CN112420197A - Intelligent public health service management system and method - Google Patents
Intelligent public health service management system and method Download PDFInfo
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- 230000005180 public health Effects 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title abstract description 8
- 230000036541 health Effects 0.000 claims abstract description 43
- 238000012502 risk assessment Methods 0.000 claims abstract description 41
- 238000007405 data analysis Methods 0.000 claims abstract description 16
- 230000004927 fusion Effects 0.000 claims abstract description 13
- 238000011156 evaluation Methods 0.000 claims description 50
- 238000010801 machine learning Methods 0.000 claims description 40
- 230000006870 function Effects 0.000 claims description 28
- 238000007726 management method Methods 0.000 claims description 27
- 230000000694 effects Effects 0.000 claims description 17
- 238000005457 optimization Methods 0.000 claims description 17
- 230000003862 health status Effects 0.000 claims description 7
- 201000010099 disease Diseases 0.000 description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 5
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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
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q50/26—Government or public services
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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
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
Abstract
The invention relates to an intelligent public health service management system and a method thereof, wherein the intelligent public health service management system comprises a data acquisition module, a data fusion module, a data analysis module and a data terminal module; the data acquisition module is used for acquiring physiological data and medical data of residents and uniformly storing the physiological data and the medical data of the residents; the data fusion module is used for providing a uniform data access interface for all physiological data and medical data; the data analysis module is used for carrying out risk assessment on the health state of residents according to the physiological data and the medical data of the residents to obtain a risk assessment result; and the data terminal module is used for acquiring the physiological data and the medical data required by the user from the unified data access interface and displaying the physiological data, the medical data and the risk assessment result to the user. The intelligent public health service management system realizes risk assessment of the health state of residents.
Description
Technical Field
The invention relates to the technical field of intelligent public health, in particular to an intelligent public health service management system and method.
Background
The domestic medical system comprises a disease diagnosis and treatment system taking a hospital as a center and a primary public health system taking primary public health as a center, wherein the disease diagnosis and treatment system mainly performs disease intervention and treatment on patients suffering from diseases and requires the patients to go to the hospital. At present, hospitals in China have great pressure, and the residents cannot know the health conditions of the residents in time, and only after the residents suffer from diseases, the residents can be treated in the hospitals, so that early detection, early discovery and early intervention are not achieved. Risk assessment is carried out on the health state of residents, medical resources are saved, the residents can check the health state of the residents as soon as possible, and the risk assessment is carried out on the health state of the residents in the prior art.
Disclosure of Invention
In view of the above, it is necessary to provide an intelligent public health service management system and method for solving the problem in the prior art that risk assessment is not performed on the health status of residents.
The invention provides an intelligent public health service management system which is characterized by comprising a data acquisition module, a data fusion module, a data analysis module and a data terminal module;
the data acquisition module is used for acquiring physiological data and medical data of residents and uniformly storing the physiological data and the medical data of the residents;
the data fusion module is used for providing a uniform data access interface for all physiological data and medical data;
the data analysis module is used for carrying out risk assessment on the health state of residents according to the physiological data and the medical data of the residents to obtain a risk assessment result;
and the data terminal module is used for acquiring the physiological data and the medical data required by the user from the unified data access interface and displaying the physiological data, the medical data and the risk assessment result to the user.
Furthermore, the data fusion module is also used for managing physiological data and medical data and providing a distributed query engine for the physiological data and the medical data.
Further, the data analysis module carries out risk assessment on the health status of residents according to the physiological data and the medical data of the residents, and specifically comprises,
segmenting a historical data set of physiological data and medical data into a plurality of test sample data sets; predicting the multiple test sample data sets by using multiple machine learning models to obtain multiple risk prediction values; constructing an evaluation function, and calculating a plurality of evaluation scores according to the plurality of risk predicted values and the evaluation function; and obtaining the optimization effect value of each machine learning model according to the plurality of evaluation values, and carrying out risk evaluation on the health state of the residents by using the machine learning model with the best optimization effect.
Further, the data analysis module calculates a plurality of assessment scores based on the plurality of risk predictors and the assessment function, specifically including,
obtaining a plurality of first predicted values in a plurality of risk predicted values corresponding to each machine learning model; acquiring a plurality of actual values corresponding to the plurality of first predicted values; calculating according to the plurality of predicted values and the plurality of actual values to obtain a health index; and calculating performance indexes according to the plurality of predicted values, and inputting the health indexes and the performance indexes into the evaluation function to obtain the evaluation score of each machine learning model.
Further, the evaluation function is, specifically, Value ═ x + y)/(x/a + y/b), where Value is an evaluation score, and x, y, a, and b are a health indicator, a performance indicator, a health indicator weight coefficient, and a performance indicator weight coefficient, respectively.
