The Aging Population in the Twenty-First Century Statistics for Health Policy (1988) / Chapter Skim
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11 Statistical Methodology for Health Policy Analysis
11 Statistical Methodology for Health Policy Analysis
Pages 236-258
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From page 236... ...
The third section of the chapter discusses methodological issues in a third area of fundamental importance in the study of aging, forecasting of the sizes and composition of populations, as well as population characteristics such as health status and needs for 236
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From page 237... ...
the need to reduce bias and improve precision of estimates of net change in populations. In many areas of investigation discussed in this report, the essential role of longitudinal data derives from the need to study aging and its consequences as processes, that is, complexes of states and events occurring over time (Rowe, 19773.
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From page 238... ...
Longitudinal data are required for the study of gross flows and for the study of individual change and its determinants-studies that cannot be carried out with cross-sectional data. Although either longitudinal data or cross-sectional data can be used to provide data about net change in populations with age, several problems can
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From page 239... ...
One way to address the issue of cohort effects is to use successive cross-sectional data for the same cohort as described above. In view of these considerations, cross-sectional data can be used to obtain valid estimates of net change if the potential bias from selective mortality and cohort effects is small (Louis et al., 1986~.
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From page 240... ...
Cross-sectional data potentially can provide some information about net change in populations due to aging, but they can give biased, and possibly misreading, estimates when the variables under study are subject to cohort or selection effects. Designing Longitudinal Studies Although the design phase of longitudinal studies has received some attention in the statistical literature, most papers have addressed single issues in highly simplified settings.
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From page 241... ...
The panel urges that sponsors of longitudinal studies make provision in study staffing and timetables to allow for considerations of the special design problems posed by individual studies. Designs and Their Implications for Longitudinal Data Analysis In empirical applications, testing whether specific classes of stochastic process models describe the occurrence of events or the evolution of continuous variables is best facilitated by observing, in full, many realizations of the underlying process for all times in a wide time interval.
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Analytical Strategies In the ideal but rather infrequent settings in which evolving processes are observed over a time interval, two quite disparate in
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From page 243... ...
When estimation of transition rates between a discrete set of states is the primary focus of the analysis, one begins with very simple, somewhat plausible classes of models as candidates to describe some portion of the observed data and within which the unobserved dynamics are well defined for example, a time series of time-homogeneous Markov chains for which each separate mode! describes only unobserved dynamics between a pair of consecutive surveys in a multiwave pane!
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From page 244... ...
One can hope that future methodological developments will lead toward more unified approches to model formulation and data analysis. An important new development for exploring high-climensional longitudinal data sets is the faintly of grade of membership (GOM)
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From page 245... ...
They may in fact be stochastic processes themselves, thereby leading to a representation of individual dynamics in terms of evolving degrees of similarity to special pure type processes. Although much further theoretical, empirical, and numerical computational development remains to be carried out before GOM can be considered to be a well understood and readily utilized framework, it has already shown sufficient promise in studies of health status dynarn~cs and health care utilization in elderly populations to warrant much more sustained investigation.
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From page 246... ...
Examples of exact record linkages that have contributed or have the potential to contribute to our information base on the status of older Americans include: Linkage of administrative data on retirement benefits to survey data collected in the Social Security Administration's Retirement History Survey (Fox, 1979~. Linkage of survey records from the Current Population Survey, the National Health Interview Survey, and the National Health and Nutrition Examination Survey to death records in the National Death Index (Patterson and Bilgrad, 1985~.
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Obstacles to Performance of Record Linkages Obstacles to carrying out record linkages include technical problems, resource constraints, legal constraints, and policy considerations. There has been considerable progress in the development of computerized record linkage techniques, but there are still many
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Substantial research and development efforts may be needed to explore feasibility and to adapt existing record linkage programs to malice them suitable for a specific application. Understandably, agencies like the Social Security Administration and the Internal Revenue Service that maintain potentially useful administrative data systems do not consider the development of statistical data bases not directly related to their own programs to be a high-priority activity.
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Nevertheless, interagency record linkages can usually be undertaken in ways that do not violate statutory prohibitions, provided the agencies controlling the record systems involved are sufficiently motivated to do the linkage. These statutory limitations may, however, be considered obstacles to record linkages in two senses.
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From page 250... ...
Obstacles to Dissemination and Use of Record Linkage Results For record linkages that are undertaken despite the obstacles just described, the benefits derived depend on how widely and in how much detail the resulting data are disseminated to potential users. Publicly collected data are disseminated in two forms: aggregate statistics and microdata files.
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From page 251... ...
The panel recognizes the Continuous Work History Sample as a potentially valuable data base for research on policy issues relating to health, Medicare benefits, disability, and mortality of the aging population. It supports current efforts of the Internal Revenue Service and the Social Security Administration to enhance the system and resume limited dissemination of microdata files.
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From page 252... ...
recommends that federal statistical agencies develop procedures for making microdata files more readily available to users, including both other federal agencies and nongovernment researchers. Technical procedures, such as curtailment of file content and the deliberate introduction of error, cannot reduce the risk of statistical disclosure to zero; therefore, other methods of protecting the confidentiality of data subjects should be explored.
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Their construction also involves judgmental procedures with potentially arbitrary assumptions about the patterns of change in mortality rates over time. This issue merits attention for assessments of health status when more extensive consideration of the biological process is useful, particularly in the development of morbidity and disability forecasts.
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. As noted previously, important factors in many projections concerning population size, composition, and health status are the levels of age-specific mortality rates in the future.
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For example, the mortality rate for males ages 45-49 was 546.1 per 100,000 in 1982, but nearly 20 times greater at ages 80~84. Higher transition rates among the elderly also apply to morbidity, hospitalization, and other experiences.
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From page 256... ...
When adequate estimation of their parameters is feasible, they can enable evaluation of factors that can affect changes in distributions of population characteristics such as health status or health services utilization. Examples of useful m~crosimulation models include POPSIM (a product of the Research Triangle Institute)
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From page 257... ...
Many research workers are concerned with methodology for combining data from different sources (see, for example, Hedges and Olkin, 1985; Wolf, 1986; Gupta and WiTton, 1987~. Speaking more generally, much of statistical methodology is
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The analysis of such information poses a challenge to statisticians and other quantitative scientists, as has been recognized by many and has led to considerable research on policy analysis, as well as the formation of new professional groups such as the Society for Decision Analysis. The panel believes that this line of research is very important not only to policy analysis on the consequences of an aging population, but also to policy analysis in many other areas of importance to this country.
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