CitiusTech’s Price Transparency Solution - RealSight™ - ingests and curates publicly available Machine Readable Files (MRFs) to provide and end-to-end Data & Analytics Solution for Price Transparency to deliver Payer, Provider & Member Insights.

Solution Focus: The “Transparency in Coverage” Rule, that went live on July 1, 2022, required health insurers, group health plans, including self-funded clients, to provide cost-sharing data to consumers via Machine-readable files (MRF). These Machine-readable files provide pricing data for covered items and services based on in-network negotiated payment rates and historical out-of-network allowed amounts.

CitiusTech has been among the pioneers, having spent close to two years working on machine readable files through building and implementing our regulatory compliance solution - MRFE (Machine Readable File Engine) for health plans. It is this foundation that’s been instrumental in designing and developing our Price Transparency Analytics solution - RealSight™.

Key Business Use Cases:

- Optimization and Rate negotiation for network provider

- Enable narrow networks & merit-based steerage

- Improved Benefit design for insurance products

RealSight key components:

- Enriched Data as a Service: Scalable data platform to ingest and store publicly available MRFs & prepare for analytics

- Bring Your Own Data: Isolated cloud platform combining MRF data with enterprise datasets, Operational analytics

- Benchmark Reports: BI dashboard & custom reporting: top provider rate benchmarking, service rate comparison

- Packaged Analytics Library: Purpose-built dashboards – e.g., network mgmt./ contract negotiation, benefit design

- Analytics as a Service: Integrated analytics to existing systems for decision making; Conversation AI solution

- Data Quality Scorecard: Scorecard for ingestion of payer MRFs; data quality and profiling measures; monthly trend

RealSight advantages:

- Scalable SaaS-based data platform to ingest & store large volume of pricing information from National, Blues and other payers

- Monthly curated data from multiple payers in readily consumable format for analytics use cases across payer value chain

- Comprehensive data quality checks and standardization to address data inconsistencies, along with clinical equivalence to analyze & extract a larger picture

- Flexible architecture to include additional payer domain datasets (claims, quality, membership etc.) for future use cases beyond MRF

- Pre-built dashboards for specific payer workflows (network management) that can be further customized per client requirements

- Reduced operational cost for payers to host and manage humungous datasets

Real Sight

Автор: CitiusTech