Prescribers

Who drives spending on the top Part D drugs? This page reads pre-aggregated views over fct_prescriber_drug_spending (one row per prescriber npi × brand × generic, ~28M rows — the raw grain never leaves the warehouse). All dollar figures are prescriber-billed drug cost: what pharmacies billed for the prescriptions a prescriber wrote, before rebates — not net Part D program spending.

Top drugs by prescriber-billed cost

The list splits into two regimes: mass-market drugs written by hundreds of thousands of prescribers at a few hundred dollars per claim (anticoagulants, GLP-1s), and specialty drugs written by a few thousand prescribers at five figures per claim.

How concentrated is each top drug?

For each of the top 25 drugs, the share of its billed cost written by its top 1% of prescribers (by cost; the 1% headcount is rounded up, so every drug keeps at least one). Spending on the biggest drugs is not dominated by a handful of prescribers:

For Eliquis — the biggest drug at $19.9B — the top 1% of its

Which specialties drive the spending?

Primary care (nurse practitioners, internal medicine, family practice, physician assistants) bills the most in aggregate through sheer claim volume, while oncology and rheumatology reach the top ten with a tiny fraction of the claims — their cost per claim runs roughly 5–30× higher.

Where is the spending written?

State totals track population; the state column also carries territories and military/unknown codes, which is why there are more than 51 values in the source.

Top prescriber-drug combinations

The largest single prescriber×drug lines among the top 25 drugs. Even the biggest individual line is a small sliver of its drug's total — the share_of_drug_cost column makes the concentration story above concrete.

Prescriber-billed vs gross Part D spending

The top 25 drugs joined to fct_part_d_drug_spending's manufacturer-roll-up gross spending for the same drug, via drug_key (exact upper-cased brand + generic match; staging strips the Part D spending file's trailing-* aggregate marker, so the names line up).

Caveats

• Single snapshot, no trend. The prescriber mart is a single snapshot (calendar-2024 claims, vintage in the mart's as_of column) with no year column, so nothing on this page is a time series.
• Small rows are suppressed entirely. CMS removes prescriber-drug rows with fewer than 11 claims, so every row here has ≥ 11 claims, totals undercount true spending, and low-volume prescribers are invisible (which also inflates the top-1% shares slightly).
• Beneficiary counts are unusable in aggregate. total_beneficiaries is NULL (suppressed below 11) on 54.5% of rows, so this page never sums beneficiaries or computes per-beneficiary figures.
• Star-marked spending rows aggregate brand and generic versions. The Part D spending file star-marks drug names whose estimates aggregate brand and generic versions; staging strips the marker so every row here conforms to dim_drug ( 0.0% of rows orphan, enforced by a dbt test) and the gross-spending comparison covers all 25 top drugs — but an aggregated gross figure can overshoot its brand-only prescriber-billed counterpart, which is why Stelara's billed/gross ratio runs low.
• Billed ≠ net. Prescriber-billed drug cost ignores manufacturer rebates and DIR; actual net Part D spending is materially lower, especially for high-rebate brand drugs.
• Specialty is self-reported. prescriber_type comes from the provider's Medicare enrollment/claims specialty, with 182 distinct values of varying granularity (plus a negligible Unknown bucket — 2 NPIs with no specialty on file).