Sociodemographics and HRQL: Mapping the SF-12 and EQ-5D

社会人口统计学和 HRQL：绘制 SF-12 和 EQ-5D

• 批准号: 6725703
• 负责人: ERICA I LUBETKIN
• 金额: $ 9.98万
• 依托单位: CITY COLLEGE OF NEW YORK
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-30 至 2005-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6725703
• 关键词: African American; Hispanic Americans; age difference; behavioral /social science research tag; caucasian American; clinical research; education; gender difference; geographic site; health economics; health insurance; human data; human population study; income; meta analysis; public health; quality of life; questionnaires; racial /ethnic difference; social status; socioeconomics; statistics /biometry

DESCRIPTION (Provided by Applicant): Background: Subjective measures of health status and health-related quality of life (HRQL) hold great promise because they realign how the health care community evaluates its programs and services and assess outcomes that are likely to be of most relevance to patients and populations. Few studies, however, have examined the performance of these measures in the U.S. general population and even less is known about their performance in racially heterogeneous, socioeconomically diverse populations. In 2000 MRS administered both the SF-12 (a health profile) and the EQ-5D (a preference-weighted health index) to a large nationally representative sample of the U.S. general population. The inclusion of both questionnaires in the same survey enables an exploration of (1) how each measure captures the effect of sociodemographic factors on HRQL and, (2) how well the SF12 can be mapped onto the EQ-5D in this representative sample. Such a mapping may allow the SF-12, an instrument known to be useful in assessing clinical outcomes in groups of patients, also to be used in cost-effectiveness studies. Specific Aims: Aim 1: (a) To examine the scores on the SF-12 and EQ-5D index and visual analogue scale (VAS) with regard to specific sociodemographic variables, including income and education, age, gender, race/ethnicity, and health insurance coverage; (b) to summarize the population decrement in HRQL (health status burden) associated with income and education, gender, race/ethnicity, and health insurance status. Aim 2: To examine the degree to which the SF-12 can predict scores on the EQ-5D index and EQ VAS. Methods: The first aim will be accomplished through a series of ordinary linear least squares regression analyses. The four dependent variables for each regression analysis will be the PCS-12, MCS-12, EQ-5D index, and EQ VAS. The independent variables will be the sociodemographic characteristics of interest. The second aim will be accomplished through regressing the EQ5D index and EQ VAS onto the MCS-12 and PCS-12 in separate regressions. We initially will use the main effects of the MCS-12 and PCS-12 together with polynomials. The validity of the predicted scores will be examined through the bootstrap approach and use of data from both low-income primary care patients and the York Population Health Laboratory project. Conclusions: The EQ-5D primarily was designed for use in economic analyses while the SF-12 was designed for measurement of clinical health status. Understanding how sociodemographic factors affect HRQL for each measure provides valuable information with which to inform both quality of care and cost-effectiveness analyses (CEA). In addition, understanding the relationship between the two measures could allow data from studies initially undertaken for one purpose (i.e. clinical trials, quality assessment) to be used for the other (i.e. CEA).

描述(由申请人提供)：背景：健康状况和健康相关生活质量(HRQL)的主观测量很有希望，因为它们重新调整了医疗保健社区评估其计划和服务的方式，并评估了可能与患者和人群最相关的结果。然而，很少有研究考察这些措施在美国普通人群中的表现，更少有人知道它们在种族不同、社会经济多样化的人群中的表现。2000年，MRS对美国普通人群中具有全国代表性的大样本进行了SF-12(健康概况)和EQ-5D(偏好加权健康指数)的测试。通过在同一调查中包含这两份问卷，可以探索(1)每个测量如何捕捉社会人口因素对HRQL的影响，以及(2)在这个具有代表性的样本中，SF12与EQ-5D的映射程度如何。这样的映射可能允许SF-12，一种已知在评估患者组的临床结果方面有用的工具，也可以用于成本效益研究。具体目标：目标1：(A)检查关于特定社会人口变量的SF-12和EQ-5D指数和视觉模拟量表(VAS)的分数，包括收入和教育、年龄、性别、种族/族裔和医疗保险覆盖范围；(B)总结与收入和教育、性别、种族/族裔和医疗保险状况有关的HRQL(健康状况负担)人口减少情况。目的2：检验SF-12对EQ-5D指数和EQ VAS得分的预测程度。方法：第一个目标通过一系列普通的线性最小二乘回归分析来实现。每个回归分析的四个因变量将是PCS-12、MCS-12、EQ-5D指数和EQ VAS。自变量将是感兴趣的社会人口学特征。第二个目标将通过将EQ5D指数和EQVAS分别回归到MCS-12和PCS-12来实现。我们首先将MCS-12和PCS-12的主效应与多项式一起使用。预测分数的有效性将通过Bootstrap方法和使用来自低收入初级保健患者和约克人口健康实验室项目的数据进行检验。结论：EQ-5D主要用于经济分析，而SF-12主要用于测量临床健康状况。了解社会人口学因素是如何影响每一项指标的HRQL的，这为医疗质量和成本效益分析(CEA)提供了有价值的信息。此外，了解这两个衡量标准之间的关系可以使最初为一个目的(即临床试验、质量评估)进行的研究的数据用于另一个目的(即CEA)。