U.S. Department of Health and Human Services
Differential Impacts Among Subgroups of Channeling Enrollees
Thomas W. Grannemann, and Jean Baldwin Grossman
Mathematica Policy Research, Inc.
This report was prepared under contract #HHS-100-80-0157 between the U.S. Department of Health and Human Services (HHS), Office of Social Services Policy (now the Office of Disability, Aging and Long-Term Care Policy) and Mathematica Policy Research, 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 office at HHS/ASPE/DALTCP, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, SW, Washington, DC 20201. The e-mail address is: webmaster.DALTCP@hhs.gov. The DALTCP Project Officer was Robert Clark.
This report examines the variation among subgroups in impacts of the National Long Term Care Channeling Demonstration. The objective of this investigation is to determine whether estimated overall channeling impacts mask important differences in impacts among subgroups. The results indicate the types of clients for whom channeling impacts were greatest and can help identify groups that might benefit most from future channeling type programs.
The samples and outcome measures used in this report are selected from those used for the other technical reports on channeling impacts. As such, the outcome measures come from Medicare and Medicaid claims, death records, provider records, and 6 and 12 month followup interviews with channeling sample members or proxy respondents. Impact estimates were calculated using multiple regression methods to control for the effects of other determinants of outcomes, including the effects of other subgroup variables.
The principal findings are:
In general we found substantial uniformity of channeling impacts within the sample. No subgroup experienced impacts that were distinctly different from those of other groups for more than a few outcomes; differential impacts among subgroups were the exceptions rather than the rule.
Differential impacts, where they existed, occurred primarily for the nursing home use and expenditure variables. There were very few noteworthy differences in impacts on life quality, unmet needs, informal care, or case management outcomes, and only limited evidence of differences in impacts among subgroups on formal community service use.
Both basic and financial control models showed reduced nursing home use and/or cost for the small fraction of the sample residing in a nursing home when screened into the program.
The financial control model also reduced nursing home use for those on a nursing home waitlist at screen, though this effect appears to be confined to persons not eligible for Medicaid.
The cost savings from reduced nursing home use appeared to accrue primarily to private payers, rather than to the Medicare or Medicaid programs.
There is also some evidence, though more limited and less clear cut, that there were other persons at the margin of nursing home admission for whom channeling tipped the balance of needs and services and reduced nursing home use.