Patient Protection and Affordable Care Act: Effect on Long-Term Federal Budget Outlook Largely Depends on Whether Cost Containment Sustained
Published: 2013-01-31T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: GAO regularly prepares long-term federal budget simulations under different assumptions about broad fiscal policy decisions. GAO's Baseline Extended simulation illustrates the long-term outlook assuming current law at the time the simulation was run is generally continued, while the Alternative simulation illustrates the long-term outlook assuming historical trends and past policy preferences continue. Under either set of assumptions, these simulations show that the federal budget is on an unsustainable fiscal path driven on the spending side by rising health care costs and the aging of the population. PPACA provides for expanded eligibility for Medicaid and federal subsidies to help individuals obtain private health insurance and includes provisions designed to slow the growth of federal health care spending.
GAO was asked to describe the longterm effects of PPACA on the federal fiscal outlook under both its Baseline Extended and Alternative simulations; how changes in assumptions for federal health care cost growth might affect the outlook; and the key drivers of health care cost growth and how the uncertainty associated with each may influence future health care spending. To do this, GAO compared the results of its long-term fiscal simulations from before and after the enactment of PPACA and examined the key factors that contributed to changes in revenue and spending components; reviewed trends in health care cost growth and performed a sensitivity analysis varying rates of excess cost growth; and reviewed literature describing key drivers of health care cost growth and areas of uncertainty related to projections of federal health care costs.
section_title: What GAO Found
paragraphs: The effect of the Patient Protection and Affordable Care Act (PPACA), enacted in March 2010, on the long-term fiscal outlook depends largely on whether elements in PPACA designed to control cost growth are sustained. There was notable improvement in the longer-term outlook after the enactment of PPACA under GAO's Fall 2010 Baseline Extended simulation, which assumes both the expansion of health care coverage and the full implementation and effectiveness of the cost-containment provisions over the entire 75-year simulation period. However, the federal budget remains on an unsustainable path. Further, questions about the implementation and sustainability of these provisions have been raised by the Centers for Medicare & Medicaid Services' Office of the Actuary and others, due in part to challenges in sustaining increased health care productivity. The Fall 2010 Alternative simulation assumed cost containment mechanisms specified in PPACA were phased out over time while the additional costs associated with expanding federal health care coverage remained. Under these assumptions, the long-term outlook worsened slightly compared to the pre-PPACA January 2010 simulation.
Federal health care spending is expected to continue growing faster than the economy. In the near term, this is driven by increasing enrollment in federal health care programs due to the aging of the population and expanded eligibility. Over the longer term, excess cost growth (the extent to which growth of health care spending per capita exceeds growth of income per capita) is a key driver. Slowing the rate of health care cost growth would help put the budget on a more sustainable path. There is general agreement that technological advancement has been the key factor in health care cost growth in the past, along with the effects of expanding health insurance coverage and increasing income, but there is considerable uncertainty about the magnitude of the impact that the different factors will have on future health care cost growth.The effect of the Patient Protection and Affordable Care Act (PPACA), enacted in March 2010, on the long-term fiscal outlook depends largely on whether elements in PPACA designed to control cost growth are sustained. There was notable improvement in the longer-term outlook after the enactment of PPACA under GAO's Fall 2010 Baseline Extended simulation, which assumes both the expansion of health care coverage and the full implementation and effectiveness of the cost-containment provisions over the entire 75-year simulation period. However, the federal budget remains on an unsustainable path. Further, questions about the implementation and sustainability of these provisions have been raised by the Centers for Medicare & Medicaid Services' Office of the Actuary and others, due in part to challenges in sustaining increased health care productivity. The Fall 2010 Alternative simulation assumed cost containment mechanisms specified in PPACA were phased out over time while the additional costs associated with expanding federal health care coverage remained. Under these assumptions, the long-term outlook worsened slightly compared to the pre-PPACA January 2010 simulation.
Federal health care spending is expected to continue growing faster than the economy. In the near term, this is driven by increasing enrollment in federal health care programs due to the aging of the population and expanded eligibility. Over the longer term, excess cost growth (the extent to which growth of health care spending per capita exceeds growth of income per capita) is a key driver. Slowing the rate of health care cost growth would help put the budget on a more sustainable path. There is general agreement that technological advancement has been the key factor in health care cost growth in the past, along with the effects of expanding health insurance coverage and increasing income, but there is considerable uncertainty about the magnitude of the impact that the different factors will have on future health care cost growth.

section_title: Letter
paragraphs: Our long-term federal budget simulations have shown federal debt as a  share of gross domestic product (GDP) continuously increasing over the  long term, which indicates that the budget is on an unsustainable path.  The specific timing of the debt buildup, however, depends on the  assumptions used. We run two simulations based on different  assumptions about broad fiscal policy options. Our Baseline Extended  simulation illustrates the long-term outlook assuming federal laws  (applicable at the time the simulation was run) remain unchanged, while  our Alternative simulation illustrates the long-term fiscal outlook assuming  historical trends and policy preferences continue.
Our fiscal simulations and projections by the Congressional Budget Office  (CBO) and others have shown that the key drivers of the federal  government’s long-term fiscal imbalance on the spending side are rising  health care costs and the aging of the population. Although health care  spending growth recently slowed, spending on federal health care  programs, including Medicare and Medicaid, growing faster than the overall economy as more members of the baby- boom generation become eligible for these federal health benefits and the  cost of caring for each enrollee increases. The number of baby boomers  turning 65 is projected to grow from an average of about 7,600 per day in  2011 to more than 11,000 per day in 2029.
Medicare is a federal health care program for the aged and disabled. Medicaid is a jointly  funded federal-state health care program for certain categories of low-income individuals.
In March 2010, the Patient Protection and Affordable Care Act (PPACA)  was enacted, which makes substantial changes to Medicare and  Medicaid as well as other components of the federal budget that will have  significant implications for the federal government’s fiscal outlook in both  the near and long term. For example, PPACA provides for the expansion  of eligibility in the Medicaid program and federal subsidies to help  individuals obtain private insurance coverage; it also includes provisions  designed to slow the growth of federal health care spending, particularly  for the Medicare program. There are, however, significant uncertainties  surrounding the effects of PPACA on health care spending and other  factors that influence future health care costs more generally, including  how the development and deployment of medical technology, future  policy decisions, and cost and availability of insurance affect growth in  health care spending per capita.
For purposes of this report, major federal health care programs are defined as Medicare,  Medicaid, and the subsidies available to assist individuals to purchase insurance coverage  through the American Health Benefit Exchanges. Federal spending on the Children’s  Health Insurance Program is also included but is considerably lower than these other  health care programs.
