A Randomized Cross-Over Trial Focused on Clinical Breast Exam Skill Acquisition Using High Fidelity versus Low Fidelity Simulation Models in Rwanda

Objective: Breast cancer incidence is rising for women in low and middle income country (LMIC)s. Growing the health care workforce trained in clinical breast exam (CBE) is critical to mitigating breast cancer globally. We developed a CBE simulation training course and determined whether training on a low-fidelity (LF) simulation model results in similar skill acquisition as training on high-fidelity (HF) models in Rwanda. Design: A single-center randomized educational crossover trial was implemented. A preintervention baseline exam (exam 1), followed by a lecture series (exam 2), and training sessions with assigned simulation models was implemented (exam 3)—participants then crossed over to their unassigned model (exam 4). The primary outcome of this study determined mean difference in CBE exam scores between HF and LF groups. Secondary outcomes identified any provider level traits and changes in overall scores. Setting: The study was implemented at the University Teaching Hospital, Kigali (CHUK) in Rwanda, Africa from July 2014 to March 2015 Participants: Medical students, residents in surgery, obstetrics and gynecology, and internal medicine residents participated in a 1-day CBE simulation training course. Results: A total of 107 individuals were analyzed in each arm of the study. Mean difference in exam scores between HF and LF models in exam 1 to 4 was not significantly different (exam 1 0.08 standard error (SE) = 0.47, p = 0.42; exam 2 0.86, SE = 0.69, p = 0.16; exam 3 0.03, SE = 0.38, p = 0.66; exam 4 0.10 SE = 0.37, p = 0.29). Overall exam scores improved from pre- to post-intervention. Conclusions: Mean difference in exams scores were not significantly different between participants trained with HF versus LF models. LF models can be utilized as cost effective teaching tools for CBE skill acquisition, in resource poor areas.