Health Spending Trends

V. Key Health Policy Issues >> B. Health Spending >> Health Spending Trends (last updated July 15, 2014)

 

Topic Outline

1. Key Questions
     a. How much does the government owe?
     b. What would it take to close the fiscal gap?
     c.  How much public debt is sustainable?
     d. Are current health spending trends affordable?
     e. Innovation and the future of medicine
     f. What are the key drivers of U.S. health spending?
     g. How does the U.S. compare to the rest of the world in terms of health care spending?
2. Links
     a.  Historical Trends in Aggregate Health Spending
     b. Historical Trends in Household Health Spending
     c.  Historical Trends in Medical Prices
     d. Key Drivers of Health Spending
     e. Health Spending Projections

 

Key Questions

Links

Historical Trends in Aggregate Health Spending

  • Congressional Budget Office, Growth in Health Care Costs, CBO Testimony before the Committee on the Budget United States Senate, January 31, 2008.
  • Getzen, Thomas, 2011. Long-run Forecasts of National Health Expenditure Growth. The “state of the art” in forecasting long run medical spending is assessed in models used by CMS, CBO, and the Society of Actuaries. Tracking medical expenditures by nominal dollar growth and real per capita spending are useful, yet focusing on the share (of wages, laborforce, or GDP) provides the perspective most immediately applicable to policy and capable of providing the most robust long run forecasts. Spending limits appear to be a variable result of politics and budgetary constraints more than morbidity and mortality. Although death and taxes may be certainties, “when” and “how much” are not.
  • Paul B. Ginsburg, High and Rising Health Care Costs: Demystifying U.S. Health Care Spending, Robert Wood
    Johnson Foundation. The Synthesis Project, October 2008.
  • Health Cost Index Report (Milliman). The Health Cost Index Report™ (HCIR) is a quarterly newsletter that presents the latest trends and forecasts from Milliman’s proprietary database of medical trends. These trends measure the market average rate of increase in medical costs for a typical $250 deductible Comprehensive Major Medical benefit package. The database measures the growth rate in medical consumption by measuring how fast provider net revenues increase. This inherently captures price, utilization and mix/intensity of service changes (technology). The HCIR presents trends by benefit and by region of the country. The quarterly reports also contain one year forecasts and Milliman’s latest research on medical trends.
  • Kaiser Family Foundation. Assessing the Effects of the Economy on the Recent Slowdown in Health Spending (April 2013). “about three-quarters (77%) of the recent decline in health spending growth can be explained by changes in the broader economy.”
  • Altarum InstituteHealth Sector Economic Indicators BriefsThe monthly HSEI briefs are designed to address significant shortcomings in the availability of timely economic data on the health sector, including employment, spending, and prices.  Official government estimates of national health expenditures are available annually only for the previous year (2009 estimates were released in January 2011). Examining updated health spending on a monthly basis significantly improves our ability to track trends and progress toward our goal of sustainable growth.

 

Historical Trends in Household Health Spending

  • Milliman Medical IndexThe annual Milliman Medical Index (MMI) measures the total cost of healthcare for a typical family of four covered by a preferred provider plan (PPO). The 2012 MMI cost is $20,728, an increase of $1,335, or 6.9% over 2011. Even though the rate of increase is slowing from prior years, it has taken fewer than nine years for such costs to more than double. In 2002, the cost of healthcare for the typical family of four was $9,235.
  • Auerbach, David I. and Arthur L. Kellermann, 2011. A Decade Of Health Care Cost Growth Has Wiped Out Real Income Gains For An Average US FamilyHealth Affairs 30(9).  Although a median-income US family of four with employer-based health insurance saw its gross annual income increase from $76,000 in 1999 to $99,000 in 2009 (in current dollars), this gain was largely offset by increased spending to pay for health care. Monthly spending increases occurred in the family’s health insurance premiums (from $490 to $1,115), out-of-pocket health spending (from $135 to $235), and taxes devoted to health care (from $345 to $440). After accounting for price increases in other goods and services, the family had $95 more in monthly income to devote to nonhealth spending in 2009 than in 1999. By contrast, had the rate of health care cost growth not exceeded general inflation, the family would have had $545 more per month instead of $95—a difference of nearly $5,400 per year. Even the $95 gain was artificial, because tax collections in 2009 were insufficient to cover actual increases in federal health spending. As a result, we argue, the burdens imposed on all payers by steadily rising health care spending can no longer be ignored.

