IMPORTANCE US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how these amounts have changed over time. OBJECTIVE To estimate US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. DESIGN AND SETTING Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. EXPOSURES Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. MAIN OUTCOMES AND MEASURES National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. RESULTS Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product [GDP]; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending

There is no single gold standard for adjusting health expenditures for inflation. Our discussion of best practices can help researchers select the index best suited to their study.

We study the degree to which greater physician concentration leads to higher service prices charged by physicians in the commercially insured medical-care market.Using a database of physicians throughout the entire United States, we construct physician-firm concentration measures based on market boundaries defined by fixed driving times-we label the"fixed-travel-time HHI" (FTHHI). Similar to the measure constructed by Kessler and McClellan [2000], the FTHHI is constructed to mitigate omitted-variable bias attributable to higher quality physicians attracting a higher share of patients. We link these concentration measures to health insurance claims.We find that physicians in more concentrated markets charge higher service prices.Cross-sectional estimates show that a ten percent increase in concentration is associated with a 0.5 to 1 percent increase in fees. Panel estimates show the effect may be twice as large, although estimates are less precisely estimated. Our estimates imply that physician consolidation has caused about an eight percent increase in fees over the last 20 years.

The pharmaceutical industry is characterized as having substantial investment in R&D and a large number of new product introductions, which poses special problems for price measurement caused by the quality of drug products changing over time. This paper applies recent demand estimation techniques to individual level data to construct a constant-quality price index for anti-cholesterol drugs. Although the average price for anti-cholesterol drugs does not change over the sample period, I …nd that the constant-quality price index drops by 27 percent, a pace more in line with our expectations in such a dynamic segment of the industry.

Our findings suggest that the health component of inflation may be overstated by 0.7 percentage points per year, and real GDP growth may be understated by a similar amount. However, more work may be necessary to precisely replicate the indexes of the BLS to obtain a more accurate measure of these price differences.

The administrative costs of providing health insurance in the US are very high, but their determinants are poorly understood. We advance the nascent literature in this field by developing new measures of billing complexity for physician care across insurers and over time, and by estimating them using a large sample of detailed insurance "remittance data" for the period 2013-15. We found dramatic variation across different types of insurance. Fee-for-service Medicaid is the most challenging type of insurer to bill, with a claim denial rate that is 17.8 percentage points higher than that for fee-for-service Medicare. The denial rate for Medicaid managed care was 6 percentage points higher than that for fee-for-service Medicare, while the rate for private insurance appeared similar to that of Medicare Advantage. Based on conservative assumptions, we estimated that the health care sector deals with $11 billion in challenged revenue annually, but this number could be as high as $54 billion. These costs have significant implications for analyses of health insurance reforms.

In 2015 the Bureau of Economic Analysis released an experimental set of measures referred to as the Health Care Satellite Account, which tracks national health care spending by medical condition. These statistics improve the understanding of the health care sector by blending medical claims data and survey data to present measures of national spending and cost of treatment by condition. This article introduces key aspects of the new account and uses it to study the health spending slowdown that occurred in the period 2000-10. Our analysis of the account reveals that the slowdown was driven by a reduction of growth in cost per case but that spending trends varied greatly across conditions and differentially affected the slowdown. More than half of the overall slowdown was accounted for by a slowdown in spending on circulatory conditions. However, there were more dramatic slowdowns in spending on categories such as endocrine system and musculoskeletal conditions than in spending on other categories, such as cancers.

Medical-care expenditures have been rising rapidly, accounting for almost one-…fth of GDP in 2009. In this study, we assess the sources of the rising medical-care expenditures in the commercial sector. We employ a novel framework for decomposing expenditure growth into four components at the disease level: service price growth, service utilization growth, treated disease prevalence growth, and demographic shift. The decomposition shows that growth in prices and treated prevalence are the primary drivers of medical-care expenditure growth over the 2003 to 2007 period. There was no growth in service utilization at the aggregate level over this period. Price and utilization growth were especially large for the treatment of malignant neoplasms. For many conditions, treated prevalence has shifted towards preventive treatment and away from treatment for late-stage illnesses.