CN111009328A - Regional population health condition assessment method and device - Google Patents
Regional population health condition assessment method and device Download PDFInfo
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Abstract
The invention discloses a regional population health condition assessment method, which comprises the following steps: collecting health index data of the same region and the same sick population; preprocessing the health index data; using an entropy weight method to endow different weights to each index of the health index data, and acquiring the health condition scores of the same diseased people in the same region; and evaluating the health conditions of the same region of the same kind of sick people according to the health condition scores, so that the problem that the health conditions of the same region of the same kind of sick people are not evaluated at present is solved.
Description
Technical Field
The application relates to the field of health assessment, in particular to a regional population health condition assessment method and a regional population health condition assessment device.
Background
The effects of the global environment on human health are persistent and many diseases are regional. People have long noted a close association of geographical environment with human health. In ancient greece, medical scientists like bocra describe the effects of external environments on human health in the works of "treatise on air, water and geography". The influence of the geographic environment on the physiology and pathology of human bodies is recognized in China as early as business, and the influence is recorded in more detail in spring and autumn warcountries. The Huangdi's classic on the five elements of Yin and Yang is used as a guide, and the influence of the geographical environment on various aspects of the human body is discussed in detail.
The population living in different regions also has different criteria for assessing physical health conditions due to different geographical locations, climate change and life habits. Therefore, the health level of the population in the area where the patient is located is an important factor that should be considered by the doctor when determining the physical health condition of the patient.
Disclosure of Invention
The application provides a regional population health condition assessment method, which solves the problem that the health condition of the same diseased population in the same region is not assessed at present.
The application provides a regional population health condition assessment method, which comprises the following steps:
collecting health index data of the same region and the same sick population;
preprocessing the health index data;
using an entropy weight method to endow different weights to each index of the health index data, and acquiring the health condition scores of the same diseased people in the same region;
and evaluating the health conditions of the same area of the same diseased population according to the health condition scores.
Preferably, the preprocessing the health index data includes:
and (4) sorting and format conversion are carried out on the health index data to obtain complete health data which is consistent in format and can be used.
Preferably, using an entropy weight method to assign different weights to each index of the health index data, and obtaining the health condition score of the same region of the same patient group, the method includes:
according to the normal value reference range of the health index data, carrying out grading processing on the health index data to obtain a matrix A of the health data,
wherein XijDetecting the value of the j index for the ith time;
the health data moment A is subjected to the normalization processing,
calculating the proportion of the ith detection in the jth index,
calculating the entropy value of the j index,
wherein k is greater than 0, 1n is a natural logarithm, ejThe constant k is related to the sample data m, generally, k is 1/lnm, and then e is more than or equal to 0 and less than or equal to 1;
the utility value of the j index is calculated,
gj＝1-ej，gjthe larger the index is, the more important the index is;
the weight of each health index is calculated,
a health condition score is calculated and,
wherein XijThe health data after normalization processing.
Preferably, the evaluation of the health status of the same area of the same patient population according to the health status score comprises:
a higher health score indicates a better health status of the patient; conversely, the worse the health status of the patient.
The application also provides a device for evaluating the health condition of regional population, which comprises:
the acquisition unit is used for acquiring health index data of the same region and the same sick population;
the preprocessing unit is used for preprocessing the health index data;
the evaluation unit is used for endowing different weights to each index of the health index data by using an entropy weight method, and obtaining the health condition evaluation of the same diseased group in the same area;
and the evaluation unit is used for evaluating the health conditions of the same region of the same kind of sick people according to the health condition scores.
Preferably, the pretreatment unit comprises:
and the preprocessing subunit is used for sorting and format conversion of the health index data to obtain complete and consistent health data which can be used.
Preferably, the evaluation unit comprises:
an assessment subunit indicating a better health status of the patient, the higher the health status score; conversely, the worse the health status of the patient.
The application provides a regional population health condition assessment method, which uses an entropy weight method to endow health index data of the same region and the same sick population with different weights, obtains health condition scores, evaluates the health condition of the same region and the same sick population according to the health condition scores, and solves the problem that the health condition of the same region and the same sick population is not evaluated at present.
