Healthcare Research Program Achieves 100% ICD-10 Code Assignment with Governed Agentic AI
Discover how Aimpoint Digital built a governed agentic AI and AgentOps framework on Databricks to increase ICD-10 auto-coding coverage from 15% to 100%.


The Challenge
In a large-scale healthcare research program, accurate ICD-10 coding ensures medical conditions are classified consistently across years, enabling reliable cost modeling, disease prevalence tracking, and trend reporting.
With only 15% of new conditions being automatically coded by the existing system, all cases required multiple manual reviews to ensure accuracy, consistency, and alignment. While necessary, this approach constrained scalability, delayed the process, increased operational cost, and introduced risk in maintaining up-to-date ICD-10 standards. The organization needed a solution that could improve coverage and reduce manual labor while maintaining strict governance and oversight.
Our Approach
Aimpoint Digital designed and deployed a governed, agentic AI retrieval solution on Databricks to automate ICD-10 code assignment with accuracy and scalability. By combining intelligent retrieval techniques with a structured agentic workflow, we ensured the system could consistently interpret medical condition descriptions, reference the most current ICD-10 standards, and return reliable, context-aware results.
To accelerate delivery and ensure enterprise readiness, we leveraged Aimpoint's AgentOps Accelerator. Rather than building evaluation, governance, and deployment processes from scratch, we applied a standardized lifecycle framework that embeds automated testing, model validation, human-in-the-loop approvals, and controlled production deployment from the outset. This allowed the team to move from development to production more quickly while maintaining strict oversight, auditability, and compliance with enterprise AI standards.
By using the AgentOps Accelerator, the organization benefited from faster implementation, improved model reliability, and a scalable foundation for future AI initiatives — all without sacrificing governance or control. A streamlined user interface within Databricks provided transparent access to model outputs, enabling business users to trust and operationalize the solution immediately.
Results
Automated ICD-10 code assignment increased assignment from 15% to 100% of new medical conditions.

Human effort decreased from two coders per condition to one, significantly reducing operational workload.

The AgentOps framework ensured human-in-the-loop approval for model promotion, supporting compliance and controlled AI lifecycle management and the organization now has a scalable, governed AI architecture capable of supporting additional healthcare research automation initiatives.

Key Takeaways
Aimpoint Digital delivered an enterprise-grade agentic AI framework that increased ICD-10 code assignment coverage from 15% to 100%, ensuring scalable, accurate automation. Simultaneously, a governed and standardized AgentOps framework on Databricks reduced manual coding effort by 50%, establishing a secure, human-in-the-loop AI lifecycle ready for production.
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