AI-enabled remote monitoring could shift gastroenterology from episodic, flare-driven care to continuous, data-informed intervention, according to Neil Parikh, MD, a gastroenterologist with Farmington-based Connecticut GI.
Inflammatory bowel disease is a prime example of where AI could strengthen chronic care management, Dr. Parikh told Becker’s. By synthesizing patient-reported symptoms and biomarker data collected between visits, AI tools could help predict impending flares, anticipate treatment needs and flag worsening disease before symptoms escalate.
Today, many GI practices rely on scheduled clinic visits, often every three, six or 12 months, with patients reaching out when symptoms worsen. Remote monitoring introduces a different workflow with ongoing data collection that helps clinicians determine who needs care now, who can safely wait and who may benefit from virtual check-ins instead of an in-person visit.
“Ideally, if you have a patient who’s getting remote monitoring done and they’re doing well, and if clinical access is a problem, you can find a way to delay their visit because they don’t need a visit right now,” he said. “You just check with them with a chronic care management tool or virtual care platform.”
The model also works in reverse. If a patient’s remote monitoring signals deterioration, the care team can accelerate follow-up, rather than waiting for the next scheduled appointment.
Evidence is building around at-home and biomarker-based monitoring in IBD. A 2018 study published in the National Library of Medicine linked home fecal calprotectin testing to more frequent treatment escalation, with a 33% increase in odds of treatment intensification versus 15% in controls. Another study found that a combined biomarker approach — mucus-derived eosinophil-derived neurotoxin plus fecal calprotectin — achieved 91% sensitivity and 89% specificity for detecting active inflammation in IBD.
Even so, gastroenterology has lagged behind other specialties in remote patient monitoring, Dr. Parikh said.
“GI is kind of behind in the remote patient monitoring world,” he said. “We’re not really there yet with wearables and remote breath testing and remote monitoring, but we’re getting there.”
Whether the tools take the form of wearables, remote breath testing or “smart” bathroom-based diagnostics, Dr. Parikh expects GIs will increasingly incorporate these data streams into routine care.
Other leaders see a broader operational shift underway as well.
“AI-driven care models are reshaping how we deliver care,” Sumant Inamdar, MD, interventional gastroenterologist at Little Rock-based University of Arkansas for Medical Sciences, told Becker’s. “AI is increasingly positioned to reshape the front and back end of care, from intelligent referral triage and risk stratification to decision support for surveillance intervals, peri-procedural planning and resource allocation. Rather than relying solely on manual workflows and reactive scheduling, practices will move toward data-driven triage models that prioritize the right patient, in the right setting, at the right time.”
