modeler assumes about future changes in the health status of the population, the extent and pace of scientific and technological breakthroughs in medical care, the preferences of the population for particular kinds of care, the likelihood that policy makers will alter current law and regulations, and how each of these factors relates to health care costs. There is need for better understanding of the factors contributing to the growth of health care spending and how these factors might be moderated in the future. There is also need to consider for policy models the trade-offs between simplicity and comprehensiveness and what is required for short-term and longer term projections.

Given the substantial growth in the Medicare population, fueled by the aging of the baby boom generation and rising life expectancy at age 65, and the continued increases in Medicare, Medicaid, and private health insurance spending, the availability of well-specified models and analyses that can provide useful information on the likely cost implications of health care policy alternatives is critical for public- and private-sector policy planning. Current models for health care cost projections range from a simple projected rate of GDP increase plus a specified percentage, to dynamic microsimulation models that “age” population cohorts over time, to computable general equilibrium models of the health care sector of the economy and long-term health care spending (see examples in Box 1-1).


It is therefore timely to review the capabilities and limitations of extant health care cost models and to identify areas for research that offer the most promise to improve modeling, not only of current U.S. health care programs, but also of policy alternatives that may be considered in the coming years. Understanding the factors that affect health care costs for the elderly and how to develop improved projection models for policy is an important area for the behavioral and social research program of the National Institute on Aging (NIA), given its concern with the health and socioeconomic well-being of the elderly, which could be significantly affected by changes in Medicare and other health care programs. NIA consequently asked the National Research Council’s Committee on National Statistics (CNSTAT) to conduct a public workshop on needed research to improve health care cost projections for the Medicare population and on the strengths and weaknesses of competing frameworks for projecting health care expenditures for the elderly.

The workshop was to consider major classes of projection and simulation models that are currently in use and the underlying data sources and research inputs for these models. It was also to consider areas in which

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