Trends in health care expenditure among US adults with heart failure: The Medical Expenditure Panel Survey 2002-2011

Abstract

Background Population-based national data on the trends in expenditures related to heart failure (HF) is scarce. Assessing the time trends in health care expenditures for HF in the United States can help to better define the burden of this condition. Methods Using 10-year data (2002–2011) from the national Medical Expenditure Panel Survey (weighted sample of 188,708,194 U.S adults aged ≥18 years) and a two-part model (adjusting for demographics, comorbidities and time); we estimated adjusted mean and incremental medical expenditures by HF status. The costs were direct total health care expenditures (out-of-pocket payments and payments by private insurance, Medicaid, Medicare, and other sources) from various sources (office-based visits, hospital outpatient, emergency room, inpatient hospital, pharmacy, home health care, and other medical expenditures). Results Compared to expenditures for individuals without HF ($5,511 [95% confidence interval (CI): 5,405–5,617]), individuals with HF had a four-fold higher mean expenditures of ($23,854 [95%CI: 21,733–25,975]). Individuals with HF had $3,446 (95%CI: 2,592–4,299) higher direct incremental expenditures compared with those without HF, after adjusting for demographics and comorbidities. Among those with HF, costs continuously increased by $5836 (28% relative increase), from $21,316 (95%CI: 18,359–24,272) in 2002/2003 to $27,152 (95%CI: 20,066–34,237) in 2010/2011; and inpatient costs ($11,318 over the whole period) were the single largest component of total medical expenditure. The estimated unadjusted total direct medical expenditures for US adults with HF were $30 billion/year and the adjusted total incremental expenditure $5.8 billion/year. Conclusions Heart failure is costly and over a recent 10-year period, direct expenditure related to HF increased markedly, mainly driven by inpatient costs.

A Systematic Review of Medical Costs Associated with Heart Failure in the USA (2014–2020)

“…The method of estimating costs was not explicitly stated in the majority of studies (58/87; 67%) (ESM 3). Based on the reviewers’ interpretation, 41 studies employed a bottom-up approach (cost profile is constructed using disaggregated patient-level data), seven used a top-down approach [ 47 , 64 , 65 , 71 , 74 , 76 , 90 ] (total expenditure divided by number of patients treated), and one study [ 25 ] used a mixed costing method. Information reported by the remaining studies ( n = 38, only published as abstracts) did not allow for conclusions to be drawn on the costing approach.…”

“…Most of the included studies captured costs for outpatient medication and physician visits within the total medical cost estimated; only seven studies itemized outpatient visit costs separately from other medical costs [ 25 , 34 , 46 , 57 , 64 , 76 , 86 ], which had a range from $297 [ 86 ] to $3859 [ 64 ] per patient. Yoon et al [ 76 ] estimated the annual average cost per patient per type of outpatient healthcare, including medical/surgical costs ($8487), diagnostic costs ($2178), behavioral costs ($550), other costs ($973), and pharmacy costs ($2904).…”

Severe Maternal Morbidity and Hospital Cost among Hospitalized Deliveries in the United States

“…It is well accepted in health economics that it is the estimated population mean cost that is the statistic of interest to policy makers, 19,20 and this approach of modeling mean cost has been widely published in the medical literature. [21][22][23] Although several methods have been developed and used in studying health care costs, the generalized linear model (GLM), especially the gamma regression model, 24 has been commonly used in the literature, 22,25,26 as it behaves well in the estimation of population means of health care costs, and does not require the normality and homoscedasticity assumptions of the data and avoids bias associated with retransforming to the raw scale. 27 In this study, a multivariable GLM employing a gamma distribution with a log-link function 24 was used to examine the association between the main outcome of hospital costs and SMM, while adjusting for several potential confounding variables: maternal age, race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, other, and unknown), singleton/multiple gestations, primary payer (private insurance, Medicaid, self-pay, other), delivery method (vaginal, cesarean), hospital bed size (small, medium, large), hospital location/teaching status (rural, urban nonteaching, urban teaching), and hospital region (Northeast, Midwest, South, West).…”

Cognitive determinants of self-care behaviors among patients with heart failure: A path analysis

“… 3 Compared to individuals without HF, the patients with HF have a 4-fold higher mean of healthcare expenditures. 6 …”