To help the government take the actions necessary to keep the Medicare trust funds solvent, the Centers for Medicare & Medicaid Services (CMS) needs to generate accurate predictions of present and future health care spending. This process will require predicting how many people of various types will be alive in each future year and what their health care spending will be. The official projections of the aged beneficiary population by age and sex are currently taken from those of the Trustees’ Reports of the Social Security Administration (SSA). These projections already take into account the long-term trends in decreasing age-specific mortality...

The unprecedented progress in biomedical research over the final quarter of the last century will continue to drive a revolution in the practice of medicine. Every aspect of the prevention, diagnosis, treatment, and monitoring of disease processes has been affected by this revolution. In some cases, what appear to be trends in particular lines of research are not smooth progressions at all, but radical paradigm shifts. Behind this wave of advancement is a convergence of progress in many scientific fields, not simply the life sciences—anatomy, biochemistry, immunology, microbiology, physiology, pharmacology, and clinical medicine—but chemistry, physics, math, computer science,...

In some lines of research, trends that appear from a distance to be smooth progressions are in fact radical paradigm shifts. Behind this wave of advancement is a convergence of progress in many scientific fields, including anatomy, biochemistry, immunology, microbiology, physiology, pharmacology, health services, and clinical medicine as well as chemistry, physics, math, computer science, and engineering. Scientists from widely divergent disciplines are now crossing over to other disciplines or collaborating to form multidisciplinary teams of investigators to tackle problems of such magnitude that they could not have been approached within any one field.

Keeping up with the rapidity of...

At the core of our model development is a demographic-economic model the primary function of which is to project future health care expenditures and health status. The second function of this model is to serve as the simulation vehicle for evaluating what-if scenarios about the future health care environment. The model diverges from traditional approaches in that it includes a multidimensional characterization of health status. In addition, conventional actuarial approaches employ cell-based models in which each cell represents a subpopulation of interest. While it is theoretically possible to extend cell-based models to support health care projections, practical shortcomings make it...

A major determinant of health care expenditures among elderly Americans is the prevalence of chronic disease and disability. Although not all of these conditions lead to persistently high medical costs, the occurrence of a stroke or the presence of cancer, and many other conditions can have a lasting effect on health status, disability, and the demand for medical services.

Efforts to control Medicare expenditures often focus on a minority of beneficiaries who use a disproportionate share of medical services. In 1998, 50.2 percent of older beneficiaries (age 65+) had Medicare reimbursements under $1,000, while 5.7 percent had annual expenses over...

As noted previously, the microsimulation model consists of three main component models. First, parameter estimates from a health status transition model form the basis of individuals’ health status forecasts from the moment they enter the simulation host data until they become deceased. Second, every year we rejuvenate the host data with age-65 individuals to ensure that the data remain representative of the entire population age 65 and older. We estimate a model to forecast trends in various measures of health status and adjust the relative weights of the rejuvenation sample in accordance with those trends. Third, we apply a model...

This subtask is designed to predict the health status of each of the future, entering cohorts of Medicare patients between the years 2001 and 2030. While it may be plausible to look simply at 65-year-olds in the year 2000 to predict the presence of chronic conditions and disability among 65-year-olds in 2001, such a procedure is likely to lead to misleading predictions for future entering cohorts, especially given the presence of well-known trends in the prevalence of disease and disability among all adult-age cohorts. If these trends continue, the health of 65-year-olds in 2030 is likely to look considerably different...

In this chapter, we show how we modified the FEM to simulate various scenarios involving likely breakthroughs identified by the expert panels. We compare the resulting disease prevalence and costs with those from the baseline scenario to evaluate the potential effectiveness of the breakthroughs.

After reviewing the list of breakthroughs identified by the expert panels with CMS, we agreed to model the following: telomerase inhibitors, cancer vaccines, diabetes prevention, compound that extends life span, changes in education, rise in Hispanic population, smoking, obesity, and an integrated cardiovascular disease scenario.

Cancerous tumors can be divided into two categories: solid tumors, which...

The Future Elderly Model is a microsimulation that projects disease, disability, and expenditures among the elderly from 2000 to 2030. It is designed to answer questions about how health status and health expenditures would change with changing disability and medical treatment.¹⁹ This chapter considers the suitability of the model for use by the Office of the Actuary (OACT) as noted in the Final Design Report. We focus on five components of the FEM: the population projection, the expenditure projections, the econometric methodology, the what-if modeling, and the overall usefulness to OACT at the Centers for Medicare and Medicaid Services.

There...

This project served several purposes. First, it identified possible breakthroughs that could greatly affect the future health and expenditures of the elderly. Second, we developed a microsimulation model that can be used to quantify the effect of these breakthroughs and other scenarios of interest to CMS and other policymakers. The model is flexible enough to consider life extensions and the interaction of treatment with disease, and it incorporates what is known about the health of future cohorts. Several key policy issues and recommendations arise as a result of this work.

The FEM starts with a nationally representative sample of beneficiaries...