National Medical Oncology Supply by State — NPPES 2026 Snapshot

The American Society of Clinical Oncology (ASCO) has published recurring workforce reports — most recently the State of Cancer Care in America and successor analyses — that document a structural and growing gap between U.S. oncologist supply and projected cancer-care demand. The American Cancer Society's annual Cancer Statistics report quantifies the demand side: cancer incidence rises with the aging population, while geographic disparity in cancer mortality is well-documented (rural-urban, Southern-Northeastern, racial-ethnic gradients).

Cancer care is unusually geographically concentrated. A small number of National Cancer Institute (NCI)-designated cancer centers, almost all in major metropolitan academic medical centers, anchor the high-density end of the distribution. Rural counties often have no medical oncologist within a one-hour drive, routing cancer treatment to community-oncology hubs, telemedicine consults from academic centers, or — in the most underserved areas — significantly delayed care.

This study reports what the public NPPES dataset shows: every active NPI-1 medical oncologist (NUCC code 207RX0202X — Internal Medicine, Medical Oncology) bucketed by Practice Address state and divided by U.S. Census Bureau 2024-vintage state population. It is a density measurement at state granularity — not a cancer-outcomes study, and not a count of all cancer-care providers (radiation oncologists, surgical oncologists, hematologic oncologists, oncology nurse practitioners are excluded — see scope qualifier below).

Source. The U.S. Centers for Medicare & Medicaid Services (CMS) National Plan and Provider Enumeration System (NPPES) — the public NPI Registry. Every U.S. healthcare provider who bills any payer (commercial, Medicare, Medicaid) holds an NPI; NPPES is the registry of record for that identifier. The public API at https://npiregistry.cms.hhs.gov/api/?version=2.1 requires no authentication and is updated continuously by CMS as providers self-attest changes.

Counted (kept). Each provider in our snapshot meets all three criteria:

1. Type 1 NPI (individual practitioner). Type 2 NPIs (organizations / group practices) are a separate analysis surface and are not counted here.

2. Active — basic.status = "A" and basic.deactivation_date is null.

3. At least one Healthcare Provider Taxonomy code in the medical oncology family:

   • 207RX0202X — Internal Medicine, Medical Oncology

This study counts only physicians whose primary NPPES taxonomy is the medical-oncology code (207RX0202X). Oncology adjacent specialties — Surgical Oncology (2086S0122X), Radiation Oncology (2085R0001X), Hematology / Hematology-Oncology (207RH0003X), Pediatric Hematology-Oncology (2080P0207X), Gynecologic Oncology (207VX0201X) — carry their own codes and are out of scope. Oncology nurse practitioners (363LX0001X-adjacent), oncology physician assistants, and oncology pharmacists are out of scope. Each of these is a defensible separate study; bundling them here would mix sub-specialty supply questions and dilute the editorial frame.

State assignment. Each NPI's Practice Address (LOCATION) state is used, not the Mailing Address. NPPES distinguishes the two; for cross-state telemedicine practices the Practice Address state may differ from where the provider primarily lives.

Not counted. Providers with deactivated NPIs, providers whose only medical oncology-adjacent taxonomy is outside the codes above, residents and fellows whose primary taxonomy is the "Student" code (390200000X), and providers without a U.S. Practice Address.

The national rate of 2.14 active medical oncologists per 100,000 residents is a single number; the state spread is what consumers, providers, and policy readers actually feel.

Top 5 by density:

• Massachusetts — 6.25 / 100k (n=446)
• District of Columbia — 4.70 / 100k (n=33)
• Maryland — 4.09 / 100k (n=256)
• Connecticut — 3.43 / 100k (n=126)
• New York — 3.27 / 100k (n=649)

Bottom 5 by density:

• Wyoming — 0.34 / 100k (n=2)
• Alaska — 0.41 / 100k (n=3)
• South Dakota — 0.43 / 100k (n=4)
• Oklahoma — 0.61 / 100k (n=25)
• Louisiana — 0.72 / 100k (n=33)

The lowest-density state holds approximately 5% of the highest-density jurisdiction's per-capita supply. The chart below shows the full ranking; the dashed marker is the 3-per-100k threshold this study uses to flag underserved jurisdictions.

