US Home Health Aide Providers
U.S. · 49,511 licensed providers
There are 49,511 Home Health Aide Providers in the US as of September 2026. They are in all 50 states, DC and Puerto Rico.
49,511 licensed healthcare providers at their practice address. 100% carry a street address, 100% a telephone number, 17% a state license number, 100% a specialty from the NUCC taxonomy.
More about this list
Built from the CMS National Plan and Provider Enumeration System (NPPES) monthly file, the NPPES deactivation report, the NUCC provider taxonomy and the CMS Care Compare Doctors and Clinicians national file. Every deactivated NPI is removed — 351,911 of them — rather than shipped as an empty row, and the address is the practice location, never the mailing address. These rows are individual providers, so the record is a licensed person at the address where they practise. Buy the organization file instead if you need businesses only. Coverage is 52 states and territories.
Need just some of them? Ask in your own words.
●Where the rows are
≡Sample Data Preview
| name | address | city | state | zip | phone | npi | entity type | specialty | county | cbsa title | credential | license number | license state | medicare specialty | facility affiliations | medical school | graduation year | est years in practice | oig excluded | npis at address | last name | first name | middle name | name prefix | name suffix | primary taxonomy code | provider grouping | classification | all taxonomy codes | taxonomy count | zip plus4 | fax | direct address | other endpoint | endpoint count | mailing address | mailing city | mailing state | mailing zip | mailing country | sex | sole proprietor | other identifiers | other identifier types | other identifier issuers | taxonomy groups | secondary practice locations | enumeration date | last update date | certification date | individual pac id | medicare enrollment id | group address | group city | group state | group zip | practices at | accepts assignment | group accepts assignment | medicare enrolled | oig exclusion type | oig exclusion date | oig exclusion category | oig exclusion specialty | oig reinstatement date | oig waiver date | oig address | oig city | oig state | secondary practice locations n | secondary address | secondary city | secondary state | secondary zip | secondary phone | secondary phone ext | secondary fax | additional name count | endpoint affiliation | county fips | state fips | cbsa code | cbsa type | zip land sqmi | geo precision | address quality | latitude | longitude | country |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AGAPITA CADISAL LLANEZA | 3713 ROBIN ST | Anchorage | AK | 99504 | (907) 339-9198 | 1124518469 | Individual | Home Health Aide | Anchorage Municipality | Anchorage, AK | 101262 | AK | 0 | N | 5 | LLANEZA | AGAPITA | CADISAL | 374U00000X | Nursing Service Related Providers | Home Health Aide | 374U00000X | 1 | 99504-4674 | 9075220564 | 0 | 3713 ROBIN ST | ANCHORAGE | AK | 99504 | US | F | N | 6876505|101262 | 05|05 | 0 | 05/11/2018 | 05/11/2018 | 0 | 0 | 02020 | 02 | 11260 | Metropolitan Statistical Area | 36.821 | source | complete | 61.190578 | -149.607154 | US | |||||||||||||||||||||||||||||||||||||||
| TABITHA PAULK | 1095 GUS PAULK RD | Ambrose | GA | 31512 | (912) 327-4967 | 1508407354 | Individual | Home Health Aide | Coffee County | Douglas, GA | 0 | N | 2 | PAULK | TABITHA | MRS. | 374U00000X | Nursing Service Related Providers | Home Health Aide | 374U00000X|376K00000X|3747A0650X|372600000X | 4 | 31512-3408 | Ambrose | 1 | 1095 GUS PAULK RD | AMBROSE | GA | 31512 | US | F | N | 0 | 10/02/2019 | 10/02/2019 | 0 | 0 | 13069 | 13 | 20060 | Micropolitan Statistical Area | 81.693 | source | complete | 31.545696 | -83.018356 | US | |||||||||||||||||||||||||||||||||||||||||||
| LAURA COSTELLO | 46 HUBBARD RD | Berwick | ME | 03901 | (978) 504-9714 | 1649817750 | Individual | Home Health Aide | York County | Portland-South Portland, ME | 0 | N | 6 | COSTELLO | LAURA | 374U00000X | Nursing Service Related Providers | Home Health Aide | 374U00000X | 1 | 03901-2342 | gmail | 1 | 46 HUBBARD RD | BERWICK | ME | 03901 | US | F | N | 0 | 12/09/2019 | 02/05/2022 | 02/05/2022 | 0 | 0 | 23031 | 23 | 38860 | Metropolitan Statistical Area | 37.505 | source | complete | 43.29932 | -70.842062 | US | |||||||||||||||||||||||||||||||||||||||||||
