PREFACE Applying item response theory to enhance health outcomes assessment Bryce B. Reeve Æ Ron D. Hays Æ Chih-Hung Chang Æ Eleanor M. Perfetto Published online: 30 May 2007 Ó Springer Science+Business Media B.V. 2007 Introduction In June 2004, the National Cancer Institute and Drug Information Association co-sponsored a conference focused on developing patient-reported outcome (PRO) questionnaires, analyzing data collected from patients, and utilizing findings to enhance decision making for treatment and health policy, ‘‘Advances in Health Outcomes Mea- surement: Exploring the Current State and the Future of Item Response Theory (IRT), Item Banks, and Computer- Adaptive Testing.’’ Invited speakers were internationally recognized experts in psychometrics and health-outcomes measurement. Their rich experiences are reflected in the articles in this supplement that focus on describing the methods of modern measurement theory and its applica- tions, as well as challenges for improving PRO measures such as pain, fatigue, physical function, and emotional distress. Many health outcomes instruments used in clinical research and practice were developed based on input from experienced researchers, clinicians, and patients. However, concerns have been raised that these instruments are cumbersome for respondents, burdensome for clinical care sites, not applicable over the continuum of care or in a variety of research settings, suffering from floor and ceiling effects, and/or lacking a standardized scoring metric to allow comparisons across different health conditions [1, 2]. The methods from modern measurement theory, which includes IRT, provide a powerful framework to address these limitations and to build instruments that are more efficient, reliable, and valid measures of health-related quality of life (HRQOL). Potential benefits of item response theory for improving health outcomes measurement The Scientific Advisory Committee of the Medical Out- comes Trust [3] identified eight key attributes of an instrument that are critical for judging its strength for measuring the health of a population or an individual. Specifically, an instrument should be evaluated for its conceptual and measurement model, reliability, validity, responsiveness, interpretability, burden, translations, and cultural adaptability. Developing a ‘‘quality’’ health-out- comes instrument to meet such standards requires a multi- disciplinary team of content experts and methodologists, to use a variety of questionnaire design and evaluation tools along with patient input. The articles in this special issue of Quality of Life Research focus on the contributions of IRT for assessing health-related outcomes. IRT is a collection of statistical models and methods used for item analysis in multi-item scales that measure a latent construct like fatigue, and for estimating an individual’s score for the construct based on their responses to those items. IRT models the relationship between a person’s health status and their probability of B. B. Reeve (&) National Cancer Institute, Bethesda, MD 20892-7344, USA e-mail: Bryce.Reeve@nih.gov R. D. Hays UCLA School of Medicine, Los Angeles, CA, USA C.-H. Chang Northwestern University Feinberg School of Medicine, Chicago, USA E. M. Perfetto Payment Policy Analysis, Global Outcomes Research, New York, USA 123 Qual Life Res (2007) 16:1–3 DOI 10.1007/s11136-007-9220-6