Medical insurance and health equity in health service utilization among the middle-aged and older adults in China: a quantile regression approach

Fan, Guorui; Deng, Zhaohua; Wu, Xiang; Wang, Yang

doi:10.1186/s12913-020-05423-y

Cited by 23 publications

(24 citation statements)

References 44 publications

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“…In our analysis, the distributions of the outcome variables in our sample were heavily skewed, as is consistent with the general understanding that ED utilization measures are typically not normally distributed and have long heavy right tails 60 . QR has become a successful analytic method in health services research because of its ability to draw inferences about individuals that rank below or above the population conditional mean and its robustness to outliers commonly present in health care data 43,61‐66 …”

Section: Discussionsupporting

confidence: 76%

Social and demographic characteristics of frequent or high‐charge emergency department users: A quantile regression application

Mayfield

Geraci

Dulin

et al. 2021

Evaluation Clinical Practice

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Objective Heavy users of the emergency department (ED) are a heterogeneous population. Few studies have captured the social and demographic complexity of patients with the largest burden of ED use. Our objective was to model associations between social and demographic patient characteristics and quantiles of the distributions of ED use, defined as frequent and high‐charge. Methods We conducted a cross‐sectional analysis of electronic health and billing records of 99 637 adults residing in an urban North Carolina county who visited an ED within Atrium Health, a large integrated health care system, in 2017. Mid‐quantile and standard quantile regression models were used for count and continuous responses, respectively. Frequent and high‐charge use outcomes were defined as the median (0.50) and upper quantiles (0.75, 0.95, 0.99) of the outcome distributions for total billed ED visits and associated charges during the study period. Patient characteristic predictors were: insurance coverage (Medicaid, Medicare, private, uninsured), total visits to ambulatory care during the study period (0, 1, >1), and patient demographics: age, gender, race, ethnicity, and living in an underprivileged community called a public health priority area (PHPA). Results Results showed heterogeneous relationships that were stronger at higher quantiles. Having Medicaid or Medicare insurance was positively associated with ED visits and ED charges at most quantiles. Racial and geographic disparities were observed. Black patients had more ED visits and lower ED charges than their White counterparts at most quantiles of the outcome distributions. Patients living in PHPAs, had lower charges than their counterparts at the median but higher charges at the 0.95 and 0.99 quantiles. Conclusions The relationships between patient characteristics and frequent and high‐charge use of the ED vary based on the level of use. These findings can be used to inform targeted interventions, tailored policy, and population health management initiatives.

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Section: Discussionsupporting

confidence: 76%

Social and demographic characteristics of frequent or high‐charge emergency department users: A quantile regression application

Mayfield

Geraci

Dulin

et al. 2021

Evaluation Clinical Practice

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“…Quantile regression was adapted over the ordinary least square (OLS) due to the highly skewed distribution of the outcome variables. This approach is less sensitive to the influence of outliers as it provides estimations of the impact of an explanatory variable along the whole distribution of outcomes variables [ 26 , 27 ]. Moreover, quantile regression fit a line that minimises the sum of the absolute residuals [ 26 , 27 ].…”

Section: Methodsmentioning

confidence: 99%

“…This approach is less sensitive to the influence of outliers as it provides estimations of the impact of an explanatory variable along the whole distribution of outcomes variables [ 26 , 27 ]. Moreover, quantile regression fit a line that minimises the sum of the absolute residuals [ 26 , 27 ]. We assessed the association between multimorbidity and various percentiles of health service use/OOPE (from 10th to 90th percentiles).…”

