Learning Lab – Advanced Data Science for Healthcare Quality Improvement
Speaker(s): Mark Sendak, MD, MPP | Emily Sterrett, MD | Will Knechtle, MBA, MPH
Healthcare delivery organizations (HDOs) are rapidly integrating artificial intelligence (AI) into clinical and operational workflows. However, many HDOs lack AI product lifecycle management capabilities, and the return-on-investment associated with AI implementation is highly variable. In this session, an interdisciplinary team of experts from the Duke Institute for Health Innovation (DIHI) and Duke Health will describe best practices for AI integration.
The presenters will describe how AI technologies can augment and complement quality and safety programs within HDOs, provide specific examples from the inpatient and outpatient context, as well as examples from population health management programs. The presenters will share lessons from HDOs across the country advancing internal AI capabilities.
The presentation will draw on the work of Health AI Partnership (HAIP), which supports well-resourced academic medical centers as well as community health centers and community hospitals. The presentation will end with a framework for how organizations can begin building AI product lifecycle management capabilities to advance the safe, effective, and equitable use of AI in healthcare.
Learning Objectives:
- Understand how AI can augment quality and safety programs to improve healthcare
- Understand the limitations and risks of AI integration in quality and safety programs, including automation bias and potential for discrimination
- Become familiar with specific examples of how AI technologies can improve quality and safety of patient care in different care delivery contexts
- Appreciate the different ways high-resource and low-resource organizations implement AI product lifecycle management activities internally
- Present opportunities for quality professionals to begin their journey advancing AI product lifecycle management capabilities within their organizations
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