From 20-Day Waits to 20-Second Matches
Our AI triage engine gets the right patient to the right provider in seconds.
Why the Status Quo Fails
-
20 days - 3 months wait to hear from provider.
-
Half of referrals are never completed.
-
Office staff without clinical background forced to guess.
-
Physicians waste slots on mismatched cases.
How We Fix It
Smart Intake
We scrape the referral and auto-populate the chart. Your team hardly types; patients sign once and move on.
Instant Triaging
The engine weighs diagnosis, urgency, and availability, then returns a routing decision in under twenty seconds.
Better Match
The right patient meets the right physician on the first try. Reschedules disappear and revenue lands on time.
Metrics That Matter
-
30-40% ↑
Triage accuracy vs. manual
-
15-20 hr ↓
Staff hours saved per week
-
7x ROI
Financially, amongst users
Why Trust IIAM
-
Built by Doctors
Crafted by head-and-neck surgeons who’ve seen firsthand how referrals slip through the cracks. Every workflow reflects real clinical routines. No vendor assumptions, just what actually works.
-
Proven in Practice
Live in-clinic results speak for themselves: triage completed in seconds, 30–40% improvement in match accuracy, and 15–20 staff hours reclaimed weekly. Speed and precision, tested where it counts.
-
Peer-Reviewed
Published studies (2024, 2025) confirm 81–88% accuracy in surgery prediction and triage urgency. Independent validation you can cite with confidence.
-
Revenue Gains
Every successful referral means a booked visit and a filled slot, on the first try. Reduce leakage, increase billable revenue, and do it all without hiring more staff.
See the Data Yourself
-
ML Model Flags Head & Neck Surgery Candidates with 81 % Accuracy
Random-forest analysis of 64 222 SEER records identified patients likely to need oncologic resection (86 % sensitivity, 71 % specificity), showing machine learning can tighten referral processing and cut treatment delays.
-
NLP Triage Engine Sorts H&N Referrals at 86–88 % Accuracy
A retrospective study of 83 new referrals proved our NLP tool can predict pathology type and appointment urgency—pinpointing high-risk cancer patients and freeing coordinators from manual triage.