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FIG. 1 is a schematic flow chart of a method for assessing the health of a regional population provided herein;
FIG. 2 is a schematic illustration of the steps involved in assessing the health of a region using a regional population health assessment;
fig. 3 is a schematic diagram of a regional population health status assessment apparatus provided in the present application.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of implementation in many different ways than those herein set forth and of similar import by those skilled in the art without departing from the spirit of this application and is therefore not limited to the specific implementations disclosed below.
Fig. 1 is a schematic flow chart of a method for evaluating health status of regional population provided by the present application, and the method provided by the present application is described in detail below with reference to fig. 1.
And S101, collecting health index data of the same area and the same sick population.
In the application, the same region refers to regions with similar geographic positions, the same climate and the same living habits, for example, the regions are located in the same plateau or basin, the regions have the same dietary structure, like the Sichuan basin in southwest, the climate belongs to the subtropical monsoon climate, the dietary habits of people are spicy, and then the Sichuan basin can be used as a region to evaluate the oral health condition in the region.
First of all. The method comprises the steps of collecting health index data of the same sick population in the same area, wherein the health index data are certain physiological and biochemical detection data, including detection results of common indexes such as blood detection and urine detection.
And step S102, preprocessing the health index data.
And (4) sorting and format conversion are carried out on the health index data to obtain complete health data which is consistent in format and can be used. The health index data may come from different databases, so the data format, etc. may also be different, and therefore, it needs to be preprocessed. For example, the health index data with a serious data loss is deleted, and the decimal positions of the same health index data are unified. After pretreatment, the jungle health index data is complete and consistent in format, and can be used. In the following steps, the health data used are preprocessed data.
And step S103, assigning different weights to each index of the health index data by using an entropy weight method, and acquiring the health condition scores of the same region and the same sick population.
Entropy weight method, the concept of entropy is derived from thermodynamics, and is a measure of the uncertainty of the system state. In information theory, information is a measure of the degree of system order. Entropy is a measure of the degree of disorder of the system; both are equal in absolute value but opposite in sign. According to the characteristic, the information entropy of each index can be obtained by an entropy weight method by utilizing the inherent information of each scheme in the evaluation, and if the information entropy of the index is smaller, the larger the information amount provided by the index is, the larger the role of the index in the comprehensive evaluation is, the higher the weight is. Therefore, the information entropy tool can be used for endowing different weights to each index of the health index data, and obtaining the health condition scores of the same region and the same sick population.
Using an entropy weight method to assign different weights to each index of the health index data, and obtaining the health condition score of the same diseased group in the same area, specifically, the method comprises the following steps:
according to the normal value reference range of the health index data, carrying out grading processing on the health index data to obtain a matrix A of the health data,
wherein XijDetecting the value of the j index for the ith time;
the health data moment A is subjected to the normalization processing,
calculating the proportion of the ith detection in the jth index,
calculating the entropy value of the j index,
wherein k is greater than 0, 1n is the natural logarithm, ejThe constant k is related to the sample data m, generally, k is 1/lnm, and then e is more than or equal to 0 and less than or equal to 1;
the utility value of the j index is calculated,
gj＝1-ej，gjthe larger the index is, the more important the index is;
the weight of each health index is calculated,
a health condition score is calculated and,
wherein XijThe health data after normalization processing.
And step S104, evaluating the health conditions of the same area of the same sick population according to the health condition scores.
The evaluation method comprises the steps that the scores of the health conditions of the same area and the same sick population are obtained by using an entropy weight method, so that the health conditions of the same area and the same sick population can be evaluated according to the scores of the health conditions to obtain the health ranking of a patient in the same area and the same sick population, and the higher the score of the health condition is, the better the health condition of the patient is; conversely, the worse the health status of the patient, the more attention is paid.
