measures that predict application. Key to such a system will be sufficient data to understand macro- and microlevel factors that distinguish participating and nonparticipating eligibles. A work disability measurement system will have to include means for modeling the decision process from both the demand side (the individual) and the supply side (the Social Security Administration).

The design of a work disability measurement system must consider the analytic needs of the system and the impact of alternative design options on meeting those analytic goals as well as the impact of various sources of survey error (should the design include the use of household-or provider-based surveys). Among the design issues the system will have to address are the following:

• data source or sources;

• cross section versus longitudinal design;

• periodicity;

• mode of data collection;

• self versus proxy response status; and

• specific wording of question, response option presentation, and overall context.

Data Source or Sources Among the various data sources that could be included, alone or in combination, in the design of a disability surveillance system are household-based survey data, provider-based survey data, administrative record data, and physical examination data. Among the options with respect to household- or provider-based survey data are stand-alone surveys that permit rich and deep national data on the size of the disabled population (e.g., similar to the NSHA, which is currently being sponsored by the SSA), survey modules administered as part of some preexisting data collection effort (e.g., a supplement to the Current Population Survey or the SIPP), or the incorporation of a limited number of questions on existing national surveys, for example, the National Health Interview Survey (NHIS) or the Behavioral Risk Factor Surveillance System. Each of these options with respect to household- or provider-based surveys has implications for the error properties of the resulting estimates, including coverage, sampling, nonresponse, and measurement error. In addition, consideration much be given to the costs associated with obtaining data from alternative sources. The use of administrative record data potentially suffers from similar sources of error, including