Health Utility Estimates and Co-Occurring Conditions

健康效用估计和同时发生的情况

• 批准号: 7222605
• 负责人: Janel Hanmer
• 金额: $ 3.67万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-30 至 2007-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7222605
• 关键词: chronic disease /disorder; clinical research; comorbidity; cost effectiveness; health care model; human data; human subject; model design /development; patient /disease registry; patient oriented research; quality of life; questionnaires

DESCRIPTION (provided by the applicant): The presence of multiple health conditions complicates Health Related Quality of Life (HRQoL) impact estimates for specific conditions used in cost-effectiveness analyses. The overall goal of this project is to find the best method to estimate the impact of a single health condition when multiple conditions are present. Previous research focused on modeling summary health scores; our research will attempt to improve summary health score estimates by modeling the individual questions which are used to calculate these scores. Specifically, we will (1) develop and validate a question-level model of co-occurring conditions in HRQoL measures, (2) evaluate this question-level model against the best summary score model (3) construct a nationally representative catalog of HRQoL impact for 117 chronic conditions, and (4) demonstrate the use of the catalog to remove the effect of co-occurring conditions from a new sample. We will use a large Medicare database to develop, validate, and evaluate our model. We will use respondents aged 18 and over from the Medical Expenditures Panel Survey, a large nationally representative survey, to catalog the impact of 117 chronic conditions. These 2 datasets include a number of AHRQ-defined priority populations such as women, racial and ethnic minorities, low income, rural, and inner city individuals. We will use a clinic-based sample of heart failure patients to demonstrate use of our methods in smaller samples. We will predict question responses with a proportional odds model that uses age, sex, and health conditions as predictors. The proposed research will provide valuable methods for health measurement which informs health policy.

描述（由申请人提供）：多种健康状况的存在使与健康相关的生活质量（HRQOL）对成本效益分析中使用的特定条件的影响估计复杂化。该项目的总体目标是找到当存在多种状况时估计单个健康状况的影响的最佳方法。先前的研究重点是建模摘要健康评分；我们的研究将尝试通过对用于计算这些分数的各个问题进行建模来改善摘要健康评分估计。具体而言，我们将（1）在HRQOL度量中开发和验证与最佳汇总得分模型（3）构建一个国家代表性的HRQOL对117个慢性条件的HRQOL影响的目录的问题级别模型，（2）评估该问题级别的模型，并且（4）（4）（4）证明了coled cole co co co-cccccrricry cocccrricry conform cocccrricry conformeng的使用效果。我们将使用大型Medicare数据库来开发，验证和评估我们的模型。我们将使用大型全国代表性调查的医疗支出小组调查中的18岁及以上的受访者对117种慢性病的影响进行分类。这两个数据集包括许多AHRQ定义的优先人群，例如妇女，种族和少数民族，低收入，农村和城市内部的个人。我们将使用基于诊所的心力衰竭患者样本来证明在较小的样本中使用我们的方法。我们将使用比例的赔率模型来预测问题回答，该模型将年龄，性别和健康状况作为预测因素。拟议的研究将为健康政策提供宝贵的健康测量方法。