Detailed steps of evaluating health conditions by using a regional population health condition evaluation method are shown in fig. 2, and firstly, selecting a region, collecting health index data of the same kind of sick population in the region, and preprocessing the health index data to obtain complete health data with consistent format for use. And then, using an entropy weight method to endow each index of the health index data with different weight values to obtain the health condition score of the same region and the same sick population, before endowing each index with different weight values, carrying out normalization detection and processing on the health index data, if singular sample data exists in the health index data, carrying out normalization processing, otherwise, not needing normalization processing, wherein the normalization processing has the function of eliminating the singular sample data, and the singular sample data has larger difference compared with other sample data, so that the calculation of the whole sample data is influenced, and the normalization processing is needed. Then, the specific gravity of each large index ticket, the entropy value and the utility value of each large index are calculated in sequence, the weight of the health index is obtained, and the health condition score of the same diseased group in the same region is obtained. The present application also provides a device 300 for assessing the health status of a regional population, as shown in fig. 3, comprising:
the acquisition unit 310 is used for acquiring health index data of the same region and the same sick population;
a preprocessing unit 320, configured to preprocess the health index data;
the scoring unit 330 is configured to assign different weights to each index of the health index data by using an entropy weight method, and obtain a score of health conditions of the same affected group in the same area;
and the evaluation unit 340 is configured to evaluate the health conditions of the same region of the same kind of patients according to the health condition scores.
Preferably, the pretreatment unit comprises:
and the preprocessing subunit is used for sorting and format conversion of the health index data to obtain complete and consistent health data which can be used.
Preferably, the evaluation unit comprises:
an assessment subunit indicating a better health status of the patient, the higher the health status score; conversely, the worse the health status of the patient.
The application provides a regional population health condition assessment method, which uses an entropy weight method to endow health index data of the same region and the same sick population with different weights, obtains health condition scores, evaluates the health condition of the same region and the same sick population according to the health condition scores, and solves the problem that the health condition of the same region and the same sick population is not evaluated at present.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the invention.
Claims (7)
1. A method for assessing the health of a regional population, comprising:
collecting health index data of the same region and the same sick population;
preprocessing the health index data;
using an entropy weight method to endow different weights to each index of the health index data, and acquiring the health condition scores of the same diseased people in the same region;
and evaluating the health conditions of the same area of the same diseased population according to the health condition scores.
2. The method of claim 1, wherein preprocessing the health indicator data comprises:
and (4) sorting and format conversion are carried out on the health index data to obtain complete health data which is consistent in format and can be used.
3. The method of claim 1, wherein the obtaining the health status score of the same patient group in the same area by assigning different weights to each index of the health index data by using an entropy weight method comprises:
according to the normal value reference range of the health index data, carrying out grading processing on the health index data to obtain a matrix A of the health data,
the health data moment A is subjected to the normalization processing,
calculating the proportion of the ith detection in the jth index,
calculating the entropy value of the j index,
wherein k is greater than 0, 1n is a natural logarithm, ejNot less than 0, in the formula, the constant k is related to the sample data m,
generally, if k is 1/ln m, then 0 ≦ e ≦ 1;
the utility value of the j index is calculated,
gj＝1-ej，gjthe larger the index is, the more important the index is;
the weight of each health index is calculated,
a health condition score is calculated and,
wherein XijThe health data after normalization processing.
4. The method of claim 1, wherein assessing the health of the same area of the same patient population based on the health score comprises:
a higher health score indicates a better health status of the patient; conversely, the worse the health status of the patient.
5. An apparatus for assessing the health of a regional population, comprising:
the acquisition unit is used for acquiring health index data of the same region and the same sick population;
the preprocessing unit is used for preprocessing the health index data;
the evaluation unit is used for endowing different weights to each index of the health index data by using an entropy weight method, and obtaining the health condition evaluation of the same diseased group in the same area;
and the evaluation unit is used for evaluating the health conditions of the same region of the same kind of sick people according to the health condition scores.
6. The apparatus of claim 5, wherein the pre-processing unit comprises:
and the preprocessing subunit is used for sorting and format conversion of the health index data to obtain complete and consistent health data which can be used.