| SWETA D SHAH | 1568 ROUTE 130 | North Brunswick | NJ | 08902 | (732) 986-5424 | 1245881655 | Individual | Home Health Aide | Middlesex County | New York-Newark-Jersey City, NY-NJ | S31427296455831 | NJ | 0 | N | 2 | SHAH | SWETA | D | 374U00000X | Nursing Service Related Providers | Home Health Aide | 374U00000X | 1 | 08902-3011 | actikare.com | 1 | 1568 ROUTE 130 | NORTH BRUNSWICK | NJ | 08902 | US | F | N | 0 | 09/26/2019 | 11/27/2023 | 0 | 0 | Acti-Kare Inc | 34023 | 34 | 35620 | Metropolitan Statistical Area | 13.17 | source | complete | 40.441513 | -74.491214 | US | ||||||||||||||||||||||||||||||||||||||||
| KAILEY FERNAU | 718 FIRETHORN TRL | Dakota Dunes | SD | 57049 | (605) 540-0266 | 1538081336 | Individual | Home Health Aide | Union County | Sioux City, IA-NE-SD | 0 | N | 13 | FERNAU | KAILEY | 374U00000X | Nursing Service Related Providers | Home Health Aide | 374U00000X | 1 | 57049-5900 | 0 | 718 FIRETHORN TRL | DAKOTA DUNES | SD | 57049 | US | F | N | 0 | 07/27/2026 | 07/27/2026 | 07/26/2026 | 0 | 0 | 46127 | 46 | 43580 | Metropolitan Statistical Area | 14.171 | source | complete | 42.523328 | -96.509711 | US |
{}What's in each row
| Field | What it is | Rows filled |
|---|---|---|
| npi | National Provider Identifier — the federal key for every US healthcare provider | 100% |
| name | Organization legal business name, or the provider's full name | 100% |
| entity_ | Organization or Individual — whether the row is a business or a licensed person | 100% |
| specialty | Primary specialty, decoded from the NUCC provider taxonomy | 100% |
| address | Practice location street address (never the mailing address) | 100% |
| city | City | 100% |
| state | Two-letter state code | 100% |
| zip | 5-digit ZIP | 100% |
| phone | Practice location telephone, digits only | 100% |
| county | County the location is in | 100% |
| cbsa_ | Cbsa title | 95% |
| latitude | Latitude | 100% |
| longitude | Longitude | 100% |
| credential | Self-reported credential text, e.g. MD, DDS, NP | 8% |
| license_ | State license number for the primary taxonomy | 17% |
| license_ | State that issued that license | 27% |
| facility_ | Facility affiliations | 100% |
| oig_ | Oig excluded | 100% |
| npis_ | How many NPIs share this practice address — the entity-vs-location fan-in | 100% |
| last_ | Last name | 100% |
| first_ | First name | 100% |
| middle_ | Middle name | 41% |
| name_ | Name prefix | 10% |
| name_ | Name suffix | 2% |
| primary_ | Primary taxonomy code | 100% |
| provider_ | NUCC top-level grouping, e.g. Allopathic & Osteopathic Physicians | 100% |
| classification | NUCC classification — the level products are cut on | 100% |
| all_ | Every taxonomy code the provider declared, pipe-separated | 100% |
| taxonomy_ | How many distinct taxonomies that is | 100% |
| zip_ | ZIP+4 where the provider filed one | 100% |
| country | Country | 100% |
| fax | Practice location fax | 12% |
| other_ | Other endpoint | 2% |
| endpoint_ | How many electronic endpoints the provider registered | 100% |
| mailing_ | Business mailing address, kept separate because it differs for a large minority | 100% |
| mailing_ | Mailing city | 100% |
| mailing_ | Mailing state | 100% |
| mailing_ | Mailing ZIP | 100% |
| mailing_ | Mailing country | 100% |
| sex | Sex | 100% |
| sole_ | Y where an individual provider is a sole proprietor | 100% |
| other_ | Other identifiers | 6% |
| other_ | Other identifier types | 6% |
| other_ | Other identifier issuers | 1% |
| taxonomy_ | Taxonomy groups | 6% |
| secondary_ | Count of additional practice locations filed since 2020 | 100% |
| enumeration_ | Date the NPI was issued | 100% |
| last_ | Date the provider last updated their NPPES record | 100% |
| certification_ | Certification date | 66% |
| secondary_ | Secondary practice locations n | 100% |
| secondary_ | Secondary address | 1% |
| secondary_ | Secondary city | 1% |
| secondary_ | Secondary state | 1% |
| secondary_ | Secondary zip | 1% |
| secondary_ | Secondary phone | 1% |
| additional_ | Additional name count | 100% |
| county_ | Five-digit federal code of that county | 100% |
| state_ | State fips | 100% |
| cbsa_ | Cbsa code | 95% |
| cbsa_ | Cbsa type | 95% |
| zip_ | Zip land sqmi | 100% |
| geo_ | How exact the map point is: the source's own point, the street address, or the ZIP code's centre | 100% |
| address_ | Whether the street address is complete, missing a house number, or a PO box | 100% |
Rows filled is measured on every row of the delivered file.
