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Next Generation Solutions for Value-Based Care.

Modern Analytics. Strategic Execution. Measurable Results.

Toolkit Item  #1

MLR Drift Calculator Logo

The MA New Cohort MLR Impact Modeler

Quantify Actuarial Risk & Forecast Margin Drift with Geographic Precision

Brief Utility Overview: a powerful, accurate tool leveraging embedded dynamic data architecture for strategic use. It features statistical and multivariate analysis, geo-adjusted county-level sourcing—including historical member mix, RAF, CMS rates, V28 sensitivity, Stars QBP impacts, and plan-specific customization—ensuring precise insights and effective decision-making.

ACCESS LINK TO MODEL HERE

Development Framework Summary  & Model Logic:

1. Goal & Strategic Use Case:

  • What it does: This tool quantifies the immediate medical loss ratio (MLR) margin dilution caused by adding new Medicare Advantage members, solving the structural "timing problem" between immediate medical costs and lagged risk-adjusted revenue.

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  • When & Why to use it: Use it during product strategy, network development, or M&A evaluation to accurately forecast how a new cohort will impact your total book of business's bottom line before their coding matures.

2. How it Works: Architecture

  • Geo-Deterministic precision: It projects revenue and cost by embedding five public data layers—including the complete CMS 2026 Rate Tables for 3,248 counties across 56 jurisdictions—directly into the calculation engine.

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  • Zero external dependencies: Requiring no external APIs, the tool securely computes weighted-average benchmarks matched to your exact service footprint and quality bonus Star tiers.

3. Statistical Frameworks Used

  • Multivariate computation: Operating as a deterministic scenario engine within a 12-dimensional parameter manifold, it uses nonlinear cost functions and bilinear revenue functions to calculate MLR Drift (the exact basis-point shift in your overall MLR).

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  • Actionable coding targets: The model computes exact break-even Risk Adjustment Factors (RAF) using $\theta* BE(s) = K(s) / \bar{B}$, providing your clinical coding teams with concrete, segment-level targets to achieve margin neutrality.

4. Segment Deep-Dive Variables

  • Actuarially distinct profiling: Incoming members are stratified into three distinct segments: Age-Ins (lowest initial demo RAF of 0.40, zero history), Switchers (partial RAF carry-over with a 5% "pent-up demand" cost surge), and D-SNP (high acuity, high absolute cost, but potentially margin-accretive).

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  • Granular assumptions: Each segment features independent, user-configurable variables for demographic vs. true RAF, historical cost PMPM, medical trend, and utilization adjustments.

5. Geo-adjusted Member Mix

  • Evidence-based composition: Instead of relying on guesswork, the tool’s "Standard Member Mix" automatically derives your expected enrollment channels at the county level using independent public data signals.

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  • Triangulated modeling: It applies a market step-function to CMS MA penetration rates (dictating the Age-In vs. Switcher split) and scales KFF state-level D-SNP enrollment shares to output a highly localized, auto-normalized member mix.

6. Interactive Toggles & Outputs

  • Flexible scenario modeling: Use the Standard Member Mix toggle to instantly generate geographically calibrated baselines, or switch it off to unlock the 9 segment sliders for manual sensitivity testing.

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  • Executive-ready KPIs: The dashboard translates these inputs into 9 primary output metrics, instantly revealing your blended cohort MLR, the absolute dollar impact on margin, and the critical revenue coding gap you need to close in Year 1.

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