Using the Pragmatic-Explanatory Continuum Indicator Summary (PRECIS) model in clinical research: Application to refine a practice-based research network (PBRN) study

Background: pragmatic clinical trials (pcts) are increasingly recommended to evaluate interventions in realworld conditions. although pcts share a common approach of evaluating variables from actual clinical practice,multiple characteristics can differ. these differences affect interpretation of the trial. the pragmatic-explanatory continuum indicator summary (precis) model was developed in 2009 by the consort work group on pragmatic trials,published by thorpe et al,to aid in trial design. precis provides clarity about the generalizability and applicability of a trial by depicting multiple study characteristics. we recently completed a national institutes of health-sponsored pilot study examining health-related outcomes for 2 complementary therapies for chronic low back pain in patients referred by primary care providers in the kentucky ambulatory network. in preparation for a larger study,we sought to characterize the pragmatic features of the study to aid in our design decisions. the purpose of this article is to introduce clinical researchers to the precis model while demonstrating its application to refine a practice based research network study.method: we designed an exercise using an audience response system integrated with a works in progress presentation to experienced researchers at the university of kentucky to examine our study methodologies of parameters suggested by the precis model.results: the exercise went smoothly and participants remained engaged throughout. the study received an overall summary score of 30.17 (scale of 0 to 48; a higher score indicates a more pragmatic approach),with component scores that differentiate design components of the study. a polar chart is presented to depict the pragmatism of the overall study methodology across each of these components.conclusions: the study was not as pragmatic as expected. the exercise results seem to be useful in identifying necessary refinements to the study methodology that may benefit future study design and increase generalizability. readers can identify how the precis model may be used to provide clarity and transparency for proposed or existing studies and may wish to replicate our exercise in planning their own studies.