Many clients rely on Patient-Reported Outcomes Measurement Information System (PROMIS) measures developed with National Institutes of Health (NIH) funding. For the most part, I am not a fan. I can appreciate the need for standardization of instruments for interoperability but it is a bit of a Heisenberg Uncertainty dilemma--I would argue the generalization of measures influences the outcome.
"The uncertainty principle says that we cannot measure the position (x) and the momentum (p) of a particle with absolute precision. The more accurately we know one of these values, the less accurately we know the other."--Alok Jha
PRO instruments are anything but standard. A loose classification by the University of Oxford Patient Reported Outcomes Group identifies a variety of instruments, for example, disease-specific, population-specific, dimension specific, generic (SF-36), individualized, summary items, utility measures and so on.
Limitations include but are not limited to the lack of application or comparison to general population, few response categories, broad focus, lack of application to real world, many developed in the 90s or older, pre-dating the digital landscape and advanced knowledge of cognitive frameworks, and many other reasons to be wary of the generalized approach to gathering subjective data.
An additional limitation can be attributed to low rigor of survey questions, choice architecture, limited disease state knowledge in question design, satisficing, and improper analyses. The rise of "do-it yourself" survey instruments has unwittingly polluted the data landscape with worthless noisy and low-value data.
Look no farther than personalized medicine to see where we are losing the trees through the forest. We attribute differences in microbiology and biochemical profiles to meaningful clinical outcomes that for the most part, have not materialized.
“Research is formalized curiosity. It is poking and prying with a purpose. ” -Zora Neale Hurston