Extended and Alternative simulations in the January 2010 Update  (released in March 2010 just before PPACA was enacted) to those in the  Fall 2010 Update (released in November 2010 shortly after the law was  enacted). We also compared the results to those in the Fall 2012 Update  (released in December 2012), which incorporated both the estimates  revised following the U.S. Supreme Court’s June 2012 decision regarding  the expansion of Medicaid to newly eligible populations and the Social  Security and Medicare Trustees (Trustees) and the Centers for Medicare  & Medicaid Services’ (CMS) Office of the Actuary’s (OACT) more recent  estimates for Medicare spending.  While we describe changes to federal  health care spending when relevant to PPACA, we focus on the changes  between our January 2010 and Fall 2010 simulations, since this  minimizes the effects of other legislative or technical changes unrelated to  PPACA on our long-term simulations and can provide a general estimate  of the act’s effects on the long-term fiscal outlook. We compared paths for  the major federal health care programs identified previously as well as  revenue and Social Security, other mandatory, discretionary, and net  interest spending. Because of the aggregate nature of projections used in  our simulations, we cannot completely isolate or quantify either the effects  of PPACA or of specific provisions of the act on the long-term outlook. We  reviewed the underlying data and assumptions from CBO, the Trustees,  and OACT used in our simulations to understand the reasons for any  differences. To assess the reliability of the data from CBO, the Trustees,  and OACT used to develop these simulations, we examined whether the  methodology used to create these projections is clear and transparent  and whether the data are reasonable given the description of the  methodology. We also examined whether the data were presented  consistently in reports and supplementary data and, when possible, were  consistent with others' reporting of similar data. We determined that the  data were sufficiently reliable for our purposes of illustrating the potential  fiscal outcomes under broad sets of different policy assumptions.
To describe how changes in assumptions for federal health care cost  growth might affect the federal government’s long-term fiscal outlook, we  examined the effect of two key assumptions on federal health care  spending: (1) enrollment in the major federal health care programs and  (2) excess cost growth—or the extent to which health care spending per  capita grows faster than the GDP per capita. We performed a sensitivity  analysis by varying assumptions for the rate of excess cost growth in our  simulations. We did not analyze what particular changes to federal health  care policies would produce specific rates of excess cost growth.
To identify the key drivers of health care cost growth and how the  uncertainty associated with each may influence future health care  spending estimates, we reviewed literature on key factors affecting health  care costs, described how uncertainty associated with each factor may  influence health care spending, and when possible, broadly outlined a  range of potential outcomes associated with the uncertainty of each  factor. We did not independently assess the validity of estimates of  uncertainty discussed in the literature. The extent to which we could  quantify the range of possible health care cost growth estimates resulting  from this uncertainty was limited by the availability of existing studies.
We conducted our work from July 2012 to January 2013 in accordance  with all sections of GAO’s Quality Assurance Framework that are relevant  to our objectives. The framework requires that we plan and perform the  engagement to obtain sufficient and appropriate evidence to meet our  stated objectives and to discuss any limitations in our work. We believe  that the information and data obtained, and the analysis conducted,  provide a reasonable basis for any findings and conclusions in this report.
subsections: section_title: Background
paragraphs: PPACA provided for additional health care coverage options for millions  of lower income individuals through the expansion of eligibility for the  Medicaid program and the creation of health insurance exchanges where  eligible individuals can qualify for federal subsidies to purchase private  health insurance coverage.
Medicaid. Medicaid is a joint federal-state program that provides  health care coverage for certain low-income individuals. Under federal  law, states historically have been required to cover certain categories  of individuals under Medicaid (mandatory populations) with the  flexibility to extend coverage to other defined groups (optional  populations). PPACA provides for states to expand Medicaid  coverage to most nonpregnant, nonelderly individuals with income  that does not exceed 133 percent of the federal poverty level (FPL)  beginning no later than January 1, 2014. The federal government will  pay the full cost of covering newly eligible enrollees until 2017 at  which point the federal share will begin to gradually decline to 90  percent by 2020.
American Health Benefit Exchanges. These are marketplaces to be  established by January 2014 to facilitate the purchase of private  insurance coverage. Individuals obtaining insurance through the  exchanges may qualify for federal subsidies (hereafter referred to as  exchange subsidies) in the form of premium tax credits and cost  sharing reductions. In order to qualify for the premium tax credit,  individuals or families must meet certain criteria including income  levels between 100 and 400 percent of the FPL and failing to qualify  for other health care coverage, such as Medicare or Medicaid, or  having access to affordable insurance of minimum value from an  employer. The premium tax credit is refundable meaning that it can  provide benefits to lower-income tax filers with little or no tax liability.
The portion of the tax credit that reduces an individual’s tax liability is categorized as a  reduction in federal revenues and the portion of credits that exceed an individual’s tax  liability is categorized as an increase in outlays.
Individuals who enroll in an exchange plan may also be eligible for  additional cost-sharing subsidies that further reduce the out-of-pocket  amount they would otherwise have to pay when accessing covered  health services.
While these changes, along with other PPACA provisions, are expected  to increase federal health care spending, PPACA also included a number  of provisions that aim to reduce the level of federal health care spending.  For example, PPACA reduced payments both Medicare and Medicaid  make to hospitals that serve a disproportionate share of low-income  patients. This change reflects the expectation that PPACA’s major  coverage expansions will result in significantly fewer uninsured hospital  patients. Also, PPACA reduced estimated Medicare spending through  changes to rates paid to Medicare Advantage organizations—Medicare’s  private plan alternative to the original Medicare fee-for-service—to align  Medicare Advantage payment rates more closely with spending on  Medicare’s fee-for-service program.
In addition, PPACA created a number of cost containment mechanisms  designed to slow future growth of health care spending, such as:
Productivity adjustments. PPACA seeks to restrain health spending  growth by reducing the payment updates for many Medicare services  for productivity gains. This is intended to provide a strong financial  incentive for health providers to enhance productivity, improve  efficiency, or otherwise reduce their costs per service.
Independent Payment Advisory Board (IPAB). PPACA called for the  creation of a 15-member board to make recommendations, with  certain restrictions, for reducing the costs of Medicare when per capita  Medicare growth exceeds specified targets beginning in 2015. These  recommendations are automatically implemented unless overridden  by lawmakers.
PPACA also incorporated certain tax provisions designed to generate  revenue. Beginning in January 2013, PPACA imposed an additional  Medicare Hospital Insurance tax on wages, compensation, and self- employment income in excess of threshold amounts, defined as $200,000  for individuals, $250,000 for spouses filing jointly, and $125,000 for  spouses filing separate returns. PPACA also imposes an excise tax on  high cost employer-sponsored health plans beginning in 2018. Employer- sponsored plans with a benefit value exceeding specified thresholds will  generally be subject to a 40 percent excise tax. levied on insurers but is expected eventually to be passed on to their  customers. CBO, OACT, and other observers expect that the excise tax  will create an incentive for employers to reduce the scope of their health  benefits and, therefore, the demand for health care services.
subsections: section_title: Projections of the Effects of PPACA
paragraphs: These threshold levels are generally $10,200 for individuals and $27,500 for families in  2018, adjusted in 2019 by growth in the Consumer Price Index plus 1 percentage point  and by growth in the Consumer Price Index thereafter.
2010. In these reports, the Trustees, CBO, and OACT all expressed  concerns about whether certain cost-containment mechanisms included  in PPACA can be sustained over the long term. CBO and OACT both  produced alternative projections that assume certain cost-containment  mechanisms are not fully maintained over the long term.
We first incorporated the Trustees’, CBO’s, and OACT’s projections of the  effects of PPACA on federal health care spending in our Fall 2010 update  of the long-term fiscal outlook. The effects of PPACA are primarily seen  through changes to assumptions for the following health care programs:
Medicare. Medicare spending in our Baseline Extended simulation  follows CBO’s baseline projections for the first 10 years, which follow  current law and assume that reductions in Medicare physician  payment rates unrelated to PPACA occur as scheduled; thereafter,  Medicare spending is based on the Trustees’ intermediate  projections.certain cost-containment mechanisms intended to slow the growth of  health care cost enacted in PPACA were sustained over the long  term. In the Alternative simulation, Medicare spending is based on  OACT’s alternative scenario, which assumes that reductions in  Medicare physician rates do not occur as scheduled under current law  and, starting in our Fall 2010 update, that certain cost-containment   Beginning in our Fall 2010 update, we assumed that  mechanisms enacted in PPACA intended to slow the growth of health  care cost begin to phase out after 2019. Our Fall 2010 simulations  also reflect changes in the level of Medicare spending resulting from  other provisions of PPACA, such as reductions to payment rates for  Medicare Advantage organizations.
