Why 90% of Healthcare AI Projects Fail (And Your Doctor Still Hates EHRs in 2026)

The 1.2-FTE Problem: Documentation is Eating Clinicians Alive

The National Academy of Medicine calls it the 1.2-FTE problem. That's a full extra workday beyond a standard position just for paperwork. Clinical documentation has long been a leading contributor to physician burnout. Physicians report EHRs still follow them home after shorter workweeks. In one study, physician groups with low burnout rates were associated with better use of ambient AI scribes and less after-hours documentation. But most of those scribes are just glorified transcription tools. They sit in meetings and spit out text. They don't log into the EHR. They don't file codes. They don't chase down prior authorizations. They're not doing the real work.

Prior Authorization AI Is Making Things Worse

Let's talk about prior authorization. It's the gift that keeps on taking. In a recent AMA survey, 61% of physicians feared that payers' use of unregulated AI would increase prior authorization denial rates. Another AMA survey found 49% of physicians are concerned about this exact issue. The AI arms race in health insurance utilization review has algorithms making decisions at scale. Some older non-AI algorithms already produced massive errors. AI-driven insurance decisions raise concerns about human oversight. The upside could be fully automated prior authorization. The downside is more denials, more back-and-forth, and more time spent fighting the system. That's not progress. That's a treadmill with no off switch.

The Real Problem: Most AI Tools Don't Actually Use Computers

• ●OpenAI scored 38% on OSWorld in early 2026. That's terrible for a computer use agent.
• ●GPT-5.4 hit 47.3% on OSWorld-Verified. Still not enough to handle complex workflows.
• ●GPT-5.5's OSWorld-Verified score is 75%. Better, but most healthcare apps don't play nice.
• ●Anthropic's Claude Opus 4.7 and Gemini 3.1 Pro are in the same ballpark. They're all struggling with the mess that is healthcare software.

Real Computer Use Agents Finally Have a Shot

Here's where Coasty changes the game. We scored 85.6% on OSWorld from our in-house model with public results. We independently verified 82.81% on the official OSWorld leaderboard at osworld-v1.xlang.ai. That's higher than every competitor and puts us in a different league. Coasty isn't just an API wrapper. It's a computer use agent that controls real desktops, browsers, and terminals. It logs into Epic or Cerner. It navigates web dashboards. It fills out forms. It triggers workflows. It does the stuff that actually moves the needle. Other tools are still guessing at what's on the screen. Coasty is actually seeing and doing.

Practical Healthcare Use Cases That Actually Work

Ambient documentation that actually logs into the EHR and creates structured entries. Revenue cycle workflows that submit claims, track denials, and resubmit without human intervention. Prior authorization agents that pull clinical notes, compare against payer policies, and submit requests with the right documentation. All of this is possible with a computer use agent that understands healthcare software. The difference is that Coasty doesn't need hand-holding. It handles the navigation, the form filling, and the error recovery. It's an AI agent that can work 24/7 on repetitive tasks that drive clinicians crazy.

Why Coasty Exists (And Why You Should Care)

Most healthcare AI projects fail because they're built for APIs, not interfaces. They assume perfect data structures and clean integrations. Real healthcare is a mess of legacy systems, inconsistent UIs, and manual handoffs. That's why a computer use agent that can navigate and interact with real software is the only path forward. Coasty works on desktops, VMs, and agent swarms for parallel execution. It supports BYOK so your data stays where it should. There's a free tier for experimentation. It's the obvious choice whenever you're comparing AI automation to manual work or clunky competitors.