U.S. Department of Health and Human Services

Brookings/ICF Long Term Care Financing Model: Designing and Using Model Simulations

Executive Summary

David L. Kennell, Lisa Maria B. Alecxih, Joshua M. Wiener, and Raymond J. Hanley

February 1992

This report was prepared under contract between the U.S. Department of Health and Human Services (HHS), Office of Disability, Aging and Long-Term Care Policy (DALTCP) and Lewin-ICF, Inc.. For additional information about the study, you may visit the DALTCP home page at http://aspe.hhs.gov/daltcp/home.htm or contact the ASPE Project Officer, John Drabek, at HHS/ASPE/DALTCP, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, SW, Washington, DC 20201. His e-mail address is: John.Drabek@hhs.gov.

This report is intended to familiarize the reader with the base case output of the Brookings/ICF Long Term Care Financing Model, the assumptions used in designing simulations, and how to use the model results.

The Brookings/ICF Long Term Care Financing Model simulates the utilization and financing of long-term care services--both nursing home and home care--for elderly individuals through 2020. Home care services include home health, homemaker, personal care, and meal preparation services. The model simulates the number of individuals receiving these services and the costs of these services as financed by various public and private sources. The objective of the model is to simulate the effects of various financing and organizational reform options on future public and private expenditures for nursing home and home care.

The two principal components of the model are the Pension and Retirement Income Simulation Model (PRISM) and the Long-Term Care Financing Model. PRISM simulates the future demographic characteristics, labor force participation, income and assets of the elderly. The Long Term Care Financing Model simulates disability, admission to and use of nursing home and home care, and methods of financing long-term care services. The model uses national data and does not take into account regional, state or local variations.

The model begins with a nationally representative sample of the adult population with a record for each person's age, sex, income, and other characteristics. The model simulates changes for each individual in the sample population from 1986 to 2020, including age, economic status, disability status, utilization of long term care, and method of paying for such care.

The model uses a Monte Carol simulation methodology. The model simulates changes in an individual's status by drawing a random number between zero and one and comparing it to the fixed probability of that event occurring for an individual with a given set of socio-demographic characteristics. For example, assume that the annual probability of death for an 85 year old noninstitutionalized female is .03 (i.e., three out of every 100 women age 85 who are not in a nursing home are expected to die). If the random number drawn by the model is less than or equal to .03 for this 85 year old woman, she is assumed to die in that year. If the number drawn lies between .03 and 1.0, then she is assumed to continue to live during that year. In order to reduce random variation due to the Monte Carlo procedure, the model is routinely run with two separate random number sets and the results are averaged.

The model can be used to simulate long-term care financing assuming changes in private financing methods (such as increased purchase of private long-term care insurance) or new public financing programs. These simulations are greatly affected by the choice of assumptions about the economy (such as the rate of growth of the overall economy and nursing home prices) and individual behavior (such as rates of nursing home utilization, insurance purchase, and induced demand). The model is designed to be run under alternative economic and behavioral assumptions. This allows one to examine how sensitive the results are to the assumptions chosen.

The current version of the model is a major revision of the model that was developed jointly by Lewin/ICF and the Brookings Institution in 1986. The model was revised in 1988 and 1989 using data from a number of newly available data sources, including the 1982-84 National Long-Term Care Survey, the 1985 National Nursing Home Survey, the 1984 Survey of Income and Program Participation (Wave 4), and Medicaid and Medicare program data provided by the Health Care Financing Administration (HCFA).

The six major components of the model are described below. A chart of these components is show in Table below.

Population Data Base: Using data from the May 1979 Current Population Survey, the model uses information for a nationally representative sample of 28,000 adult individuals in 1979. We selected this 1979 data base because it has been merged with social security earnings histories for each individual in the sample.

Income Simulator: The model simulates labor force activity, marital status, income, and assets for each individual. The probabilities in this part of the model are based upon Census Bureau data on the likelihood of marriage, work, etc. for different demographic groups. The economic assumptions underlying the simulations are generally those used in Alternative II-B of the 1988 Social Security Trustee's Report. The model simulates income from private sector defined benefit and defined contribution pension plans, public pension plans, social security, Individual Retirement Accounts and Keoghs. The model also simulates the assets of elderly individuals, including the value of home equity.

Disability of the Elderly: Using probabilities estimated primarily from the 1982-84 National Long-Term Care Survey (NLTCS) and the 1985 National Nursing Home Survey (NNHS), the model simulates the level of disability for persons age 65 and over. The model simulates the onset of disability, the level of disability, changes in disability, and recovery from disability.

Utilization of Long Term Care Services: The model uses probabilities estimated from the 1982-84 NLTCS and the 1985 NNHS to simulate admission to and length of stay in a nursing home. For non-institutionalized persons, the model also simulates the use and length of use of paid home and community-based care services using probabilities derived primarily from the 1982-84 NLTCS and Medicare program data.

Sources and Levels of Payment: The fifth component of the model simulates the sources of payment and the level of expenditures for each individual receiving nursing home or home and community-based services. The model incorporates Medicare eligibility and coverage provisions and uses a set of uniform assumptions about the Medicaid program. If a resident has financial assets less than the Medicaid asset limit and his or her monthly income less a personal needs allowance is not sufficient to cover nursing home expenses, the model assumes the resident will receive Medicaid reimbursement for care not covered by income. State Medicaid program variations are not modeled.

Aggregate Expenditures and Utilization: The model accumulates Medicare, Medicaid, private expenditures, and utilization for each simulated individual for each year. The final output file from the model provides detailed information for each individual age 65 and older for each year from 1986 to 2020. For each individual, this information includes age, sex, marital status, disability, sources and amounts of income, assets, and use of and payment sources for nursing home and home and community-based services. One can tabulate this file to show aggregate long-term care expenditures for various demographic groups (e.g., age, income, and use of long-term care services) and by sources of financing (e.g., Medicare, Medicaid, out-of-pocket, and program expenditures).