Appreciative Inquiry for Quality Improvement in Primary Care Practices
Quality Management in Healthcare/Lipincott Williams & Wilkins,
January (1st Quarter/Winter)
Purpose: To test the effect of an Appreciative Inquiry (AI) quality improvement strategy, on clinical quality management and practice development outcomes. AI enables discovery of shared motivations, envisioning a transformed future, and learning around implementation of a change process.
Methods: Thirty diverse primary care practices were randomly assigned to receive an AI-based intervention focused on a practice-chosen topic and on improving preventive service delivery (PSD) rates. Medical record review assessed change in PSD rates. Ethnographic fieldnotes and observational checklist analysis used editing and immersion/crystallization methods to identify factors affecting intervention implementation and practice development outcomes.
Results: PSD rates did not change. Fieldnote analysis suggested that the intervention elicited core motivations, facilitated development of a shared vision, defined change objectives and fostered respectful interactions. Practices most likely to implement the intervention or develop new practice capacities exhibited one or more of the following: support from key leader(s), a sense of urgency for change, a mission focused on serving patients, health care system and practice flexibility, and a history of constructive practice change.
Conclusions: An AI approach and enabling practice conditions can lead to intervention implementation and practice development by connecting individual and practice strengths and motivations to the change objective.