Measuring Multimorbidity with Individualized Disease-specific QOL Impact Scales

描述（由申请人提供）：有充分的证据表明，多发病或多种慢性疾病（MCC）会损害患者的功能和健康相关的生活质量（QOL）。然而，我们的能力，研究的影响，并占多morphology是阻碍了其概念化和测量的方法问题。这些因素包括缺乏统一的定义，多样化的多指标扩散，广泛依赖于使用人口权重的指标，而这些权重并不是用来解释患者QOL的变化，以及缺乏考虑疾病负担个体评估的指标。本项目的目标是改善MCC影响的评估，以分析和解释通用的患者报告结局（PRO）QOL指标。我们将对2011年和2012年从两个独立样本中收集的10，624名成年人的横截面和纵向数据进行二次分析（一个样本代表美国一般人群，第二个队列从预先确定患有关节炎、心血管疾病、慢性肾病、糖尿病或呼吸系统疾病的成年人中过采样），根据NIA赞助的疾病影响计算机自适应评估（DICAT）资助（R44 AG025589，Ware，PI）。对于36种疾病，DICAT开发了标准化的疾病特异性量表，测量归因于每种疾病的QOL影响。这些疾病特异性QOL影响评分已在逐种疾病基础上进行了评价，但尚未进行集体评价以确定其测量多发病及其影响的程度。我们建议扩展这项工作，以更好地了解患者的能力，使有效的生活质量归因于个人条件的背景下，MCC。我们还将确定差异的重要性，在MCC的存在下，特别是为了分析和解释通用PROs.The项目的目的聚合条件特定的患者QOL影响评级的替代方法有以下具体目标：（1）探索MCC患者在何种程度上可以作出有效的归因于特定条件时，报告疾病对QOL的影响。(2)系统评价用于预测一般PRO结局的不同MCC聚集方法。(3)用独立数据交叉验证方法和结果。可能需要进行更多的研究，以充分实施在这项研究中证明有用的方法学进展。然而，本项目中评价的MCC影响的概念化和测量方法最终可能使基于PRO的MCC影响标准化措施能够更好地估计和解释比较有效性研究中患者病例组合和PRO结局的差异。

DESCRIPTION (provided by applicant): It is well documented that multimorbidity, or multiple chronic conditions (MCC), impairs patients' functioning and health-related quality of life (QOL). However, our ability to study the impact of and account for multimorbidity is hampered by methodological problems underlying its conceptualization and measurement. These include lack of a uniform definition, proliferation of diverse multimorbidity indexes, widespread reliance on indexes using population weights that were not developed to explain variations in patients' QOL, and a paucity of indexes that take individual assessments of disease burden into account. The goal of this project is to improve the assessment of MCC impact for the purposes of analyzing and interpreting generic patient- reported outcome (PRO) measures of QOL. We will conduct secondary analyses of cross-sectional and longitudinal data collected in 2011 and 2012 for 10,624 adults from two independent samples (one sampled to represent the US general population and a second cohort oversampled from adults pre-identified with arthritis, cardiovascular disease, chronic kidney disease, diabetes or respiratory disease), pursuant to the NIA- sponsored Computerized Adaptive Assessment of Disease Impact (DICAT) grant (R44 AG025589, Ware, PI). For 36 conditions, DICAT developed standardized disease-specific scales measuring the QOL impact attributed to each condition. These condition-specific QOL impact scores have been evaluated on a disease- by-disease basis but have not been evaluated collectively to determine how well they measure multimorbidity and its impact. We propose to extend this work to better understand the ability of patients to make valid QOL attributions to individual conditions in the context of MCC. We will also determine the importance of differences in alternative approaches to aggregating condition-specific patient QOL impact ratings in the presence of MCC, specifically for purposes of analyzing and interpreting generic PROs. The project has the following specific aims: (1) Explore the extent to which patients with MCC can make valid attributions to specific conditions when reporting disease impact on QOL. (2) Systematically evaluate different MCC aggregation methods used to predict generic PRO outcomes. (3) Cross-validate methods and results with independent data. Additional research will likely be required to fully implement the methodological advances proven to be useful in this research. However, the approach to conceptualizing and measuring MCC impact evaluated in this project ultimately may enable the use of standardized PRO-based MCC impact measures to better estimate and interpret differences in patient case-mix and PRO outcomes in comparative effectiveness research.