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Exclusive survey report

The State of Healthcare Quality Improvement

How AI Accelerates QI and Automates Quality Interventions at Scale

Key findings from a survey of 100 quality leaders

Care inconsistency drains $345 billion annually from the U.S. healthcare system. While everyone wants better patient outcomes, payers and CMS are equally focused on controlling costs. That's why regulatory accountability around quality is intensifying—with models like TEAM set to become mandatory for one in five U.S. hospitals starting in 2026.

But are hospitals equipped to meet the challenge? Our survey reveals a troubling gap: 77% of quality leaders say their organization is not fully prepared for TEAM requirements. The root cause is knowledge chaos. When protocols are inaccessible, training varies by preceptor, and adherence can't be measured, even well-resourced teams struggle to demonstrate the standardized, accountable care that new regulations demand.

The good news: Our report identifies exactly what's breaking—and how high-performing quality programs are fixing it.

Report highlights:

  • 76% or quality leaders cite knowledge chaos—fragmented systems, inconsistent training, and lack of protocol visibility—as the top barrier to success
  • 89% already use digital knowledge tools, but they're creating new silos instead of eliminating them
  • 64% say they don’t feel empowered to affect meaningful change, despite a strong corollary between empowerment and QI success
  • 61% believe AI can reduce burnout and improve care consistency. High performers are 9X more likely to see AI as transformative.
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Proven at 100+ hospitals, including Mount Sinai and Brigham & Women's

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