Download eBook for Free

Full Document

FormatFile SizeNotes
PDF file 1.2 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.

Summary Only

FormatFile SizeNotes
PDF file 0.3 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.


Purchase Print Copy

 Format Price
Add to Cart Paperback264 pages $30.00

The ability to predict future health care costs reasonably accurately is critical to planning for the Centers for Medicare and Medicaid Services (CMS). The models used for such projections to date, however, are limited in terms of their capacity to take into account the complex array of factors likely to affect future spending. To improve CMS’s ability to map the effects on spending of such factors as medical breakthroughs and demographic trends, RAND Health developed the Future Elderly Model (FEM), a demographic-economic model framework of health spending projections that enables the user to answer “what-if” questions about the effects of changes in health status and disease treatment on future health care costs. What distinguishes the FEM from other models is its inclusion of a multidimensional characterization of health status, which allows the user to include a richer set of demographic controls as well as comorbid conditions and functional status. This report describes the development of the FEM and its application in four clinical areas: cardiovascular disease, the biology of aging and cancer, neurological disease, and changes in health care services. Beside those involved in planning at the Centers for Medicare and Medicaid Services, it should be of interest to health policy planners and health economists.

The research described in the report was conducted by RAND Health for the Centers for Medicare and Medicaid Services.

This report is part of the RAND technical report series. RAND technical reports may include research findings on a specific topic that is limited in scope or intended for a narrow audience; present discussions of the methodology employed in research; provide literature reviews, survey instruments, modeling exercises, guidelines for practitioners and research professionals, and supporting documentation; or deliver preliminary findings. All RAND reports undergo rigorous peer review to ensure that they meet high standards for research quality and objectivity.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.