Section: Methodsmentioning

confidence: 99%

Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis

Anindya

Atun

et al. 2021

BMC Health Serv Res

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Background Multimorbidity (the presence of two or more non-communicable diseases) is a major growing challenge for many low-income and middle-income countries (LMICs). Yet, its effects on health care costs and financial burden for patients have not been adequately studied. This study investigates the effect of multimorbidity across the different percentiles of healthcare utilisation and out-of-pocket expenditure (OOPE). Methods We conducted a secondary data analysis of the 2014/2015 Indonesian Family Life Survey (IFLS-5), which included 13,798 respondents aged ≥40 years. Poisson regression was used to assess the association between sociodemographic characteristics and the total number of non-communicable diseases (NCDs), while multivariate logistic regression and quantile regression analysis was used to estimate the associations between multimorbidity, health service use and OOPE. Results Overall, 20.8% of total participants had two or more NCDs in 2014/2015. The number of NCDs was associated with higher healthcare utilisation (coefficient 0.11, 95% CI 0.07–0.14 for outpatient care and coefficient 0.09 (95% CI 0.02–0.16 for inpatient care) and higher four-weekly OOPE (coefficient 27.0, 95% CI 11.4–42.7). The quantile regression results indicated that the marginal effect of having three or more NCDs on the absolute amount of four-weekly OOPE was smaller for the lower percentiles (at the 25th percentile, coefficient 1.0, 95% CI 0.5–1.5) but more pronounced for the higher percentile of out-of-pocket spending distribution (at the 90th percentile, coefficient 31.0, 95% CI 15.9–46.2). Conclusion Multimorbidity is positively correlated with health service utilisation and OOPE and has a significant effect, especially among those in the upper tail of the utilisation/costs distribution. Health financing strategies are urgently required to meet the needs of patients with multimorbidity, particularly for vulnerable groups that have a higher level of health care utilisation.

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“…The URRBMI program covers children, students and other unemployed adult residents living in urban and rural areas, and UEBMI enrollees represent all adult (at least 18 years) employees and retirees of the public and private sectors. Due to the different reimbursement benefits between the two types of medical insurance systems (the URRBMI program covers fewer healthcare items and pays less than UEBMI), inhabitants who are enrolled in the URRBMI program always have a lower utilization rate of healthcare resources than those enrolled in the UEBMI plan [ 24 ]. The evidence from the UEBMI claims database could more truly reflect the level of diagnosis and treatment, as well as the epidemiology data of a city.…”

Section: Methodsmentioning

confidence: 99%

Trends and Age-Period-Cohort Effects on the Prevalence, Incidence and Mortality of Hepatocellular Carcinoma from 2008 to 2017 in Tianjin, China

Liu

Chang

2021

IJERPH

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Objectives: China is the country most afflicted by hepatocellular carcinoma in the world. However, little is known about the epidemiology of hepatocellular carcinoma in China. This study aimed to examine the trends of the prevalence, incidence, and mortality of hepatocellular carcinoma in China, and to investigate the effects of age, period, and birth cohort on the epidemiological trend. Methods: The data were obtained from the Urban Employee Basic Medical Insurance claims database (2003–2017) in Tianjin, China, which covers 5.95 million individuals. The average annual percentage change of the prevalence, incidence, and mortality were accessed using joinpoint regression. Age-period-cohort models were produced to quantify the effects of age, period, and cohort. Results: The hepatocellular carcinoma prevalence rate increased by 5.13% annually from 20.12/100,000 in 2008 to 30.49/100,000 in 2017, and the incidence rate was almost unchanged, from 13.91/100,000 in 2008 to 14.09/100,000 in 2017, but mortality decreased by 1.80% annually from 8.18/100,000 in 2008 to 7.34/100,000 in 2017. The age-period-cohort analysis revealed that the prevalence rate was remarkably increased from age 25, peaked in age 60, and decreased at age 70 and over. In the period index, the prevalence rate increased gradually from 2008 to 2016, and decreased a little in 2017. In the cohort index, the prevalence rate decreased approximately linearly from the 1925 cohort to the 1990 cohort. The result for the incidence was similar to the prevalence. The mortality rate increased approximately linearly from age 45 to 85, decreased from the 1925 cohort to the 1990 cohort, but it changed a little with the change of period. Conclusions: The findings of this study could inform the necessity of conducting earlier screening for high-risk individuals and improving the treatment of hepatocellular carcinoma, which may also help to predict future changes in hepatocellular carcinoma epidemiology.

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Medical insurance and health equity in health service utilization among the middle-aged and older adults in China: a quantile regression approach

Cited by 23 publications

References 44 publications

Social and demographic characteristics of frequent or high‐charge emergency department users: A quantile regression application

Social and demographic characteristics of frequent or high‐charge emergency department users: A quantile regression application

Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis

Trends and Age-Period-Cohort Effects on the Prevalence, Incidence and Mortality of Hepatocellular Carcinoma from 2008 to 2017 in Tianjin, China

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