The AI Blind Spot: How Med Device Can Drive Throughput

Mar 17, 2026 | by Brad Bichey
Brad Bichey, MD, MPH | CEO Nemedic, Inc.

Why This Matters—Now More Than Ever

If you’re a medical device executive watching AI integrations roll out across healthcare, you need to be aware of a new threat: watching your surgeons outsource their AI agenda to EHR companies is not just an IT decision, it’s a commercial risk. When device companies rely on their surgeon customers to simply “go with” whatever AI tool their EHR offers, they may be inadvertently supporting technologies that limit surgical throughput and, ultimately, device utilization.

We recently analyzed ModMed’s much-hyped AI fax solution as a case study for how EHR-native AI is failing the clinical front-lines—and why medical device leaders can’t afford to ignore this trend.

What’s Wrong with EHR-Led AI?

EHR vendors, by their DNA, develop tools to optimize records, compliance, and audit trails. Their AI solutions match this: playing to documentation efficiency rather than what actually moves the needle for surgeons (and, by extension, the device lines that depend on operative volume).

Our breakdown of ModMed’s new AI-driven fax workflow found:

  • Minimal impact on reducing staff workload, streamlining scheduling, or improving patient access.
  • Misclassification errors that led to inefficiencies and wasted follow-up.
  • Workflow enhancements that served the record—not the surgeon or patient.

A Missed Opportunity: The Front Door of Surgical Practice

Most data you buy today (for sales forecasting, analytics, targeting, etc.) is “back door” data—what happened after the patient was already in the system. But what if you knew what business was coming in the front door? A custom AI trained on real referral and scheduling workflows:

  • Rapidly identifies, triages, and engages new patients.
  • Surfaces actionable insight at the point of scheduling, and helps mitigate lost business.
  • Directly drives throughput, maximizing not just patient volume but device utilization.

Our real-world comparison showed that a custom-trained AI agent—learning from a practice’s own referral patterns—could cut fax-related labor by 60–80%, rapidly engage patients to prevent referral drop-out, and provide real-time analytics on where new cases originate.

Strategic Implications for Device Companies

Here’s the real risk: If you leave surgeons to adopt only what the EHR market provides, you risk aligning your sales growth with AI that actively slows their practices down.

AI designed around record-keeping has been a source of physician burnout for over a decade—now it’s becoming a bottleneck that could reduce demand for devices through slower, less efficient throughput of surgical patients.

Conversely, device companies that step up as true partners—guiding their surgeons to purpose-built AI that optimizes business processes and clinical workflow—stand to own the front-end data and drive higher case volume. You’re not just selling implants or disposables; you’re selling throughput, profitability, and practitioner empowerment.

Three Strategic Moves You Can Make Now

  • Champion the Right AI: Support your surgeons with AI that improves business and care—not just documentation. Provide tools or partnerships centered on referral management, patient engagement, and real-time workflow improvement.
  • Monetize Front-Door Data: Access to inbound referral, scheduling, and patient triage data is an untapped analytic goldmine—far richer for predicting future business and optimizing targeting than post-procedure data feeds.
  • Lead, Don’t Follow: Medical device should be driving the AI conversation in tandem with clinical partners, not as an afterthought to EHR-driven compliance projects. Help surgeons reclaim operational efficiency, and your products will follow them into more cases, more often.

Bottom Line—And a Call to Action

This isn’t about outsmarting EHR AI; it’s about out-serving your market. The companies that recognize and act on this shift—standing beside surgeons, ushering in technology that multiplies their effectiveness—will not only protect but grow their footprint as healthcare moves beyond documentation and into true AI-powered operations.

Will your team guide the change, or be swept away by it?