MRF Engine for Payers

mrfdatasolutions.com

CitiusTech’s Machine-Readable File Engine (MRFE) is a platform-agnostic SaaS solution within Health Care Software that supports payers in meeting CMS Transparency in Coverage requirements. It produces machine-readable files that list in-network negotiated provider reimbursement rates, enabling health plans to publish payer–provider coverage rates as mandated. By making detailed pricing data available, it supports members in evaluating procedure and treatment options based on cost.

MRFE features a highly scalable architecture to handle large data volumes and complex, iterative business rules, along with a configurable, modular design for customization and enhancement. Its auditability and transparency capabilities include granular logging and notifications. The solution can assist health plans with faster deployment of personalized cost estimator tools, a unified view of negotiated rates for analytics and value-based payment models, improved provider network management using market insights, and the ability to accommodate CMS schema changes with monthly machine-readable file updates. This can help health plans offer easier access to cost information across in-network providers, supporting informed decision-making and increased price transparency that may drive competitive pricing and lower overall costs.

LLM mention score The LLM mention score is the total number of mentions of this brand in different LLM chatbots, normalized to the scale from 0 to 100. You can get actual, non-normalized numbers via the LLM Mention API from DataForSEO.

Normalized 0–100 · last 8 weeks

DataForSeo API

Get LLM mention data of any company via DataForSEO API

Get access to the structured data on keyword, brand, and website mentions in LLMs, including metrics like AI search volume, impressions, and mentions count. 

How to get LLM mention data →
// Fetch MRF Engine for Payers mention score
POST /v3/content_analysis/summary
{
  "keyword": "MRF Engine for Payers",
  "type": "llm_mentions",
  "date_from": "2025-01-01"
}