Medicare Part D prescribers by geography and drug
Centers for Medicare & Medicaid Services
In a RepVector build, this dataset shows where money is actually being spent and by whom.
Enter one NPI and see that prescriber's Medicare Part D drug mix, free.
Look up a Part D prescriber| Brand name | Generic name | Total prescribers | Total claims | Total 30-day fills | Total drug cost |
|---|---|---|---|---|---|
| Abiraterone Acetate | Abiraterone Acetate | 360 | 9,001 | 9,458.1 | $16,854,622 |
| Abilify Maintena | Aripiprazole | 546 | 6,002 | 6,311.4 | $16,683,670 |
| Albuterol Sulfate Hfa | Albuterol Sulfate | 13,460 | 448,207 | 531,738.5 | $13,195,706 |
| Abrysvo | Rsv Vacc, Pref A And Pref B/Pf | 1,331 | 39,757 | 39,887.1 | $11,147,736 |
| Acthar | Corticotropin | 17 | 111 | 136.6 | $10,477,748 |
| Adempas | Riociguat | 44 | 612 | 627 | $8,465,818 |
| Advair Hfa | Fluticasone Propion/Salmeterol | 2,502 | 14,906 | 19,503 | $6,294,696 |
| Actemra Actpen | Tocilizumab | 122 | 1,335 | 1,590.5 | $5,841,974 |
What this dataset is
Aggregated Medicare Part D prescribing volume and drug cost by state, broken out by brand and generic drug name — total prescribers, claims, 30-day fills and total drug cost. Shows which drugs are prescribed most, and at what cost, to Medicare enrollees in a state. It is published by Centers for Medicare & Medicaid Services and can be queried at state level, refreshed annual. Each row is an aggregate statistic for a geography, so results describe a market as a whole rather than a single account.
Why it is useful
- Ranks targets by observed volume rather than by guesswork or list order.
- Surfaces high-volume accounts that a headcount-only view would rank as average.
- Provides the evidence a manager expects behind a territory investment ask.
Questions it helps answer
- Which accounts here already transact at meaningful volume?
- Where is spend concentrated inside an otherwise flat market?
- Which targets justify a named-account plan rather than a routine call?
How different verticals use it
RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.
Shows where reimbursement dollars actually land, not just where patients are.
Finds agencies and awardees with budget already committed to your category.
Tracks funded projects before they become public procurement notices.
Identifies buyers with recurring contract spend in your product line.
How RepVector uses it
- You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at state runs without you knowing any codes.
- The planner selects Medicare Part D prescribers by geography and drug only when your question matches what it actually reports. It is never included to pad a result.
- Returned rows are normalised into the shared metric layer, so figures from Centers for Medicare & Medicaid Services line up with every other source in the same dashboard instead of sitting in an isolated table.
- Quality checks score coverage and recency. If Centers for Medicare & Medicaid Services suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
- The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.
What it does not tell you
- Reported with a lag and often suppressed at low counts, so recent shifts may not appear yet.
| Field | Key | Type |
|---|---|---|
| Brand name | brandName | string |
| Generic name | genericName | string |
| Total prescribers | totalPrescribers | number |
| Total claims | totalClaims | number |
| Total 30-day fills | total30DayFills | number |
| Total drug cost | totalDrugCost | currency |
| Total beneficiaries | totalBeneficiaries | number |
| Opioid | opioid | string |
How it fits with the rest of the catalog
Spending data is the ranking signal; provider registries supply the identity it attaches to. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to Medicare Part D prescribers by geography and drug:
Other spending datasets
Common questions
What does Medicare Part D prescribers by geography and drug contain?
Aggregated Medicare Part D prescribing volume and drug cost by state, broken out by brand and generic drug name — total prescribers, claims, 30-day fills and total drug cost. Shows which drugs are prescribed most, and at what cost, to Medicare enrollees in a state. It is published by Centers for Medicare & Medicaid Services at state grain.
How often is it refreshed?
Centers for Medicare & Medicaid Services publishes on a annual cycle. RepVector re-reads the source on that cadence and keeps every prior capture, so you can see what changed.
Do I need an account to use it?
No. Browsing the catalog and the free lookup tools needs no account. Running a full market build across every county in a territory is the paid product.
Build the list for one county and see whether the names are right.
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