What is the typical traditional cost per code?
Traditional human coding typically lands at $1.85 to $3.25 per code blended for a US-based coder mix. Offshore-only coding lands lower, around $0.85 to $1.40. Both numbers exclude denial rework, audit prep, and turnover costs, which are real and significant.
What is the typical autonomous cost per code?
Autonomous coding platforms today run $0.32 to $0.78 per code at scale, with the autonomous platform handling 65 to 92 percent of charts and a slim coder team reviewing the rest. The blended cost across the volume is typically 55 to 70 percent below traditional.
What hidden costs do traditional coding teams carry?
Coder hiring, onboarding, retention bonuses, continuing-education subsidies, RAC and RADV audit prep teams, denial rework hours, quality assurance coders, and the productivity lag of new coders ramping. These typically add 30 to 50 percent to the headline cost-per-code number.
What hidden costs do autonomous platforms carry?
Platform subscription, sandbox period of 30 to 60 days, EHR integration, internal change management, coder retraining for AI-review workflow, ongoing rule-pack tuning, and the cost of running a coder team in parallel for 90 days during cutover.
How does volume scale change the math?
Autonomous ROI compounds with volume. At 100K codes per year, the savings are real but smaller in absolute dollars. At 500K codes the savings cross the $1M annual mark. At 1M codes the savings cross $2.5M and the platform becomes a strategic-asset decision rather than an efficiency project.
What is the Year-1 vs Year-3 difference?
Year 1 carries one-time costs: integration, sandbox, change management, parallel coder run. Year 3 has those costs amortized away and adds tuning gains: auto-accept rate rises by 4 to 8 points, denial prediction lift compounds, and the coder team has been redeployed to higher-value work. Year-3 ROI is typically 1.6 to 2.1 times Year-1 ROI.
What error rate should I expect?
On tuned specialties, autonomous platforms run at human-baseline or slightly better error rates, around 2 to 4 percent. On complex specialties, autonomous error rates rise to 5 to 8 percent, which is why coder-in-loop review of below-threshold codes is non-negotiable. The total system error rate (AI plus coder review) typically beats the human baseline by 0.5 to 1.5 points.
When is autonomous coding the wrong choice?
When your annual volume is under 50K codes, when your specialty mix is dominated by complex codes that fall into the 65 percent tier, when your IT team cannot support an EHR integration in the next 12 months, or when your CFO is unwilling to underwrite a 90-day parallel run. Honest vendors will tell you these are bad fits.