In 2018, the AHRQ EPC program started a project to enhance learning health systems' adoption of evidence to improve the quality and effectiveness of patient care. To do this, it will convene a learning health systems panel to guide the development of products and tools that will help health systems use findings from EPC evidence reviews. The learning health systems panel will generate ideas, provide feedback, make improvements, and implement and evaluate materials. To conduct this 3-year project, the American Institutes for Research (AIR) will be supported by Cognitive Medical Systems Inc., Kaiser Permanente Northwest, the University of California, San Francisco, and expert consultants.
Key tasks and activities include:
- Convene a learning health systems panel.
- Convene a panel of representatives from a diverse group of 11 learning systems to gather ideas, feedback, and recommendations on topics of interest to health systems, products and tools to help health systems use findings from evidence reviews, and other methods to improve the usefulness and uptake of evidence review findings.
- Develop products.
- Develop products that learning health systems can use to assess and integrate EPC evidence review findings into routine operations. A new tool or resource might include a range of products, such as continuing medical education webinars, a shared decision-making tool, an evidence template, a platform for communication between a learning health system and EPC, or clinical artifacts from clinical decision support systems.
- Conduct virtual cognitive testing of new materials with potential product end-users at learning health systems.
- Implement and evaluate.
- Work with learning health systems to tailor implementation plans to their local context and needs.
- Implement and evaluate products and tools with each participating learning health system.
- Revise products based on the evaluation.
- Describe strategies to overcome implementation challenges, including contextual information about audience characteristics that might affect usability and adoptability.