A Sustainable Model for Improved Quality for Pancreatic Cyst Surveillance and Early Pancreatic Cancer Detection – [Mini Podcast] Ep 158

This AI-driven incidental findings program identifies and then monitors pancreatic abnormalities to improve the quality of care to patients who are at increased risk for developing pancreatic cancer. To do so, the patient management software integrates with the electronic health record and facilitates patient identification, risk assessment, care plan tracking, patient and provider communication, outcomes recording, and registry functionality. In the 2 years following program implementation, 82 pancreatic cancers were detected from incidental findings with 65% of patients being diagnosed in earlier stages (stages I, II, and II), as well as instances of ampullary cancer, gallbladder cancer, and gastric cancer.

Guest:

“There remains a knowledge gap with respect to the risk associated with pancreatic cysts. Many patients are identified to have a pancreatic cyst on an incidental scan and then told [by providers] that there’s no risk. [Some] patients will then return years later with pancreatic cancer. And it’s very unfortunate because we know that risk could have been addressed when it was in its precancerous state.” —Russell Langan, MD, FACS, FSSO

Hear more about this innovation at the ACCC 41^st National Oncology Conference, October 9-11, 2024, in Minneapolis, Minnesota. Register today.

Additional Resources:

• Reimagining Healthcare for Incidental Lung Nodules
• Oncology Capture of ED Patients with Incidental Radiologic Findings
• Pancreatic Cancer and Community Engagement: A Scoping Review of the Literature
• Let’s Win Pancreatic Cancer: A Partner for Patients and Care Teams