7. The apparatus of claim 5, wherein the evaluation unit comprises:
an assessment subunit indicating a better health status of the patient, the higher the health status score; conversely, the worse the health status of the patient.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112349415A (en) * | 2020-11-05 | 2021-02-09 | 大连东软教育科技集团有限公司 | Physical examination big data-based resident health index construction method and device and storage medium |
| CN112465231A (en) * | 2020-12-01 | 2021-03-09 | 平安医疗健康管理股份有限公司 | Method, apparatus and readable storage medium for predicting regional population health status |
| WO2021159747A1 (en) * | 2020-09-04 | 2021-08-19 | 平安科技（深圳）有限公司 | Regional health construction process evaluation method, apparatus and device, and storage medium |
| CN113488169A (en) * | 2021-07-01 | 2021-10-08 | 新绎健康科技有限公司 | Human health assessment method and device based on energy metabolism |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104850758A (en) * | 2015-06-10 | 2015-08-19 | 史方 | Health index scoring method |
| CN105512505A (en) * | 2016-01-19 | 2016-04-20 | 宇龙计算机通信科技(深圳)有限公司 | Health prompting method and terminal equipment |
| CN105962918A (en) * | 2016-06-12 | 2016-09-28 | 夏茂 | Human body health evaluation method based on physical health indexes |
| CN106407644A (en) * | 2016-08-03 | 2017-02-15 | 无锡金世纪国民体质与健康研究有限公司 | Assessment system used for health risk assessment |
| CN107169307A (en) * | 2017-07-07 | 2017-09-15 | 中北大学 | Health risk assessment method and apparatus |
| CN108877936A (en) * | 2018-04-28 | 2018-11-23 | 见道（杭州）科技有限公司 | Health evaluating method, system and computer readable storage medium |
| CN109087706A (en) * | 2018-07-13 | 2018-12-25 | 浙江清华长三角研究院 | Human health appraisal procedure and assessment system based on sleep big data |
| CN109102888A (en) * | 2017-06-20 | 2018-12-28 | 深圳大森智能科技有限公司 | A kind of human health methods of marking |
-
2019
- 2019-12-25 CN CN201911354962.6A patent/CN111009328A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104850758A (en) * | 2015-06-10 | 2015-08-19 | 史方 | Health index scoring method |
| CN105512505A (en) * | 2016-01-19 | 2016-04-20 | 宇龙计算机通信科技(深圳)有限公司 | Health prompting method and terminal equipment |
| CN105962918A (en) * | 2016-06-12 | 2016-09-28 | 夏茂 | Human body health evaluation method based on physical health indexes |
| CN106407644A (en) * | 2016-08-03 | 2017-02-15 | 无锡金世纪国民体质与健康研究有限公司 | Assessment system used for health risk assessment |
| CN109102888A (en) * | 2017-06-20 | 2018-12-28 | 深圳大森智能科技有限公司 | A kind of human health methods of marking |
| CN107169307A (en) * | 2017-07-07 | 2017-09-15 | 中北大学 | Health risk assessment method and apparatus |
| CN108877936A (en) * | 2018-04-28 | 2018-11-23 | 见道（杭州）科技有限公司 | Health evaluating method, system and computer readable storage medium |
| CN109087706A (en) * | 2018-07-13 | 2018-12-25 | 浙江清华长三角研究院 | Human health appraisal procedure and assessment system based on sleep big data |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021159747A1 (en) * | 2020-09-04 | 2021-08-19 | 平安科技（深圳）有限公司 | Regional health construction process evaluation method, apparatus and device, and storage medium |
| CN112349415A (en) * | 2020-11-05 | 2021-02-09 | 大连东软教育科技集团有限公司 | Physical examination big data-based resident health index construction method and device and storage medium |
| CN112465231A (en) * | 2020-12-01 | 2021-03-09 | 平安医疗健康管理股份有限公司 | Method, apparatus and readable storage medium for predicting regional population health status |
| CN112465231B (en) * | 2020-12-01 | 2023-02-03 | 深圳平安医疗健康科技服务有限公司 | Method, apparatus and readable storage medium for predicting regional population health status |
| CN113488169A (en) * | 2021-07-01 | 2021-10-08 | 新绎健康科技有限公司 | Human health assessment method and device based on energy metabolism |
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