AI-Powered Analytics for Payer & Rebate Analytics Teams
Tellius helps payer analytics and rebates teams make better-informed contracting and reimbursement decisions by connecting disparate data sources—prescriber, patient, market, sales, finance, digital, third-party (e.g. IQVIA, Symphony, and others), and much more—and upon this connected unified source, offering:
- A Google-like natural language search interface and AutoViz layer for ad hoc exploration
- Intuitive point-and-click live dashboarding, reporting, and embedded analytics
- Robust automated insights to isolate key drivers, root causes, and anomalies
- Accessible advanced analytics, such as AutoML, for HCP targeting
This approach allows payer analytics teams to self-serve ad hoc analysis to better inform decision-making and become truly data-driven.
Rebate Utilization Tracking
Track rebate utilization rates and measure the performance of reimbursement programs to improve patient access and adherence to medication. Tellius ML-powered alerts provide 24/7 visibility into shifts in rebate usage, while trend-based insights provide root causes of high variance so your team has the necessary data and insights to intelligently manage costs and negotiate rebates.
Formulary & Plan-Level Performance Management
Analyze your brand’s formulary placement and plan-level performance compared to competitors on a national and subnational level via natural language ad hoc analysis and intuitive point-and-click live dashboarding. Tellius automates formulary monitoring and provides intelligent proactive alerts—freeing up time, reducing risk, and revealing opportunities. Measuring the impact of patient cost and payer utilization management controls on brand performance has never been easier.
Rebate / Cash Flow Forecasting
Cash flow forecasting can be tricky when multiple rebates, TPAs/PBMs, and rebate thresholds are simultaneously at play or when there are submission delays. With Tellius, payer and rebate analytics teams can more quickly resolve larger-than-usual rebate submissions via automated trend-based insights that pinpoint likely contributing factors. Teams can further perform no-code rebate and cash flow forecasting based on historical data.
Automated Rebate Reviews
Tellius helps managed market finance and rebate analytics teams significantly improve detecting disputable rebate dollars for greater profitability compared to traditional manual rebate evaluation approaches. Tellius can be used to orchestrate and automate invoice, rebate, sales, and formulary data processing, enrichment, and monitoring. Then, automated insights on incoming data can uncover disputable rebate dollars.
Customer Success Story
The managed markets finance (MMF) team at a global pharmaceutical company receives thousands of requests each month for rebates from pharmacy benefit management (PBM) firms seeking payouts for hitting certain drug script processing levels. Some portions of these claims are disputable, but spotting them within the federally dictated 21-day payment window was challenging due to the immense amount of data wrangling and analysis required (e.g., 100+ sources pertaining to numerous drugs from thousands of pharmacies with different insurance plan IDs, etc.). The MMF team lacked a timely way to catch disputable rebates, so they paid them.
The MMF team now uses Tellius to orchestrate and automate invoice data processing, enrichment, and monitoring, then relies on automated insights to uncover disputable rebate dollars. Using this approach, the MMF team cut down analysis time from three weeks to four days (81% efficacy gain) and uncovered $5 million/year in disputable rebate dollars from this single use case.
Why Tellius for Payer Analytics
- Get intelligent alerts on shifts in rebate utilization and trend-based insights into areas with the highest variance to spot costly fraudulent cases.
- Create interactive views and answer ad hoc questions related to any rebate or payer to drive profitability, improved forecasting and budgeting, and price negotiation.
- Scheduled and automatable data blending of invoice data, market share data, and third-party data.
- Real-time anomaly detection and forecasting.
📄 Download the Payer Analytics use case in PDF.