Medicaid, Children’s Health Insurance Program (CHIP), and  exchange subsidies. In both the January 2010 and Fall 2010 Baseline  Extended simulations, spending for Medicaid and exchange subsidies  follows CBO’s baseline projections for the first 10 years and is then  based on growth in spending for these programs consistent with  CBO’s long-term assumptions for the number and age composition of  enrollees and the Medicare Trustees’ intermediate assumptions for  excess cost growth. Prior to Fall 2010, federal spending for CHIP  was included in our simulations under other mandatory spending.  Starting in Fall 2010, consistent with CBO, we include federal  spending for CHIP along with subsidies for the newly created health  insurance exchanges in a single category with Medicaid. Our Fall  2010 Alternative simulation assumes that provisions in current law  designed to limit the growth in spending on exchange subsidies are  not maintained over the long term.
Several provisions of PPACA affected federal revenue, including an  excise tax on high cost employer-sponsored health plans and increase in  the Medicare Hospital Insurance tax for higher income individuals and  families. While the effects of these provisions are incorporated into our  simulations in the first 10 years, we do not make assumptions about the  composition of revenue over the long term in our simulations. The  Baseline Extended simulation follows CBO’s baseline projections, which  generally reflect current law, for the first 10 years and then holds revenue  constant as a share of GDP. As a result, over the long term, revenue as a  share of GDP is higher in the Baseline Extended than historical averages.  In the Alternative simulation, expiring tax provisions are generally  extended and the alternative minimum tax (AMT) amount is indexed to  inflation. Revenue in the Alternative simulation is then held at the 40-year  historical average. This assumption implies that, consistent with past  experience, legislation will be enacted to offset some of the increases in  revenue scheduled in current law.
Both simulations follow CBO’s projections for Social Security for the first  10 years and the Trustees’ intermediate projections thereafter. See  appendix I for more information on the assumptions used in the  simulations and a description of technical changes that were made for  this report.
section_title: Effect of PPACA on the Long-Term Fiscal Outlook Depends on Whether Cost- Containment Mechanisms are Sustained
paragraphs: The effect of PPACA on the long-term fiscal outlook depends largely on  whether elements designed to control cost growth are sustained. Overall,  there was notable improvement in the longer-term outlook after the  enactment of PPACA under our Fall 2010 Baseline Extended simulation,  which, consistent with federal law at the time the simulation was run,  assumed the full implementation and effectiveness of the cost- containment provisions over the entire 75-year simulation period. In  contrast, the long-term outlook in the Fall 2010 Alternative simulation  worsened slightly compared to our January 2010 simulation. This is  largely due to the fact that cost-containment mechanisms specified in  PPACA are assumed to phase out over time while the additional costs  associated with expanding federal health care coverage remain.
Figure 1 shows that while the steps taken in PPACA to restrain spending  on the federal health programs were significant, they were not sufficient to  prevent an unsustainable increase in debt held by the public even under  the more optimistic assumptions in our Baseline Extended simulation.  The net effect of changes to spending and revenue on the federal budget  were relatively small in the first few decades in both simulations, and the  improvements in the Baseline Extended simulations from January 2010 to  Fall 2010 do not significantly slow the growth in debt held by the public  until the outyears. Debt as a share of GDP still reached the historical high  of 109 percent by 2036 in the Fall 2010 Baseline Extended simulation— just 1 year later than it did in the January 2010 Baseline Extended  simulation. There was no change in the date when debt held by the public  reached the historic high from the January 2010 Alternative simulation to  the Fall 2010 Alternative simulation.
The effect of PPACA on the long-term fiscal outlook is seen largely  through changes in federal spending on major federal health care  programs. Figure 2 shows that federal spending on Medicaid, CHIP, and  exchange subsidies increased in the Baseline Extended simulation,  reflecting expanded eligibility and coverage. By 2035, spending on  Medicaid, CHIP, and exchange subsidies in the Fall 2010 Baseline  Extended simulation equaled 3.3 percent of GDP—0.7 percentage points  higher than Medicaid spending in the January 2010 Baseline Extended  simulation—and continued to grow thereafter.
Spending on Medicare declined substantially in our Fall 2010 Baseline  Extended simulation, reflecting the assumption of full implementation and  effectiveness of the cost-containment mechanisms in PPACA. Spending  on Medicare, for example, decreased 1.5 percentage points from 6.2  percent of GDP in 2035 in the simulations run before PPACA was  enacted to 4.7 percent in the simulations run immediately after  enactment. The difference between our January 2010 and Fall 2010  simulations widens in subsequent decades as the effects of slower  growth in Medicare spending compound over time. Given the large role of  Medicare spending in the federal budget, slowing growth of spending on  the program would reduce, though not eliminate, the pressure federal  health care spending is expected to put on the rest of the federal budget  in coming decades.
The Trustees, CBO, and OACT have questioned whether the cost- containment mechanisms enacted in PPACA can be sustained over the  long term, due in part to the challenges in sustaining increases in health  care productivity. Prior to PPACA, payment updates for many Medicare  services were based on the prices of goods and services, such as  medical equipment and labor, needed to serve patients. PPACA required  that these payment updates be reduced by a productivity adjustment,  defined as a 10-year average of changes in annual economy-wide private  productivity. This is expected to provide a strong financial incentive for  health providers to enhance productivity, improve efficiency, or otherwise  reduce their costs per service. The lower payment rate updates to most  categories of Medicare providers specified under PPACA have only  begun to be implemented. It remains unclear what actions providers will  take to improve their productivity and reduce unnecessary expenditures in  response to these lower payment rate updates. According to OACT,  however, health care productivity gains have historically been small due  to such factors as the labor-intensive nature of the industry and the  individual customization of treatments in many cases. Consequently,  OACT said this makes it unlikely that actual health provider productivity  will be equal to the economy as a whole over sustained periods.
PPACA created a number of research and development initiatives––such  as bundling Medicare payments for services that patients receive across  a single episode of care and establishing the Medicare Shared Savings  Program through which accountable care organizations can better  manage and coordinate care across different settings—that have the  potential to transform the health care payment and delivery system in  ways that reduce federal health care spending consistent with the  productivity adjustments. However, these initiatives are only just  beginning to be tested. Accordingly, it is too early to know which will result  in lasting changes and what effect they will have on future federal  spending.
The role of IPAB in controlling cost growth is assumed to be limited under  current law projections given that the productivity adjustments and other  provisions contained in PPACA are estimated by the Trustees to keep  Medicare spending below the targeted growth rate in all but 1 year.  Absent the full and effective implementation of productivity adjustments,  IPAB’s task would be more daunting. It is not possible to predict at this  time, however, what changes IPAB will propose to keep Medicare  spending within the specified target and what the disposition of the  recommendations will be.
