In the News: How AI in Specialty Care is Reshaping Margins and Referrals
As hospitals look toward 2026, the pressure to optimize margins while improving patient outcomes has never been higher. Health systems are increasingly turning to artificial intelligence not just for clinical support, but as a strategic lever to fix the economics of high-value service lines.
In a recent Q&A with Healthcare IT News, Lucem Health CEO and co-founder Sean Cassidy discusses the transformative potential of AI in specialty care. He outlines how AI-driven proactive outreach can flip the traditional referral dynamic and why the vendor-provider relationship is due for a major economic overhaul.
Optimizing the Patient Mix
One of the most persistent challenges in healthcare is the “flooding” of specialty departments—such as cardiology, hepatology, and GI—with low-acuity patients. These patients often could be treated effectively in primary care, yet they consume high-value exam room time, forcing specialists to practice below the top of their licenses.
In the interview, Cassidy explains how AI in specialty care can solve this upstream:
“Specialists and the unit economics of their service lines could benefit greatly from an upstream process that proactively and programmatically routes patients into care pathways tailored to disease stage, progression and acuity… This higher yield, higher impact approach to care delivery would increase specialty care margins by enabling specialists to focus their attention on the sickest patients.”
By surfacing hidden risk signals in EHR data, health systems can ensure that the patients entering specialty care are those who require complex interventions, thereby maximizing the utility of scarce specialist resources.
From Reactive to Proactive Referrals
The current referral model is largely reactive, waiting for patients to become symptomatic enough to seek help. Cassidy argues that AI in specialty care offers a way to “flip” this dynamic. By moving toward AI-driven patient identification, providers can initiate care pathways before diseases become life-threatening.
“In an ideal world, we would eliminate or sharply reduce the number of interactions and modalities patients would have to navigate to get positive outcomes,” Cassidy notes. This proactive approach doesn’t just improve clinical outcomes; it creates a more harmonious workflow between primary care physicians (PCPs) and specialists.
The Rise of Shared-Risk Models
Looking ahead to 2026, the conversation shifts to how health systems pay for this innovation. Cassidy predicts a move away from traditional volume-based software licenses toward shared-risk models. In this future, vendors must prove the value of AI in specialty care by tying costs to measurable clinical or financial benefits.
“Vendors become vested and embedded rather than just software suppliers,” Cassidy states. “Those that deliver quantifiable value will establish long-term relationships grounded in transparency and trust.”
Read the full Q&A at Healthcare IT News: https://www.healthcareitnews.com/news/how-ai-may-impact-specialty-margins-and-referrals-2026
