Supporting care engagement in primary care; the development of a maturity matrix.

backgroundCare engagement or active patient involvement in healthcare contributes to the quality of primary care, but organisational preconditions in routine practice need to be aligned. A Maturity Matrix for Care Engagement to assess and discuss these preconditions in the general practice team was developed and tested on feasibility and acceptability in general practice. METHODS AND

findingsA systematic user-centred approach was applied, starting with a scoping literature search to describe the domains on the horizontal axis of the maturity matrix. The domains and growing steps (vertical axis) were refined by patients (n = 16) and general practice staff (n = 11) in three focus group discussions and reviewed by six experts (local facilitators and scientists). Seven domains could be distinguished: Personalised Care, Shared Decision Making, Self-Management, Patient as Partner, Supportive Means, Patient Environment, and Teamwork among Healthcare Professionals. The growing steps described three to six activities per domain (n = 32 in total) that contribute to care engagement. Local facilitators implemented the tool in two general practice teams according to a user guide, starting with a two-hour kick-off meeting on care engagement. In the next step, practitioners, nurses and assistants in each practice indicated their score on the domains individually. The scores were discussed in the facilitated practice meeting which was aimed at SMART improvement plans. Feasibility and acceptability were assessed in interviews showing that the tool was well received by the pilot practices, although the practice assistants had difficulties scoring some of the activities as they did not always relate to their daily work. An assessment after three months showed changes in practice organisation towards increased care engagement.

conclusionsThe maturity matrix on care engagement is a tool to identify the organisational practice maturity for care engagement. Suggested adaptations must be implemented before large-scale testing.