There is a paucity of studies that focus on the economic burden in daily care in China using electronic health data. The aim of this study is to describe the development of the economic burden of diabetic patients in a sample city in China from 2009 to 2011 using electronic data of patients' claims records. Methods This study is a retrospective, longitudinal study in an open cohort of Chinese patients with diabetes. The patient population consisted of people living in a provincial capital city in east China, covered by the provincial urban employee basic medical insurance (UEBMI). We included any patient who had at least one explicit diabetes diagnosis or received blood glucose lowering medication in at least one registered outpatient visit or hospitalization during a calendar year in the years 2009-2011. Cross-sectional descriptions of different types of costs, prevalence of diabetic complications and related diseases, medication use were performed for each year separately and differences between three years were compared using a chi-square test or the non-parametric Kruskal-Wallis H test. Results Our results showed an increasing trend in total medical cost (from 2,383 to 2,780 USD, p = 0.032) and diabetes related cost (from 1,655 to 1,857 USD) for those diabetic patients during the study period. The diabetes related economic burden was significantly related to the prevalence of complications and related diseases (p<0.001). The overall medication cost during diabetes related visits also increased (from 1,335 to 1,383 USD, p = 0.021). But the use pattern and cost of diabetes-related medication did not show significant changes during the study period. Conclusion The economic burden of diabetes increased significantly in urban China. It is important to improve the prevention and treatment of diabetes to contribute to the sustainability of the Chinese health-care system.
Huang, Y., Vemer, P., Zhu, J., Postma, M. J., & Chen, W. (2016). Economic burden in Chinese patients with diabetes mellitus using electronic insurance claims data. PLoS ONE, 11(8). https://doi.org/10.1371/journal.pone.0159297