 

Historical Trends in Medical Prices

  • Hospital, Employment and Price Indicators. Includes a) community hospital statistics; b) Medicare trust fund data; c) health sector employment, earnings and hours; d) medical prices; and e) HCFA projected price indices for hospital, nursing home, and home health.
  • AHRQ. Using Appropriate Price Indices for Analysis of Health Care Expenditures or Income Across Multiple Years. This document provides guidelines to help ensure consistency and avoid confusion about the use of price indices with MEPS expenditure or income data..
  • Bureau of Labor StatisticsConsumer Price Index. BLS tracks prices for a) Medical care, which is a composite of 1) Medical care commodities and 2) Medical care services.
    • Medical care commodities includes a) Medicinal drugs, which is a composite of 1) Prescription drugs; and 2) Nonprescription drugs; and b) Medical equipment and supplies.
    • Medical care services is a composite of a) Professional services, which includes 1) Physicians’ services, 2) Dental services, 3) Eyeglasses and eye care, and 4) Services by other medical professionals; b) Hospital and related services, which includes 1) Hospital services [which includes Inpatient hospital services and Outpatient hospital services], 2) Nursing homes and adult day services, and 3) Care of invalids and elderly at home; and c) Health insurance.
  • Bureau of Labor Statistics.  Producer Price Index. BLS tracks prices for a) Offices of physicians, b) Offices of dentists, c) Medical and diagnostic laboratories, d) Home health care services, e) Blood and organ banks, f) Hospitals, g) Nursing care facilities, and h) Residential mental retardation facilities.
  • Aizcorbe, AnaRalph BradleyRyan Greenaway-McGrevyBrad HeraufRichard KaneEli LiebmanSara Pack, and Lyubov Rozental, 2011. Alternative Price Indexes for Medical Care: Evidence from the MEPS Survey. Bureau of Labor Statistics, Washington DC. Spending on medical care is a large and growing component of GDP. There are well-known measurement problems that are estimated to overstate inflation and understate real growth for this sector by as much as 1-1/2 percentage points per year. Because of its size, this would translate into an overstatement of inflation for the overall economy of about ¼ percentage point with an equal understatement in real GDP growth. In this paper, we use data from the Medical Expenditure Panel Survey to obtain new, more comprehensive estimates for this bias and to explore a possible adjustment to existing official price indexes. The MEPS data show an upward bias to price growth in this sector of 1 percentage point, which translates into an overstatement of overall inflation of .2 percentage point and an understatement of GDP growth of the same amount. We also find that an adjustment recently used in Bradley et al provides a useful approximation to the indexes advocated by health economists.

 

Key Drivers of Health Spending

  • Chandra A, Skinner J., 2012. Technology growth and expenditure growth in health care. Journal of Economic Literature 2012; 50(3):645-80. In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to GDP has also grown more rapidly than in any other country. We develop a model of patient demand and supplier behavior to explain these parallel trends in technology growth and cost growth. We show that health care productivity depends on the heterogeneity of treatment effects across patients, the shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. The model implies a typology of medical technology productivity: (I) highly cost-effective “home run” innovations with little chance of overuse, such as anti-retroviral therapy for HIV, (II) treatments highly effective for some but not for all (e.g. stents), and (III) “gray area” treatments with uncertain clinical value such as ICU days among chronically ill patients. Not surprisingly, countries adopting Category I and effective Category II treatments gain the greatest health improvements, while countries adopting ineffective Category II and Category III treatments experience the most rapid cost growth. Ultimately, economic and political resistance in the U.S. to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth.
  • Clemens, Jeffrey, 2011. The Effect of U.S. Health Insurance Expansions on Medical Innovation, SIEPR Discussion Paper No. 11-016, Stanford University. I study the effect of health insurance expansions on medical innovation. Innovation by practitioners creates important roles for local patient flows and payment systems as drivers of medical technology development. I show that, over the 15 years following Medicare and Medicaid’s passage, U.S.-based medical-equipment patenting rose by nearly 50 percent relative to both other U.S. patenting and foreign medical-equipment patenting. Surges in medical-equipment patenting were largest in the states most significantly affected by the Great Society programs. No relative increase occurred among pharmaceutical patents, for which markets were not directly affected. The dynamic effect of U.S. insurance expansions may account for 25 percent of recent global medical-equipment innovation and 15 percent of the rise in U.S. health spending in hospitals, physicians’ offices, and other clinical settings from 1960 to 2010.

