Today’s CIOs are faced with countless opportunities to invest in AI, but with little more than promises that any project will result in measurable ROI. If we believe AI can transform operations across the hospital, what’s the right decision framework?
While the EHR remains the most important IT investment, it typically relies on manual documentation. AI built on incomplete, inaccurate, or delayed data produces recommendations nobody follows. And that’s where things fall apart.
Two leading systems drove results from their AI strategies by starting with the data. Houston Methodist’s peer-reviewed research found that computer vision measurably increased case volume and reduced late-ending surgical days without adding staff, hours, or rooms.
Tampa General found that ambient AI’s influx of timely, trustworthy data significantly reduced procedure room disruptions that lead to case delays and surgical site infections.
Register to learn:
- The criteria health systems use to evaluate AI opportunities against ROI, team, and patient impact
- Integration requirements to ensure AI projects create more value from the EHR and other existing IT investments
- How to evaluate AI technologies — computer vision, agentic assistants, deep neural networks — starting with data quality
- The best practices, lessons learned, and outstanding questions from two high-volume surgical programs