Although collected and structured for the specific purpose of evaluating the channeling demonstration, the resulting data can be used for a wide variety of other research. In this section, we briefly review completed and planned research, discuss potential applications, and caution users about some pitfalls.
A. Completed and Planned Analyses
Analyses conducted as part of the channeling evaluation and a followup study of targeting those at high risk of nursing home placement are now completed. A series of detailed technical reports on channeling document the results, data collection procedures, sample definitions, and methodology. Paragraph summaries of the reports and information on ordering them can be found in a summary the of Channeling Demonstration and an abstract list of reports available from the Office of Social Services Policy, Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services (DHHS), Room 410E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, D.C. 20201. The followup study of targeting is reported by Grannemann et al. (1986). It is currently not available for distribution.
We are aware of the following analyses that are currently being undertaken with the public use files:
Robert Clark of the Office of the Assistant Secretary for Planning and Evaluation of DHHS: (1) estimation of the total cost of care, both public and private, with particular emphasis on out-of-pocket costs, and (2) analysis of service use by the oldest old.
Corbin Liu of the Urban Institute: analysis of the costs of care of older persons with cognitive impairments, both those in nursing homes and those in the community.
Peter Kemper of the National Center for Health Services Research of DHHS: analysis of the determinants of the use of formal and informal community care.
Jim Callahan and Phyllis Mutschler of Brandeis University: analysis of changes over one year in the use of all types of care by the control group.
Other research will undoubtedly be initiated as more researchers obtain the public use files.
B. Potential Applications
The extensive data collected for the channeling evaluation create many research possibilities. Its special purpose--to form the basis of an evaluation--makes it better suited for some analyses than for others. Because it is a selected sample--data came from ten sites selected through competition, and the sample comprises applicants referred to a special community care program-descriptive analysis using the channeling data are less likely to be informative than analysis of the same questions using nationally representative data. The channeling data appear more appropriate for analyses that do not depend on representativeness but capitalize on the richness of the data or their original purpose.
The channeling data appear most useful for analyses of behavioral relationships, methodological research, or re-analysis of experimental results. The extensive data on the well-being of the elderly sample, for example, is fertile ground for psychometric analysis of quality of life measures or analysis of the determinants of well-being, but would not be appropriate for an analysis of the extent of unmet need in the United States. To estimate the cost of community care and nursing home care for use in calculating premiums for LTC insurance, channeling data would have to be used in conjunction with other data (e.g., a nationally representative sample); otherwise, the estimates would pertain to the selected channeling sample rather than to likely purchasers of LTC insurance.
C. Some Cautions
Although the richness and comprehensiveness of the channeling data set open numerous research possibilities, researchers should be aware of their complexity. Researchers accustomed to using cross-section surveys designed to collect data on a population, rather than longitudinal data designed to evaluate a program, are likely to be surprised by the complexity of the channeling data. One researcher who was not involved in the evaluation but has begun using the channeling data remarked that this is "the most complicated data set [he had] ever seen." The complexity arises from the large number of data sources, the structure of the files, and the special evaluation sampling objectives.
The data sources, as described above, are numerous: five interviews with the elderly sample members or their proxies (screen, baseline, and 6-, 12-, and 18-month followups), three interviews with primary informal caregivers (baseline and 6- and 12-month followups), Medicare claims, Medicaid claims, financial model channeling claims, provider billing records, client tracking data, and death records. The data set thus contains a massive amount of data. Variables can be constructed from more than one source, individually or in combination, so that researchers need to understand exactly how variables on the public use file are constructed before using them in analysis. Not all data are present in every case called for in the design--numerous data sources also provide numerous opportunities for missing data.
Evaluation needs determined the way in which files were structured and variables were constructed. Files were organized, for example, by analytic area so that data needed for a particular analysis were all on one file. Because all analyses controlled for baseline characteristics, a standard set of baseline variables were included among constructed followup variables. Constructed variables also were defined to meet evaluation needs. For example, because some baseline data were not comparably measured for treatment and control groups, screen data were sometimes used when a baseline measure might be better for other purposes.
Evaluation objectives also drove the hundreds of big and little decisions in the design of the data collection. Most important were the sampling decisions which optimized the usefulness of the data for evaluation purposes. Not all data were collected for all sample members. Indeed, the only data that are available for the entire sample are the screen and death records. Two examples will illustrate how sample design decisions could affect analysis possibilities. First, in order to limit the duration of the demonstration, only the first half of the sample to enroll were followed for 18 months. Longitudinal analysis must be limited, therefore, to 12 months of followup data or to the relatively small sample with 18 months of followup data. Second, in order to minimize data collection costs, provider billing records on community care costs were collected only for 20 percent of the sample for the first six months and 10 percent for the second six months. Consequently, data on the community service expenditures of private individuals and government programs other than Medicaid and Medicare are quite limited. Although these and other sample design decisions made sense in the evaluation, they may hinder the use of the data for other purposes.
Before undertaking a project using the channeling data, it is suggested that researchers begin by assessing the implications of the complexity of the data base for their project by reading the following reports:
The final report (Kemper et al., 1986), to gain an overview of the evaluation design and available data
The report on data collection procedures (Phillips et al., 1986), to learn how the data were collected
The particular technical report on the relevant substantive area, to understand how analysis files were constructed, how samples were defined, what variables were constructed, and what analysis was done as part of the evaluation. (For example, researchers planning analysis of informal care should read the technical report on that subject by Christianson, 1986. In addition, those seeking to replicate the evaluation analysis should read the report on research methodology by Brown, 1986).
Only after having assessed the complexity of the data and its implications for the contemplated research does it make sense to invest in the purchase of the public use tapes and associated documentation.