44 jurisdictions rank below the 3 active medical oncologists per 100,000 residents threshold this study uses to flag underserved jurisdictions. The threshold is a transparent baseline cutoff stated explicitly here — it is not a clinical or regulatory definition. Stated baseline cutoff aligned with American Society of Clinical Oncology (ASCO) workforce literature, which has flagged a documented and growing national gap between oncologist supply and projected cancer-care demand. National-average medical-oncologist density runs roughly 4–5 per 100,000; bottom-quartile states fall below 3 per 100,000. We use 3 / 100k as the underserved cutoff. Stated explicitly here; not a clinical or regulatory definition.

The states below the threshold collectively hold 296,025,386 residents — about 87.0% of the U.S. population.

Important framing. "Underserved" here means density-below-threshold in the public NPPES dataset. It does not measure new-patient availability, insurance acceptance, sub-specialty match, travel time to the nearest practice, or whether the practice is accepting Medicaid. Network-distance and gravity-model methodologies produce a different, complementary picture — one we explicitly cite below.

Density per 100,000 residents is the most transparent supply baseline. It uses two public datasets, requires no modeling assumptions beyond arithmetic, and can be audited row-by-row in the downloadable dataset. Every reader can audit the numbers themselves.

It is not spatial access. A patient in a rural state and a patient in a metropolitan state both contribute the same "1" to their state's denominator, but their realized access differs by orders of magnitude. Headline figures derived from network-distance models (e.g. "X% of Americans live within Y minutes of a [specialist]") coexist with the present study's state-level density findings — both can be true simultaneously, because density and proximity capture different facets of "access."

The healthcare workforce literature has more advanced approaches:

• Two-Step Floating Catchment Area (E2SFCA) and gravity models treat access as a function of provider supply, population demand, and distance decay. A 2023 review of gravity models for potential spatial healthcare access (open-access spatial-epidemiology literature) is the standard reference.
• Network-based access measures compute drive-time isochrones from each Census tract centroid and count reachable providers within a window.

This study does not implement E2SFCA, gravity, or network distance. It reports state-level density and acknowledges the gap. Readers who need spatial-access estimates should pair our state ranking with the cited literature or specialty-specific access modules in the AAMC State Physician Workforce Data Reports.

Public-health relevance. The American Cancer Society's Cancer Statistics report and ASCO's workforce literature together document a strong geographic pattern: states with the lowest oncologist density also tend to have higher cancer mortality and longer time-to-treatment intervals, particularly for cancers where time-to-treatment matters most (lung, pancreatic, esophageal). The shape of the relationship is sharp at the low end — moving a county from zero medical oncologists to even modest presence has substantially higher marginal value than moving an already-saturated metro from 8 / 100k to 10 / 100k.

Capacity-expansion vehicles flagged in the ASCO workforce literature: oncology nurse practitioners and physician assistants (oncology APPs), tele-oncology consultations from NCI-designated cancer centers, hub-and-spoke partnerships between academic and community-oncology practices, and reimbursement reform for telehealth oncology. None of these alters the NPI-1 medical-oncologist count this study tracks — but each materially changes patient-facing capacity.

Citation transparency. This study makes no clinical claims about any individual provider. The density-to-outcomes link is documented in the cancer-policy literature; we cite it as context for why density matters, not as a finding our dataset proves.

Most state-level medical oncology supply numbers in circulation come from one of three places: (1) the AAMC State Physician Workforce reports, which use specialty-society membership and AMA Masterfile cross-references; (2) commercial workforce-data vendors that license those underlying datasets; or (3) press-release figures from advocacy organizations.

This study is different in three concrete ways:

1. Single public source family. Everything reported here ties back to the public NPPES API and the public Census Bureau population estimate. Both are free. Both are updated on cadences CMS and Census publish. Anyone with a web browser can re-run the underlying queries.
2. Record-level traceability. Every provider in the count has an NPI. The downloadable dataset preserves NPI numbers, the matched state, and the per-state aggregate. A reader auditing a specific state's count can pull the corresponding NPI list, look each one up in NPPES, and audit the active-medical oncology-taxonomy criterion themselves.
3. No quality attestation. Fonteum does not run a checking process for individual medical oncologists. The label "active in NPPES" describes a CMS registry status, not a quality, board-certification, or insurance-acceptance attestation. Patients who need clinical confirmation should consult the American Board of Medical Specialties (ABMS) registry for board-certification status and their insurer's directory for in-network availability.

