We sought to determine if real-time patient simulation technology, designed to mimic a patient visit, could improve clinicians’ knowledge/competence regarding the management of hypoglycemia in patients with type 2 diabetes (T2D). The patient simulation technology, DecisionSim, was incorporated as part of a live symposium, and changes in competence and knowledge were evaluated using pre-/post-assessment questions. A Chi-Square test was used to analyze the percentage of correct responses and determine statistical significance (p <0.05 indicated statistical significance). The live activity took place on October 26, 2018. In total, 66 allied health professionals (PAs, RNs, NPs, PharmDs, CDE/RDs) and 41 MDs/DOs answered the assessment questions. An increase in knowledge was observed, albeit not statistically significant (4% relative increase compared to baseline, p = 0.6). A significant increase in competence in selecting the most appropriate treatment to address hypoglycemia risk for a patient with T2D was observed (120% relative increase compared to baseline, p <0.0001). 82% selected the correct treatment decisions in the branching simulation platform, including the intensification of therapy that addresses HbA1c goals while minimizing the risk of hypoglycemia in a virtual patient with T2D. Additionally, 83% indicated in the post-activity survey that they would make changes to practice based on information received, including to provide patient-centered care, assess the current diabetes guidelines, and use diabetes treatments that minimize hypoglycemia. Continued educational gaps were identified: lack of knowledge about the benefits of GLP-1RA/insulin combinations (17%), and lack of competence in individualizing T2D therapy in the context of hypoglycemia risk (21%). These results indicate that simulation-based CME can lead to significant improvements in competence related to hypoglycemia management, as well as commitment to change among learners.


S. Karandrea: None. N. Agarwal: None. A. Jamrogiewicz: None.


Sanofi US (IME-2017-12078)

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