The opioid map
Fig. 01 · opioid claims as a share of all Part D claimsOpioids are a small slice of Part D claims nationally, but the rate is not spread evenly. It runs highest across the South and the Mountain West and lowest across the Northeast and mid-Atlantic - Alabama (5.4%) sits more than twice as high as New York (2.2%).
- < 3.5%
- 3.5 - 4.0%
- 4.0 - 4.5%
- 4.5 - 5.0%
- 5.0% +
State-by-state table (51 rows, sorted high to low)
| State | Opioid claim rate | Part D spend | Claims |
|---|---|---|---|
| Alabama | 5.4% | $5.09B | 31M |
| Utah | 5.4% | $1.45B | 9M |
| Idaho | 5.2% | $1.2B | 8M |
| Oklahoma | 5% | $3.09B | 19M |
| Arkansas | 4.9% | $2.55B | 19M |
| Colorado | 4.8% | $3.41B | 19M |
| Nevada | 4.8% | $1.87B | 11M |
| Oregon | 4.8% | $2.81B | 18M |
| Montana | 4.6% | $0.67B | 5M |
| Tennessee | 4.6% | $6.89B | 42M |
| Wyoming | 4.6% | $0.25B | 2M |
| Georgia | 4.5% | $8.62B | 51M |
| Kentucky | 4.5% | $4.88B | 31M |
| Washington | 4.5% | $4.55B | 28M |
| Indiana | 4.4% | $6.28B | 38M |
| Louisiana | 4.4% | $4.52B | 29M |
| Michigan | 4.4% | $9.4B | 55M |
| North Carolina | 4.4% | $9.75B | 57M |
| Arizona | 4.3% | $4.96B | 29M |
| Kansas | 4.3% | $2.23B | 15M |
| Mississippi | 4.2% | $2.65B | 18M |
| Alaska | 4.1% | $0.39B | 2M |
| Missouri | 4.1% | $5.75B | 38M |
| South Carolina | 4.1% | $4.88B | 28M |
| Maryland | 4% | $4.03B | 21M |
| New Mexico | 4% | $1.23B | 8M |
| Delaware | 3.9% | $0.9B | 5M |
| Texas | 3.8% | $19.28B | 108M |
| Florida | 3.7% | $20.29B | 124M |
| California | 3.5% | $27.1B | 146M |
| Maine | 3.5% | $1.47B | 8M |
| Nebraska | 3.5% | $1.48B | 10M |
| South Dakota | 3.5% | $0.65B | 5M |
| Virginia | 3.5% | $5.54B | 34M |
| Wisconsin | 3.5% | $4.73B | 30M |
| Illinois | 3.3% | $9.23B | 56M |
| Iowa | 3.3% | $2.41B | 18M |
| Ohio | 3.3% | $10.85B | 68M |
| Vermont | 3.3% | $0.54B | 3M |
| West Virginia | 3.3% | $1.85B | 12M |
| Minnesota | 3.2% | $3.95B | 26M |
| New Hampshire | 3.2% | $1.13B | 7M |
| North Dakota | 3% | $0.52B | 4M |
| Pennsylvania | 3% | $13.21B | 79M |
| Connecticut | 2.9% | $3.95B | 19M |
| Hawaii | 2.9% | $0.92B | 4M |
| Massachusetts | 2.9% | $7.22B | 37M |
| District of Columbia | 2.6% | $0.62B | 2M |
| New Jersey | 2.6% | $7.72B | 40M |
| Rhode Island | 2.5% | $0.88B | 6M |
| New York | 2.2% | $22.47B | 106M |
Full Real DY2023 ingest: Opioid_Drug_Flag = Y claims as a share of all Part D claims, rolled up per Prscrbr_Geo_Cd (state).
Fifty states, one gradient
Fig. 02 · states by opioid claim rateThe map colours space; this is the same data as a shape. Most states pile up just below and around the 4% mark - the median state sits at 4% - and then the distribution thins into a short, dark tail: only a handful of states clear 5%, but those are the ones the map paints deepest. Same buckets, same ramp as the map above.
State counts by bucket (51 states)
| Opioid claim rate | States | Share of states |
|---|---|---|
| < 3.5% (most common) | 16 | 31% |
| 3.5-4.0% | 9 | 18% |
| 4.0-4.5% | 12 | 24% |
| 4.5-5.0% | 10 | 20% |
| 5.0% + | 4 | 8% |
Full Real DY2023 ingest: the 51 states binned from the same per-state opioid rates as the map, on the identical thresholds.
The handful that dominates
Fig. 03 · top brand drugs by Part D spend, 2023Part D is a river that pools in a few places. A single blood thinner, Eliquis, is the largest line item in the entire program - and the diabetes and obesity drugs stacked behind it are the fastest-climbing money in American medicine. Bar length is gross spend; the ledger beneath adds the tell that spend alone hides - cost per claim.
