About the Client
A healthcare technology company that simplifies self-insurance for employers by consolidating health plan solutions onto a single centralized platform. Serving employers, payers, providers, and members, their mission is to optimize the cost, quality, and utilization of healthcare through tools spanning care navigation, claims management, and member engagement.
Goals
The client sought to modernize how medical plan documents are stored, accessed, and interpreted, for both their customers and internal support teams. The core objective was to digitize dense, historically difficult-to-navigate plan documents and enable fast, accurate retrieval of specific plan details on demand.
To achieve this, they needed to overcome several structural challenges inherent to the industry. Payers frequently operate under long, complex names or multiple aliases, creating friction in document retrieval. Compounding this, inconsistent terminology for foundational concepts such as In-Network and Out-of-Network providers made it difficult to standardize data at scale.
They required a robust, intelligent solution capable of cutting through this complexity, reducing reliance on manual lookup, and delivering reliable plan information with speed and precision.
Key objectives included:
- Digitize complex medical plan documents to make them easily searchable using natural language.
- Standardize varying payer nomenclature to ensure accurate AI-driven categorization and retrieval.
- Build a secure, user-friendly platform for administrators to manage plans, payers, and data workspaces.
- Provide a reliable analytics module to track system usage, performance metrics, and user feedback.
- Implement an automated testing framework to validate AI responses and ensure consistent accuracy.
Solution
The client partnered with Bridgenext to design a web application, securely hosted on Microsoft Azure, for plan document queries. By leveraging a React front end, .NET Core backend, and specialized Python functionalities, Bridgenext enabled a scalable and intelligent platform tailored to the client’s unique needs.
- Intelligent Library and Workspace Management: Specialized modules were developed to manage payer and plan information. The Library and Workspace features allow administrators to organize plan-related documents efficiently, while the File Management system streamlines viewing and sorting operations.
- Secure and Scalable Architecture: To protect sensitive healthcare data, the solution integrates seamlessly with Active Directory for Single Sign-On (SSO). Strict Role-Based Access Control (RBAC) was implemented to provide granular access to different functions based on specific user permissions.
- Advanced AI and Human-in-the-Loop Workflow: An AI-driven automation engine was engineered that adapts easily to varying plan documents and payer-specific terms. To maintain maximum accuracy, an automated AI testing framework was integrated alongside a Human-in-the-Loop (HITL) feedback system. This ensures human experts review uncertain cases, constantly improving the AI’s efficiency.
Results
This partnership transformed how the organization manages and distributes critical medical plan information, driving operational efficiency.
- Reducing impacts of terminology inconsistencies across payer documents streamlines data maintenance.
- Greater accuracy, adaptability, and operational efficiency in processing large volumes of plan documents.
- Users receive highly accurate, context-aware, and well-validated responses through an AI-powered query workflow.
- A custom automated testing framework accelerates AI validation and fosters continuous system improvement.
