---
name: payer-landscape-analyzer
description: "Analyzes the payer landscape for a therapeutic area and geography — segmenting payers by coverage type, mapping formulary tier dynamics, prior authorization requirements, coverage restrictions, decision-maker influence, and reimbursement pathways into a structured payer segment profile. Use when preparing market access strategy, pricing decisions, launch planning, or account-level engagement for a drug or therapeutic area."
argument-hint: "[therapeutic-area] [geography]"
allowed-tools: ["Read"]
---

# Payer Landscape Analyzer

## Purpose
Produce a structured payer segment profile for a given therapeutic area and geography — segmenting payers by coverage type, mapping the decision-makers who control formulary access, and specifying tier dynamics, prior authorization requirements, coverage restrictions, and reimbursement pathways. Replaces scattered, anecdotal payer knowledge with a repeatable framework that market access and pricing teams can act on for launch planning, pricing, and account strategy.

## When to Use
Invoke this skill when the user asks to:
- Analyze the payer landscape for a drug, indication, or therapeutic area
- Segment payers by coverage type (commercial, Medicare, Medicaid, managed Medicaid)
- Understand formulary tier placement and prior authorization dynamics for a product
- Map payer decision-makers and their influence before an account engagement or advisory board
- Prepare payer strategy inputs for a pre-launch or launch market access plan
- Assess coverage restrictions and reimbursement pathways in a specific geography

## Inputs Required
Before starting, collect:
- **Therapeutic area / indication**: The disease state and target patient population
- **Product profile**: Drug type (small molecule, biologic, specialty, buy-and-bill vs. pharmacy benefit), stage (pre-launch, launched), and key differentiators
- **Geography**: Country and, for the US, national vs. specific state/region focus
- **Competitive context**: Standard of care and key competitors already reimbursed
- **Anticipated price / cost position**: WAC, expected net, or "high-cost specialty" positioning
- **Benefit type**: Pharmacy benefit, medical benefit, or both
- **Strategic objective**: What the analysis feeds — pricing decision, launch plan, account targeting, or contracting strategy

If price position or benefit type is missing, infer from the product profile (e.g., infused biologic → medical benefit / buy-and-bill) and state the assumption.

## Instructions

### Step 1: Segment the Payer Universe by Coverage Type
Divide the landscape into distinct payer segments and profile each. For the US, use the following segments (adapt for ex-US single-payer or regional systems as needed):

- **Commercial (Employer & Individual)**: National plans, regional plans, and self-insured employer groups. Note the largest carriers in the geography and their covered-life share.
- **Medicare (Part D & Part B)**: Distinguish Part D (pharmacy benefit, formulary-driven) from Part B (medical benefit, physician-administered). Note MA-PD plan dynamics.
- **Medicaid (FFS & Managed Medicaid)**: Fee-for-service state programs vs. managed Medicaid MCOs. Flag Medicaid Drug Rebate Program implications and state-specific PDLs.
- **Integrated Delivery Networks / IDNs & Health Systems**: Where the system controls both coverage and site of care.
- **PBM Layer**: Which PBMs (and their formulary templates) sit above the plans in this geography — this often drives access more than the plan itself.

For each segment capture: approximate covered-life share, benefit type control, and formulary decision speed.

### Step 2: Map Decision-Makers and Influence
For each payer segment, identify the roles that control or influence access and rank their decision influence (High / Medium / Low):

- **P&T Committee**: Clinical formulary decisions and tier placement
- **Chief Medical Officer / Medical Director**: Clinical policy and PA criteria authorship
- **Pharmacy Director / Chief Pharmacy Officer**: Formulary strategy and cost management
- **PBM Formulary & Trade Teams**: Rebate negotiation and formulary template placement
- **VP Market Access / Contracting**: Net pricing and value-based arrangements
- **State Medicaid Pharmacy / DUR Board** (Medicaid): PDL placement and clinical criteria

For each, note what they optimize for (clinical evidence, budget impact, rebate value) and the evidence or economic argument that moves them.