The invention also provides an intelligent public health service management method, which comprises the following steps:
acquiring physiological data and medical data of residents, and uniformly storing the physiological data and the medical data of the residents;
a unified data access interface is provided for all physiological data and medical data;
according to the physiological data and the medical data of the residents, performing risk assessment on the health state of the residents to obtain a risk assessment result;
and acquiring physiological data and medical data required by the user from the unified data access interface, and displaying the physiological data, the medical data and a risk assessment result to the user.
Furthermore, the intelligent public health service management method further comprises the steps of managing physiological data and medical data and carrying out distributed query on the physiological data and the medical data.
Further, according to the physiological data and medical data of residents, the risk assessment is carried out on the health status of the residents, which specifically comprises,
segmenting a historical data set of physiological data and medical data into a plurality of test sample data sets; predicting the multiple test sample data sets by using multiple machine learning models to obtain multiple risk prediction values; constructing an evaluation function, and calculating a plurality of evaluation scores according to the plurality of risk predicted values and the evaluation function; and obtaining the optimization effect value of each machine learning model according to the plurality of evaluation values, and carrying out risk evaluation on the health state of the residents by using the machine learning model with the best optimization effect.
Further, calculating a plurality of assessment scores based on the plurality of risk predictors and the assessment function, specifically comprising,
obtaining a plurality of first predicted values in a plurality of risk predicted values corresponding to each machine learning model; acquiring a plurality of actual values corresponding to the plurality of first predicted values; calculating according to the plurality of predicted values and the plurality of actual values to obtain a health index; and calculating performance indexes according to the plurality of predicted values, and inputting the health indexes and the performance indexes into the evaluation function to obtain the evaluation score of each machine learning model.
Compared with the prior art, the invention has the beneficial effects that: acquiring physiological data and medical data of residents through a data acquisition module, and uniformly storing the physiological data and the medical data of the residents; a unified data access interface is provided for all physiological data and medical data through the data fusion module; performing risk assessment on the health state of the residents according to the physiological data and the medical data of the residents through a data analysis module to obtain a risk assessment result; acquiring physiological data and medical data required by the user from the unified data access interface through a data terminal module, and displaying the physiological data, the medical data and a risk evaluation result to the user; the risk assessment of the health state of residents is realized.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent public health service management system provided by the present invention;
fig. 2 is a schematic flow chart of the intelligent public health service management method provided by the present invention.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
Example 1
The embodiment of the invention provides an intelligent public health service management system, which has a structural schematic diagram, as shown in fig. 1, and comprises a data acquisition module 1, a data fusion module 2, a data analysis module 3 and a data terminal module 4;
the data acquisition module 1 is used for acquiring physiological data and medical data of residents and uniformly storing the physiological data and the medical data of the residents;
the data fusion module 2 is used for providing a uniform data access interface for all physiological data and medical data;
the data analysis module 3 is used for carrying out risk assessment on the health state of residents according to the physiological data and the medical data of the residents to obtain a risk assessment result;
and the data terminal module 4 is used for acquiring the physiological data and the medical data required by the user from the unified data access interface, and displaying the physiological data, the medical data and the risk assessment result to the user.
In a specific embodiment, the physiological data includes physical sign data, i.e. blood pressure, blood oxygen, etc., and the medical data includes electrocardiographic data, CT data, etc.; the data can be automatically acquired after physical examination is completed by professional equipment, and the physiological data and the medical data can be manually input into the data acquisition module;
preferably, the data fusion module is further used for managing physiological data and medical data and providing a distributed query engine for the physiological data and the medical data.
