Dr. McMahon encourages innovation and experimentation in CME
We want to do everything we can to encourage innovation and experimentation in CME, so that educators are free to respond nimbly to their learners’ changing needs while staying true to core principles for educational excellence and independence. We thank accredited CME providers for their participation in this process and look forward to their feedback on our proposal and to our continued work together to drive quality in postgraduate medical education and improve care for the patients and communities we all serve,” said Graham McMahon, MD, MMSc, President and CEO, ACCME.
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Data analysis
Data analysis will rely on three segments (Figure 5):
- Phenomenographic research will draw a picture of how QIE/IPL is perceived. My goal is to make the process as collaborative, iterative and transparent as possible/approved. Therefore, in addition to the standard phenomenographic method illustrated below, to evaluate the findings I will 1) organize a follow-up interview with selected participants and 2) share findings with a few leaders and the public (if approved) and ask for feedback. If there are moderate differences between groups, I will reflect on them. If those differences are significant, it may be possible to create separate outcome spaces for each group.
- A case study of each professional organization involved in the research will be focused on QIE/IPL-related practices and technology, and the official policy used in the organization. That can help us better interpret data from phenomenographic research and get insight into what is possible in reality. For example, in my most recent research (Hlede, 2015) I found that in the ASA all research participants indicated that IPL is the preferred way to go. However, the official policy of the organization doesn’t reflect that.
- Interaction between groups and existing and potential QIE/IPL projects will be analyzed through activity theory, so we can get a better picture of interprofessional activities that at this moment shape perceptions of each profession.
Figure 5. Data analysis.
Reference
Hlede, V. (2015). Interprofessional Learning: Anesthesiologists’ Perspectives. Assignment, Doctoral Programme in E-Research and Technology Enhanced Learning. Department of Educational Research. Lancaster University.
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