example, in diabetes, the monitoring information of blood glucose concentration is essential information, while in chronic heart disease, the monitoring information of blood glucose concentration is non-essential information, and the monitoring information of blood glucose concentration is one of the single disease type constraint rules corresponding to diabetes.
Different chronic diseases correspond to different single disease constraint rules, and the information type of the information configurable module is determined by integrating the respective single disease constraint rules of various diseases according to the number and types of the diseases in the target structured information.
For example, when diabetes and hypertension are both target structured information of a certain user, the blood glucose concentration is a necessary item for diabetes, and the blood pressure is a necessary item for hypertension, then in the information configurable module, the blood glucose concentration and the blood pressure are both necessary information types. Of course, the same parameter is used as a necessary item for some chronic diseases, and repeated input is not needed.
When the target structured information of the user comprises the names of two or more chronic diseases, the chronic disease file management system can simultaneously record and analyze multiple diseases, and the chronic diseases are separately recorded and managed due to certain association of the chronic diseases, so that influence of each chronic disease is often considered, the multiple diseases are simultaneously recorded and analyzed, chronic disease management is carried out in a systematic mode, and a better management effect is achieved on the chronic diseases. Meanwhile, different single disease constraint rules are set for different chronic diseases, and the information types of the information configurable module are determined by combining the number of the diseases and the disease types in the target structured information, so that the system management of multiple chronic diseases is realized.
The personalized information module comprises a diagnosis library, a check library and a symptom library. The data of the diagnosis library, the inspection library and the symptom library can be supplemented. The information of the personalized information module is partially classified and marked, so that a basis is provided for the identification of the data, the data can be supplemented to form complete chronic disease tracking, on one hand, the reliability of chronic disease diagnosis and chronic disease monitoring is facilitated, on the other hand, the data analysis on the chronic disease condition is facilitated, and the improvement scheme of chronic disease treatment is planned in a targeted manner. For example, after a certain living habit is improved, the data in the symptom library has a significant improvement trend, and at this time, the living habit can be considered to have a good effect on improving the corresponding chronic diseases and should be insisted on. Because the human body is a complex system, and certain difference exists between individuals, the information classification mark is continuously supplemented to form records, so that the data can be effectively analyzed, an improved scheme suitable for the individuals is obtained, and the method has very important significance for treating chronic diseases.
The control end can adjust the constraint rule of a single disease. The control end adjusts the single disease constraint rule based on a slow disease control method obtained by big data screening, the control end comprises an intelligent model unit, the intelligent model unit generates a corresponding artificial intelligent model according to the doctor visit data of corresponding doctors of each slow disease, and the single disease constraint rule is determined according to the information screened by the artificial intelligent model. In the development process of chronic disease medicine, factors which have influence on a certain chronic disease continuously change along with the understanding of human beings on the chronic disease, so that the setting of the control end can make necessary adjustment on the chronic disease file management system in time according to new clinical experience of different doctors and medical findings without redesigning the chronic disease file management system.
The feedback module can analyze big data according to the real patient input information and transmit feedback opinions to the control end, and the control end adjusts the state judgment threshold. The management of chronic diseases is a practice science to a certain extent, so that big data analysis is carried out on the information of patients, corresponding feedback opinions are obtained, and better management strategy reference can be provided for the management of chronic diseases.
Claims (10)
1. The chronic disease archive management system based on big data is characterized by comprising a data acquisition module, a structured information module, an individualized information module and a data storage module; the data acquisition module acquires user information to the chronic disease file management system; the structured information module interactively acquires user structured information according to system requirements; the personalized information module comprises an information configurable module, and the chronic disease file management system determines the content of the information configurable module according to the acquired target structured information of the user; the information acquired by the chronic disease file management system can be stored in the chronic disease file management system through the data storage module.
2. The big-data based chronicle management system of claim 1, wherein the target structured information includes names of two or more chronic diseases.
3. The big-data based chronicle management system of claim 1, wherein the personalized information module comprises an information-fixing module, the information-fixing module comprising a lifestyle.
4. The big data based chronic disease archive management system of claim 2, wherein the information configurable module comprises disease information, family history, exam examinations, medication information, symptom information.
5. The big-data-based chronic disease archive management system according to claim 2, wherein the information configurable module sets a single disease type constraint rule, the single disease type constraint rule determines the necessary information type of the information configurable module, different chronic diseases correspond to different single disease type constraint rules, and the information type of the information configurable module is determined by integrating the respective single disease type constraint rules of each disease type according to the number of the disease types and the disease type in the target structured information.
6. The big-data-based chronic disease archive management system of claim 1, wherein the data collection module comprises an automatic collection mode, and in the automatic collection mode, the data collection module is in signal connection with a home monitoring instrument, and the home monitoring instrument automatically uploads the data to the data collection module after acquiring data of a user.
7. The big-data based chronicle management system of any one of claims 1-6, wherein the personalized information module comprises a diagnosis library, a test examination library, a symptoms library.
8. The big data based chronicle management system of claim 7, wherein data of diagnosis library, examination library, symptom library may be supplemented.
9. The big-data-based chronic disease archive management system according to claim 5, comprising a control end, wherein the control end can adjust the single-disease constraint rules, the control end adjusts the single-disease constraint rules based on a single-disease control method obtained by big data screening, the control end comprises an intelligent model unit, the intelligent model unit generates a corresponding artificial intelligent model according to the visit data of doctors corresponding to each chronic disease, and the single-disease constraint rules are determined according to the information screened by the artificial intelligent model.
10. The big-data based chronicle management system of claim 9, comprising a feedback module, wherein the feedback module is capable of analyzing big data according to real patient entered information and transmitting feedback comments to the control end, and the control end adjusts the status decision threshold.
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