### Step 3: Analyze Formulary Tier Dynamics
For the product in this therapeutic area, model likely tier placement per segment:

- **Expected tier**: Preferred brand, non-preferred brand, specialty tier, or excluded
- **Tier drivers**: Presence of preferred competitors, class dynamics, generic/biosimilar availability
- **Cost-share implications**: Copay vs. coinsurance and the resulting patient out-of-pocket exposure
- **Competitive tier positioning**: Where standard of care and key competitors sit today

Flag whether the class is a "managed class" (aggressive utilization management) or open access.

### Step 4: Detail Utilization Management & Coverage Restrictions
Specify the utilization management (UM) hurdles the product will likely face by segment:

- **Prior Authorization (PA)**: Likely criteria (diagnosis confirmation, labs, specialist prescriber, prior therapy documentation)
- **Step Therapy**: Which agents must be tried and failed first, and typical step count
- **Quantity Limits / Dosing edits**
- **Site-of-Care restrictions** (for medical benefit / infused products)
- **Reauthorization requirements**: Response-based continuation criteria

For each restriction, note severity (access-blocking vs. administrative friction) and the clinical evidence needed to negotiate softer criteria.

### Step 5: Map Reimbursement Pathways
Trace how the product gets paid for in each segment:

- **Pharmacy benefit path**: PBM adjudication → pharmacy dispense → member cost-share
- **Medical benefit path**: Buy-and-bill or specialty pharmacy → J-code / miscellaneous code → claim submission → provider reimbursement (ASP+ dynamics for Part B)
- **Coding readiness**: Whether a permanent J-code exists or a miscellaneous code applies at launch
- **Patient support needs**: Copay assistance, PA support hubs, appeals support implied by the access profile

### Step 6: Synthesize the Payer Segment Profile
Assemble a prioritized view: rank segments by access opportunity and difficulty, and flag the 2–3 segments that most determine commercial success. State the single largest access barrier and the highest-leverage lever to address it.

## Output Format
- **Structure**: Segment-by-segment profile with a summary priority table up front, followed by detailed sections per analysis dimension
- **Length**: 1,000–1,400 words
- **Format**: Structured document with a summary table (payer segment × covered-life share × benefit type × expected tier × UM severity × decision influence) plus supporting prose and bulleted detail
- **Sections**: Payer Segmentation → Decision-Maker & Influence Map → Formulary Tier Dynamics → Utilization Management & Restrictions → Reimbursement Pathways → Synthesized Segment Priority & Key Barrier
- **Tone**: Market access strategist — precise, evidence-grounded, decision-oriented; uses correct payer terminology without over-explaining basics

## Quality Checklist
Before delivering output, verify:
- [ ] Every payer segment (commercial, Medicare, Medicaid/managed Medicaid, plus PBM layer) is profiled — none omitted
- [ ] Each segment has a decision-influence ranking tied to specific roles, not generic "the payer decides"
- [ ] Expected formulary tier is stated per segment with named tier drivers
- [ ] UM section specifies concrete PA/step-therapy criteria, not just "expect prior auth"
- [ ] Both pharmacy benefit and medical benefit pathways are addressed where the product profile warrants it
- [ ] Synthesis names the 2–3 highest-priority segments and the single largest access barrier

## Notes
- For US analyses, the PBM layer frequently controls access more than the plan itself — always surface it even when the user only names insurers
- For ex-US geographies, replace commercial/government segmentation with the relevant national HTA and reimbursement bodies; the same dimensions (decision-makers, restrictions, pathways) still apply
- Distinguish medical benefit vs. pharmacy benefit early — it determines whether buy-and-bill, site-of-care, and J-code dynamics dominate the analysis
- When product data is pre-launch and uncertain, model the likely landscape based on class analogs and state the analog used

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## How to use this skill

This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top.

**Installing in Claude Code:**
- `~/.claude/skills/<folder-name>/SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
- `<your-project>/.claude/skills/<folder-name>/SKILL.md` — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

**Using in Claude.ai, ChatGPT, Gemini, or other AI tools:**

1. Drag this file into a new chat, or copy and paste its contents
2. Send your task or request as your next message — the AI will apply the skill where it fits

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