Searching for an efficient institutional review board review model: Interrelationship of trainee-investigators, funding, and initial approval

In this study we sought to identify variables associated with institutional review board (IRB) decisions to develop an efficient “pre-IRB” review model. We explored several variables, including relationships among the identification of trainees as investigators, external sources of funding, and initial approval. The sample consisted of all new submissions reviewed by the 2 medical IRBs at the University of Miami (UM) during a 1-year period. Trainees included students, residents, and fellows. At least 1 trainee had to be identified for a proposal to be considered a trainee submission. The medical-science committees (MSCs) were similar with regard to the numbers of new submissions they reviewed during convened meetings (MSC-A 242, MSC-B 241) and the percentages of proposals that were initially approved (MSC-A 52.9%, MSC-B 53.1%). Approved submissions were defined as those initially approved or conditionally approved pending minor modifications. We noted a robust statistical difference between the percentages of trainee submissions initially approved (39.9%) and submissions that did not identify a trainee (59.4%) (P<.0001). Of the proposals that were initially not approved (tabled [deferred] or rejected [not approved]), 28.9% of those including a trainee were rejected, compared with 11.0% without a trainee (P<.001). Proposals in which the source of funding was identified were more likely to be approved (64.2%) than were those in which it was not (30.8%) (P<.0001). Funding also seemed to influence the trainee and initial-approval interaction. Our results show that new submissions that identified trainee investigators were more likely to be deferred or not approved than those that did not. Nonapproved proposals that identified a trainee were 3.8 times more likely to be initially rejected than those that did not. A prereview model could target those submissions that list a trainee, lack funding, or both.