In our Fall 2010 Alternative simulation based on the CMS OACT’s alternative scenario,  physician payment rates grew with inflation (using the Medicare Economic Index), as  opposed to the 0 percent physician fee schedule update assumed in January 2010, which  resulted in higher spending. This offset some of the reductions in spending resulting from  the cost containment mechanisms enacted in PPACA. subsidies.exchange subsidies equaled 3.5 percent of GDP in 2035—or roughly 0.9  percentage points higher than in the January 2010 Alternative simulation.  As a result, total federal health care spending was higher in the Fall 2010  Alternative simulation than in the January 2010 simulation.
section_title: Health Care Spending in Our Long-Term Simulations Largely Depends on Assumptions about Enrollment and Excess Cost Growth
paragraphs: Our simulations provided two scenarios based on broad sets of  assumptions about health care spending and other components of federal  spending and revenue. Long-term projections, however, are inherently  uncertain and future health care costs in particular are difficult to  estimate. This uncertainty, which predates the enactment of PPACA,  increases the further the model looks out into the future. While some of  this uncertainty is related to the implementation and effectiveness of  provisions of PPACA, there is also broader uncertainty about the future  underlying rate of health care cost growth before cost-containment  mechanisms are applied. The projected rate of growth largely depends on  the assumptions used. To examine these assumptions, we divided  spending growth into two types of drivers: (1) enrollment in the major  federal health care programs and (2) growth in health care spending per  capita. While both have contributed to the growth in federal health care  spending over the past several decades, their relative role in explaining  rising future federal health care spending differs over time.
subsections: section_title: Enrollment is a Key Driver of Federal Health Care Spending Growth in the Near Term
paragraphs: Spending on both Medicare and Medicaid has increased in the past  several decades due in part to a steady increase in the number of  enrollees. In calendar year 1970, approximately 9 percent of the U.S.  population was enrolled in Medicare. As the U.S. population has aged  and more people have enrolled in the program, this increased to  approximately 15 percent in calendar year 2011. Medicaid enrollment,  while more volatile than Medicare enrollment, has also generally  increased as states have decided to expand eligibility and economic  recessions have increased the number of people eligible. For example, in  fiscal year 1970, approximately 7 percent of the U.S. population was  enrolled in Medicaid. This increased to approximately 17 percent in fiscal  year 2010 (the most recent year historical data is available). However,  there have been periods when enrollment did not grow. For example, in  the 1990’s, strong economic growth and the move from Aid to Families  With Dependent Children to the Temporary Assistance for Needy  Families block grant, which was designed to help needy families reduce  their dependence on federal assistance, helped keep enrollment steady  at approximately 12 percent of the population between fiscal years 1995  and 2000.
Enrollment in the major federal health care programs is expected to  continue to increase in the near term due both to the aging of the U.S.  population and to expanded eligibility. Consequently, increasing  enrollment is expected to be the most important driver of federal health  care spending over the next couple of decades. Future enrollment trends  for Medicare, particularly in the near term, are reasonably clear. The  Trustees expect a large increase in enrollment in Medicare between 2010  and 2030 as the baby boom generation reaches age 65 and are eligible  to receive benefits. As figure 6 shows, the number of baby boomers  turning 65 is projected to grow in coming years from an average of about  7,600 per day in 2011 to more than 11,000 per day in 2029.
Future enrollment patterns for Medicaid and the exchange subsidies are  less clear due both to the uncertainty about future policy changes and to  other factors such as income growth that affect individuals’ eligibility.
Medicaid. In its March 2012 projections, which assumed states will  expand Medicaid coverage to all eligible individuals as provided in  PPACA, CBO estimated that enrollment in Medicaid would increase  from roughly 54 million people in fiscal year 2011 (or roughly 17  percent of the population) to 75 million by fiscal year 2022 (or roughly  22 percent of the population). This includes roughly 17 million  nonelderly people projected to be enrolled in the program in 2022 as a  result of expanded coverage provided by PPACA. The people who  will be newly eligible for Medicaid under PPACA consist primarily of  nonelderly adults with low income along with a smaller number of  children from low income households. According to OACT, both  groups are expected to be less costly to cover on a per enrollee basis  than current enrollees. In March 2012, CBO estimated that expanding  Medicaid coverage and CHIP coverage as provided for in PPACA  would increase federal spending by $136 billion in 2022.
CBO has since updated its estimates to reflect the June 2012 U.S.  Supreme Court decision on PPACA. PPACA, as enacted, required  states to extend Medicaid to most nonpregnant nonelderly individuals up  to 133 percent of the FPL and provided states with an enhanced federal  match for this newly eligible population. States that fail to cover  mandatory Medicaid populations are at risk of losing federal match for  their entire Medicaid program. The Supreme Court subsequently ruled  that states that choose not to expand Medicaid eligibility to these newly  eligible individuals will only be subject to a penalty of forgoing the  enhanced federal matching funds associated with covering this population  rather than foregoing federal matching funds for their entire program.  States therefore have the option of deciding whether to expand Medicaid  coverage to newly eligible populations as provided by PPACA. CBO  notes that what states will decide to do regarding the Medicaid expansion  under PPACA is highly uncertain. States face both financial incentives  and disincentives to participate in the Medicaid expansion. On the one  hand, the federal government will cover a large share of the costs of the  expansion. On the other hand, states would ultimately have to bear some  costs during a period when their budgets are already under pressure, in  part from the rising costs of the existing Medicaid program.
Exchange subsidies. In projections prepared prior to the Supreme  Court ruling, CBO estimated the exchanges would subsidize health  insurance coverage for 22 million nonelderly people by fiscal year  2022 and increase federal spending by $127 billion in that year.  Following the Supreme Court ruling, CBO revised this estimate  anticipating that a portion of the people will not be eligible for Medicaid  as a result of states choosing not to expand their Medicaid programs  and will instead be eligible for federal subsidies for coverage offered  through the exchanges. As a result, CBO increased its estimates of  the cost of exchange subsidies. However, as noted earlier, it remains  uncertain how the states will respond to the Supreme Court’s ruling.  Further, CBO notes some people will find the exchange subsidies less  attractive than Medicaid because of the higher out-of-pocket costs  they will face in the exchanges. There is also uncertainty about the  extent to which private employers might choose to drop health  insurance coverage and shift workers to the exchanges.
Spending on major federal health programs is affected not just by the  number of enrollees but also by the age composition and health status of  the enrollees. Elderly individuals, for example, typically have higher health  care costs than younger individuals and very elderly individuals, those 85  or older, typically have the highest costs. For Medicare enrollees 85 or  older, spending in 2008 was more than $13,000 per enrollee compared to  about $7,600 for enrollees ages 65 to 74. Similarly, Medicaid’s spending  varies considerably among different type of enrollees. Children and adults  under the age of 65 account for almost 75 percent of Medicaid’s  enrollees, but have much lower per capita costs than the aged (those 65  or older) or disabled. For example, in fiscal year 2010, Medicaid spent  approximately $3,000 per child and $4,000 per adult under age 65,  compared to approximately $15,000 and $17,000, for each aged  beneficiary and each disabled beneficiary, respectively. Medicaid already  has a large role in funding long-term care, such as nursing homes, for  aged persons. The increase in the number of people 85 or older in the  next 10 years is expected to have a major effect on long-term care  spending for Medicaid. As such, a key driver of federal spending for both  Medicare and Medicaid is the aging of the population. Enrollment from  this population did not change as a result of PPACA.
section_title: Growth in Health Care Spending Per Capita is a Key Driver of Federal Health Care Spending Over the Long Term
paragraphs: The share of the federal budget devoted to Medicare and Medicaid has  increased over the past several decades due not only to increases in  enrollment but also due to increases in health care spending per enrollee.  The extent to which the annual growth rate of health care spending per  capita exceeds the annual growth rate of potential GDP per capita  adjusted for demographic characteristics, is referred to as excess cost  growth. Over the last 35 years, excess cost growth averaged around 2  percent but has fluctuated during this time period. Excess cost growth  slowed for Medicare, for example, after the introduction of a prospective  payment system in fiscal year 1984 in which Medicare pays a  predetermined rate for each hospital admission—rather than simply  reimbursing providers for costs, which provides little incentive for  efficiency. Excess cost growth also slowed in the 1990s as enrollment  increased in managed care plans. However, it is not clear to what extent  these slowdowns represent one-time downward shifts in health care costs  or more permanent changes in the underlying growth rate. Overall excess  cost growth in the United States is thought to have returned closer to the  historical average in the 2000s.
