Costs of Hospitalization for Dementia in Urban China: Estimates from Two Urban Health Insurance Scheme Claims Data in Guangzhou City

Abstract

Background: Dementia is one of the public health priorities in China. This study aimed to examine the hospitalization costs of patients with dementia and analyzed the factors associated with their inpatient costs. Methods: This was a prevalence-based, observational study using claims data derived from two urban insurance schemes during the period from 2008 through 2013 in Guangzhou. The extended estimating equations model was performed to identify the main drivers of total inpatient costs. Results: We identified 5747 dementia patients with an average age of 77.4. The average length of stay (LOS) was 24.2 days. The average hospitalization costs per inpatient was Chinese Yuan (CNY) 9169.0 (CNY 9169.0 = US$1479.8 in 2013). The mean inpatient costs for dementia patients with the Urban Employee-based Basic Medical Insurance (UEBMI) scheme (CNY 9425.0 = US$1521.1) were higher than those for patients with the Urban Resident-based Basic Medical Insurance scheme (CNY 7420.5 = US$1197.6) (p < 0.001). Having UEBMI coverage, dementia subtypes, having hypertension, being admitted in larger hospitals, and longer LOS were significantly associated with hospitalization costs of dementia. Conclusions: The costs of hospitalization for dementia were high and differed by types of insurance schemes. Dementia was associated with substantial hospitalization costs, mainly driven by insurance type and long LOS. These findings provided economic evidence for evaluating the burden of dementia in China.

Direct Medical Costs of Parkinson’s Disease in Southern China: A Cross-Sectional Study Based on Health Insurance Claims Data in Guangzhou City

“…The regression analysis also found that the type of health insurance (UEBMI) was significantly correlated with higher inpatient costs of PD patients. These findings were consistent with prior studies exploring disparities in medical costs of patients with other diseases between these two types of health insurance schemes in China [ 34 , 35 , 48 ]. The possible explanations were discussed as follows.…”

“…Due to the administrative restrictions on accessing the social insurance claims database, this was the most recent data available for this study. The UEBMI and URBMI are two social health insurance schemes covering the population of urban employees and urban non-employed residents in Guangzhou City, with a great deal of differences in service coverages and reimbursement rates [ 34 , 35 ]. The detailed comparisons of UEBMI and URBMI policies for PD patients in Guangzhou City were summarized in Table 1 .…”

“…The direct medical costs, inpatient costs and outpatient costs all contained the individual out-of-pocket (OOP) spending and the reimbursement part from the UEBMI or URBMI scheme. According to the classification of cost composition used in these two schemes, direct medical costs were divided into five groups: bed fees, medication costs, laboratory and diagnostic costs, non-medication treatment costs and other fees [ 35 , 37 ]. Table 2 described the definitions of different classifications of direct medical costs and showed the calculation methods in detail.…”

“…In this study, the predictors of inpatient costs for patients with PD were selected based on this theoretical framework [ 38 ] and the results of the literature review. Individual influential factors were selected from the following three parts: (1) predisposing characteristics: existing conditions that predispose individuals to health services utilization (such as gender [ 41 , 42 ] and age [ 28 , 30 , 43 , 44 , 45 , 46 , 47 ]); (2) enabling characteristics: conditions that facilitate or impede health services usage (for example, type of insurance [ 31 , 32 ]); (3) need characteristics: conditions that medical providers consider as requiring professional treatment (such as disease subtypes [ 35 , 37 ], hospital levels [ 34 , 48 ], length of stay (LOS) [ 35 , 48 ] and presence of any comorbidities [ 44 , 49 ]).…”

“…However, the EEE model can estimate by flexible link and variance functions, which would reduce bias and inefficiency in estimation [ 56 ]. The EEE model has been used in previous studies [ 35 , 37 , 57 , 58 , 59 ]. Statistical analyses were conducted using the R language version 4.0.3 and STATA version 12.0 (STATA Corporation, Collection Station, TX, USA).…”