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Improving Health Care Cost Projections for the Medicare Population: Summary of a Workshop
longer term projections). In turn, Congress must use the CBO estimates in assessing the estimated cost of a specific legislative proposal and its effects on the deficit. CMS OACT estimates are used by the Medicare Trustees to describe the projected financial condition of the program over the short, medium, and long terms out to 75 years. In turn, the Trustees’ reports affect the policy debate on possible changes to the program that could affect benefits and costs. MEPS is a key source of data on many aspects of health care cost modeling, including estimates of people lacking health insurance coverage, provisions of employer-provided health care plans, and estimates of health care coverage and expenditures for the most populous states.
PREDICTING MEDICARE COST GROWTH
John Friedman (Harvard University) began by noting that over the past 45 years Medicare spending has grown faster than the gross domestic product (GDP). If allowed to continue without some change, by 2080 Medicare health care expenditures alone would reach 99 percent of GDP. Clearly that cannot be allowed to happen. The nation is faced with the questions of how and when cost growth will slow and what the consequences of this slowing will be. To solve this problem, academic and government researchers and policy analysts have been developing models for projecting Medicare cost growth.
Friedman provided a brief review of the three main approaches to projecting Medicare cost growth—extrapolation, microsimulation, and computable general equilibrium. He then briefly explained the assumptions, mechanics, strengths, and weaknesses of each and showed how policy makers use these methods.
Extrapolation is the most direct approach to forecasting future growth. It uses historical patterns in aggregate spending as a guide for projecting future growth, relying entirely on a statistical or actuarial approach rather than an economic approach, and is essentially based on a regression. Its transparency is its strength. The end result is clearly the sum of its parts, and that is a real value in keeping things transparent. Extrapolation is best suited for short- to medium-run projections. Its long-run numbers may be accurate but without detailing what drives such numbers, correct or not, extrapolation leaves the researcher unsatisfied.
The fundamental problem with the extrapolation approach is that it does not address the fact that something has to change. In practice, however, researchers often do not simply extrapolate, but also impose some brakes on the system to limit growth. For example, a constraint used by the CBO as a brake on the system is that nonhealth care consumption cannot