In a specific embodiment, the intelligent public health service management system further comprises a service support module, wherein the service support module is used for providing support for related services of a business application layer and mainly comprises service construction, service support, an application development framework and application development support, the service framework comprises foundation construction, a public component and a business component, and the service support comprises foundation support, distributed service scheduling support and service integration;
in another specific embodiment, the intelligent public health service management system further includes a data exchange module, where the data exchange module mainly includes a management component and a distributed data bus, and the data management component includes an adapter, a converter, a data quality check, a scheduling engine, a process engine, a persistent cache, a file/message exchange, a configuration analysis, a rule engine, and a metadata management. The distributed data bus provides a data exchange function for the intelligent public health service management system;
preferably, the data analysis module performs risk assessment on the health status of the residents according to the physiological data and the medical data of the residents, and specifically includes,
segmenting a historical data set of physiological data and medical data into a plurality of test sample data sets; predicting the multiple test sample data sets by using multiple machine learning models to obtain multiple risk prediction values; constructing an evaluation function, and calculating a plurality of evaluation scores according to the plurality of risk predicted values and the evaluation function; obtaining an optimization effect value of each machine learning model according to the plurality of evaluation values, and carrying out risk evaluation on the health state of residents by using the machine learning model with the best optimization effect;
it should be noted that the maximum optimization effect value is determined by comparing the optimization effect values corresponding to the machine learning models, the larger the optimization effect value is, the better the performance of the corresponding machine learning model applied to the health risk assessment is, and the smaller the optimization effect value is, the worse the performance of the corresponding machine learning model applied to the health risk assessment is; performing risk assessment according to the health state of residents of the target machine learning model by selecting the machine learning model corresponding to the maximum optimization effect value as the target machine learning model;
in a specific embodiment, 3 machine learning models are provided, each machine learning model corresponds to 1 test sample data set, each test sample data set comprises 4 test samples, each machine learning model tests each test sample data set and outputs 4 risk prediction values, that is, each machine learning model outputs 12 prediction values in total, wherein the risk prediction values are any values between 0 and 1, and the larger the value is, the larger the risk is;
preferably, the data analysis module calculates a plurality of assessment scores according to the plurality of risk prediction values and the assessment function, and specifically includes,
obtaining a plurality of first predicted values in a plurality of risk predicted values corresponding to each machine learning model; acquiring a plurality of actual values corresponding to the plurality of first predicted values; calculating according to the plurality of predicted values and the plurality of actual values to obtain a health index; calculating performance indexes according to the plurality of predicted values, and inputting the health indexes and the performance indexes into the evaluation function to obtain an evaluation score of each machine learning model;
preferably, the evaluation function is, specifically, Value ═ x + y)/(x/a + y/b), where Value is an evaluation score, and x, y, a, and b are a health indicator, a performance indicator, a health indicator weight coefficient, and a performance indicator weight coefficient, respectively;
it should be noted that x + y is 1, and a may be 0.5, and b may be 0 if the accuracy of the risk assessment is important and the performance index of the system is ignored.
Example 2
The invention also provides an intelligent public health service management method, the flow diagram of which is shown in fig. 2, and the method comprises the following steps:
s1, acquiring physiological data and medical data of residents, and uniformly storing the physiological data and the medical data of the residents;
s2, providing a uniform data access interface for all physiological data and medical data;
s3, performing risk assessment on the health state of the residents according to the physiological data and the medical data of the residents to obtain a risk assessment result;
and S4, acquiring the physiological data and the medical data required by the user from the unified data access interface, and displaying the physiological data, the medical data and the risk assessment result to the user.
Preferably, the intelligent public health service management method further comprises the steps of managing physiological data and medical data and performing distributed query on the physiological data and the medical data.
Preferably, the risk assessment is performed on the health status of the residents according to the physiological data and the medical data of the residents, and specifically comprises,
segmenting a historical data set of physiological data and medical data into a plurality of test sample data sets; predicting the multiple test sample data sets by using multiple machine learning models to obtain multiple risk prediction values; constructing an evaluation function, and calculating a plurality of evaluation scores according to the plurality of risk predicted values and the evaluation function; and obtaining the optimization effect value of each machine learning model according to the plurality of evaluation values, and carrying out risk evaluation on the health state of the residents by using the machine learning model with the best optimization effect.
Preferably, a plurality of assessment scores are calculated based on the plurality of risk predictors and the assessment function, including in particular,
obtaining a plurality of first predicted values in a plurality of risk predicted values corresponding to each machine learning model; acquiring a plurality of actual values corresponding to the plurality of first predicted values; calculating according to the plurality of predicted values and the plurality of actual values to obtain a health index; and calculating performance indexes according to the plurality of predicted values, and inputting the health indexes and the performance indexes into the evaluation function to obtain the evaluation score of each machine learning model.
The invention discloses an intelligent public health service management system and method, which are characterized in that physiological data and medical data of residents are acquired through a data acquisition module and are uniformly stored; a unified data access interface is provided for all physiological data and medical data through the data fusion module; performing risk assessment on the health state of the residents according to the physiological data and the medical data of the residents through a data analysis module to obtain a risk assessment result; acquiring physiological data and medical data required by the user from the unified data access interface through a data terminal module, and displaying the physiological data, the medical data and a risk evaluation result to the user; the risk assessment of the health state of residents is realized.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (9)
1. An intelligent public health service management system is characterized by comprising a data acquisition module, a data fusion module, a data analysis module and a data terminal module;
the data acquisition module is used for acquiring physiological data and medical data of residents and uniformly storing the physiological data and the medical data of the residents;
the data fusion module is used for providing a uniform data access interface for all physiological data and medical data;
the data analysis module is used for carrying out risk assessment on the health state of residents according to the physiological data and the medical data of the residents to obtain a risk assessment result;
and the data terminal module is used for acquiring the physiological data and the medical data required by the user from the unified data access interface and displaying the physiological data, the medical data and the risk assessment result to the user.
