Standardizing disease-specific quality of life measures across multiple chronic conditions: development and initial evaluation of the QOL Disease Impact Scale (QDIS®)

Health and Quality of Life Outcomes

Research

Nina Deng¹  Rick Guyer²  Barbara Gandek³  John E. Ware³ 

[1] Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA;Measured Progress, Dover, NH, USA;John Ware Research Group, 10 Wheeler Court, 02472, Watertown, MA, USA;John Ware Research Group, 10 Wheeler Court, 02472, Watertown, MA, USA;Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA;

关键词: Patient-reported outcomes;    Health-related quality of life;    Disease-specific measures;    Multiple chronic conditions;    Item response theory;    Norm-based scoring;    Validity;    Responsiveness;   

DOI  :  10.1186/s12955-016-0483-x

 received in 2016-01-17, accepted in 2016-05-06,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundTo document the development and evaluation of the Quality of life Disease Impact Scale (QDIS®), a measure that standardizes item content and scoring across chronic conditions and provides a summary, norm-based QOL impact score for each disease.MethodsA bank of 49 disease impact items was constructed from previously-used descriptions of health impact to represent ten frequently-measured quality of life (QOL) content areas and operational definitions successfully utilized in generic QOL surveys. In contrast to health in general, all items were administered with attribution to a specific disease (osteoarthritis, rheumatoid arthritis, angina, myocardial infarction, congestive heart failure, chronic kidney disease (CKD), diabetes, asthma, or COPD). Responses from 5418 adults were analyzed as five disease groups: arthritis, cardiovascular, CKD, diabetes, and respiratory. Unidimensionality, item parameter and scale-level invariance, reliability, validity and responsiveness to change during 9-month follow-up were evaluated by disease group and for all groups combined using multi-group confirmatory factor analysis (MGCFA), item response theory (IRT) and analysis of variance methods. QDIS was normed in an independent chronically ill US population sample (N = 4120).ResultsMGCFA confirmed a 1-factor model, justifying a summary score estimated using equal parameters for each item across disease groups. In support of standardized IRT-based scoring, correlations were very high between disease-specific and standardized IRT item slopes (r = 0.88–0.96), thresholds (r = 0.93–0.99) and person-level scores (r ≥ 0.99). Internal consistency, test-retest and person-level IRT reliability were consistently satisfactory across groups. In support of interpreting QDIS as a disease-specific measure, in comparison with generic measures, QDIS consistently discriminated markedly better across disease severity levels, correlated higher with other disease-specific measures in cross-sectional tests, and was more responsive in comparisons of groups with better, same or worse evaluations of disease-specific outcomes at the 9-month follow-up.ConclusionsStandardization of content and scoring across diseases was shown to be justified psychometrically and enabled the first summary measure of disease-specific QOL impact normed in the chronically ill population. This disease-specific approach substantially improves discriminant validity and responsiveness over generic measures and provides a basis for better understanding the relative QOL impact of multiple chronic conditions in research and clinical practice.

【 授权许可】

CC BY   
© Ware et al. 2016