Webinar – Managing Principal Eric Wu and Manager Min Yang Discuss an Innovative and Practical Disease-Specific Quality of Life Impact Scale with Affiliate Dr. John Ware

Event:Introduction to an Innovative and Practical Disease-Specific Quality of Life Impact Scale with Dr. John Ware
Date: May 09, 2017
Host:Analysis Group
Times:9:00–10:30 a.m. (PT) / 12:00–1:30 p.m. (ET)

Analysis Group affiliate Dr. John Ware, the developer of the SF-36® Health Survey and other widely-used generic and disease-specific patient-reported outcomes (PRO), will introduce a practical and innovative new approach to PRO measurement during this webinar. This new tool fills the conceptual and methodological gaps between disease-specific symptoms that do not measure quality of life (QOL) and generic QOL measures that do not measure disease-specific outcomes.

During the webinar, Analysis Group Managing Principal Eric Wu and Manager Min Yang will interview Dr. Ware to discuss practical questions for designing a clinical study using the tool.

The new tool is the Quality of Life Disease Impact Scale (QDIS®), a set of disease-specific scales that standardize the measurement of both content and scoring of QOL impact across chronic conditions. QDIS blends the best of generic and disease-specific measurement traditions. By asking a range of questions about the QOL impact of a specific condition, QDIS retains the advantage of generic measures such as the SF-36, which comprehensively measure physical, mental, and social health. At the same time, each QDIS question increases specificity by using attribution to a specific disease. QDIS scores are standardized across diseases, so scores can be meaningfully compared across conditions and interpreted in relation to available norms for the chronically-ill US general population. 

QDIS scales are much shorter than most legacy PRO. QDIS can be administered as a computerized adaptive test (CAT), a 7-item fixed-length short form, or a single global QDIS impact item. All methods have comparable scoring. 

QDIS has been shown to discriminate better across disease severity levels than generic health surveys and to be more responsive in tests comparing groups differing in disease-specific and generic outcomes. QDIS feasibility and advantages have been demonstrated in Internet-based studies of nine diseases and in samples of 35 conditions in the US general population. The QDIS approach also may provide a practical solution to developing measures of disease-specific QOL impact in rare diseases.


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