✓Where this data comes from
This dataset is built from the CMS National Plan and Provider Enumeration System (NPPES) monthly file — the federal registry every billing provider must maintain — with the NPPES deactivation report applied so retired NPIs are excluded, specialties resolved against the NUCC provider taxonomy, and Medicare participation joined from the CMS Care Compare Doctors and Clinicians national file. Nothing here comes from a provider's own website; every record is the provider's own registered entry.
September 14, 2026
File built
90 fields
Columns in the file
Fill measured
On every row of the delivered file
Deactivated NPIs are removed using the CMS deactivation report, specialties are resolved against the NUCC taxonomy rather than kept as raw codes, and addresses are validated to US bounds and ZIP format. Records are otherwise published as registered — the federal file is the record of truth, and correcting it would make the dataset disagree with the source buyers reconcile against.
How we build and date every file: methodology.
Using ChatGPT, Claude or an API?
No setup needed. Ask ChatGPT or Claude your question about the US Home Health Aide Providers and give it this page: it can open https://locationlists.com/find?dataset=us-home-health-aide with the filters you need and show you the count and price.
Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.
How assistants ask
No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.
If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.
Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>
Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>
Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.
Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:
- Only Maryland, the state with the most: https://locationlists.com/find?dataset=us-home-health-aide&state=MD
- Within 25 miles of Washington, DC, the busiest area: https://locationlists.com/find?dataset=us-home-health-aide&near=Washington+DC&radius=25
- Within a 30-minute drive of Washington, DC: https://locationlists.com/find?dataset=us-home-health-aide&near=Washington+DC&drive=30
- Only rows where zip_land_sqmi is over 36.82: https://locationlists.com/find?dataset=us-home-health-aide&where=zip_land_sqmi%3Agt%3A36.82
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=us-home-health-aide - In plain words: "US Home Health Aide Providers in Maryland": https://locationlists.com/find?q=US+Home+Health+Aide+Providers+in+Maryland
- In plain words: "US Home Health Aide Providers within 25 miles of Washington, DC": https://locationlists.com/find?q=US+Home+Health+Aide+Providers+within+25+miles+of+Washington%2C+DC
Optional: connect for repeat use or wallet payments:
Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the US Home Health Aide Providers list.Your assistant will walk you through setup and show you the price before you pay.
For developers
Every step below has a no-connector equivalent: https://locationlists.com/find?dataset=us-home-health-aide with the same filters as query parameters.
- Connect your agent to
https://locationlists.com/mcp(no key, no signup). - Call
count_locationswithdataset: "us-home-health-aide"and any filter — it is free, and returns how many rows match and what they cost. - Fetch the rows with
query_locations: $0.21 per 100 rows from this dataset. Above 24,756 rows, buying the whole file is cheaper.
Paid in USDC over x402 — the agent gets an HTTP 402 with the exact price, signs, and retries. Money moves only after rows are delivered, so a failed or empty query costs nothing. Setup for Claude, Cursor and VS Code
?Frequently Asked Questions
How many Home Health Aide Providers are there in the US?
There are 49,511 Home Health Aide Providers in the US as of September 2026. They are in all 50 states, DC and Puerto Rico.
Where does this data come from?
The CMS National Plan and Provider Enumeration System — the federal NPI registry — plus the NUCC provider taxonomy and the CMS Care Compare clinician file. All three are published by the government and free to download; what you are buying is the parsing, the taxonomy decode, the deactivation cleanup and the cut. Every vendor selling an NPI-based list is working from the same files.
Are these businesses or individual people?
Individual providers — a licensed person at the address where they practise. CMS publishes NPPES for public use with the practice address attached. If you need businesses only, buy the organization file or one of the practice cuts instead.
Is this the same data Definitive Healthcare or IQVIA sell?
The registry underneath is the same public CMS file. What those vendors add on top is their own layer — hospital affiliations they research, executive contacts, claims-derived volumes, purchasing intent. If you need that, buy them. If you need the registry itself as a file you own, this is it, at a fraction of a subscription.
Does this include email addresses?
No, and no honest NPI-based product does — NPPES has no email field. What it does have is the Direct secure-messaging address that some providers register for clinical data exchange, and those ship in their own column, labelled, because they are not marketing addresses. Any vendor selling you a 'physician email list' built on NPI data appended those emails from somewhere else.
How current is it?
File built on September 14, 2026. It is not on an automatic refresh schedule, so check the build date above before you buy.
What format is the download?
A single UTF-8 CSV with a header row, one row per NPI, ready for Excel, a CRM import or a database load. Commercial licence, one-off purchase, no subscription.