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Learning Health Systems Panel

Series Overview

More Details on the Learning Health Systems Panel

In 2018, the AHRQ Evidence-based Practice Center (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 is convening 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 is generating ideas, providing feedback, and making improvements to products and tools. In 2020-21, learning health systems represented in the panel will implement and evaluate materials. To conduct this 3-year project, the American Institutes for Research (AIR) is being supported by Kaiser Permanente Northwest, the University of California, San Francisco, and expert consultants.

Key tasks and activities include:

  • Convene a learning health systems panel.
  • Develop products.
    • Develop products that learning health systems can use to assess and integrate EPC evidence review findings into routine operations, including a Summary of Findings tool that will help the user quickly evaluate the relevance of evidence. This tool includes brief, summarized information about key review findings; review questions; contextual information about other related systematic reviews and clinical guidelines; clinical and policy implications; and review limitations. This tool and others, including a data visualization tool, will be available to users via a dynamic, interactive website.
    • 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.