State concentration across 13 organization NPI profiles

Our data

We computed this report from 27,965 NPI records in 13 existing legal-organization profiles. The downloadable dataset contains 402 rows at the legal organization and primary-practice state code level. The cohort consists of these selected legal-name profiles; each retains its own source boundaries.

Download the computed CSV · JSON dataset · Input checksums and provenance · Reproduction method

Two concentrated profiles illustrate different scales

Novant Health Medical Group LLC has 538 records in North Carolina out of 546, giving that state 98.53% of its extract. New York City Health and Hospitals Corporation has 59 records in New York out of 61, or 96.72%. Both distributions are concentrated, but their denominators differ substantially. The registration count gives a territory team the workload behind each percentage.

Publix Super Markets Inc. places 857 of 1,167 records in Florida, a 73.44% share. CVS Pharmacy Inc. places 749 of 1,234 in Texas, or 60.70%. These figures describe the named extracts. Use the legal-name labels when quoting them so the denominator remains tied to the selected records.

Code counts and state concentrations describe different patterns

Walgreen Co and Luxottica of America Inc. each appear under 52 primary-address state codes in these files. Their largest groups are Florida with 856 of 11,140 records and California with 268 of 1,855 records, respectively. A count of codes tells you breadth; the size of each group tells you distribution.

Genoa Healthcare LLC appears under 49 codes, with Arizona accounting for 65 of 831 records, or 7.82%. Costco Wholesale Corporation also appears under 49 codes, but California accounts for 409 of 1,917, or 21.34%. Equal code counts therefore conceal different concentrations. The full 402-row download is more useful for territory allocation than the summary's single largest-state column.

Use the right geography for the question

This report groups primary practice addresses. Mailing addresses, headquarters, secondary locations and individual-provider residences are separate geographic fields. Those alternatives can be useful for other tasks, but mixing them in one table makes the result difficult to interpret.

A team assigning operational service areas might begin with primary practice geography and then add verified secondary locations. A team assigning parent-account ownership may need a separately verified headquarters field. The NPI source fields should stay labelled in the CRM so a later user can distinguish practice geography from a central purchasing office.

Reconcile state totals before comparing territories

For every organization, the state-row counts sum to the NPI count in its source CSV. The organization_npis column repeats that denominator in the download so each row can be recomputed independently. organization_share_pct equals npi_records divided by organization_npis, multiplied by 100 and rounded to two decimals.

Rounded percentages may sum slightly above or below 100%. That display effect leaves the NPI count unchanged. Use integer counts for reconciliation and calculate aggregate shares from those counts. Keep percentages grouped by organization; each uses a different denominator and answers a within-profile question.

Build an accountable state drill-down

Choose an organization and filter the dataset to its slug. Sort its rows by NPI count, then open the existing state profile for a state you want to inspect. That profile retains the organization context and links to the underlying records. Keeping the organization in the route avoids presenting one legal-name slice as a complete state market.

When a source state code is unusual, preserve it and inspect the original record before relabelling it. A planning spreadsheet that expects 50 states needs separate handling for territory and District of Columbia codes. If a team excludes certain jurisdictions from its operating area, record that as a business filter and recalculate the denominator explicitly.

Use the distribution to plan a closer review

The download can support a review of where registrations in these 13 extracts are concentrated, which state profiles deserve closer inspection, and how a source-data workload might be divided geographically. Use the state counts to choose which source records to inspect next.

Those commercial questions require additional definitions and evidence. Unique address counts, current operating status, independently established ownership and a defined market population would each change the denominator. Keep this table as a dated source distribution, then document any additional transformations in a separate analysis instead of presenting them as facts supplied by NPPES.

Method and reproducibility

Group each retained organization CSV by the primary practice state field. Count NPI rows in each group, preserve the source state code, and divide by the total NPI rows in the same organization file. Emit one row per organization and state-code pair. The summary table shows the largest group per organization. No secondary address, mailing address, corporate headquarters or external ownership data enters the calculation.

Limitations: A state-code count measures where the selected registrations list their primary practice addresses. It is not a count of unique facilities, active offices, customers or headquarters. Codes can include the District of Columbia and territories; a count above 50 must not be presented as more than 50 states. Selected legal names do not necessarily cover a whole brand, and the cohort is not representative of all providers. These distributions cannot establish reachable buyers, revenue, local demand or market share. Those questions require verified operating locations, ownership and a defined market population.

This analysis and its prose were prepared with AI assistance. The 13 input CSV files are the downloads already attached to the organization profiles below. We read identifiers and ZIP codes as text, preserve legal names, and calculate each organization independently. The provenance file records every input SHA256 and row count. The analysis code is included with the reviewable source; the public CSV and JSON contain identical rows. The derived downloads contain aggregate organization-level counts and source-field summaries.

Underlying source: CMS NPPES dissemination files, identified in each profile as the September 2026 monthly release. The public CMS index was under maintenance when this analysis was prepared; we used the retained extracts and their recorded provenance, using the original recorded source vintage. CMS explains the NPI standard.

Source profiles and state drill-downs

• COSTCO WHOLESALE CORPORATION profile, source records and method
• CVS PHARMACY INC profile, source records and method
• GENOA HEALTHCARE LLC profile, source records and method
• LUXOTTICA OF AMERICA INC profile, source records and method
• NATIONAL VISION INC profile, source records and method
• NEW YORK CITY HEALTH AND HOSPITALS CORPORATION profile, source records and method
• NOVANT HEALTH MEDICAL GROUP, LLC profile, source records and method
• PUBLIX SUPER MARKETS INC profile, source records and method
• TOTAL RENAL CARE INC profile, source records and method
• WALGREEN CO profile, source records and method
• WALMART INC. profile, source records and method
• WAL-MART STORES EAST LP profile, source records and method
• WAL-MART STORES, INC profile, source records and method

Each profile links to its existing state page and filtered source records. Those pages provide the next level of detail; use them to inspect the records behind a legal-name distribution. Start with CVS Pharmacy Inc. in Texas, Novant Health Medical Group in North Carolina, or the organization research directory.