March 7, 2018 | Integrated Health Care Conference, Arizona State University Doctor of Behavioral Health Program, Scottsdale, AZ In a keynote lecture, Dr. Ware provided an overview of the history of the conceptualization and measurement of patient-reported outcomes (PROs), and noteworthy methodological advances and their implications for going forward. Applications of item response theory (IRT) methods have improved the quantification of health-related quality of life (QOL) domains and are the basis for more efficient computerized adaptive test (CAT) survey administrations and scoring. However, a consequence of the development of very homogeneous survey item banks preferred by IRT models is a conceptual shift favoring measures of very specific symptoms (e.g., depression) and activities (e.g., walking) as opposed to broader concepts of mental, physical and social functioning and well-being. In contrast, an emphasis on summary measures – the “tips of the QOL icebergs” that enable more efficient adaptive approaches – makes it practical to drill down to measure specific limitations in QOL only when are more likely to occur and to adapt automatically to multiple chronic conditions when they are present. This adaptive approach is the most practical and useful way represent PROs in “big data.” Dr. Ware presented examples of published and forthcoming JWRG findings from evaluations of new generic “super” short-form items that improve survey efficiency over legacy tools and use standardized IRT-based metrics to cross-calibrate new and legacy PROs. New, more valid and responsive disease-specific PROs were also discussed. The latter QOL Disease Impact Scale (QDIS) measures, which are standardized across diseases and […]