Unlocking $6.4 Million in Enrollment Growth: How HealthWorksAI’s Benefit Simulator Optimized Medicare Advantage Benefit Strategies
Executive Summary
As Medicare Advantage payors shift from fee-for-service to value-based care, they face escalating cost pressures driven by healthcare inflation, prescription drug prices, and increased demand for long-term care services. This case study highlights how a leading national payor partnered with HealthWorksAI to leverage ProductIntelTM’s Benefit simulation, to strategically align benefits with enrollment goals and optimize product offerings. Through our advanced benefit simulations across multiple markets, the payor achieved data-backed insights, driving both significant cost savings and potential growth of over 3,700 members in key regions.
Context and Background
Industry Shift from Fee-for-Service to Value-Based Care
In recent years, Medicare has embraced value-based care models to enhance patient outcomes while managing costs. However, rising healthcare inflation, especially in prescription drugs and hospital services, continues to place substantial financial pressure on payors, making efficient benefit structuring essential. Payors are compelled to explore strategic product adjustments that align with market demands without sacrificing coverage or enrollment.
Challenges for a Leading National Payor
“Our enrollment predictions were subjective, lacking the hard data science needed for confident decision-making. We needed a big change to satisfy both our shareholders and our financial planning goals,” said Payor’s CFO.
Solution Approach with ProductIntelTM
HealthWorksAI’s ProductIntelTM solution provided a powerful simulation tool, allowing the payor to evaluate benefit offerings with precision and confidence.
Step 1: Strategic Simulation and Scenario Modeling
The payor ran 81 simulated scenarios with a total of 3,699 permutations across 10 states, using ProductIntelTM’s Benefit Simulator to evaluate both Dual Eligible Special Needs Plans (D-SNP) and Special Needs Plans (SNP) offerings. This allowed the team to pinpoint how adjustments in benefits—such as Dental, NPH, and OTC benefits—impacted potential enrollment outcomes, streamlining their product strategy based on accurate data rather than assumptions.
Step 2: Benefit Sensitivity Testing
One of ProductIntelTM’s core capabilities, benefit sensitivity testing, enabled the team to map market tolerance for various benefit adjustments. This incremental testing provided clear insights into member preferences, showing which benefit investments would drive enrollment and which could be deprioritized without negative impact.
“Just by tweaking a few parameters, we could simulate various scenarios within seconds to see which benefits were worth investing in,” noted the payor’s Director of Strategy and Product Development.
Step 3: Real-World Application of Simulation Insights
In San Diego County, California, the payor tested increasing dental coverage benefits, expecting an enrollment boost. Instead, simulations revealed that these enhancements would have no impact on enrollment, allowing the payor to reallocate resources more effectively.
Conversely, in a midwestern state, simulations indicated that 22 changes across four benefit categories could yield over 3,700 new members. Testing the same benefits in Houston, Texas, revealed a 1,001-member reduction, demonstrating the importance of market-specific benefit adjustments.
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Opportunity Identification and Quantification
By leveraging ProductIntelTM’s simulations, the payor achieved measurable impacts that supported both cost savings and enrollment growth:
- Precision Cost Savings: In Pima County, Arizona, simulations showed that OTC benefit changes would not affect enrollment, allowing the payor to save approximately $0.75 per member, redirecting $180,000 in annualized savings to higher-impact areas.
- Enhanced Enrollment Forecasting: The Ohio simulations projected a potential enrollment increase of 3,700 members, translating to an incremental profit of $6.4 million, even with a conservative estimate of a 3,000-member gain. This data-backed approach offered the payor greater financial stability and growth forecasting.
- Informed Product Strategy: By running multiple, real-time benefit simulations, the payor optimized benefit offerings according to regional demands, resulting in both cost-effective benefit structures and a more competitive market presence.
Strategic Insights for Medicare Advantage Leaders
- Adopt Data-Driven Benefit Simulations: Tools like ProductIntelTM empower payors to move beyond qualitative insights, providing hard data to refine benefit offerings for specific markets.
- Optimize Benefits According to Market Sensitivity: Benefit sensitivity testing enables payors to understand market tolerance, allowing them to prioritize high-value benefits while avoiding unnecessary costs.
- Maximize Enrollment Potential Through Regional Adjustments: By tailoring benefit structures according to regional member preferences, payors can drive enrollment growth and improve overall financial performance.
Outcomes
Better Forecasting
3,700 New Members
projected, generating incremental revenue of
$6.4 Million
Optimized Strategy
Winning benefit offerings
with Real-time simulations.
Challenges
- Industry Shift: Medicare’s move to value-based care drives need for cost-efficient benefits.
- Cost Pressures: Rising drug and care costs require strategic adjustments.
- Payor Challenge: Inaccurate forecasting caused inefficiencies and unmet shareholder goals.
Our Approach
- Ran 81 scenarios across 10 states, refining D-SNP and SNP strategies with data-driven insights.
- Tested market tolerance, pinpointing which benefits drove enrollment
Key Findings
- No enrollment impact from dental benefits in San Diego, enabling cost reallocation.
- Benefit adjustments projected 3,700 new members in a midwestern state
- Similar changes led to a 1,001-member loss, underscoring regional needs in Houston.
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