Scoring MEAs Based on Concerns and Success Criteria

When evaluating Market Access Agreements (MEAs), you need a clear way to compare them. This lesson explains how to combine different factors into a single, comparable score. By the end of this lesson you'll be able to calculate an MEA's composite score based on its alignment with payer concerns and manufacturer success criteria.

Core idea

An MEA's overall suitability is determined by how well it addresses payer concerns and how strongly it aligns with manufacturer success criteria. These two components are combined into a single composite score. The composite score gives more weight to payer concerns (60%) than to manufacturer success criteria (40%), reflecting their primary importance in MEA selection.

To calculate the composite score, you first need to determine the concern score and the success criteria (SC) score for each MEA.

The concern score is derived from a payer concerns matrix. This matrix assigns a score (from 0 to 2) for how well each MEA addresses specific payer concerns. You sum these scores for all active concerns identified for a given asset. For example, if an asset triggers "weak evidence" and "high cost per patient" concerns, and a particular MEA scores 2 for the first and 1 for the second, its raw concern score would be 3.

The success criteria score is calculated using a success criteria matrix. This matrix indicates how much each MEA supports or harms various manufacturer success criteria (scores from -2 to +2). Unlike the concern score, the SC score also considers the priority of each success criterion. Criteria ranked higher by the manufacturer contribute more to the overall SC score. This is done by multiplying the matrix score by a weight that decreases with the criterion's rank position.

Finally, both the concern score and the SC score are normalized and combined using the 60/40 weighting to produce the final composite score.

Walkthrough

Let's calculate the composite score for an example MEA.

Imagine an asset profile has triggered two active payer concerns: "Weak or uncertain evidence base" and "High cost per patient (affordability)".

The manufacturer has ranked their success criteria as follows (from highest to lowest priority):

1. Revenue predictability
2. Broad access
3. Net price sustainability
4. Minimal complexity
5. Indication expansions
6. RWE collection
7. IRP exposure

We will use the "Prospective fixed rebate / discount" (FxR) MEA for this example.

Task: Calculate the composite score for the FxR MEA.

1. Calculate the raw concern score:

   • From the Payer Concerns Matrix (Section 9 in source):
     • FxR addresses "Weak or uncertain evidence base" with a score of 2.
     • FxR addresses "High cost per patient (affordability)" with a score of 1.
   • Raw concern score = 2 + 1 = 3.

2. Calculate the raw success criteria score:

   • From the Success Criteria Matrix (Section 8 in source) and the manufacturer's ranked criteria:
     • Revenue predictability (Rank 0): FxR score = 2. Weighted score = 2 * (7 - 0) / 7 = 2 * 1 = 2.
     • Broad access (Rank 1): FxR score = 2. Weighted score = 2 * (7 - 1) / 7 = 2 * 0.857 = 1.714.
     • Net price sustainability (Rank 2): FxR score = 1. Weighted score = 1 * (7 - 2) / 7 = 1 * 0.714 = 0.714.
     • Minimal complexity (Rank 3): FxR score = 0 (blank). Weighted score = 0 * (7 - 3) / 7 = 0.
     • Indication expansions (Rank 4): FxR score = 0 (blank). Weighted score = 0 * (7 - 4) / 7 = 0.
     • RWE collection (Rank 5): FxR score = 0 (blank). Weighted score = 0 * (7 - 5) / 7 = 0.
     • IRP exposure (Rank 6): FxR score = -1. Weighted score = -1 * (7 - 6) / 7 = -1 * 0.143 = -0.143.
   • Raw SC score = 2 + 1.714 + 0.714 + 0 + 0 + 0 - 0.143 = 4.285.

3. Normalize and combine for the composite score:

   • Assume the max_concern_score for this asset profile is 8 (this value would come from comparing all MEAs).
   • Normalized concern score = 3 / 8 = 0.375.
   • Normalized SC score = 4.285 / 4 (reference max) = 1.071.
   • Composite score = (0.375 * 0.6) + (1.071 * 0.4) = 0.225 + 0.4284 = 0.6534.

The FxR MEA would have a composite score of approximately 0.65 (or 65%).

Common mistakes

• Forgetting the 60/40 weighting: It's easy to sum the normalized scores directly, but payer concerns are weighted more heavily. Always apply the 0.6 and 0.4 factors.
• Incorrectly applying SC rank weighting: The formula (n - rank_position) / n is crucial for success criteria. Ensure n is the total number of criteria (7) and rank_position starts from 0 for the highest-ranked criterion.
• Ignoring the minimum concern threshold: An MEA with a raw concern score below 2 is automatically excluded, regardless of how high its success criteria score is. Always check this threshold first.

Key takeaways

• An MEA's composite score combines its fit with payer concerns and manufacturer success criteria.
• Payer concerns are weighted at 60% and success criteria at 40% in the composite score calculation.
• The concern score sums how well an MEA addresses all active payer concerns.
• The success criteria score sums weighted scores based on how an MEA supports or harms each criterion, with higher-ranked criteria contributing more.
• MEAs with a raw concern score below 2 are excluded, as they are not relevant to active payer concerns.