Quality Adjusted Life Expectancy Estimates for the US General Population

描述(由申请者提供)：准确的人口健康测量是为政策提供信息、制定研究议程和分配公共资源所必需的。这项建议旨在利用几个公开可用的数据集来推进质量调整预期寿命(QALE)估计的科学。QALE是推荐用于跟踪美国人口健康的指标。QALE综合了预期寿命(死亡率)和生活质量(发病率)。我们组建了一支在生活质量测量(Janel Hanmer，MD，PhD，Rachel Hess，MD，MS，Mark Roberts，MD，MPP)、QALE使用(Rachel Hess，MD，MS，Mark Roberts，MD，MPP)以及调查和纵向方法(Janel Hanmer，MD，PhD，Lan Yu，PhD)方面经验丰富的研究团队。用于量化QALE生活质量的指标称为健康效用指标。在各种调查中都纳入了卫生效用的衡量标准，从而可以对卫生效用进行横断面估计。以前的QALE估计是通过将卫生效用的横断面估计与预期寿命结合起来进行的。虽然这样的估计可以从相对较少的数据中计算出来，但这样的模型有几个局限性，包括假设按年龄和性别分层的卫生效用随着时间的推移将是静态的。该项目开发了一种替代技术，使用同一样本的健康效用和预期寿命的联合估计来估计QALE。这项技术有几个理论优势，包括：在同一样本中估计发病率和死亡率的一致性，通过在模型中包括年龄和队列效应来包括年龄和性别分层卫生效用的变化的明确方法，提高了为感兴趣的亚群(如慢性病患者)修改模型的灵活性。我们将通过以下具体目标来实现这一目标：1：估计独立的年龄、周期和队列效应对美国普通人群的HRQOL变化的影响。2：为美国普通人群编制按年龄和性别分层的10年QALE。3：对美国普通人群的常见健康状况进行10年QALE评估。该项目将使用具有全国代表性的公开可用的数据集，包括国家健康访谈调查、医疗支出小组调查和国家死亡指数。该项目的结果将提供国家标准的QALE估计，较小的社区和临床样本可以与之进行比较。我们将在一个公开的网站上发布我们的最终模型，用户可以在网站上输入年龄、性别和健康信息，并获得10年的QALE。将有一个高级版本的计算器，用户可以在其中修改疾病对预期寿命或健康效用的影响这个项目将极大地改善美国对QALE的估计。准确的QALE评估将提高研究人员、公共卫生专业人员和政策制定者了解美国人口健康状况以及常见健康状况的相对影响的能力。

DESCRIPTION (provided by applicant): 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.