How a Large Academic Medical Center in the South Cut Documentation Time by 90% without Compromising Accuracy

Client Overview

This academic medical center is one of the state’s most respected care networks. In fact, it is home to approximately 25 oncologists practicing across multiple locations. Like many specialty-driven practices, they face intense pressure to maintain documentation quality while minimizing the administrative toll on their providers.
With documentation time per encounter routinely reaching 15 minutes, leadership sought a next-generation AI-powered solution that would reduce this burden—without creating new inefficiencies or disrupting Flatiron EMR workflows.

Their two core requirements:

• High-quality documentation that required little to no review
• Meaningful reductions in total documentation time

The Challenge – Cut Documentation Time Without Losing Accuracy

Most of the vendors the academic medical center evaluated offered what appeared to be AI-forward solutions–but functioned more like advanced transcription services. These tools generated basic first-draft notes from ambient listening. But, they lacked the clinical oversight needed to consistently meet oncology’s complex documentation requirements.

This created a problematic dynamic: AI did the drafting, but doctors were stuck reviewing and correcting output, leading to new time demands and variable accuracy. Promises of 70% time savings often fell short in practice due to high error rates and missing context—ultimately stalling adoption.

For oncology, that wasn’t good enough. They needed a partner that understood clinical nuance and respected provider workflow. And most importantly, could deliver a near-final note—not a rough draft.

The Solution

The academic medical center partnered with Onpoint to implement ChartFlow from the Iris Medical AI Platform—a solution purpose-built to follow the patient and provider journey, not just record the conversation.

Unlike traditional scribe models, ChartFlow combines ambient listening with embedded clinical expertise, enabling automation that is both context-aware and safety-focused.

Each note is clinician-audited before delivery, meaning oncologists receive highly accurate, structured documentation that reflects their intent—without the extra work. Seamless integration with Flatiron EMR allowed for rapid onboarding and easy adoption, without the disruption of retooling existing systems.

With Iris, the academic medical center gained a documentation assistant that works the way they do—supporting their practice, not forcing change.

The Results

With Iris, documentation time didn’t just shrink—it was redefined.

• 90% Decrease in Documentation Time
  Providers now spend just 1.5 minutes per encounter on notes—down from 15 minutes—freeing up nearly 150 minutes per provider per day.
• 98.4% Documentation Accuracy
  Clinical auditing, AI precision, and oncology-specific configuration resulted in a 98.4% accuracy rate, minimizing review fatigue and restoring provider confidence.
• Built for Scale
  Encouraged by the outcomes, the academic medical center is expanding its partnership with Onpoint through CodeFlow, a powerful AI + expert-validated coding solution aimed at accelerating A/R and reducing back-end friction.