Spend :01 of your time each Monday morning as Twelve:01 delivers timely tools, trends, strategies, and/or compliance insights for the CME/CE enterprise.
Notion AI has evolved into a central hub for research synthesis, note-taking, and knowledge management, and a recent update makes it more useful for CME/CE teams working across platforms. New federated connectors (i.e., integration tools) now let Notion data flow directly into Microsoft 365 workflows, eliminating the manual export/import cycle between Notion and Outlook or Teams. For CME/CE professionals juggling activity planning docs, compliance trackers, or committee notes across both ecosystems, this closes a real workflow gap. As AI tools mature, interoperability between platforms is becoming a critical feature.
The American Board of Surgery (ABS) has added a new credit type, Quality Improvement (Part IV – QA), under Accredited CME Improvement Activity. ABS now supports several credit combinations within a single activity: Accredited CME alone, Accredited CME plus Self-Assessment, Quality Improvement with or without Accredited CME, and all three combined. Self-Assessment credit cannot be reported independently. For accredited providers registering activities for MOC credit, this expands the ways surgeon learners can earn credit toward their continuing certification requirements. ACCME is hosting two informational webinars on the new credit type, August 19 and September 8, for providers who want to learn more before updating their activity registration workflows.
A proposed federal rule known as HTI-5 would roll back key transparency requirements for AI used in certified health IT, including standardized disclosures about validation, fairness, performance, and ongoing risk management. Without such disclosures, health systems may need to build their own processes for evaluating and monitoring AI tools, including those that fall outside FDA regulation. For the CME/CE enterprise, that governance gap creates an educational opportunity that extends beyond teaching clinicians how to use AI – leaders may increasingly need competencies in evaluating evidence, recognizing model limitations, and understanding organizational accountability for AI-enabled care. Education planners should consider whether emerging AI curricula adequately address these governance responsibilities, particularly for quality, safety, compliance, and clinical leadership audiences.
