scholarly journals Main Driving Factors and Prediction Model of Total Health Expenditure in China: A Study Based on Grey System Theory

2019 ◽  
Author(s):  
Huanhuan Jia ◽  
Xihe Yu ◽  
Jianxing Yu ◽  
Zhou Zheng ◽  
Yingying Li ◽  
...  
Keyword(s):  
System Theory ◽  
Prediction Model ◽  
Health Expenditure ◽  
The Elderly ◽  
Grey System Theory ◽  
Driving Factors ◽  
System Reform ◽  
Total Health Expenditure ◽  
Grey System ◽  
Correlation Degree

Abstract Background: The continuous increase in total health expenditure has become a social issue of common concern in most countries. In China, the total health expenditure still maintains a fast growth trend which is much higher than the growth of the country’s economy, although the new health system reform had been going on for 8 years until 2017. The aims of the current study were thus to investigate the main driving factors affecting total health expenditure and to establish a prediction model. Methods: Gray system theory was employed to explore the correlation degree between total health expenditure and 13 hot spots from the fields of economy, population, health service utilization, and public policy using national data in China from 2009 to 2017. Besides, a prediction model was established using the main driving factors among the 13 hot spots. Results: The main driving factors related to the changes of total health expenditure were public policy (ranked first), health development, economics, and aging, which correlation degrees were more than 0.7. The average error of the GM(1,7) model was 3.17%, the correlation degree, β , between the predicted simulation sequence and the original sequence was 0.78, the variance ratio, C, was 0.138, and the probability of residuals, P, was 1.0000. Therefore, the prediction model of total health expenditure with 6 main driving factors was excellent. Conclusion: The paper finds that since the new health system reform in China, government policies and social invest have contributed greatly to reducing the burden of health expenditure. However, the development of economic and the increase in the elderly population, which are main driving factors, will increase the total health expenditure, so improving the efficiency of investment and providing the precautionary health care and nursing for the elderly are crucial. Besides, the grey system theory had a good application in the field of health economics and policy.

Study on the Relationship between Soil Nutrients and the Corn Yield Based on Grey System Theory

2015 ◽  
Vol 733 ◽  
pp. 391-394
Author(s):  
Xing Mei Xu ◽  
Li Ying Cao ◽  
Jing Zhou
Keyword(s):  
System Theory ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Grey System Theory ◽  
Available Phosphorus ◽  
Corn Yield ◽  
Grey System ◽  
Correlation Degree ◽  
Soil Nutrient Content ◽  
The Relationship

Take the test zone 110 sampling plots of soil nutrient content as the research data, to study the correlation between the soil nutrient content and the corn yield. It used the grey system theory to analysis the correlation between the content of soil nutrient, and established GM (1, N) prediction model. Soil nutrient correlation degree analysis showed that the correlation coefficient of available phosphorus and available potassium were 0.4742, 0.4492, it has a significant effect on the corn yield, the average prediction error of the GM (1, N) model was 7.38%. The model reflected the relationship between soil nutrient content and the corn yield well; it can be used to predict the yield test area.

Research on Duration Prediction of the Coupled Task Set Based on the Grey System Theory

2012 ◽  
Vol 220-223 ◽  
pp. 169-173
Author(s):  
Peng Jia ◽  
Qi Gao ◽  
Rong Zhen Xu ◽  
Xiao Chen Zheng ◽  
Gang Liu
Keyword(s):  
System Theory ◽  
Prediction Model ◽  
Grey System Theory ◽  
Small Sample ◽  
Practical Application ◽  
Grey System ◽  
Task Set ◽  
Posterior Variance ◽  
Duration Prediction

In order to solve the problem of duration predicting in the project with poor information, small sample and uncertainty, a method based on grey system theory is put forward to predicting the duration of the coupled task set. A grey duration prediction model GM(1,1) is built, and the accuracy of the model is tested through residual, degree of incidence and posterior variance. Finally, the feasibility of the prediction model is verified by a practical application case.

scholarly journals Total Health Expenditure and Its Driving Factors in China: A Gray Theory Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 207
Author(s):  
Huanhuan Jia ◽  
Hairui Jiang ◽  
Jianxing Yu ◽  
Jingru Zhang ◽  
Peng Cao ◽  
...  
Keyword(s):  
21St Century ◽  
Health Expenditure ◽  
Driving Factors ◽  
Chinese Government ◽  
Good Prediction ◽  
Total Health Expenditure ◽  
Growth Trend ◽  
Continuous Growth ◽  
Correlation Degree ◽  
Good Prediction Accuracy

