Medical Cost Trajectories and Onset of Age-Associated Diseases
Aging-related deterioration in health impacts an important economic component: the medical costs associated with disease diagnosis and treatment. Because almost all U.S. residents aged 65+ years old are covered by the Medicare system, prediction of future Medicare costs is crucial for health care planning. These costs represent the sum of the medical costs associated with every person enrolled in the system. Individual costs deal with expenditures associated with disease onsets, their treatment, and subsequent causes of acute and chronic conditions. In this Chapter, we analyze time trajectories of medical costs associated with the onset of 12 aging-related conditions: acute coronary heart disease, stroke, ulcer, breast cancer, prostate cancer, melanoma, lung cancer, colon cancer, diabetes, asthma, Parkinson’s disease, and Alzheimer’s disease. These trajectories were reconstructed using the NLTCS data linked to the Medicare Files of Service Use (NLTCS-M). We developed a special procedure for selecting individuals with onset of each geriatric disease and used it for identification of the date of the disease onset. We found that the time patterns of medical cost trajectories are similar for all studied diseases. These patterns can be described in terms of four components representing: (i) the cost associated with initial comorbidity (reflected in medical expenditures); (ii) the cost of the onset of each disease; (iii) the rate of decline in medical costs due to recovery, reflecting a reduction of medical expenditures after disease onset; and (iv) an acquired comorbidity characterizing the steady-state of medical costs after disease onset. The description of the trajectories was formalized by a model that explicitly involves four parameters reflecting these four components of the medical cost trajectories. The four components were evaluated for the entire U.S. population as well as for the subpopulation conditional on age, disability, and comorbidity states, and survival for 2.5 years after the date of the disease onset. The approach developed results in a family of new forecasting models with covariates. The properties of Medicare expenditures for older U.S. adults revealed in these analyses contribute to an understanding of the impacts of screening effectiveness and therapeutic innovations on the dynamics of disease incidence with advancing age as well as for projecting future Medicare costs.
