Direct medical costs of hospitalizations for cardiovascular diseases in Shanghai, China: trends and projections

Abstract

Few studies in China have focused on direct expenditures for cardiovascular diseases (CVDs), making cost trends for CVDs uncertain. Epidemic modeling and forecasting may be essential for health workers and policy makers to reduce the cost burden of CVDs.To develop a time series model using Box-Jenkins methodology for a 15-year forecasting of CVD hospitalization costs in Shanghai.Daily visits and medical expenditures for CVD hospitalizations between January 1, 2008 and December 31, 2012 were analyzed. Data from 2012 were used for further analyses, including yearly total health expenditures and expenditures per visit for each disease, as well as per-visit-per-year medical costs of each service for CVD hospitalizations. Time series analyses were performed to determine the long-time trend of total direct medical expenditures for CVDs and specific expenditures for each disease, which were used to forecast expenditures until December 31, 2030.From 2008 to 2012, there were increased yearly trends for both hospitalizations (from 250,354 to 322,676) and total costs (from US $ 388.52 to 721.58 million per year in 2014 currency) in Shanghai. Cost per CVD hospitalization in 2012 averaged US $ 2236.29, with the highest being for chronic rheumatic heart diseases (US $ 4710.78). Most direct medical costs were spent on medication. By the end of 2030, the average cost per visit per month for all CVDs was estimated to be US $ 4042.68 (95% CI: US $ 3795.04-4290.31) for all CVDs, and the total health expenditure for CVDs would reach over US $1.12 billion (95% CI: US $ 1.05-1.19 billion) without additional government interventions.Total health expenditures for CVDs in Shanghai are estimated to be higher in the future. These results should be a valuable future resource for both researchers on the economic effects of CVDs and for policy makers.

FIGURE 1

Yearly cumulative visits and expenditures for patients hospitalized with cardiovascular diseases in Shanghai (2014 US $ million). The line with symbol “X” represents the yearly visits for patients hospitalized, and the black bars represent the yearly total expenditures for total population, while gray bars represent expenditures for employed population and white bars represent expenditures for unemployed population.

FIGURE 2

Forecasted costs for cardiovascular diseases per month per visit (2014 US $). The gray solid lines show observed values, while the black solid lines show fit values (before the reference line) and projected values (after the reference line), and the dotted lines show 95% confidence intervals of the series: (A) all cardiovascular diseases; (B) acute rheumatic fever; (C) chronic rheumatic heart diseases; (D) hypertensive diseases; (E) ischemic heart diseases; (F) cerebrovascular diseases; and (G) stroke.

FIGURE 3

Sensitivity analysis of predicted hospitalization expenditure based on different population scheme (2014 US $ billion). This figure showed the results of sensitivity analysis, which was calculated by multiplying the projected average costs with different population schemes. The line with the symbol “X” represents the annual total hospitalization expenditure of the high population scheme, while the line with the symbol “▴” represents the expenditure of middle scheme and the line with the symbol “▪” represents the expenditure of the low scheme.