Rationale: Both Dravet syndrome (DS) and Lennox Gastaut syndrome (LGS) are pediatric-onset epileptic encephalopathies that can present a challenge for both timely recognition and determining the optimal therapeutic approach to controlling seizures. To address these challenges, this study utilized an online medical simulation platform to improve the ability of neurologists to assess, diagnose, and select appropriate therapies for the care of patients with either DS or LGS. In addition, this platform allowed neurologist learners to provide rationales for the selection of anti-epileptic therapies.
Methods: The simulation consisted of two cases presented in a platform that allowed physician learners to choose from numerous lab tests and assessment scales as well as thousands of diagnoses, treatments, and procedures matching the scope and depth of actual practice. The clinical decisions made by the learners were analyzed using an artificial intelligence engine and instantaneous clinical guidance was provided employing current evidence-based and expert faculty recommendations. Participant decisions were collected after clinical guidance and compared with each user’s baseline data using a McNemar’s test to assess the impact of simulation-based education on clinical decisions made by participants. Data was collected from June 12, 2020 through October 14, 2020.
Results: The assessment sample consisted of neurologists (n=99 for case 1 and n=59 for case 2) who made clinical decisions within the simulation and proceeded to the concluding debrief section. As a result of clinical guidance provided through simulation, significant improvements were observed in several areas:
- Improvement in the selecting the appropriate tests to confirm a diagnosis of LGS in a patient not responding to an initial anti-seizure medication (P < 0.01 for all comparisons)