Excess cost growth leads to an ever-growing share of the nation’s income  being spent on health care, crowding out spending on all other goods and  services. Going forward, CBO and the Trustees both assume that excess  cost growth will decrease over time because of the financial pressure  health care spending is putting on the federal government, states,  businesses, and households. How and when this transition takes place,  however, is highly uncertain. Figure 7 shows that varying the excess cost  growth assumption in our simulations dramatically alters the share of  national income needed to fund federal health care spending. Under the  standard set of assumptions for health care spending in the Baseline  Extended simulation, excess cost growth averages 0.2 percentage points  for Medicare and 0.8 percentage points for Medicaid, CHIP, and  exchange subsidies over the long term. Under these assumptions,  spending on these programs would rise from less than 5 percent of GDP  in 2012 to more than 9 percent in 2050. If excess cost growth averaged 2  percent per year after 2022—the average rate between 1975 and 2010— federal health spending in our Baseline Extended simulation would rise  quickly and would account for more than 13 percent of the entire U.S.  economy by 2050.
Even with lower assumptions about excess cost growth, a growing share  of national income would be needed to fund federal health programs.  Under the 0-percent excess cost growth scenario, spending on Medicare,  Medicaid, CHIP, and exchange subsidies would continue to grow as a  share of GDP due to the aging of the population and other enrollment and  demographic trends described earlier. In 2050, spending on the major  federal health care programs would be 8 percent of GDP and gradually  increase thereafter. At the end of the 75-year simulation period, spending  on Medicare, Medicaid, CHIP, and exchange subsidies in the 0-percent  excess cost growth scenario would be higher than at the beginning of the  scenario in fiscal year 2022, but still below the levels shown in our  standard Baseline Extended and Alternative simulations.
Figure 8 shows that slowing the rate of excess cost growth could slow the  buildup of debt held by the public considerably and help put the budget on  a more sustainable path. Assuming revenue and nonhealth spending  follow the assumptions in the Baseline Extended simulation and excess  cost growth for health care averages 2 percentage points each year, debt  held by the public would be more than 170 percent of GDP in 2050.  Assuming 0 percent excess cost growth after 2022—an outcome that has  not been sustained for any extended length of time over the past several  decades—debt held by the public would be roughly 91 percent of GDP in  2050 in the Baseline Extended simulation. Debt held by the public would  continue to slowly increase thereafter largely because of the interest  costs of financing the federal government’s accumulated debt and  increasing enrollment in federal health programs.
Figure 8 also shows that slowing health care cost growth is insufficient to  close the imbalance between spending and revenue in the Alternative  simulation in the next few decades. In this simulation, revenue and  spending follow historic trends and past policy preferences. Even  assuming 0 percent excess cost growth after 2022, debt held by the  public rises steeply in the Alternative simulation, reaching more than 100  percent of GDP (or the size of the total economy) by 2025, and continuing  to grow at a rapid rate thereafter. This demonstrates that significant policy  changes beyond those designed to control health care cost growth would  need to be taken in the near term to put federal debt on a more  sustainable path.
Simulations based on broad assumptions about future excess cost growth  such as these are helpful for illustrating how different rates of growth in  spending per capita would affect future federal spending on health care.  However, the simulations do not provide insight into the underlying factors  driving growth in health care cost per capita. The major federal health  care programs are highly integrated with the rest of the health care  system and influenced not only by policies and laws, but also by future  demographic and economic trends; the development and deployment of  medical technology; the cost and availability of insurance; and the  responses of health care providers, consumers, and policymakers to  these trends. As policymakers consider how to put the federal  government on a more sustainable path, it will be important to understand  what the specific factors driving cost growth are, how they are  interrelated, and how changes in these factors could affect federal health  care spending.
section_title: Technological Change Has Been the Largest Driver of Health Care Cost Growth, and with Health Insurance Coverage and Increasing Income, is Likely the Largest Source of Uncertainty for Health Care Cost Projections
subsections: section_title: Technological Change Accounts for about 50 Percent of Health Care Cost Growth
paragraphs: A growing U.S. population directly increases overall health care spending;  however, the causes of rising health care cost per capita are more difficult  to identify. Per capita health care spending grew at an average of 4.9  percent per year between 1965 and 2005, while per capita GDP grew at  an average of 2.1 percent per year. There is general agreement among  researchers about the factors that drive health care cost growth and the  relative size of influence of this growth, although each factor has a unique  mechanism to affect health care costs, and therefore, a different relative  influence on health care cost growth (see fig. 9).
Technological change (36 to 65 percent): Technological change  affecting health care cost growth may take many forms. CBO defines  technological advances as changes in clinical practice that enhance the  ability of providers to diagnose, treat, or prevent health problems.  Examples of technological advances include new drugs, devices,  procedures, and therapies, as well as new applications of existing  technologies. While not all new technologies increase health care costs,  technological change as a whole has been the dominant cause of  increases in health care spending.
The effect of technological change on health care costs may depend, in  part, on the type of treatment to which the new technology is applied.  Cutler describes the following classes of treatment and their relative  costs:
Nontreatment applies to diseases that cannot be treated, such as  end-stage cancers, and thus have a relatively low cost of medical  care.
Disease management refers to halfway technologies that can improve  quality of life when cure or prevention is not possible. Disease  management, such as dialysis for end-stage renal disease, is often  very expensive.
Prevention and cures for disease may have low marginal costs when  they are available; however, preventative therapies are often provided  to an entire population, and to the extent that new cures are more  effective and cheaper than older treatments, demand for new cures  may increase significantly. Thus, even when the unit price of new  preventative therapies and cures are low, large quantities provided  may increase overall spending for these treatments.
In general, a technological change that enables providers to treat a  previously untreatable disease will increase health care spending, while  expanding disease management or shifting disease management to  prevention or cure can lead to either increased or decreased health care  spending. However, the introduction of new treatments and technologies  may result in increased health care spending due to the possibility that  health complications may arise from a new treatment, or that patients  survive one disease long enough and eventually are diagnosed with an  additional disease with additional treatment cost.
It should be noted that a complete assessment of health care spending  for new technologies should also consider the value, often measured by  improved health functioning; increased life expectancy; or improved  economic productivity produced by those technologies. For example,  Cutler and McClellan found that increases in health care costs due to  technological changes in the treatments for heart attacks, low-birthweight  infants, depression, and cataracts was more than offset by increased life  expectancy and improved productivity made possible by improved  health. They also concluded that the value of increased longevity per  person between 1950 and 1990 was larger than the increase in per capita  health care spending over the same period.
