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Marlee Ravid

Harnessing AI for Clinical and Operational Efficiency in Radiology: In Conversation with Sriram Mannava, MD, Columbus Radiology

Adoption, Incidental Pulmonary Embolism, Outcomes, Pulmonary Embolism, Turnaround Time
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The implementation of AI in radiology has been nothing short of transformative, offering both financial and clinical benefits. As hospitals and radiology practices across the country continue to grapple with increasing patient volumes and staffing challenges, AI has emerged as a crucial tool in improving patient care and streamlining workflows. We spoke with Sriram Mannava, MD, President of Columbus Radiology, a Radiology Partners practice, on the positive impact Aidoc has brought to his practice.

AI Implementation: Financial and Clinical Benefits

Dr. Mannava highlighted how AI has improved efficiency in Columbus Radiology’s operations and workflows. One of the most significant benefits observed is the reduction in turnaround times. Faster turnaround time not only accelerates patient care and treatment but also decreases the length of stay in emergency departments and reduces the need for unnecessary testing. This efficiency is not just a win for patient care but also offers considerable financial savings for hospital systems.

According to Dr. Mannava, “Hospital administrations are gradually recognizing the financial and clinical advantages of AI. It’s a game-changer for long-term sustainability in radiology.” This recognition is leading to increased investment in AI technologies, particularly as radiologists and clinicians collaborate to present compelling cases to hospital administrative teams.

Improving Patient Care With AI

Despite the challenges posed by high patient volumes and overextended staff, AI has proven its worth by aiding in the identification of critical conditions. Dr. Mannava shares an example where AI-assisted workflows have led to quicker identification of conditions like head bleeds and pulmonary emboli (PE), which are critical in emergency settings.

He recounts, “In our practice, the facilities running Aidoc’s AI algorithms have shown quicker turnaround times and reduced instances of incidental PE or prolonged head bleeds. The sensitivity and specificity of these algorithms are impressively high, offering radiologists a powerful tool to assist them in their routine work.” This heightened accuracy is particularly vital in scenarios where the sheer volume of cases might lead to diagnostic fatigue.

Streamlining Radiology Workflows With AI

The operational integration of AI into radiology practices has been a game-changer, particularly in addressing the volume crunch that radiologists face today. As Dr. Mannava notes, excessive imaging orders, especially in emergency departments, have made it challenging for radiologists to keep up. AI helps by allowing for quicker triage of urgent and incidental findings. In one example, Dr. Mannava shared how AI flagged a pulmonary embolism on an abdominal CT scan—demonstrating the opportunity for AI to provide value in identifying the unexpected.

The Way Forward With AI

The adoption of AI in radiology is no longer a question of if, but when. As demonstrated by the experiences of Columbus Radiology under Dr. Mannava’s leadership, AI offers unparalleled benefits in improving patient outcomes, enhancing operational efficiency, and providing financial advantages to healthcare systems. By leveraging AI, radiology practices can navigate the challenges of high patient volumes and staffing shortages, ensuring that they deliver the best possible care to patients and the tools necessary to their providers.

Watch the full interview with Sriram Mannava, MD,  President of Columbus Radiology, a Radiology Partners practice, by clicking here.

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Marlee Ravid

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