Exploring Medical Expenditure Clustering and the Determinants of High-Cost Populations from the Family Perspective: A Population-Based Retrospective Study from Rural China

Shan Lu, Yan Zhang, Yadong Niu and Liang Zhang
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Shan Lu: School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Yan Zhang: School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Yadong Niu: School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Liang Zhang: School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

IJERPH, 2018, vol. 15, issue 12, 1-14

Abstract: The costliest 5% of the population (identified as the “high-cost” population) accounts for 50% of healthcare spending. Understanding the high-cost population in rural China from the family perspective is essential for health insurers, governments, and families. Using the health insurance database, we tallied 202,482 families that generated medical expenditure in 2014. The Lorentz curve and the Gini coefficient were adopted to describe the medical expenditure clustering, and a logistic regression model was used to identify the determinants of high-cost families. Household medical expenditure showed an extremely uneven distribution, with a Gini coefficient of 0.76. High-cost families spent 54.0% of the total expenditure. The values for family size, average age, and distance from and arrival time to the county hospital of high-cost families were 4.05, 43.18 years, 29.67 km, and 45.09 min, respectively, which differed from the values of the remaining families (3.68, 42.46 years, 30.47 km, and 46.29 min, respectively). More high-cost families live in towns with low-capacity township hospitals and better traffic conditions than the remaining families (28.98% vs. 12.99%, and 71.19% vs. 69.6%, respectively). The logistic regression model indicated that family size, average age, children, time to county hospital, capacity of township hospital, traffic conditions, economic status, healthcare utilizations, and the utilization level were associated with high household medical expenditure. Primary care and health insurance policy should be improved to guide the behaviors of rural residents, reduce their economic burden, and minimize healthcare spending.

Keywords: medical expenditure; high-cost family; clustering; rural China (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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