Chandra and Skinner assess technological change by categorizing  innovations based on their health care productivity, or the improvement in  health outcomes, such as longevity or health functioning, per dollar  increase in cost. The first category includes highly productive  treatments, which may be inexpensive, such as aspirin and beta-blockers,  or expensive, such as anti-retroviral drugs for treating people with  HIV/AIDS. The second category includes treatments with substantial  benefits for some patients, but a diminished benefit for others. For  example, heart attack patients treated within 12 hours of a heart attack  receive large benefits from angioplasty and placement of a stent;  however, the benefits for patients with stable angina, chest pain or  discomfort, are less clear. The final category includes treatments with little  benefit or scientific evidence. Treatments in this category are more likely  to be focused on treatment for chronic conditions. Chandra and Skinner  find that much of the improvement in health is generated by treatments in  the first category, while much of the cost is generated by treatments in the  third category, and therefore conclude that health insurance interacts with  technological change to drive health care cost growth as health insurance  provides access to new technologies for patients who may experience  little health benefit.
Increases in income (5 to 36 percent): As personal income increases,  people demand more and better goods and services, including health  care. This means that holding other factors constant, as higher personal  income increases the quantity and quality of care demanded, overall  health care spending increases as well. GDP is a good indicator of the  effect of increasing income on health care spending. When GDP is  growing, many Americans experience increases in income and will  demand more health care services. When the rate of GDP growth  declines, such as during the recent recession, health care spending  growth may slow down; however, the magnitude of impact on health care  spending may be smaller than compared to periods of higher GDP growth  due to the persistent relationship of increasing income leading to the  production of new technologies. To add further context to this  relationship, the income elasticity for health care services, that is the  magnitude of the association between income and demand for health  care services, may vary across households and over time. While there  are a variety of assessments of the effect of income on health care  expenditures, historical data from the United States suggest that for a 10  percent increase in income, health expenditures will rise between 2 and 4  percent. Incorporating data from other countries to estimate the  relationship at the national level and including the effect of other factors  affecting health spending that are correlated with real per capita GDP  raises the increase in health care expenditures to about 14 percent.
Health insurance expansions (10 to 13 percent): The expansion of  health insurance increases health care cost per capita as people demand  more health care when they are better insured. Health insurance has  expanded in two ways: (1) by covering an increasing share of the  population and (2) by covering each person more completely. Both of  these pathways decrease the out-of-pocket expenses that beneficiaries  pay through deductibles and cost-sharing, which have declined as a  share of overall health care spending.
These two pathways help explain how health care costs may be affected  when considering different types of health insurance. A recent study  found that having Medicaid insurance in Oregon increased the likelihood of any hospitalization by 30 percent compared to having no insurance.Older research from the Rand health insurance experiment suggests that  total per capita expenditures increased by about 30 percent for  beneficiaries receiving free care compared to those in a plan similar to  current high-deductable insurance plans.
Furthermore, the relative comprehensiveness of coverage and out-of- pocket expenses differs by insurer category, such as a private insurer,  Medicare, or Medicaid. Therefore, health care spending may increase  when people switch to a more comprehensive type of health insurance  coverage, such as switching from Medicaid to private health insurance.
Health care price inflation (10 to 19 percent): Health care price inflation  contributes to health care cost growth; however, the precise impact of  health care price inflation on overall health care cost growth is not known.  Unlike many markets, prices in the health care market are difficult for  consumers to discern and therefore, infrequently used to determine which  provider to see or which service to undergo, when options are available.  While there may not be a strong or direct influence from competition on  price inflation, there are indirect mechanisms in both the public and  private health insurance markets. In the private health insurance market,  some consumers comparison shop for health insurance plans—or  employers comparison shop on their behalf—and insurance plans use  contracts with providers to restrict the prices charged for services  provided. The extent to which this mechanism limits cost growth varies by  insurance plan type and the incentives each plan type imposes to limit  health care costs. For example, fee-for-service plans generally pay  providers a set amount to provide a specific service and therefore provide  little or no incentive to limit costs; however, plans offered by health  maintenance organizations may limit health care costs by encouraging  the efficient provision of health care services through mechanisms such  as capitated payments and utilization review, as well as through contracts  with low-cost providers or those offering discounted rates. In the market  for public health insurance, various strategies by federal and state  governments to restrict inflation have been used over time, including state  certificate of need requirements and prospective payment systems for  Medicare services.
Increases in administrative expenses (7 to 13 percent): The cost of  administering health care has several sources, and has proven difficult to  identify. Despite the difficulty in estimating administrative expenses,  economists generally agree that they contribute to health care cost  growth. Increases in administrative expenses may be due to the more  complex and changing structure of the insurer and provider relationship.  As a result, increased effort and new technology to deal with coding and  filing claims, billing, and maintaining medical records may have increased  administrative expenses.
Aging (2 to 7 percent): The relative aging of the U.S. population  contributes to increasing health care costs. An increasing share of the  population that is older increases average health care costs per capita  due to the additional medical care older Americans generally require.  While an aging U.S. population has increased health care costs overall,  the contribution of aging has been relatively small.
Changes in the amount of defensive medicine and supplier-induced  demand: Because the clinical value of a medical service may vary by  patient and categorization of a service as defensive or supplier-induced  depends on intent, it is difficult to identify these services. Defensive  medicine and supplier-induced demand were either not included or found  to be zero in the macro-studies determining the relative influence of  various factors on health care cost growth presented in figure 9; however,  several studies on specific procedures show that they do contribute to  increasing health care costs. CBO reported that enacting certain tort  reform proposals designed to limit defensive medicine would have  reduced national health care spending by $11 billion in 2009, or 0.5  percent of health care expenditures, through decreased medical liability  insurance premiums and lower utilization of health care services. While  several studies show evidence of supplier-induced demand for particular  services, including imaging services and procedures provided at  physician-owned specialty hospitals, no study characterizes the overall  impact of supplier-induced demand on health care cost growth.
Many of the factors listed previously may not affect health care cost  growth independently; instead they have combined effects through  interactions in the health care market. For example, researchers believe  that the influence of technological change on health care spending has  been facilitated by higher historical levels of fee-for-service insurance,  which incorporates less utilization review compared to managed care,  and by periods of increasing per capita income which is associated with  increased demand for new technologies.
section_title: Key Uncertainties for Health Care Cost Projections are Technological Change, Increases in Income, and Health Insurance Expansions
paragraphs: Although there is some consensus among researchers about which  factors drive health care cost growth, there is considerable uncertainty  about the magnitude of impact of each factor on future health care cost  growth. Population growth is relatively predictable and barring a  pandemic or similar catastrophic event, is not likely to contribute much  uncertainty to health care cost projections. More uncertainty is likely to be  associated with factors influencing health care spending per capita,  particularly technological change, given its varied pathways of influence  on health care cost growth. The following is our analysis of the relative  uncertainty associated with factors influencing health care spending per  capita.
Technological change: While analysis of the number and types of  medical technologies that are expected to be introduced in the next few  years may yield some information about the range of possible impact of  technology on health care spending per capita, the large number of  sources of technological change makes this cost driver the most  uncertain for estimating future health care costs. Much of this uncertainty  is due to the unknown costs and effectiveness of changes in clinical  practice—such as the introduction of new pharmaceutical drugs, medical  devices, diagnostic tests, and procedures to treat disease—while the  development and incorporation of nonclinical technologies—such as  health information technology—also contribute to the uncertainty of future  health care costs. Moreover, the development of new medical technology  is influenced by future health insurance expansions and increases in  income, further reducing the predictability of the impact of technological  change on future health care costs.