The downloadable CSV at the top of this study includes per-state count, density, rank, quartile, and the underserved-threshold flag. The downloadable JSON adds the snapshot metadata and source URLs.

Suggested citation:

Ownlisted Research. (2026). National Medical Oncology Supply by State — NPPES 2026 Snapshot. Ownlisted. Retrieved from https://fonteum.com/research/oncology-supply-by-state-2026

Reuse and attribution. Charts, tables, and the downloadable CSV / JSON may be cited or reproduced with attribution to Ownlisted Research and a link to this study. Carry the snapshot date (2026-05-06) so readers know the dataset version. Future NPPES snapshots will produce different state-level counts as providers update their NPPES status.

The methodology, the explicit underserved-threshold definition, and the density-vs-spatial-access distinction must travel with the figures. Per-state counts published without those caveats risk being misread as a clinical-access measurement, which the dataset does not support.

Press / media inquiries. Reach the Ownlisted Research team via the brand-hub contact page. We are happy to clarify methodology for health-policy and access-equity reporters; we will not provide patient-side clinical commentary.

Cited literature (suggested for follow-up reading):

• American Society of Clinical Oncology (ASCO) — most recent oncology workforce study and the State of Cancer Care in America series. The standard references for U.S. oncologist supply, demand, and projection forecasts.
• American Cancer Society. Cancer Statistics — annual report. State-level cancer incidence, mortality, and stage-at-diagnosis statistics.
• U.S. National Cancer Institute (NCI). NCI-designated Cancer Centers directory; geographic distribution of comprehensive cancer-care infrastructure.
• Peer-reviewed oncology workforce studies (e.g., Journal of Clinical Oncology, JAMA Oncology, Health Affairs) on density-to-outcomes linkage and projected supply gaps.
• Gravity models for potential spatial healthcare access (2023). Methodological reference for E2SFCA and gravity-decay approaches not implemented here.

• Density is not spatial access. Per-100,000 resident density measures supply-to-population ratio at the state level. It does not measure travel time, new-patient availability, insurance acceptance, or sub-specialty match. Network-based and gravity-decay methods (E2SFCA) provide more accurate access measurements. We have not implemented those methods.
• NPPES taxonomies are self-reported. Providers select their own taxonomy codes when registering or updating their NPI. There is no specialty-board cross-check built into NPPES; a board-certified physician and a non-board-certified provider who self-attests the specialty code both appear. Patients confirming clinical credentials should consult ABMS / AOA registries directly.
• Practice Address state, not where the provider lives or practices most. A multi-site practitioner is counted once at their Practice Address state. Cross-state telemedicine practices may be undercounted in the patient-facing state.
• Active-flag accuracy. NPPES updates active/deactivated status as providers self-attest. Some providers carry stale NPIs from earlier career stages. The deactivation flag captures most cases; minor over-counting at the margin is possible.
• Census ACS 2024 vintage uncertainty. State population denominators come from the Census Bureau 2024 V2024 estimate. ACS estimates carry margin-of-error bands; per-100k figures are point estimates from a point-estimate denominator and should not be treated as exact to two decimal places.
• No procedure-mix or sub-specialty breakout. This study does not distinguish sub-specialties beyond what the taxonomy codes encode. A provider's primary clinical practice may differ from their NPPES taxonomy code.
• Type 2 (organization) NPIs excluded. Hospital-employed medical oncologists who only operate under a Type 2 organization NPI are under-counted. Most medical oncologists carry both, so the under-count effect is small but non-zero.
• No outcomes / quality-of-care claims. This study reports NPPES-listed counts and Census-derived densities. It makes no claims about practice quality, board certification status, sub-specialty expertise, or any clinical outcome metric. This is not medical advice. Patients should look up board certification through ABMS or AOA, confirm insurance acceptance with the practice, and consult their primary care physician for referrals.
• Snapshot in time. Counts reflect the 2026-05-06 NPPES snapshot. The cached dataset is preserved at data/nppes/oncology-2026-05-06.json for re-analysis.