Data Standards Provide a Focus for CME Initiatives

May 17, 2016 9:45 AM – 11:15 AM

Ed Kennedy, BS, Jennifer Dunleavy, MSA, CPA

Since 2010, the Accreditation Council for Continuing Medical Education’s (ACCME) web-based portal, the Program and Activity Reporting System (PARS) has facilitated the collection of program and activity data from accredited continuing medical education (CME) providers.  These providers are the organizations and institutions that comprise the national educational enterprise to fulfill the professional requirements for US physician life-long learning. In recent years, ACCME has leveraged the Medbiquitous Data Standards in the ongoing development of PARS to support two major of strategic initiatives—FDA Risk Evaluation and Mitigation Strategies for Extended-release/Long-Acting Opioids and Collaboration between ACCME and the American Board of Internal Medicine (ABIM) Maintenance of Certification® (MOC) Program. In this demonstration, ACCME’s Senior Vice President for Operations, Jennifer Dunleavy, MSA CPA and Edward Kennedy, Assistant Director of Information and Technology will explore each of these initiatives as case studies in the challenge (and opportunity) presented, the process of leveraging Medbiquitous data standards, and the outcome that has been achieved. The session will conclude with a reflective discussion with participants on (1) what has been learned, and (2) how others might integrate lessons learned into their own strategic data projects.

  • Case Study 1. How did the continuing education accreditation data systems evolve to address new data collection and reporting expectations of a federal continuing health care education mandate?
  • Case Study 2. How can data systems evolve and integrate to simplify the processes of planning, registering, and tracking physician participation in accredited CME that meets ABIM requirements for MOC?

Through the case discussion, the facilitators will address common themes that include strategic collaboration, customer/user value, leveraging existing data standards, and simplification.