Increases in income: Based on expectations of future GDP growth and  changes in the distribution of income among Americans, the influence of  increases in income on health care cost growth is somewhat uncertain in  the near future and likely to increase in uncertainty in the long-run.  Because increasing personal income generally increases demand for  health care services, the extent to which future increases in personal  income will affect health care cost growth can be approximated using  expectations of future growth in aggregate income, as measured by GDP,  and changes in how that income is distributed. If a given increase in GDP  is associated with an increase in income for a larger proportion of  Americans, then the increase in GDP will generate a larger increase in  health care cost growth. Together, the expected volatility in future GDP  growth and possible changes in the distribution of income among  Americans leads us to believe that there is some uncertainty surrounding  the size of the impact that increases in income may have on future health  care cost growth, and that the uncertainty is larger for the more distant  future.
Health insurance expansions: The expansion of health insurance may  have some associated uncertainty for future health care costs per capita.  This uncertainty is likely to have a lower bound of maintaining current  insurance levels and an upper bound based on increasing both the  number of insured Americans and the depth of coverage for each person.  While future scenarios with decreasing insurance levels are possible,  current policy debate is focused on increasing insurance levels. Possible  increases in health insurance include the expansion of private insurance  and Medicaid to cover the approximately 49 million Americans uninsured  as of 2011, which would remove barriers to health care and increase  health care spending.
Health care price inflation: Changes in the structure of payment models  and health insurance plan types will help limit health care price inflation,  likely resulting in relatively little uncertainty in the amount of future health  care cost growth caused by health care price inflation. Health care prices  have been increasing steadily between 3 and 5 percent annually in recent  decades. While some factors, such as consolidation of providers and  integration of provider types, can reinforce price inflation, insurance plan  types and insurance models have also been evolving to incorporate new  methods of restraining health care cost growth. The trend of shifting  toward more capitated payment, rather than fee-for-service, may  continue as new capitated payment models are introduced and more  beneficiaries switch to managed care health plans. In addition, the  introduction of groups of providers organized into accountable care  organizations may also restrain health care cost growth through payment  models designed to promote quality care and coordinate care.
Increases in administrative expenses: While it is difficult to assess the  uncertainty associated with administrative expenses, it is clear that  administrative expenses represent a relatively small portion of overall  health care spending, and thus are likely to impose a relatively small  amount of uncertainty on health care cost projections. The largest near- term change in administrative expenses is likely to be from increased use  of electronic medical records, which may have large initial implementation  costs, but also may decrease administrative expenses over the long-term.
Aging: Similar to population growth, the aging of the U.S. population is  relatively predictable; therefore, aging is not likely to produce much  uncertainty for long-term health care projections. Changes in the age  profile of the United States may affect health costs per capita through  relatively unlikely events such as a pandemic or other catastrophic event,  or a major technological breakthrough that significantly affects life  expectancy.
Changes in the amount of defensive medicine: Because it is difficult to  separate health care services provided due to defensive medicine from  those that would have been otherwise provided, it may be also somewhat  difficult to affect change on the influence of these factors on health care  spending. There are legislative proposals to limit the ability of individuals  to bring medical malpractice actions, which are designed to limit  defensive medicine spending; however, the uncertainty associated with  health care spending due to these factors is likely to be small.
Changes in the amount of supplier-induced demand: It is also difficult  to identify services provided due to supplier-induced demand, and  therefore difficult to estimate the uncertainty associated with supplier- induced demand. However, some changes in supplier-induced demand  may impact future health care cost growth. For example, PPACA’s  limiting of the expansion of physician-owned hospitals, and increased  use of prospective and bundled payments may improve productivity and  limit supplier-induced demand because the payment structure gives  providers an incentive to find ways to treat patients more efficiently.
Increases in direct-to-consumer advertising and consumer  information: Uncertainty associated with increases in direct-to-consumer  advertising and consumer information is relatively unknown as the  phenomenon is quite new and its impact on future health care cost growth  depends on many factors, including advertising regulations and physician  attitudes toward patient requests.
section_title: Concluding Observations
paragraphs: Comparing the results of our simulations before and after the enactment  of PPACA helps to illustrate the important role that efforts to slow the  growth in health care spending have in improving the long-term fiscal  outlook. These efforts will require a sustained commitment and  understanding of the key factors affecting health care cost and how they  interrelate. Reducing health care cost growth alone, however, is not  sufficient to put the federal budget on a sustainable path. Even in  simulations assuming health care cost growth can be constrained for an  extended period, our simulations show debt held by the public rising as a  share of GDP over time, particularly assuming historical trends and policy  preferences for revenue and other spending continue. Therefore, more  needs to be done to change the fiscal path. This will likely require difficult  decisions about both federal spending and revenue.
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If you or your staff have any questions about this report, please contact  Susan J. Irving at (202) 512-6806 or irvings@gao.gov, or James C.  Cosgrove at (202) 512-7114 or cosgrovej@gao.gov. Contact points for  our Offices of Congressional Relations and Public Affairs may be found  on the last page of this report. GAO staff who made major contributions to  this report are listed in appendix III.
section_title: Appendix I: Key Assumptions and Technical Changes in Our Federal Simulations for this Report
paragraphs: We run two simulations showing federal deficits and debt under different  sets of policy assumptions. Our Baseline Extended simulation illustrates  the long-term outlook assuming current law is generally continued, while  the Alternative simulation illustrates the long-term outlook assuming  historical trends and policy preferences are continued.
In the Baseline Extended simulation, we closely follow the Congressional  Budget Office’s (CBO) 10-year baseline budget projections, which  incorporate the assumption that current law remains in effect. Revenue  and spending other than interest on the debt and large mandatory  programs such as Social Security and Medicare are then held constant as  a share of gross domestic product (GDP). Under current law, revenue as  a share of GDP would increase over time because of several factors,  including the expiration of tax provisions; “real bracket creep,” wherein the  growth of real income causes a greater proportion of taxpayers’ income to  be taxed in higher brackets and be subject to the alternative minimum tax  (AMT); and increased retirement income subject to taxation upon  withdrawal (i.e., deferred taxes). However, history suggests that  legislation will be enacted to offset such increases in revenue. In the  Alternative simulation, expiring tax provisions are extended and the AMT  exemption amount is indexed to inflation in the near term. Discretionary  spending in the Alternative simulation grows with the economy in the first  10 years unless specific limits are specified in law. Over the long term,  discretionary spending and revenue are held constant at or near their 40- year historical average share of GDP.
Long-term spending on Social Security and Medicare in the Baseline  Extended simulation is based on the Social Security and Medicare  Trustees (Trustees) intermediate projections, which follow current law.  Spending on Medicare in the Alternative simulation for all years is based  on the Centers for Medicare & Medicaid Services’ Office of the Actuary’s  (OACT) illustrative alternative projections, which deviate from current law.  In these projections, for example, Medicare physician payment rate  updates are adjusted to reflect the fact that in most years, Congress has  acted to override reductions that would occur under current law. In both  simulations, we assume that Social Security and Medicare benefits will  continue to be paid even after the Federal Old-Age and Survivors  Insurance and Federal Disability Insurance trust funds and the Federal  Hospital Insurance and Federal Supplementary Medical Insurance trust  funds are exhausted.