Full ledger (spend, claims, beneficiaries, cost per claim)
| Drug | Class | Spend | Claims | Benef. | Cost / claim |
|---|---|---|---|---|---|
| Eliquis Apixaban | Anticoagulant | $18.3B | 21.2M | 3.93M | $862 |
| Ozempic Semaglutide | GLP-1 diabetes | $9.2B | 6.9M | 1.46M | $1,327 |
| Jardiance Empagliflozin | SGLT2 diabetes | $8.8B | 8.1M | 1.88M | $1,084 |
| Trulicity Dulaglutide | GLP-1 diabetes | $7.4B | 5.3M | 0.94M | $1,385 |
| Xarelto Rivaroxaban | Anticoagulant | $6.3B | 6.7M | 1.32M | $948 |
| Trelegy Ellipta Fluticasone/Umeclidin/Vilanter | Respiratory inhaler | $4.5B | 5M | 1.05M | $889 |
| Humira(Cf) Pen Adalimumab | Autoimmune biologic | $4.4B | 0.5M | 0.06M | $9,231 |
| Farxiga Dapagliflozin Propanediol | SGLT2 diabetes | $4.3B | 4.3M | 0.99M | $1,010 |
| Januvia Sitagliptin Phosphate | DPP-4 diabetes | $4.1B | 4M | 0.84M | $1,015 |
| Revlimid Lenalidomide | Cancer therapy | $3.9B | 0.2M | 0.04M | $17,852 |
| Entresto Sacubitril/Valsartan | Heart failure | $3.4B | 3.2M | 0.66M | $1,072 |
| Lantus Solostar Insulin Glargine,hum.Rec.Anlog | Insulin | $3.2B | 4.9M | 1.2M | $640 |
Full Real DY2023 ingest: national rows ranked by Tot_Drug_Cst (Eliquis led at $18.3B). Spend, claims, and beneficiary counts are the source values; the therapeutic-class tag beneath each name is a curator label.
Two economies of a blockbuster
Fig. 04 · cost per claim vs claim volumeThe same top-of-the-leaderboard spend arrives two completely different ways. Down and to the right sit the maintenance drugs - Eliquis, the diabetes pills - filling tens of millions of prescriptions at a few hundred to a thousand dollars each. Up and to the left sit the specialty drugs - Revlimid, Humira - reaching a fraction as many people at four and five figures a fill. Bubble area is total spend.
Reading: a maintenance drug and a specialty drug can post the same $3-5B in spend from opposite corners - one on volume, one on price. Both axes are log scaled to hold the 30x spread.
The two economies, as a table (sorted by cost per claim)
| Drug | Cost / claim | Claims | Spend |
|---|---|---|---|
| Revlimid | $17,852 | 0.2M | $3.9B |
| Humira(Cf) Pen | $9,231 | 0.5M | $4.4B |
| Trulicity | $1,385 | 5.3M | $7.4B |
| Ozempic | $1,327 | 6.9M | $9.2B |
| Jardiance | $1,084 | 8.1M | $8.8B |
| Entresto | $1,072 | 3.2M | $3.4B |
| Januvia | $1,015 | 4M | $4.1B |
| Farxiga | $1,010 | 4.3M | $4.3B |
| Xarelto | $948 | 6.7M | $6.3B |
| Trelegy Ellipta | $889 | 5M | $4.5B |
| Eliquis | $862 | 21.2M | $18.3B |
| Lantus Solostar | $640 | 4.9M | $3.2B |
Full Real DY2023 ingest: cost per claim is Tot_Drug_Cst / Tot_Clms for each of the top national brand rows.
A short head, a long tail
Fig. 05 · cumulative share of spend by cumulative share of productsPart D covers more than 3,607 distinct drug products, but the money does not spread across them. Ranked most-expensive first, the top 10 drugs - 0.3% of the catalog - already take 26% of the spend, and the top 100 take 64%. The curve leaps off the origin and then crawls: the remaining thousands of products are a very long, very flat tail.
Concentration by ranked cut (products vs spend)
| Ranked cut | Share of products | Share of spend | Cumulative spend |
|---|---|---|---|
| Top 10 drugs | 0.3% | 26% | $71B |
| Top 100 drugs | 2.8% | 64% | $176B |
| Top 500 drugs | 13.9% | 91% | $250B |
| All drugs | 100% | 100% | $276B |
Full Real DY2023 ingest: cumulative Tot_Drug_Cst over the national drug list ranked most-expensive first (top 10 = 0.3% of products / 26% of gross spend; top 100 = 2.8% / 64%).
