Objective
Patient-reported outcomes (PROs) are essential when evaluating many new treatments in health care, yet current measures have been limited by a lack of precision, standardization and comparability of scores across studies and diseases. The Patient-Reported Outcomes Measurement Information System (PROMIS™) provides item banks that offer the potential for PRO measurement that is efficient (minimizes item number without compromising reliability) flexible (enables optional use of interchangeable items), and precise (has minimal error in estimate) measurement of commonly-studied PROs. We report results from the first large-scale testing of PROMIS items.
Study Design and Setting
Fourteen item pools were tested in the U.S. general population and clinical groups using an online panel and clinic recruitment. A scale-setting sub-sample was created reflecting demographics proportional to the 2000 U.S. census.
Results
Using item response theory (graded response model), 11 item banks were calibrated on a sample of 21,133, measuring components of self-reported physical, mental and social health, along with a 10-item global health scale. Short forms from each bank were developed and compared to the overall bank as well as with other well-validated and widely accepted (“legacy”) measures. All item banks demonstrated good reliability across the majority of the score distributions. Construct validity was supported by moderate to strong correlations with legacy measures.
Conclusion
PROMIS item banks and their short forms provide evidence they are reliable and precise measures of generic symptoms and functional reports comparable to legacy instruments. Further testing will continue to validate and test PROMIS items and banks in diverse clinical populations.
The NIH PROMIS network derived a consensus-based framework for self-reported health, systematically reviewed available instruments and datasets that address the initial PROMIS domains. Qualitative item research led to the first wave of network testing which began in the second year.
The development of these minimum measurement standards is intended to promote the appropriate use of PRO measures to inform PCOR and CER, which in turn can improve the effectiveness and efficiency of healthcare delivery. A next step is to expand these minimum standards to identify best practices for selecting decision-relevant PRO measures.
When used appropriately, IRT can be a powerful tool for questionnaire development, evaluation, and refinement, resulting in precise, valid, and relatively brief instruments that minimize response burden.
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