The continuous growth in total health expenditure (THE) has become a social issue of common concern in most countries. In China, the total health expenditure (THE) is maintaining a rapid growth trend that is higher than that of the economy, which has become increasingly obvious in the 21st century and has brought a heavy burden to the government and residents. To analyze the main driving factors of THE in China in the 21st century and establish a predictive model, gray system theory was employed to explore the correlation degree between THE and nine hot topics in the areas of the economy, population, health service utilization, and policy using national data from 2000 to 2018. Additionally, a New Structure of the Multivariate Gray Prediction Model of THE was established and compared with the traditional grey model and widely used BP neural network to evaluate the prediction effectiveness of the model. We concluded that the Chinese government and society have played a crucial role in reducing residents’ medical burden. Besides this, the improved economy and aging population have increased the demand for health services, leading to the continual increase in THE. Lastly, the improved NSGM(1,N) model achieved good prediction accuracy and has unique advantages in simulating and predicting THE, which can provide a basis for policy formulation.

scholarly journals Total Health Expenditure and Its Driving Factors in China: A Gray Theory Analysis

2021 ◽  
Author(s):  
Huanhuan Jia ◽  
Hairui Jiang ◽  
Jianxing Yu ◽  
Jingru Zhang ◽  
Peng Cao ◽  
...  
Keyword(s):  
21St Century ◽  
Health Expenditure ◽  
Driving Factors ◽  
Infant Mortality Rate ◽  
Chinese Government ◽  
Total Health Expenditure ◽  
Growth Trend ◽  
Continuous Growth ◽  
Correlation Degree ◽  
Good Prediction Accuracy

Abstract Background: The continuous growth in total health expenditure (THE) has become a social issue of common concern in most countries. In China, THE is maintaining a rapid growth trend that is faster than that of the economy, and this trend has become increasingly obvious in the 21st century and has placed a heavy burden on the government and residents. Therefore, the aims of this paper are to analyze the main driving factors and establish a predictive model of the growth of THE in China in the 21st century.Methods: Gray system theory was employed to explore the correlation degree between THE and 9 hot topics in the areas of the economy, population, health service utilization, and policy using national data for China from 2000 to 2018. Additionally, a New Structure of the Multivariate Gray (NSGM) prediction model of health expenditure was established and compared with the traditional grey model and widely used Back Propagation (BP) neural network.Results: General government expenditures on health, the economy, and out-of-pocket health expenditures were highly correlated with THE, with all correlation degrees greater than 0.8. The correlation degrees between health institutions, population and THE were 0.6-0.8, whereas infant mortality rate and THE was only 0.573. The average of the residual percentage of the training data of the NSGM(1,10) model is 0.36%, and that of the test data is 1.85%, which is better than the results of the other models.Conclusion: The Chinese government and society have played a crucial role in reducing residents’ medical burden, whereas the improved economy and aging population have increased the demand for health services, leading to the continual increase in THE. The improved NSGM(1,N) model achieved good prediction accuracy and has unique advantages in simulating and predicting THE, which can provide a basis for policy formulation.

A Grey System Theory-Based Default Prediction Model for Construction Firms

2014 ◽  
Vol 30 (2) ◽  
pp. 120-134 ◽  
Author(s):  
Hui Ping Tserng ◽  
Thanh Long Ngo ◽  
Po Cheng Chen ◽  
Le Quyen Tran
Keyword(s):  
System Theory ◽  
Prediction Model ◽  
Grey System Theory ◽  
Grey System ◽  
Construction Firms ◽  
Default Prediction

Prediction of Technical Reserves Based on Grey Model — GM(1,1): Evidence from Non-life Egyptian Insurance Market

2019 ◽  
Vol 10 (9) ◽  
pp. 852-860
Author(s):  
Mahmoud Elsayed ◽  
◽  
Amr Soliman ◽  
Keyword(s):  
System Theory ◽  
Grey System Theory ◽  
Insurance Market ◽  
Grey Model ◽  
Loss Ratio ◽  
Grey System ◽  
Mathematical Technique ◽  
Supervisory Authority ◽  
Error Ratio ◽  
Using Data

Grey system theory is a mathematical technique used to predict data with known and unknown characteristics. The aim of our research is to forecast the future amount of technical reserves (outstanding claims reserve, loss ratio fluctuations reserve and unearned premiums reserve) up to 2029/2030. This study applies the Grey Model GM(1,1) using data obtained from the Egyptian Financial Supervisory Authority (EFSA) over the period from 2005/2006 to 2015/2016 for non-life Egyptian insurance market. We found that the predicted amounts of outstanding claims reserve and loss ratio fluctuations reserve are highly significant than the unearned premiums reserve according to the value of Posterior Error Ratio (PER).

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