Health Spending Projections

  • Aaron, Henry. “There Is No Entitlement Problem,” Brookings Institution, February 23, 2009. “That the United States faces daunting long-term budget challenges is indisputable. But the very projections—those of the Congressional Budget Office—cited to document the long-term budget challenge, show that there is no general entitlement problem. Rather, the nation faces a daunting health care financing problem that bedevils private insurers and public programs alike.”
  • Altarum Institute. Altarum Health Sector Model (AHSM) forecasts health spending as captured in the National Health Expenditure Ac­counts (NHEA), based upon population demographics, disease prevalence, pre­vailing treatment patterns, insurance coverage/care access, and payment rates. This structure makes AHSM a powerful tool for integrating broad research strains related to health expenditure determinants. Altarum plans to create state-based ver­sions.
  • Altarum InstituteLong-Term U.S. Fiscal Crisis: Introduction to Altarum’s Triangle of Painful Choices. This short video describes a novel way to understand the long-term fiscal challenge the U.S. faces in light of choices regarding tax revenues, national health care spending, and federal spending on non-health items. It convincingly demonstrates that severe sacrifices are needed along all three dimensions if the country is to regain fiscal balance at reasonable debt levels.
  • Blahous, Charles.  CBO Explodes the Health Care Myth, Hudson Institute, June 30,2009, argues that 2007 CBO long term health projections report substantially understated the contribution of population aging on health spending trends.
  • Centers for Medicare and Medicaid Services, U.S. Department of Health and Human Services. CMS annually issues 10-year health spending projections.
  • Centers for Medicare and Medicaid Services, U.S. Department of Health and Human Services. Projections of National Health Expenditures: Methodology and Model Specification. July 28, 2011.
  • Congressional Budget Office, The Long-Term Outlook for Health Care Spending, November, 2007.
  • Congressional Budget OfficeLong-Term Budget Outlook, June 2010. This report concludes that through 2035, population aging would account for fully 64 percent of the cost growth in the major federal mandatory health programs and Social Security, with excess health cost inflation being a relatively smaller factor. By 2080, health spending is projected to account for 41% of GDP under the baseline scenario and 43% of GDP under the more realistic alternative fiscal scenario (p. 42).
  • The U.S. Healthcare System: Can This Patient Be Saved?” The Global Human Capital Journal, February 24, 2008. Provides assessments of U.S. health system from key experts, including Ian Morrison, Ph.D., healthcare futurist, Dean Harrison, CEO Northwestern Memorial Healthcare; William Novelli, CEO AARP; and Scott P. Serota, CEO BlueCross BlueShield Association.
  • Institute for the FutureWhat could health and health care in the US look like in 2020? This group postulates what health care could be like under 4 alternative scenarios: a) a growth scenario that manifests the results of current trends and conditions, extrapolated forward. This includes both positive and negative growth; b) a discipline scenario in which a core guiding value or purpose is used to organize society and control behavior (e.g., population control); c) a collapse scenario in which major social systems are strained beyond the breaking point, causing system collapse and social disarray; and d) a transformation scenario in which a fundamental reorganization of a society or system signals a break from previous systems (e.g., greater-than-human machine intelligence).