Accurate measurement of population health is necessary to inform policy, set research agendas, and allocate public resources. This proposal is designed to leverage several publicly available datasets to advance the science of Quality Adjusted Life Expectancy (QALE) estimation. QALE is the metric recommended to track population health in the United States. QALE integrates life expectancy (mortality) with quality-of-life (morbidity). We have assembled a research team with experience in quality of life measurement (Janel Hanmer, MD, PhD, Rachel Hess, MD, MS, Mark Roberts, MD, MPP), QALE use (Rachel Hess, MD, MS, Mark Roberts, MD, MPP), and both survey and longitudinal methods (Janel Hanmer, MD, PhD, Lan Yu, PhD). The measures used to quantify quality-of-life for QALE are called health utility measures. Health utility measures have been included in a variety of surveys allowing for cross-sectional estimates of health utility. Previous QALE estimates have been made by combining cross-sectional estimates of health utility with life expectancy. While such estimates can be calculated from relatively few data, such models have several limitations including the assumption that age- and sex-stratified health utility will be static over time. This project develops an alternative technique which uses joint estimation of health utility and life expectancy from the same sample to estimate QALE. This technique has several theoretical advantages including: consistency in estimating morbidity and mortality from the same sample, an explicit method to include changes in age- and sex-stratified health utility by including age and cohort effects in the model, improved flexibility for modifying the model for subpopulations of interest (such as those with chronic disease). We will achieve this goal through the following specific aims: 1: Estimate independent age, period, and cohort effects in HRQoL changes in the US general population. 2: Produce age- and sex-stratified 10-year QALE for the US general population. 3: Produce 10-year QALE estimates for common health conditions in the US general population. This project will use nationally representative publicly available datasets including the National Health Interview Survey, the Medical Expenditures Panel Survey, and the National Death Index. The results of this project will provide national normative QALE estimates to which smaller community and clinical samples can be compared. We will disseminate our final models on a publicly available website where users can input age, sex, and health information and receive 10-year QALE. There will be an advanced version of the calculator where the user can modify the effect of disease on life expectancy or health utility This project will vastly improve the estimates of QALE in the United States. Accurate QALE estimates will improve the ability of researchers, public health professionals, and policy makers to understand the health of the US population as well as the relative impacts of common health conditions.
Accurate measures of population health are necessary to inform policy, set research agendas, and allocate public resources. One commonly used measure of population health is Quality Adjusted Life Expectancy - a metric which combines mortality and morbidity into a single value. This project will improve current Quality Adjusted Lif Expectancy estimates by using large nationally-representative datasets, modeling expected changes in morbidity, and allowing estimates for specific health conditions.