2. The intelligent public health service management system of claim 1, wherein the data fusion module is further used for management of physiological data and medical data, and provides a distributed query engine for the physiological data and the medical data.
3. The intelligent public health service management system according to claim 1, wherein the data analysis module performs risk assessment on the health status of residents according to the physiological data and medical data of the residents, specifically comprising,
segmenting a historical data set of physiological data and medical data into a plurality of test sample data sets; predicting the multiple test sample data sets by using multiple machine learning models to obtain multiple risk prediction values; constructing an evaluation function, and calculating a plurality of evaluation scores according to the plurality of risk predicted values and the evaluation function; and obtaining the optimization effect value of each machine learning model according to the plurality of evaluation values, and carrying out risk evaluation on the health state of the residents by using the machine learning model with the best optimization effect.
4. The intelligent public health service management system of claim 3, wherein the data analysis module calculates a plurality of assessment scores based on the plurality of risk predictors and the assessment function, in particular comprising,
obtaining a plurality of first predicted values in a plurality of risk predicted values corresponding to each machine learning model; acquiring a plurality of actual values corresponding to the plurality of first predicted values; calculating according to the plurality of predicted values and the plurality of actual values to obtain a health index; and calculating performance indexes according to the plurality of predicted values, and inputting the health indexes and the performance indexes into the evaluation function to obtain the evaluation score of each machine learning model.
5. The intelligent public health service management system of claim 4, wherein the evaluation function is Value ═ x + y)/(x/a + y/b), where Value is an evaluation score, and x, y, a, and b are a health indicator, a performance indicator, a health indicator weight coefficient, and a performance indicator weight coefficient, respectively.
6. An intelligent public health service management method is characterized by comprising the following steps:
acquiring physiological data and medical data of residents, and uniformly storing the physiological data and the medical data of the residents;
a unified data access interface is provided for all physiological data and medical data;
according to the physiological data and the medical data of the residents, performing risk assessment on the health state of the residents to obtain a risk assessment result;
and acquiring physiological data and medical data required by the user from the unified data access interface, and displaying the physiological data, the medical data and a risk assessment result to the user.
7. The intelligent public health service management method according to claim 6, further comprising managing physiological data and medical data, and performing distributed query on the physiological data and the medical data.
8. The intelligent public health service management method according to claim 6, wherein the risk assessment is performed on the health status of the residents according to the physiological data and medical data of the residents, specifically comprising,
segmenting a historical data set of physiological data and medical data into a plurality of test sample data sets; predicting the multiple test sample data sets by using multiple machine learning models to obtain multiple risk prediction values; constructing an evaluation function, and calculating a plurality of evaluation scores according to the plurality of risk predicted values and the evaluation function; and obtaining the optimization effect value of each machine learning model according to the plurality of evaluation values, and carrying out risk evaluation on the health state of the residents by using the machine learning model with the best optimization effect.
9. The intelligent public health service management method of claim 8, wherein calculating a plurality of assessment scores based on the plurality of risk predictors and the assessment function comprises,
obtaining a plurality of first predicted values in a plurality of risk predicted values corresponding to each machine learning model; acquiring a plurality of actual values corresponding to the plurality of first predicted values; calculating according to the plurality of predicted values and the plurality of actual values to obtain a health index; and calculating performance indexes according to the plurality of predicted values, and inputting the health indexes and the performance indexes into the evaluation function to obtain the evaluation score of each machine learning model.
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| CN113782208A (en) * | 2021-10-19 | 2021-12-10 | 四川省康复辅具技术服务中心 | Family health assessment and intervention system based on intelligent rehabilitation equipment |
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| CN108766570A (en) * | 2018-05-24 | 2018-11-06 | 文丹 | A kind of resident's personal health management service system |
| CN111950738A (en) * | 2020-08-10 | 2020-11-17 | 中国平安人寿保险股份有限公司 | Machine learning model optimization effect evaluation method and device, terminal and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108766570A (en) * | 2018-05-24 | 2018-11-06 | 文丹 | A kind of resident's personal health management service system |
| CN111950738A (en) * | 2020-08-10 | 2020-11-17 | 中国平安人寿保险股份有限公司 | Machine learning model optimization effect evaluation method and device, terminal and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113782208A (en) * | 2021-10-19 | 2021-12-10 | 四川省康复辅具技术服务中心 | Family health assessment and intervention system based on intelligent rehabilitation equipment |
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Application publication date: 20210226 |