Friday 12 April | 13:30-14:15

Format: Online session
Stream: Science
Content filters: n/a

Why do learning and evaluation often take a back seat in QI? The elements of good improvement design – a clear description of program theory, understanding and mitigating bias, accounting for secular change and the “counterfactual”, and considering a broader range of study designs – can accelerate learning and impact. In this session we will present examples of QI projects that demonstrate why and how programs succeed or fail. We will propose a simple 3-part framework to promote learning, evaluation and dissemination. We will be your guides, building your knowledge and confidence to move these important principles to the “front seat” of your improvement work.

As a result of the session, participants will be able to:

1. Appreciate gaps in rigour and credibility of QI programs


2. Understand and apply methods for mitigating bias and strengthening causal inference


3. Apply rigorous approaches to designing QI programs that promote credible results and learning


4. Understand, explain, and test commonly used evaluation frameworks and measures


5. Deploy IHI’s evolving evaluation framework for adaptive designs, learning and dissemination

Pierre Barker Institute of Healthcare Improvement (IHI), USA

Don Goldman Institute of Healthcare Improvement (IHI), USA