Effect of Peer Benchmarking on Specialist Electronic Consult Performance in a Los Angeles Safety-Net: a Cluster Randomized Trial

Background: Since the advent of COVID-19, accelerated adoption of systems that reduce face-to-face encounters has outpaced training and best practices. Electronic consultations (eConsults), structured communications between PCPs and specialists regarding a case, have been effective in reducing face-to-face specialist encounters. As the health system rapidly adapts to multiple new practices and communication tools, new mechanisms to measure and improve performance in this context are needed. Objective: To test whether feedback comparing physicians to top performing peers using co-specialists’ ratings improves performance. Design: Cluster-randomized controlled trial Participants: Eighty facility-specialty clusters and 214 clinicians Intervention: Providers in the feedback arms were sent messages that announced their membership in an elite group of “Top Performers” or provided actionable recommendations with feedback for providers that were “Not Top Performers.” Main Measures: The primary outcomes were changes in peer ratings in the following performance dimensions after feedback was received: (1) elicitation of information from primary care practitioners; (2) adherence to institutional clinical guidelines; (3) agreement with peer’s medical decision-making; (4) educational value; (5) relationship building. Key Results: Specialists showed significant improvements on 3 of the 5 consultation performance dimensions: medical decision-making (odds ratio 1.52, 95% confidence interval 1.08–2.14, p<.05), educational value (1.86, 1.17–2.96) and relationship building (1.63, 1.13–2.35) (both p<.01). Conclusions: The pandemic has shed light on clinicians’ commitment to professionalism and service as we rapidly adapt to changing paradigms. Interventions that appeal to professional norms can help improve the efficacy of new systems of practice. We show that specialists’ performance can be measured and improved with feedback using aspirational norms. Trial Registration: clinicaltrials.gov