From Charburgers to Charting: What Healthcare Can Learn From Fast Food

HAPPY VALLEY, OR – November 26, 2025

This week, a press release announced that The Habit Burger Grill, a California-based fast-casual chain, is opening its first Oregon location in this Portland suburb. There will be VIP events, free Charburgers for loyalty club members, and a grand opening on December 3rd. On the surface, this is a minor business story, a familiar headline in the endless churn of retail expansion. It seems to have absolutely nothing to do with the complex, high-stakes world of healthcare innovation.

But look closer. The meticulous, data-driven, and customer-centric strategy behind bringing a flame-grilled burger to a new market holds a surprising and powerful mirror to the challenges facing healthcare. As hospital systems struggle to implement artificial intelligence, improve patient outcomes, and manage costs, the playbook for success might not be buried in academic journals, but on display in plain sight at the local strip mall. The strategies used to scale a consistent, quality experience from one location to over 385 are precisely the kinds of strategies healthcare needs to master to effectively deploy AI. What can the implementation of a burger franchise teach a chief innovation officer at a major health system? As it turns out, quite a lot.

The "Total Access" Patient: Engineering a Seamless Journey

Habit Burger describes its growth plan as becoming a “total access brand.” A customer in Happy Valley can walk in and order, use a self-serve kiosk, order ahead on the Habit Mobile App, or get delivery from a half-dozen different platforms. The company’s goal is to eliminate friction and meet customers wherever they are, on their own terms. This stands in stark contrast to the typical patient journey, which is often a fragmented and frustrating maze of phone calls, siloed portals, and redundant paperwork.

This is where healthcare can take its first lesson. The concept of a “digital front door,” powered by AI, seeks to create the same seamless experience. Imagine an integrated health system app that doesn't just hold records but actively engages the patient. An AI-powered chatbot could handle initial symptom triage and appointment scheduling, intelligently routing the patient to the right level of care—be it a virtual visit, an urgent care clinic, or a specialist—optimizing the use of clinical resources.

Furthermore, Habit’s pre-opening events are exclusively for its “CharClub” and mobile app members, a clear strategy to drive adoption of its digital loyalty platform. In healthcare, “loyalty” isn’t about collecting points; it’s about patient engagement and adherence. AI can personalize this engagement at a scale never before possible. Instead of generic appointment reminders, an AI system can send tailored educational content about a patient’s specific condition, track medication adherence through app check-ins, and provide positive reinforcement for healthy behaviors. By making the digital experience convenient, personalized, and rewarding, health systems can foster the kind of engagement that directly leads to better health outcomes, transforming the patient from a passive recipient of care into an active participant in their own wellness.

Standardizing Excellence: Personalized Medicine at Scale

The Habit’s core promise is its “cooked-to-order” mantra. Whether you want a Double Char with no onions or a sushi-grade ahi tuna sandwich on a wheat bun, you get a customized product. Yet, this customization is delivered within a highly standardized and ruthlessly efficient operational framework. This is the very essence of the challenge in modern medicine: delivering personalized care at scale.

The promise of AI in clinical settings is to make personalized medicine a reality. By analyzing vast datasets—including a patient’s electronic health record, genomic information, family history, and lifestyle factors—AI algorithms can identify patterns and predict risks that are invisible to the human eye. This allows for the creation of truly bespoke treatment plans. The problem, however, has been operationalizing it. How does a health system with thousands of clinicians ensure that this high level of personalization is delivered consistently and based on the latest evidence?

Again, the fast-food model provides a clue. The key is to embed the intelligence into the workflow. In healthcare, this means deploying AI-driven clinical decision support (CDS) tools. These systems don’t replace the clinician’s judgment but augment it, serving up evidence-based, personalized recommendations at the point of care. An AI-CDS tool could, for example, flag a potential adverse drug reaction based on a patient’s genetic markers or suggest a more effective chemotherapy regimen based on the latest clinical trial data matched to the tumor’s specific profile. This creates a system that, like the fast-food kitchen, combines a bespoke output (a personalized treatment plan) with a reliable, high-quality, and repeatable process.

The Implementation Playbook: A Recipe for Successful AI Deployment

Perhaps the most critical lesson lies in Habit’s market-entry strategy. The company didn't just drop a pin on a map of Oregon. The research accompanying their launch reveals a careful analysis of the local competitive landscape, which already includes national players like Five Guys and beloved local chains. This strategic intelligence is fundamental to success.

Similarly, before a hospital deploys a new diagnostic AI, it must perform a deep “market analysis” of its own internal environment. What are the existing clinical workflows? What are the capabilities of the legacy IT systems? What is the cultural readiness of the staff? An AI tool that is technically brilliant but disrupts an established and effective workflow is doomed to fail. It must solve a real, identified problem for the people who will be using it.

The pre-opening VIP events serve as a controlled, low-risk pilot program. By inviting in a select group of “CharClub members,” Habit generates buzz, tests its kitchen and staff under live conditions, and gathers immediate feedback before the public grand opening. This is the gold standard for AI implementation in healthcare. A new algorithm shouldn’t be deployed system-wide overnight. It should be piloted in a single, receptive department with clear success metrics. This allows the organization to work out the kinks, prove the tool’s value, and—most importantly—create a cohort of clinical champions who can attest to its benefits. These champions become the internal influencers who drive broader adoption, a far more effective strategy than a top-down mandate.

By carefully planning the deployment, starting with a pilot, and demonstrating clear value to its “community” of users, a health system can ensure its multi-million dollar AI investment doesn’t become expensive shelfware. The goal is to make the new tool feel like an indispensable part of the team, not an unwelcome intruder.

While the worlds of fast food and medicine may seem galaxies apart, the underlying principles of success in the 21st century are strikingly similar. They are rooted in a deep understanding of the end-user, a commitment to a seamless experience, and a data-driven strategy for scaling quality. For healthcare leaders navigating the complexities of AI innovation, the path forward may be illuminated not just by the glow of a computer screen, but by the open flame of a burger grill. It’s a powerful reminder that the best solutions are often found by looking beyond our own walls to see how others have already solved the problems we face, one successful implementation at a time.