Coders Think They're 95% Accurate. They're Closer to 75% | Gail Airasian, CodaMetrix

When you test the results rather than trust the belief, a twenty-point gap appears. And payer bots are about to make it expensive. Book Ian for your event → iankhan.com | booking@iankhan.com SUMMARY Gail Airasian is Chief Growth Officer at CodaMetrix. She explains what happens when medical coding accuracy is actually measured rather than assumed, why a twenty-point gap is a commercial differentiator, and why the problem compounds as payers deploy more automation. KEY FINDINGS • Coding teams believe they are at 95% accuracy • Testing the results puts real accuracy closer to 75% • A twenty-point gap most health systems do not know they have • The ability to test ten coders and measure the true rate • Why payer-side bots make sub-95% accuracy far more costly • Accuracy as a measurable differentiator rather than a claim • What health systems should be auditing before buying automation NOTABLE QUOTES "While they believe that they are at 95% accuracy, when you dig under the covers and start to test their results, they're more like 75%." — Gail Airasian "As the payer builds more bots, you are going to have more problems with those things that are not at 95% accuracy." — Gail Airasian GUEST Gail Airasian, Chief Growth Officer, CodaMetrix FULL TRANSCRIPT iankhan.com/futurist/gail-airasian-codametrix-coding-accuracy Recorded at HLTH 2025 for The Futurist. ──────────────────── ABOUT IAN KHAN — HEALTHCARE AI KEYNOTE SPEAKER Most AI keynotes end with a better understanding. Mine end with