There are several good reasons. Among the most important:

PROMIS measures have greater precision than most conventional measures. Greater precision (less error) enhances power in a less costly way than increasing sample size.

PROMIS measures have a larger range of measurement than most conventional measures, decreasing floor and ceiling effects as a result.

PROMIS measures do all this with fewer items than conventional measures, thereby decreasing respondent burden. When used as computerized adaptive tests, our experience is that PROMIS measures require just 4-6 items for precise measurement of health-related constructs.

PROMIS measures provide a common metric that can be used across diverse clinical conditions and diverse samples. The metric is reported as a T-score (mean = 50, standard deviation = 10) and has been normed against the US general population. This metric has also been linked to many other conventional measures, and even if other measures are used, it may be possible to report results on the PROMIS metric, a considerable advantage for ensuring comparability across studies.