Asembia 2025: Why AI Could Be the Key to Solving Access Challenges in Healthcare

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Chip Parkinson, CEO, GiftHealth, explains how AI-powered data integration is bringing new hope to patients by revealing hidden access barriers, streamlining treatment pathways, and challenging outdated utilization management practices.

In an interview with Pharmaceutical Executive, Chip Parkinson, the new CEO of Gift Health, shared his perspective on stepping into the role and the evolving challenges and opportunities across the healthcare landscape. Drawing on a diverse background that spans manufacturers, payers, and employer consulting, Parkinson discussed how his new position places him in closer contact with patients and prescribers than ever before. He also reflected on the state of specialty pharmacy, the potential of AI to improve access and affordability, and the importance of seeking diverse viewpoints in a rapidly shifting industry.

Pharmaceutical Executive: Patient access and affordability continue to be huge focuses—did you see any new solutions or partnerships at Asembia that excite you in that area?

Chip Parkinson: Absolutely. This is a rapidly evolving space, especially with the emergence of AI and large language models. For the first time, we have the ability to analyze vast datasets—pharmacy and medical claims, refill data, first fills—and gain a true understanding of what patients are experiencing.

Take migraine, for example. It typically takes patients six years to get properly diagnosed and treated, even though it’s the leading cause of workplace disability. Once they finally reach the right therapy, they often face utilization management hurdles like step therapy or fail-first policies. These barriers exist largely because we’ve lacked the ability to integrate and interpret the data to assess the trade-offs.

When migraine medications cost just pennies or dollars per capsule, we need to rethink whether these access barriers are justified. With AI-driven data integration, we can start answering those hard questions—and ultimately, improve access for patients.

Full Interview Summary: As of today, Chip Parkinson has stepped into role of CEO at Gift Health. Reflecting on the transition, Parkinson notes that this position brings him closer to patients than at any previous point in his career. With a background spanning manufacturers, payers, and employer consulting, he now sees firsthand the daily barriers patients and prescribers face—citing the company’s volume of 4,000 daily calls and 400 chats as a window into the patient experience.

Looking ahead, Parkinson sees several evolving roles for specialty pharmacies. He highlights the opportunity to better connect prescribers, pharmacies, and patients in real time—not just through improved logistics but with greater transparency into the patient’s journey. He also points to closer collaboration between payers and pharmacies as a potential area of growth, particularly where technology allows specialty pharmacies to integrate more directly into the care team. Parkinson emphasizes that artificial intelligence could be key in analyzing complex patient data sets—such as pharmacy claims and utilization management policies—to uncover patterns and inefficiencies that currently limit access.

When asked about prescription access and affordability, Parkinson suggests that AI may help better identify systemic barriers, using migraine treatment as an example where data gaps contribute to delays in care. He also discusses the growing demand for weight-loss medications, projecting major increases in utilization. Gift Health, he says, is looking into targeted interventions in underserved regions and through employer partnerships to address access challenges more effectively.

For other healthcare leaders attending industry events, Parkinson encourages building relationships outside familiar networks. He stresses the value of engaging with those who may hold different perspectives, particularly in a rapidly changing environment where policy, drug availability, and access continue to shift.

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