In the insurance industry, claims review organizations are responsible for processing high volumes of medical bills, applying regulatory rules, and negotiating discounts across multiple payors and provider networks. These processes are complex, data-intensive, and prone to inefficiency when managed through outdated systems. To remain competitive, insurers and claims administrators require scalable automation platforms that can execute large rule sets, adapt to policy changes, and ensure compliance across jurisdictions.
Challenge
Before Decisions, the company relied on a legacy rules engine that was being sunset. The system struggled with:
- High operational overhead for maintaining thousands of rules across customers.
- Slow cycle times for implementing rule updates or changes.
- Scalability limits, especially when processing thousands of bills simultaneously.
- Manual interventions, including editing bills and rerouting documents.
- Format complexity, with claims arriving in varied file types (PDFs, XML, flat files).
These issues drove the need for a modern automation platform that could handle parallel processing, integrate with existing workflows, and simplify ongoing rules management.
Solution
The company implemented Decisions as the central rules engine for its Explanation of Review (EOR) process. Key capabilities included:
- Rule-driven document routing, automatically directing bills based on allowance thresholds, customer-specific policies, and regulatory requirements.
- PPO network determination, applying routing logic to evaluate which provider network rules applied based on customer, line of business, and services rendered.
- Validation services, executing rules in isolation with parallel processing to ensure accuracy, while allowing analysts to fix data when needed.
- Rate comparison logic, enabling automated evaluation of multiple rate sets and updating databases with the correct negotiated rates.
- Automated handling of special conditions, such as flagging negative allowances or compressing/routing documents to appropriate folders.
In this implementation, Decisions native dashboards, reporting, and scheduled jobs were sufficient, eliminating the need for external analytics or orchestration tools.
Differentiators
Decisions was selected for its ability to handle large-scale, rules-driven processes with flexibility and speed. Key differentiators included:
- Rules Differentiators: Centralized and source-agnostic rules, governance for experimentation, rapid updates, and real-time/batch execution ensured compliance while reducing cycle time.
- Flow Engine Differentiators: No-code design with reusable flows meant analystsnot just developerscould manage updates.
- Integrations: Native support for REST endpoints and smart database connections simplified integration with claims systems and provider networks.
- Platform-Level Attributes: On-prem hosting and direct database connectivity ensured security and compliance for sensitive healthcare data.