QOL Disease-specific Impact Scale (QDIS®) enables more specific outcome measurements across chronic disease conditions*

JWRG’s multi-year NIH-sponsored Disease Specific Impact CAT (DICAT) Project improved patient reported outcome (PRO) estimates for disease-specific health-related quality of life (QOL). Improvements include:

Broadened QOL domain content (Physical and Role Functioning, Health Outlook, Social activities, Fatigue, Sleep, Cognitive functioning and Emotional Health)

Standardized content and US chronically ill norm-based scoring across chronic disease conditions.

The main difference, in comparison with generic QOL tools, is QDIS item attributions to a specific disease or condition as opposed to health in general. For example, a QDIS question for chronic kidney disease asks, “How much did your kidney disease limit your everyday activities or your quality of life?”, while the same question was also asked with attribution to specific diseases (osteoarthritis, rheumatoid arthritis, angina, myocardial infarction, congestive heart failure, , diabetes, asthma or COPD) in early DICAT project studies. This standardization of content and scoring of disease-specific impact across conditions combines the precision and discrimination of disease-specific with the content representation of generic QOL measures. Further, impact estimates for all diseases can be compared on the same metric and interpreted using norm-based scores computed from representative population samples of chronically ill adults (mean=50, SD=10).

The methods are documented and results from tests of crucial assumptions underlying the QDIS approach were evaluated favorably in an article published in Health and Quality of Life Outcomes. Briefly, a bank of 49 disease impact items was constructed and calibrated to represent the frequently measured QOL content areas (see above) b y applying different operational definitions including limitations in functioning, feelings and health outlook evaluations. Responses (N= 5,418) for adults were analyzed by disease group and for all groups combined to confirm hypothesized unidimensionality, item parameter and scale-level invariance, reliability and validity using multi-group confirmatory factor analysis and item response theory (IRT) methods. QDIS was normed in an independent NORC sample representing chronically ill US population adults (N=4,120). In support of the validity of disease-specific attributions, QDIS discriminated significantly better than the generic SF-8™ Health Survey across groups differing in disease severity levels and was more responsive across groups differing in their evaluations (better, same or worse) of their changes in specific disease conditions in follow-up surveys.

By integrating the richness of broader QOL item content with disease-specific attributions and by standardizing scoring metrics, QDIS achieves some of the advantages of both disease-specific and generic measurement traditions. Because all disease-specific QDIS scores are on the same metric, clinicians can better compare the relative specific impact of each of a patient’s comorbid conditions with more specific and actionable information than is possible with generic measures. In addition, for observational outcomes research, QDIS provides a practical way of adjusting for case-mix differences in QOL impact for each disease condition or an aggregate estimate of total multiple chronic condition QOL impact. QDIS also may enable a practical short-cut to achieving disease-specific QOL impact estimates for conditions for which comprehensive measures are not available, such as some rare diseases, or in the evaluation of orphan drugs.

In summary, QDIS standardization of content and scoring based upon a single (1-factor model) disease-specific summary impact score for each disease condition has proven to be both psychometrically sound and to improve validity over legacy generic tools for purposes of responding to clinically defined group differences across diagnoses studied to date. Directly comparable single item (QDIS-1), static multi-item (QDIS-7) or CAT-based (QDIS-CAT) administration estimates offer flexibility in managing respondent burden for each disease and enabling the first norm-based scoring and interpretation of disease-specific QOL impact across conditions. The JWRG DICAT Project launch of disease-specific QOL measurement innovation appears to be on the right track toward filling the gaps between specific symptoms that fail to comprehensively capture disease-specific QOL impact and generic QOL measures that are not disease-specific.