Streamlining Prior Authorization Insurance processes by leveraging real-time data integration and AI-driven predictions
The Challenge
The client faced multiple challenges in navigating fragmented payer systems and diverse insurance plans, which led to complications in prior authorization (PA) and benefits verification. High rejection rates, delays in PA approvals, and inefficient manual processes resulted in operational bottlenecks, increased costs, and non-compliance risks. Also, inconsistent PA success rates due to varying payer requirements and patient demographics compounded the need for scalable solutions to address the increasing complexity of multi-payer and multi-product patient support scenarios.
Our Solution
Agilisium developed an AI-driven solution to streamline and enhance the PA process:
AI-Powered PA Predictions
Implemented models to predict PA requirements, improving predictability and reducing approval delays.
Real-Time Benefits Integration
Integrated benefits investigation into existing workflows, boosting efficiency.
Machine Learning for PA Success Rates
Deployed algorithms to assess PA success probabilities dynamically.
Automated Insurance Coverage Predictions
Enabled faster patient onboarding with automated, accurate coverage insights.
Advanced Data Integration
Ensured high-quality, compliant data through sophisticated integration and processing techniques.
The Outcomes
Faster, more efficient patient access to critical therapies, with reduced costs and higher prior authorization approval rates.
25% Reduction in PA Processing Time
Streamlined workflows accelerates decisions and improved patient access.
30% Increase in Approval Rates
Enhanced accuracy in predicting PA outcomes leads to higher insurance approval rates.
20% Decrease in Operational Costs
Automation of manual processes reduced labor costs and minimized errors.
15% Improvement in Patient Onboarding Efficiency
Faster and more accurate insurance coverage decisions accelerated the enrollment process.