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Objective: To measure the burden of financing health care costs and quantify redistribution among population groups. Data Sources: A synthetic population using data combined from multiple sources, including the Survey of Income and Program Participation (SIPP), Medical Expenditure Panel Survey (MEPS), Kaiser Family Foundation (KFF)/Health Research Educational Trust (HRET) Employer Health Benefits Survey, American Community Survey (ACS), and National Health Expenditure Accounts (NHEA). Study Design: We estimate two dollar amounts for each individual in the synthetic population: (a) payments to finance health care services, which includes all payments by a household and their employers to finance health care, including premiums, out-of-pocket payments, federal and state taxes, and other payments; and (b) the dollar value of health care services received, which equals the amount paid to providers for those services. Data Extraction Methods: We linked the nationally representative survey data using statistical matching. We allocated health care expenditures from the NHEA to individuals and households based on expenditures reported in the MEPS. Principal Findings: We show that higher-income households pay the most to finance health care in dollar amounts, but the burden of payments as a share of income is greater among lower-income households. Conclusions: Accounting for all sources of payments provides a clear picture of the burden of financing health care costs, and how that burden is spread under our current financing system. KEYWORDS health care costs, health care financing, health economics, redistribution, 1 | INTRODUCTION In 2015, health care costs in the United States accounted for nearly 18 percent of GDP. (1) Over the coming 10 years, the share of GDP spent [...]

Objective. To measure the contribution of market-level prices, utilization, and health risk to medical spending variation among the Blue Cross Blue Shield of Texas (BCBSTX) privately insured population and the Texas Medicare population. Data Sources. Claims data for all BCBSTX members and publicly available CMS data for Texas in 2011. Study Design. We used observational data and decomposed overall and service-specific spending into health status and health status adjusted utilization and input prices and input prices adjusted for the BCBSTX and Medicare populations. Principal Findings. Variation in overall BCBSTX spending across HRRs appeared driven by price variation, whereas utilization variation factored more prominently in Medicare. The contribution of price to spending variation differed by service category. Price drove inpatient spending variation, while utilization drove outpatient and professional spending variation in BCBSTX. The context in which negotiations occur may help explain the patterns across services. Conclusions. The conventional wisdom that Medicare does a better job of controlling prices and private plans do a better job of controlling volume is an oversimplification. BCBSTX does a good job of controlling outpatient and professional prices, but not at controlling inpatient prices. Strategies to manage the variation in spending may need to differ substantially depending on the service and payer. Key Words. Health care spending variation, price, utilization, private payer, Medicare, Health care costs account for almost 18 percent of GDP in the United States, higher than in all other developed countries, which has prompted an intense search for opportunities to [...]

Objective. To measure spillover effects of Medicare inpatient hospital prices on the nonelderly (under age 65). Primary Data Sources. Healthcare Cost and Utilization Project State Inpatient Databases (10 states, 1995-2009) and Medicare Hospital Cost Reports. Study Design. Outcomes include nonelderly discharges, length of stay and case mix, staffed hospital bed-days, and the share of discharges and days provided to the elderly. We use metropolitan statistical areas as our markets. We use descriptive analyses comparing 1995 and 2009 and panel data fixed-effects regressions. We instrument for Medicare prices using accumulated changes in the Medicare payment formula. Principal Findings. Medicare price reductions are strongly associated with reductions in nonelderly discharges and hospital capacity. A 10-percent reduction in the Medicare price is estimated to reduce discharges among the nonelderly by about 5 percent. Changes in the Medicare price are not associated with changes in the share of inpatient hospital care provided to the elderly versus nonelderly. Conclusions. Medicare price reductions appear to broadly constrain hospital operations, with significant reductions in utilization among the nonelderly. The slow Medicare price growth under the Affordable Care Act may result in a spillover slowdown in hospital utilization and spending among the nonelderly. Key Words. Medicare, hospitals, prices, access/demand/utilization of services, health economics, instrumental variables, Congress has on several occasions cut the prices paid to medical providers to rein in the growth in spending on Medicare, the federal health care program for the elderly and [...]

Objective. To estimate the effects of changes in Medicare inpatient hospital prices on hospitals' overall revenues, operating expenses, profits, assets, and staffing. Primary Data Source. Medicare hospital cost reports (1996-2009). Study Design. For each hospital, we quantify the year-to-year price impacts from changes in the Medicare payment formula. We use cumulative simulated price impacts as instruments for Medicare inpatient revenues. We use a series of two-stage least squares panel data regressions to estimate the effects of changes in Medicare revenues among all hospitals, and separately among not-for-profit versus for-profit hospitals, and among hospitals experiencing real price increases ('gainers') versus decreases ('losers'). Principal Findings. Medicare price cuts are associated with reductions in overall revenues even larger than the direct Medicare price effect, consistent with price spillovers. Among not-for-profit hospitals, revenue reductions are fully offset by reductions in operating expenses, and profits are unchanged. Among for-profit hospitals, revenue reductions decrease profits one-for-one. Responses of gainers and losers are roughly symmetrical. Conclusions. On average, hospitals do not appear to make up for Medicare cuts by 'cost shifting,' but by adjusting their operating expenses over the long run. The Medicare price cuts in the Affordable Care Act will 'bend the curve,' that is, significantly slow the growth in hospitals' total revenues and operating expenses. Key Words. Medicare, hospitals, health care costs, payment, Congress, when faced with pressure to slow Medicare spending growth, has typically responded by reducing prices paid to providers. The Balanced Budget Act of 1997 (BBA97), for example, cut prices [...]

Resource utilization groups, version III (RUG-III) is used by CMS to classify skilled nursing facility (SNF) residents into Medicare payment groups. Using a sample of 1,304 SNF residents with Medicare-covered stays, we find that RUG-III only explains 10.4 percent of the variance in total per diem costs. RUG-III explains variance in staff-time costs fairly well, but does not explain variance in non-therapy ancillary costs. Receipt of special treatments such as intravenous medications and respiratory therapy is strongly associated with high residual costs (p, INTRODUCTION As mandated by the Balanced Budget Act of 1997, the Health Care Financing Administration on July 1, 1998 began phasing in a prospective payment system (PPS) for Medicare-covered stays [...]

14790 Changes in U.S. Hospitalization and Mortality Rates Following Smoking Bans U.S. state and local governments are increasingly restricting smoking in public places. This paper analyzes nationally representative databases, including [...]