UH Scales AI Deployment to Quickly Spot Serious Conditions

Clinical applications of artificial intelligence (AI) continue to grow, but many of these initiatives remain at the pilot or small-scale level. Ohio-based University Hospitals is taking its efforts a step further.

The health system is deploying an AI platform across 13 hospitals and dozens of outpatient facilities to quickly identify conditions like pulmonary embolism, coronary artery calcification, vertebral compression fracture and intracranial hemorrhaging.

The platform, Aidoc’s aiOS, will streamline workflows with access to 17 Food and Drug Administration-cleared AI algorithms.

When a patient arrives at a University Hospitals facility and undergoes a CT scan for an injury or pain, Aidoc's AI analyzes the scan using its algorithms. The technology identifies both expected and unexpected findings, helps physicians prioritize urgent cases and ensures that all flagged conditions are reviewed by the care team. The platform facilitates communication among care team members to enhance collaboration and accelerate treatment.

The platform reportedly addresses common AI implementation challenges such as integrating with existing IT systems, ensuring electronic health record compatibility and managing data and reporting.

"Today's care delivery is incredibly complex with numerous moving parts," Donna Plecha, M.D., chair of radiology at University Hospitals, said in a statement. "Aidoc’s AI technology assists our radiologists in evaluating various patient images, allowing our clinicians to access precise, actionable data quickly. The AI technology enables our care teams to be more accurate and efficient, leading to even more exceptional care for our patients.”

University Hospitals also envisions the platform helping to reduce wait times for outpatient and ambulatory patient visits.