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成本效益分析中使用的特定状况的健康相关生活质量 (HRQoL) 影响估计变得复杂。该项目的总体目标是找到在存在多种状况时评估单一健康状况影响的最佳方法。之前的研究重点是对健康总分进行建模；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进汇总健康分数估计。具体来说，我们将 (1) 开发并验证 HRQoL 测量中同时发生的病症的问题级模型，(2) 根据最佳汇总评分模型评估该问题级模型，(3) 构建 117 种慢性病的 HRQoL 影响的全国代表性目录，以及 (4) 演示如何使用该目录从新样本中消除同时发生的病症的影响。我们将使用大型医疗保险数据库来开发、验证和评估我们的模型。我们将使用医疗支出小组调查（一项具有全国代表性的大型调查）中 18 岁及以上的受访者来对 117 种慢性病的影响进行分类。这两个数据集包括一些 AHRQ 定义的优先人群，例如妇女、种族和民族、低收入、农村和内城区个人。我们将使用基于临床的心力衰竭患者样本来演示我们的方法在较小样本中的使用。我们将使用比例优势模型来预测问题回答，该模型使用年龄、性别和健康状况作为预测因子。拟议的研究将为健康测量提供有价值的方法，为健康政策提供信息。