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

描述（由申请人提供）：背景：健康状况和健康相关生活质量（HRQL）的主观测量具有很大的前景，因为它们重新调整了医疗保健社区如何评估其计划和服务，并评估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，甚至更少有人知道它们在种族异质性，社会经济多样性人群中的表现。2000年，MRS对美国全国代表性的大样本人群进行了SF-12（健康状况）和EQ-5D（偏好加权健康指数）测试。在同一调查中纳入两份问卷，可以探索（1）每项测量如何捕捉社会人口因素对HRQL的影响，以及（2）在该代表性样本中SF 12与EQ-5D的映射程度。这种映射可以允许SF-12，一种已知用于评估患者组临床结果的工具，也可以用于成本效益研究。具体目标：目标1：（a）检查SF-12和EQ-5D指数以及视觉模拟量表（VAS）关于特定社会人口统计学变量的评分，包括收入和教育、年龄、性别、人种/种族以及健康保险覆盖范围;（B）总结与收入和教育、性别、人种/种族以及健康保险状况相关的HRQL（健康状况负担）人群下降情况。目的2：检查SF-12可预测EQ-5D指数和EQ VAS评分的程度。方法：通过一系列普通的线性最小二乘回归分析来实现第一个目的。每项回归分析的4个因变量为PCS-12、MCS-12、EQ-5D指数和EQ VAS。自变量将是感兴趣的社会人口特征。第二个目标将通过在单独的回归中将EQ 5D指数和EQ VAS回归到MCS-12和PCS-12上来实现。我们最初将使用MCS-12和PCS-12的主效应以及多项式。预测得分的有效性将通过自助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查。结论：EQ-5D主要用于经济分析，而SF-12用于测量临床健康状况。了解社会人口因素如何影响HRQL的每一个措施提供了有价值的信息，告知护理质量和成本效益分析（CEA）。此外，了解这两种措施之间的关系可以允许最初为一个目的（即临床试验，质量评估）进行的研究数据用于另一个目的（即CEA）。

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).