Bridging Racial and Ethnic Minority Disparities in Pancreatic Cyst Surveillance
A computational linguistics model has mitigated disparities in surveillance of the pancreas that primarily affected racial and ethnic minorities.
According to Russell C. Langan, MD, FACS, FSSO, associate chief of Surgical Officer for System Integration and Quality and director of Surgical Oncology at Northern Region, RWJBarnabas Health and Rutgers Cancer Institute of New Jersey, there are racial and ethnic minority disparities in the medical fields current ability to detect pancreatic cysts and pancreatic cancer.
In an interview with CancerNetwork® at the 2024 Annual Oncology Clinical Practice and Research Summit, Langan said that the computational linguistics model he created with Eon Health helps mitigate the disparities by being agnostic to the medical record. This, he said, is beneficial because many patients who have lower socioeconomic status often use the emergency department (ED) as primary care treatment.
For patients who receive imaging in the ED, the software will automatically identify risk factors like pancreatic cysts. The patient doesn’t have to follow-up and instead the software will contact the patient. Langan emphasized that this can lead a patient to quicker, higher-quality care than older tools would have led to. Beyond that, it expands the demographic of patients with access to treatment and surveillance.
Transcript:
One of the main limitations [with our methods of detecting pancreatic cysts and pancreatic cancer] is the fact that in traditional methods of pancreatic cyst surveillance or early cancer detection, there are racial and ethnic minority disparities, whereas our software runs in the medical record, it’s agnostic to a medical record, and it runs in the background. Patients who go to an ED, many times are of lower socioeconomic status, and many times use an ED as primary care treatment.
If they are getting their imaging through the ED, our software will identify them. It can be the first point of contact to the patient [that] gets them expeditious, high-quality care. On top of improving quality for [detecting] cancer, it also improves the [ability] to mitigate these racial and ethnic disparities that exist in the natural delivery of health care.
