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.