Mon, April 6
Jinkook Lee, Wellbeing of the Elderly in East Asia
a PSC Research Project
Investigator: Vicki Freedman
An issue that has received a great deal of attention in recent years is the relative importance of age and time to death in determining health care costs. It is well-known that health care costs rise sharply at the end of life, especially in the year before death. This has led many to the view that population aging, insofar as it is a consequence of increased life expectancy, might not produce proportionate increases in Medicare costs, because the costs associated with the extra years lived may simply be experienced later in life. However, all studies of the age-versus-time-to-death question have used a model in which, conditional upon measured attributes, there is a single population-level pathway of expected Medicare costs. Yet there are strong reasons to suppose that there are several prototypical mean pathways of Medicare costs as individuals approach death. This project, carried out in collaboration with Syracuse University, will build a short-term Medicare-cost forecasting model that recognizes the existence of a set of distinctive, but unobserved, cost-trajectory types. Specifically, this project will: Estimate an integrated model of mortality and Medicare costs-both in the aggregate and within major categories such as inpatient care, outpatient care, SNF usage and so on-using a generalization of latent-class trajectory models and applying longitudinal data from the National Long Term Care Survey and the Cardiovascular Health Study, both of which have been linked to continuous Medicare claims records; produce new estimates of the relative effects of age and time to death on health care costs, while controlling for diagnoses and selected service-use indicators; and use microsimulation to compute complete-cohort estimates of total and component Medicare costs, for samples of synthetic observations created from the 2 data files used in the analysis. The ultimate goal of the project is to produce improved means of forecasting future Medicare costs.
|Funding:||National Institute on Aging (Subaward No. 23620-02268 SO2)|
Funding Period: 10/01/2009 to 08/31/2012
Country of Focus: USA