Perspectives on Implementing Quality Improvement Collaboratives Effectively: Qualitative Findings for the CHIPRA Demonstration Grant Program
The most frequently pursued intervention in the $100 million, 18-state Children’s Health Insurance Program Reauthorization Act of 2009 (CHIPRA) quality demonstration (2010–2015) was quality improvement collaboratives, which 12 states offered to more than 300 primary care practices. A study was conducted to identify which aspects of these collaboratives were viewed by organizers and participants as working well and which were not.
Some 223 interviews were conducted in these states near the end of their collaboratives. Interview notes were coded and analyzed to identify trends.
Aspects of collaboratives that interviewees valued were aimed at attracting participation, maintaining engagement, or facilitating learning. To attract participants, interviewees recommended offering maintenance-of-certification credits, aligning content with existing financial incentives, hiring a knowledgeable collaborative organizer of the same medical specialty as participants, and having national experts speak at meetings. Positively viewed approaches for maintaining engagement included meeting one-on-one with practices to articulate participation expectations in advance, tying disbursal of stipends to meeting participation expectations, and soliciting feedback and making mid-course adjustments. To facilitate learning, interviewees liked learning from other practices, interactive exercises, practical handouts, and meeting face-to-face with new referral partners.
Prior studies have tended to focus on strategies to maintain engagement. The interviewees valued these features but also valued aspects of collaboratives that attracted participants in the first place and facilitated learning after participants were actively engaged. The findings suggest that a wider array of features may be important when developing or evaluating collaboratives. Collaborative organizers may benefit from incorporating the recommended collaborative features into their own collaboratives
Overview of model