Since the 1950s, life expectancy has risen at a steady pace, driven mostly by improvements in mortality at older ages. Functional status of the elderly has also improved, although gains have leveled off recently. These gains have been driven by advances in public health and a highly targeted disease model which independently delayed or forestalled mortality from major fatal diseases-through earlier detection, reduction of risk factors, and effective new treatments. Taken together, the social value of these improvements is tremendous-perhaps up to 50% of US gross domestic product. But these improvements do not come without costs. The United States has devoted an increasing share of its income to health care. Looking ahead, trends in medical innovation will increasingly carry important implications for the economy as a whole, with the health care sector representing almost 20% of the economy. With support from NIH, we have developed and used the Future Elderly Model (FEM) to better understand-and predict- future health, spending, and longevity consequences of these trends. This project will use the Future Americans Model (FAM), the extension of the FEM to ages 25 and over, to examine broader macroeconomic issues related to medical technology growth. We will first assemble technical expert panels to systematically identify technologies that will most affect Americans for the next 20 years, and assess their impact on disease incidence, disease management, morbidity, disability, mortality, and treatment costs. We will then project fiscal consequences of health care innovation scenarios using the FAM. Finally, we will introduce in the FAM a mechanism for innovation to respond to trends in population health and aging and analyze counterfactual population scenarios to study how demographic and economic trends influence innovation, health, longevity, and health spending over time. Overall, the project will constitute an important step toward understanding the `black box' of technology and its consequences for population health, spending, and the fiscal outlook.
Most models of future health care costs assume technology - one of the primary drivers of health spending -- is fixed, or treat it as a black box with a genera growth factor. However, technology is dynamic and responsive to future demand. This project pursues several approaches - including formal assessment based on multidisciplinary expert judgment and simulation modeling - to identify and quantify the fiscal and welfare consequences of medical innovation.
| Goldman, Dana P; Fillit, Howard; Neumann, Peter (2018) Accelerating Alzheimer's disease drug innovations from the research pipeline to patients. Alzheimers Dement 14:833-836 |