Where the dollars pool by class
Fig. 06 · therapeutic-class share of the branded tierGroup the branded tier by what the drugs are for and one family now dwarfs the rest. Diabetes & obesity - the GLP-1 and SGLT2 drugs and their diabetes cousins - is roughly 28% of branded spend on its own, more than anticoagulants and autoimmune biologics put together. A decade ago it would have been a sliver.
- Diabetes & obesity 28%
- Oncology & specialty 23%
- Autoimmune & biologics 17%
- Other brands 17%
- Anticoagulants 15%
Class breakdown (spend, share, representative brands)
| Therapeutic family | Share | Spend | Representative brands |
|---|---|---|---|
| Diabetes & obesity | 28% | $71B | Ozempic, Jardiance, Trulicity, Farxiga |
| Oncology & specialty | 23% | $58B | Revlimid, Imbruvica, Biktarvy |
| Autoimmune & biologics | 17% | $43B | Humira, Enbrel, Otezla |
| Other brands | 17% | $43B | Trelegy, Dupixent, and the rest of the branded tier |
| Anticoagulants | 15% | $38B | Eliquis, Xarelto |
Illustrative The rest of this page is a real CMS ingest, but therapeutic-class families are a curator-added editorial layer (CMS ships no class column, and there is no reproducible "branded tier" boundary), so this split stays an illustrative stand-in anchored to the diabetes-drug surge.
Two curves, opposite ways
Fig. 07 · Part D spend and opioid share, 2013-2023Across the decade the two headline numbers moved in opposite directions. Gross Part D spend more than doubled, from $104B to $276B, with the GLP-1 and SGLT2 class erupting from almost nothing to $36.8B - a rise steep enough to bend the whole program's total. Meanwhile the opioid share of claims slid from 5.8% to 3.7% as prescribing tightened. Two panels, one shared year axis; never a dual axis.
Full Real ingest: national totals looped over every Geography-and-Drug vintage, 2013-2023. GLP-1/SGLT2 spend is the sum of Tot_Drug_Cst for that ingredient class; opioid share is Opioid_Drug_Flag = Y claims over all claims.
The class that ate the decade
Fig. 08 · share of branded spend, 2013 vs 2023The same families, ten years apart. Anticoagulants and oncology drugs climbed; the old autoimmune giants ceded ground as biosimilars arrived. But one line runs away from the rest: Diabetes & obesity went from 9% of branded spend to 28% - a re-sorting of the whole branded market around a single therapeutic idea.
Share shift by class (2013, 2023, change)
| Therapeutic family | 2013 | 2023 | Change |
|---|---|---|---|
| Diabetes & obesity | 9% | 28% | +19 pts |
| Oncology & specialty | 15% | 23% | +8 pts |
| Autoimmune & biologics | 24% | 17% | -7 pts |
| Anticoagulants | 6% | 15% | +9 pts |
Illustrative Like the class mix above, this slope rests on curator-defined families (no CMS class column), so the two endpoints stay illustrative stand-ins anchored to the documented GLP-1/SGLT2 surge and the biosimilar erosion of legacy biologics.
Who writes the opioids
Fig. 09 · opioid share of a specialty's Part D claimsThe state map hides the sharper split. Opioid prescribing concentrates by specialty far more than by geography: interventional pain and pain management write opioids on a huge fraction of their claims, while primary care sits near the 3.6% national line. But volume flips the story - family practice alone files 404.9M claims, so the low-rate generalists still write most opioid prescriptions overall.
Rate vs volume by specialty (the counterweight the bars hide)
| Specialty | Opioid rate | vs national | Claims |
|---|---|---|---|
| Interventional Pain Management | 56% | +52.4 pts | 3.9M |
| Pain Management | 52.5% | +48.9 pts | 5.2M |
| Anesthesiology | 49.1% | +45.5 pts | 5M |
| Physical Medicine & Rehab | 33.8% | +30.2 pts | 7.3M |
| Orthopedic Surgery | 30% | +26.4 pts | 7.5M |
| General Surgery | 20.2% | +16.6 pts | 3.3M |
| Emergency Medicine | 7.8% | +4.2 pts | 15.6M |
| Hematology/Oncology | 7% | +3.4 pts | 8.2M |
| Dentist | 6.8% | +3.2 pts | 11.6M |
| Nurse Practitioner | 3.6% | +0 pts | 286.6M |
| Family Practice | 2.9% | -0.7 pts | 404.9M |
| Internal Medicine | 2.3% | -1.3 pts | 366.1M |
Full Real DY2023 ingest: opioid share (Opioid_Tot_Clms / Tot_Clms) volume-weighted by Prscrbr_Type over the ~1.4M-row companion by-Provider file. The twelve specialties shown are an editorial selection spanning the rate range.