Outlays for Medicaid, the Children’s Health Insurance Program (CHIP),  and federal exchange subsidies are based on CBO’s most recent 10-year  baseline in both of the simulations. Thereafter, growth in spending in our  Baseline Extended simulations is consistent with CBO’s most recent long- term assumptions for the number and age composition of enrollees and  the Medicare Trustees’ intermediate assumptions for excess cost growth.  The excess cost growth assumption in our January 2010 Alternative  simulation is also consistent with the Trustees’ intermediate assumptions.  In our Fall 2010 Alternative simulation, excess cost growth is consistent  with OACT’s alternative scenario.
We regularly update these simulations as new data from CBO, the  Trustees, and OACT become available. In recent years, we have updated  our simulations twice a year: in the spring and in the fall. With each  update, we also revisit the assumptions used in our model and update  them to reflect legislative or technical changes, as needed. For example,  after the enactment of the Patient Protection and Affordable Care Act  (PPACA), consistent with CBO, we included federal spending for CHIP  and federal exchange subsidies in the same category with Medicaid.
To facilitate comparisons between different sets of simulations over time,  we made technical changes to our January 2010 and Fall 2010  simulations. The key changes are described below.  1.  GDP in our January 2010 and Fall 2010 simulations was originally  determined by growth in the labor force, capital stock, and total factor  productivity after the first 10 years, and projections of Social Security  spending were adjusted accordingly. Beginning with the Fall 2011  update, our GDP growth assumption was changed to match the  Trustees’ intermediate assumptions over the long term. This GDP  growth assumption is more consistent with the growth in labor force,  wages, and other factors underlying the Trustees’ Social Security and  Medicare projections used in our simulations. We revised the GDP  assumption in our January 2010 and Fall 2010 simulations to be  consistent with this approach. Specifically, in this report, real GDP  growth in the January 2010 and Fall 2010 simulations is based on the  Trustees’ 2009 and 2010 reports, respectively, and averages 2.1  percent over the long term in both sets of simulations. This is up from  the average of 1.9 percent in our original January 2010 simulations  and the same average real GDP growth in the original Fall 2010  simulations.  2.  Prior to our Fall 2011 update, we adjusted the Trustees’ intermediate  projections for Social Security spending in our simulations to reflect  wage growth implied in our simulations. After we made the change to  our GDP assumption described above, it was no longer necessary to  make adjustments to the Trustees’ Social Security projections.  Therefore, in this report, Social Security spending in the January 2010  and Fall 2010 simulations is based on the Trustees’ 2009 and 2010  intermediate projections, respectively, without any additional  adjustments.  3.  In prior updates, our excess cost growth assumption, while based on  growth for the U.S. health sector as a whole, was affected by  productivity adjustments and other cost-containment mechanisms for  Medicare. Beginning with our Fall 2012 update, we removed the  effects of productivity adjustments and other cost-containment  mechanisms for Medicare from our estimates of excess cost growth  for Medicaid, CHIP, and exchange subsidies. We made similar  changes to excess cost growth in our January 2010 and Fall 2010  simulations. In the revised January 2010 and Fall 2010 simulations  used in this report, excess cost growth for Medicaid, CHIP, and  exchange subsidies averages 0.8 percentage points per year over the  long term in both the Baseline Extended and Alternative simulations.  This is roughly the same as the assumption used in the original  January 2010 Baseline Extended and Alternative simulations and the  original Fall 2010 Alternative simulation and a small increase from the  assumption used in the original Fall 2010 Baseline Extended  simulation that averaged 0.7 percentage points per year.
Together these changes reduced the deficit by 0.9 percentage points of  GDP in 2050 in our January 2010 Baseline Extended simulation and 1.3  percentage points in our January 2010 Alternative simulation. They also  reduced the deficit by 0.2 percentage points of GDP in 2050 in our Fall  2010 Baseline Extended simulation. These changes did not affect the  size of the deficit in 2050 in our Fall 2010 Alternative simulation. Because  of these changes, the assumptions and results of the simulations in this  report differ slightly from those originally published in 2010.
Tables 1 and 2 list the key budget assumptions underlying the January  2010 and Fall 2010 Baseline Extended and Alternative simulations used  in this report.
Through 2020, GDP grows at the rates underlying CBO’s most recent  baseline estimates at the time the simulations were run. Thereafter, we  follow the intermediate estimates from the most recent Trustees’ report at  the time the simulations were run. These estimates are consistent with  the growth in labor force, wages, and other factors underlying the  estimates for Social Security and Medicare spending in our simulations.  GDP is held constant across simulations and does not respond to  changes in fiscal policy.
The interest rate on federal debt is held constant even when deficits climb  and the national saving rate plummets. Under such conditions, there  could be a rise in the rate of interest and a more rapid increase in federal  interest payments than our simulations display. Sensitivity analyses  reveal that variations in these assumptions generally would not affect the  relative outcomes of alternative policies.
The key economic assumptions in the simulations in this report are shown  in table 3.
section_title: Appendix II: Changes in the Long-Term Fiscal Outlook since 2010
paragraphs: Overall, the federal government’s long-term fiscal outlook has improved  since 2010 based in part on laws enacted after PPACA, including the  Budget Control Act of 2011. (See fig. 10.) The provisions of the Budget  Control Act primarily affected discretionary spending, and under both of  our simulations, discretionary spending as a share of the economy would  be lower in 2022 than at any point in the last 50 years. The Budget  Control Act’s automatic enforcement procedures would reduce Medicare  spending by up to 2 percent under current law. Many other mandatory  programs, including Medicaid, are exempt from the spending reductions.  Our Fall 2012 simulations show that health care spending remains a key  driver of the federal government’s long-term fiscal imbalance. Under the  Fall 2012 Alternative simulation, spending for Medicare, Medicaid, CHIP,  and federal exchange subsidies almost doubles as a share of GDP by  2035.
The results of our more recent Fall 2012 simulations for spending on  Medicaid, CHIP and exchange subsidies do not differ significantly from  the results from the Fall 2010 simulations that were run not long after the  enactment of PPACA. Our most recent simulations published in Fall 2012  incorporate CBO’s and the Joint Committee on Taxation’s revised  estimates through 2022 for the coverage provisions following the  Supreme Court’s ruling. Spending on Medicaid, CHIP, and federal  exchange subsidies is not significantly different from those in our Fall  2010 simulations in part because the reduction in federal matching funds  associated with covering fewer individuals in state Medicaid programs is  partially offset by increased costs of the federal exchange subsidies as a  result of larger numbers of low-income individuals enrolling in exchange  plans.
Medicare spending is slightly higher in our most recent Baseline  Extended simulation due to technical refinements the Medicare Trustees  made in response to recommendations by the 2010-2011 Technical  Review Panel on the Medicare Trustees Report; they were not directly  related to PPACA. In our most recent Alternative simulation, Medicare  spending is slightly lower than it was in our Fall 2010 Alternative  simulation due to a change in the OACT’s assumption for physician  payment updates in their alternative projections; this change was also  unrelated to PPACA.
The key budget assumptions in our Fall 2012 simulations are shown in  table 4.
The key economic assumptions in our Fall 2012 simulations are shown in  table 5.
section_title: Appendix III: GAO Contacts and Staff Acknowledgments
subsections: section_title: GAO Contacts
section_title: Staff Acknowledgments
paragraphs: In addition to the contacts named above, Melissa Wolf (Assistant  Director), Andrew Johnson, Richard Krashevski, Thomas McCabe,  Thomas McCool, Michael O’Neill, Albert Sim, and Phyllis Thorburn made  key contributions to this report. Robert Robinson assisted with the  graphics.