New disease-specific QOL impact scale (QDIS®) for multiple chronic conditions published by JWRG
WATERTOWN, MA, JUNE 1, 2016 – JWRG’s multi-year effort to broaden the content of disease-specific health-related quality of life (QOL) measurement with a briefer scale standardized and scored in relation to norms for the chronically ill US population has been documented in an article about the Quality of life Disease Impact Scale (QDIS®), published in Health and Quality of Life Outcomes. QDIS is a suite of disease-specific measures, including a 25-item bank which can be used in computerized adaptive testing, a 7-item fixed-length short form and a global QOL item, each of which estimates a summary QOL disease impact score. The content of QDIS questions is standardized across conditions, but questions vary in their disease-specific attribution. For example, a QDIS question for chronic kidney disease might ask “How much did your kidney disease limit your everyday activities or your quality of life?”, while the same question also might be asked with attribution to asthma. Scores on both the kidney disease impact and asthma impact measures are interpreted in relation to general population norms. By standardizing the content and scoring of disease-specific measures across conditions, QDIS provides a new approach to measurement, one that combines the precision and discrimination of disease-specific measures with the comprehensiveness and standardization of generic QOL measures which are not specific to any disease or treatment.
Crucial assumptions underlying the QDIS approach were evaluated favorably in the Health and Quality of Life Outcomes article, which documents the development of QDIS and Internet administration of QDIS items with attribution to one of nine diseases (osteoarthritis, rheumatoid arthritis, angina, myocardial infarction, congestive heart failure, chronic kidney disease, diabetes, asthma or COPD) to 5,418 chronically ill adults. Psychometric methods used to standardize QDIS scoring across conditions were justified and QDIS reliability, validity and responsiveness were demonstrated for different disease groups and all diseases combined. Methods for norming QDIS in a separate representative sample of 4,120 chronically ill US adults also were described. In support of the validity of disease-specific attributions, QDIS discriminated better than the generic SF-8™ Health Survey across disease severity levels and was more responsive in tests comparing groups who rated their disease-specific outcomes as better, same or worse 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 scores are on the same metric, clinicians can better compare the relative impact of a patient’s multiple conditions using more specific and actionable information than is possible with generic measures. In addition, for observational studies, QDIS may provide a practical way of adjusting for case-mix differences using an aggregate measure of the impact of multiple chronic conditions. 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.
Overall, the QDIS pursuit of disease-specific QOL measurement innovation appears to be on the right track toward filling the conceptual and methodological gaps between disease-specific symptoms that do not measure quality of life and generic QOL measures that do not measure disease-specific outcomes.
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