Nppes Pathology Lab Leads Scraper
Pricing
from $6.00 / 1,000 leads
Nppes Pathology Lab Leads Scraper
Scrapes the CMS NPI Registry for licensed pathologists and clinical laboratories by state and subspecialty. Returns NPI, practice name, physician name, phone, address, and specialty type. Covers anatomic, clinical, forensic, dermo, hemato, neuro, and molecular pathology. Ideal for digital pathology
Pricing
from $6.00 / 1,000 leads
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Developer
GoCreative AI
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2
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1
Monthly active users
4 days ago
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📊 Example output (real run)

A real record from a live run — clean structured data, exported as CSV / JSON / Excel or via API.
Scrapes the CMS NPI Registry for licensed pathologists and clinical laboratories by state and subspecialty. Returns NPI, practice name, physician name, phone, address, and specialty type. Covers anatomic, clinical, forensic, dermo, hemato, neuro, and molecular pathology. Ideal for digital pathology
No API key, no signup, no subscription — pay only for what you scrape. Clean, structured output ready for CSV, JSON, Excel, or direct API export into your own pipeline.
What this scraper does
Scrapes the CMS NPI Registry for licensed pathologists and clinical laboratories by state and subspecialty. Returns NPI, practice name, physician name, phone, address, and specialty type. Covers anatomic, clinical, forensic, dermo, hemato, neuro, and molecular pathology. Ideal for digital pathology
Every run pulls fresh data straight from the source and pushes clean, typed records to the dataset — ready for your CRM, spreadsheet, AI agent, or data pipeline.
Use cases
- B2B lead generation — build targeted prospect lists with verified, structured data
- Sales prospecting — find companies and contacts that match your ICP
- Market research & competitive intelligence — track an industry or niche in structured form
- AI agents & automation — feed agents clean external data without scraping infra
- Data enrichment — append fresh fields to your existing lists
Input
| Field | Description |
|---|---|
state | Two-letter US state code to filter results (e.g. CA, TX, NY, FL). Leave blank to search all states (requires city or zip). |
city | City name to filter results (e.g. Los Angeles, Chicago). Optional — combines with State. |
zip_code | 5-digit ZIP code to filter results. Optional. |
specialty | Pathology subspecialty to filter by. 'all' returns all pathology types. |
entity_type | Whether to return individual pathologists (NPI-1), pathology organizations/labs (NPI-2), or both. |
active_only | If enabled, only return active NPI registrations (status = A). |
max_results | Maximum number of records to return. Default 500. Maximum 5,000. |
Output
Every result is a clean structured record. Export the full dataset as CSV, JSON, or Excel from the Apify console, or pull it via the Apify API straight into your own tools.
Why use this actor
- Scrape nppes pathology lab leads — fast, structured, reliable.
- Nppes pathology lab leads data export (csv, json, excel) — fast, structured, reliable.
- Nppes pathology lab leads api alternative — no key required — fast, structured, reliable.
- Automated nppes pathology lab leads monitoring on a schedule — fast, structured, reliable.
- Structured nppes pathology lab leads records for ai agents and pipelines — fast, structured, reliable.
How it works
This actor pulls data directly from the source, structures it into clean rows, and pushes each result to the dataset. It runs on Apify's infrastructure — reliable, schedulable, and pay-per-result so you only pay for data you actually get.
Pricing
Pay-per-result via the Apify Store. No monthly subscription, no minimums — run it once or schedule it daily; you're only charged for the results returned.
FAQ
Do I need an API key or account? No. Just provide your input and run it.
Can I schedule it to run automatically? Yes — use Apify Schedules to run it hourly, daily, or weekly and get fresh data on autopilot.
What formats can I export? CSV, JSON, Excel, or via the Apify API.
Can I integrate it into my own app? Yes — call it via the Apify API and pull results directly into your pipeline.
Is the data accurate and fresh? Data is pulled live from the source on each run, so it reflects what's available at run time.