Abstracts

Rationale: Recognizing acute repetitive seizures (ARS) and having a Seizure Action Plan (SAP) that is developed through shared decision-making can improve quality of life for the millions of individuals impacted by epilepsy. Emerging treatments have the potential to enhance available options, thereby altering the treatment landscape reflected in SAPs.Continuing medical education (CME) has an opportunity to play a valuable role as a key stakeholder assisting HCPs to integrate shared decision-making into the development of much needed SAPs for patients with different seizure types. However, HCPs face several challenges when managing patients with ARS, and it is important to understand the barriers preventing HCPs from implementing best practices. The goal of this study was to utilize predictive modeling to determine factors influencing implementation of SAPs so that any barriers may be addressed in future educational activities, or even on an individual HCP basis. Methods: Educational outcomes data were obtained from an educational activity on developing and implementing SAPs, which consisted of a faculty-led live and on-demand webcast, including a 60-minute panel discussion as well as a 30-minute Q&A. In addition, audio recordings of patient interviews were integrated into the content. HCP surveys assessing knowledge, confidence, and behavior were administered before, immediately following, and 3 months following the activity. An analysis using PredictCME (based on chi-square automatic interaction detection) was conducted on data from the pre-activity survey, which included a behavior question evaluating HCPs’ promotion of active patient participation in shared decision-making when developing SAPs. Data from this behavior question were used as the response variable in the analysis, with demographics, knowledge, confidence, and evaluation data entered as predictors. Results: Over 4,580 HCPs participated in the activity, with pre-survey data from 204 participants available for analysis. Findings revealed academic degree to be the strongest predictor of behavior, with NPs, MDs, DOs, and PAs more likely than PharmDs, RPhs, and RNs to promote shared decision-making with patients to create SAPs (31.5% vs. 6.1%, respectively, χ2(1) = 23.47, p < .001). A secondary predictor was confidence, but only for those who were NPs, MDs, DOs, and PAs (thereby demonstrating an interaction); those who were confident were more likely to implement shared decision-making for developing SAPs than those who were not confident (50.0% versus 22.4%, respectively, χ2(2) = 17.37, p < .01). Conclusions: Results from the PredictCME analysis are not surprising; NPs, MDs, DOs, and PAs have more opportunities to work directly with patients to develop SAPs and would therefore be expected to implement the behavior more often. The secondary predictor of confidence is also not surprising, as prior studies have shown confidence to predict behavior (data on file). Taken together, these findings suggest that building HCP confidence is an important step toward encouraging best practices in developing SAPs with patients. Future education can address HCP confidence, and perhaps sharing these findings with HCPs may also encourage them to reflect on ways they can increase utilization of SAPs in their practices. Funding: The educational activity described in this presentation was supported by an educational grant from Upsher-Smith Laboratories, Inc.