The future of measuring patient-reported outcomes in rheumatology: Patient-Reported Outcomes Measurement Information System (PROMIS).

The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS; trademarked by the National Institutes of Health) Roadmap initiative (available at www.nihpromis.org) is a cooperative research program designed to develop, evaluate, and standardize item banks to measure patient-reported outcomes across different medical conditions as well as the US population (1). The goal of PROMIS is to develop reliable and valid item banks using item response theory (IRT) that can be administered in a variety of formats including short forms and computerized adaptive tests (CAT) (1–3). IRT is often referred to as “modern psychometric theory,” in contrast to “classic test theory,” or CTT. The basic idea behind both IRT and CTT is that there is some latent construct, or “trait,” underlying an illness experience. This construct cannot be directly measured, but can be indirectly measured by creating items that are scaled and scored. For example, fatigue, pain, disability, or even “happiness” are latent constructs, i.e., subjective feelings—we cannot take a picture, snap a radiograph to view them, or run a blood test to check for them. However, we know they exist. People can experience more or less of these constructs; therefore, it is helpful to try to translate that experience into several levels represented by scores. IRT models the associations between items and the latent construct. Specifically, IRT models describe relationships between a respondent’s underlying level on a construct and the probability of particular item responses. Tests developed with CTT (such as the Health Assessment Questionnaire disability index [HAQ DI] [4], or the Scleroderma Gastrointestinal Tract instrument [5]) require administering all items, even though only some are appropriate for the person’s trait level. Some items are too high for those with low trait levels (e.g., “can you walk 100 yards” to a patient in a wheelchair) or too low for those with high trait levels (e.g., “can you get up from the chair?” to a runner). In contrast, IRT methods make it possible to estimate person trait levels with any subset of items appropriate for the person’s trait levels in an item pool. As such, any set of items from the pool could be administered as a fixed form or, for greatest efficiency, administered as a CAT. CAT is an approach to administering the subset of items in an item bank that are most informative for measuring the health construct in order to achieve a target standard error of measurement. A good item bank will have items that represent a range of content and difficulty, provide high levels of information, and have items that perform equivalently in different subgroups of the target population.