I left clinical practice after residency. My husband remained in the field and now runs a small private office. I observe him spending most of his day on prior authorizations, documentation, and chasing referrals instead of patient care.
A 2025 time-motion study from Vanderbilt University School of Medicine revealed nurses devote only 34% of their time to direct patient care. The remaining hours go to indirect tasks, primarily documentation.
The Problem Isn’t Just Workload—It’s the System
Large health organizations rely on hundreds of applications, each managed by a different department. Biomedical services, facilities, environmental services, and IT all use separate tools. Requests frequently fall through gaps. Shift changes lead to communication failures. Clinicians become the connective tissue holding together systems that were never designed to integrate.
Margins are under pressure. Clinicians are burning out. The infrastructure works against those trying to deliver care.
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I recall my surgical training, where discharging a single patient took longer than the operating room cases I was there to learn from. Billions of dollars in healthcare technology later, the coordination problems haven’t gone away.
AI Can’t Fix What Was Never Built Right
There’s been enormous enthusiasm for artificial intelligence in healthcare. Unfortunately, organizations make the same mistake repeatedly: They layer AI onto a fragmented foundation and expect it to fix the underlying problem. It doesn’t.
Large language models are powerful, but they are not a system of governance. They don’t enforce ownership. They don’t connect systems of record or complete workflows. An AI copilot on top of hundreds of disconnected applications just exposes fragmentation.
For AI to deliver real value in healthcare operations, it needs a unified foundation: a shared operational system of record embedded directly into the clinical environment, including the electronic health records system, so care teams can raise requests as part of their normal workflow without breaking focus.
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When that foundation exists, AI agents can do real work: triaging requests, routing them to the right team and keeping tasks moving without manual intervention. Consider something as simple as broken equipment on a hospital floor. Today, a nurse calls the biomed department, waits on hold, explains the problem and hopes it gets tracked. With a unified operational platform, she flags it in the system she’s already working in. It’s automatically routed with the context the support team needs. The issue is resolved with clear ownership and real-time status. Every action is captured because the platform recorded it as work happened, not because someone filed a report.
The reason is structural. Clinicians trained to heal are spending their days handling broken systems. When support services move at the speed clinicians need, the effects compound: fewer care disruptions, reduced burnout, and operating margins protected from the waste of manual coordination.
Organizations must first build the foundation AI requires to complete tasks: a single operational platform shared across departments and embedded in clinical environments.
My husband still cares deeply about his patients. Yet the administrative load makes him want to walk away from medicine entirely—not the patients, but the administrative burden. The challenge isn’t whether AI can assist. It’s whether healthcare will finally create the right foundation.