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BackgroundAfter incorporating quality improvement (QI) education as a required curriculum for our trainees in 2010, a need arose to readdress our didactic sessions as they were too long, difficult to schedule, and resulting in a drop in attendance. A ‘flipped classroom’ (FC) model to deliver QI education was touted to be an effective delivery method as it allows the trainees to view didactic materials on videos, on their own time, and uses the classroom to clarify concepts and employ learned tools on case-based scenarios including workshops.MethodsThe Mayo Quality Academy prepared 29 videos that incorporated the previously delivered 17 weekly didactic sessions, for a total duration of 135 min. The half-day session clarified questions related to the videos, followed by case examples and a hands-on workshop on how to perform and utilize a few commonly used QI tools and methods.ResultsSeven trainees participated. There was a significant improvement in knowledge as measured by pre- and post-FC model test results [improvement by 40.34% (SD 16.34), p<0.001]. The survey results were overall positive about the FC model with all trainees strongly agreeing that we should continue with this model to deliver QI education.ConclusionsThe pilot project of using the FC model to deliver QI education was successful in a small sample of trainees.

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BackgroundLittle is known about how practicing Internal Medicine (IM) clinicians perceive diagnostic error, and whether perceptions are in agreement with the published literature.MethodsA 16-question survey was administered across two IM practices: one a referral practice providing care for patients traveling for a second opinion and the other a traditional community-based primary care practice. Our aim was to identify individual- and system-level factors contributing to diagnostic error (primary outcome) and conditions at greatest risk of diagnostic error (secondary outcome).ResultsSixty-five of 125 clinicians surveyed (51%) responded. The most commonly perceived individual factors contributing to diagnostic error included atypical patient presentations (83%), failure to consider other diagnoses (63%) and inadequate follow-up of test results (53%). The most commonly cited system-level factors included cognitive burden created by the volume of data in the electronic health record (EHR) (68%), lack of time to think (64%) and systems that do not support collaboration (40%). Conditions felt to be at greatest risk of diagnostic error included cancer (46%), pulmonary embolism (43%) and infection (37%).ConclusionsInadequate clinician time and sub-optimal patient and test follow-up are perceived by IM clinicians to be persistent contributors to diagnostic error. Clinician perceptions of conditions at greatest risk of diagnostic error may differ from the published literature.

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