Cohere Health Enhances Clinical Policy Digitization with Amazon Bedrock AgentCore

Cohere Health has developed a sophisticated system for digitizing clinical policies using Amazon Bedrock AgentCore, addressing a critical bottleneck in healthcare prior authorization workflows. This system transforms static, unstructured policy documents into structured, machine-readable data, enabling more consistent and automated workflows that support health plan operations.

The core challenge was managing the complexity and variability of policies across different clinical areas, geographies, and regulations, while ensuring compliance with upcoming mandates such as CMS API-based electronic prior authorization by 2027. To meet these needs, Cohere Health built Cohere Policy Studio on a multi-tenant architecture leveraging AgentCore's secure MicroVM isolation, unified tool access via AgentCore Gateway, and AgentCore Memory for feedback loops.

This architecture allows rapid scaling of policy digitization capabilities, with extensive workflow management and automatic version control. The deployment utilizes reusable Amazon Elastic Container Registry (Amazon ECR) base images, enabling teams to deploy new agents with minimal overhead. The system also integrates various tools, including AWS Lambda functions and internal APIs, through AgentCore Gateway, which consolidates access behind a single authenticated endpoint.

A modular skills framework enables domain experts to author and refine policy-specific skills without rebuilding infrastructure, supporting continuous evaluation and iteration. This approach accelerates deployment from months to weeks, reduces policy digitization time by 30%, and broadens policy coverage, supporting thousands of policies to date.

Looking ahead, Cohere Health plans to develop an intelligent knowledge graph using Amazon Neptune, mapping policies to standardized healthcare ontologies like UMLS and SNOMED. This semantic layer aims to enhance interoperability, automate conflict detection, and support real-time policy updates across decisioning systems, further advancing the goal of achieving 80% real-time prior authorization approvals.

Overall, the implementation demonstrates how architectural patterns such as reusable base images, unified tool access, and modular skills can significantly improve the scalability, transparency, and efficiency of AI-powered healthcare workflows, paving the way for more adaptive and reliable clinical policy management.