End-of-Life Trajectories: A Prospective Model

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DESCRIPTION (provided by applicant): Growing life expectancy and the successes of modern medicine have made increasingly common a late-life condition of frailty, a trend to which the nation's health care system has not fully adapted. This project is intended to provide improved understanding of the age profile of health and health care needs, along with their implications for disability levels and Medicare costs. It will employ a recently developed typology of end- of-life functional trajectories, of which frailty is one type. Nearly all of the empirical work to date that employs this conceptual scheme has used retrospective methods. To further develop and apply this conceptual scheme, and to investigate its usefulness as a forecasting and planning tool in the area of population health and care costs, we will develop a prospective model of end-of-life functional trajectories. We will use the typology as a way of imposing a structure on what is otherwise ignored, or undifferentiated, heterogeneity in end-of-life functional and service-use patterns. Our specific aims are to (1) estimate an integrated model of mortality, disability, and Medicare costs, using longitudinal data from the National Long Term Care Survey (NLTCS; 1984-2004), linked to continuous Medicare claims records for 1982-2004; (2) produce new estimates of the relative effects of age and time to death on health care costs, while controlling for diagnoses and treatments; (3) conduct an intensive review of a selected set of individual treatment histories (taken from the linked NLTCS-Medicare claims records) in order to validate and refine the statistical model; and (4) develop a database and algorithms with which to conduct microsimulation forecasts of cohort disability and Medicare-cost profiles based on the estimated statistical model. Using the microsimulation framework, we will conduct several "experiments" intended to inform important issues of substance, method, policy and practice. Relevance to public health: The predictive model to be developed will lead to improved understanding of the relationships between end-of-life health and health care patterns, disability, and Medicare costs. As people's average lifetimes continue to grow, patterns of service use, costs, and experiences with declining function as death approaches will all change, requiring new practice patterns and affecting the lives of patients and their families. Our model is intended to improve our ability to predict these end-of-life patterns. Finally, Active Life Expectancy-the number of years people can expect to live in an "active" or healthy state-has become a widely-accepted index of public health, and our model will produce improved estimates of this index.