🩺 Doximity Physician Directory Scraper

🚀 Pull US physician profiles from Doximity in minutes. Education, credentials, hospital affiliations, certifications, publications. No login.

🕒 Last updated: 2026-05-09 · 📊 25+ fields per physician · 🩺 Specialty + state filters · 🚫 No auth required

Pull structured records from Doximity Physician Directory — clean fields ready as CSV, JSON, JSONL, Excel, or XML for downstream pipelines.

Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

parseforge/doximity-scraper on Apify. Call: ApifyClient("TOKEN").actor("parseforge/doximity-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs: startUrl (string), maxItems (integer, default 10), specialty (string, default "cardiology"), state (string), includeDetails (boolean, default false), maxConcurrency (integer, default 5). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parseforge~doximity-scraper (Bearer TOKEN). Get token: https://console.apify.com/account/integrations

Pull live physician profiles from Doximity, the largest US medical professional network with 80%+ of U.S. doctors registered. The actor accepts a specialty plus optional state (or a direct URL), walks the directory pages, and returns one structured record per physician ready for healthcare recruiting, medical-affairs research, lead-gen, or KOL identification.

Every run fetches data live so you get the current state of Doximity at run time. Records include the physician name, specialty, education (medical school, residency, fellowship), hospital affiliations, board certifications, publications, professional memberships, and a back-reference URL.

👥 Built for	🎯 Primary use cases
Healthcare recruiting	Find specialists by training and affiliation
Medical-affairs teams	Identify KOLs by specialty and publication record
Pharma / med device sales	Build prescriber prospect lists
CRM enrichment	Add credentials to existing physician records
Researchers	Map physician networks by specialty
Hospital systems	Track competitor faculty and affiliations

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📋 What the Doximity Scraper does

• 🩺 Specialty filter. 30+ medical specialties from cardiology to urology.
• 🌎 State filter. Narrow by US state.
• 🔗 Direct URL. Pass a Doximity directory URL.
• 🎓 Education. Medical school, residency, fellowship.
• 🏥 Hospital affiliations. All affiliated hospitals listed.
• 📚 Publications. Publication count and titles where exposed.

The scraper walks Doximity's directory, extracts each profile's metadata, and pushes structured records to the dataset.

💡 Why it matters: Doximity is the canonical US physician network with comprehensive credentials data, but its UI is paginated and lacks bulk export. A live, structured pull beats manual lookup for recruiting, KOL identification, and medical-affairs research.

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🎬 Full Demo

🚧 Coming soon: a 3-minute walkthrough showing setup, a live run, and how to pipe results into Salesforce or HubSpot via Apify integrations.

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⚙️ Input

Field	Type	Name	Description
startUrl	string	Start URL	Direct Doximity directory URL. Overrides specialty/state.
maxItems	integer	Max Items	Free users: limited to 10 items (preview). Paid users: optional, max 1,000,000.
specialty	enum	Specialty	Medical specialty (cardiology, dermatology, neurology, etc.).
state	string	State	Optional US state.

Example 1. Cardiologists nationwide.

{
  "specialty": "cardiology",
  "maxItems": 100
}

Example 2. Dermatologists in California.

{
  "specialty": "dermatology",
  "state": "California",
  "maxItems": 50
}

⚠️ Good to Know: when startUrl is set, specialty/state are ignored. Use specialty slugs from the input enum (e.g. colon-rectal-surgery not Colon and Rectal Surgery).

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📊 Output

The dataset returns one structured record per physician. Each record carries identifiers, name, specialty, education, hospital affiliations, certifications, publications, memberships, and a back-reference URL. Consume the dataset as JSON, CSV, Excel, XML, or RSS via the Apify console or API.

🧾 Schema

Field	Type	Example
👤 name	string	Dr. Jane Smith MD
🩺 specialty	string	Cardiology
🎓 medicalSchool	string	Columbia University Vagelos College
🎓 residency	string	New York-Presbyterian Hospital
🎓 fellowship	string or null	Massachusetts General Hospital
🏥 hospitalAffiliations	array	["Mount Sinai Hospital", "NYU Langone"]
📜 boardCertifications	array	["American Board of Internal Medicine - Cardiology"]
📚 publicationCount	number	42
📚 publications	array	[{"title":"...","journal":"NEJM","year":2024}]
🏛️ memberships	array	["American College of Cardiology", "Heart Rhythm Society"]
📞 phone	string or null	+1 212 555 1212
🏠 practiceAddress	string	123 5th Ave, New York, NY 10003
🌐 website	string or null	https://www.smithcardiology.com
🔗 doximityUrl	string (url)	https://www.doximity.com/profiles/jane-smith-md
📅 scrapedAt	ISO datetime	2026-05-09T12:00:00.000Z

📦 Sample records

1. Senior cardiologist with publications

{
  "name": "Dr. Jane Smith MD",
  "specialty": "Cardiology",
  "medicalSchool": "Columbia University Vagelos College",
  "residency": "New York-Presbyterian Hospital",
  "fellowship": "Massachusetts General Hospital",
  "hospitalAffiliations": ["Mount Sinai Hospital", "NYU Langone"],
  "boardCertifications": ["American Board of Internal Medicine - Cardiology"],
  "publicationCount": 42,
  "publications": [
    {"title": "Outcomes of Catheter Ablation in AF", "journal": "NEJM", "year": 2024}
  ],
  "memberships": ["American College of Cardiology", "Heart Rhythm Society"],
  "phone": "+1 212 555 1212",
  "practiceAddress": "123 5th Ave, New York, NY 10003",
  "doximityUrl": "https://www.doximity.com/profiles/jane-smith-md",
  "scrapedAt": "2026-05-09T12:00:00.000Z"
}

2. Mid-career dermatologist

{
  "name": "Dr. John Doe MD",
  "specialty": "Dermatology",
  "medicalSchool": "UCLA School of Medicine",
  "residency": "UCSF",
  "hospitalAffiliations": ["UCLA Medical Center"],
  "boardCertifications": ["American Board of Dermatology"],
  "publicationCount": 8,
  "memberships": ["American Academy of Dermatology"],
  "phone": "+1 213 555 1212",
  "practiceAddress": "456 Wilshire Blvd, Los Angeles, CA 90017",
  "doximityUrl": "https://www.doximity.com/profiles/john-doe-md",
  "scrapedAt": "2026-05-09T12:00:00.000Z"
}

3. Sparse record (early-career physician)

{
  "name": "Dr. Sarah Lee MD",
  "specialty": "Pediatrics",
  "medicalSchool": "Northwestern University",
  "residency": "Lurie Children's Hospital",
  "hospitalAffiliations": ["Lurie Children's Hospital"],
  "publicationCount": 0,
  "doximityUrl": "https://www.doximity.com/profiles/sarah-lee-md",
  "scrapedAt": "2026-05-09T12:00:00.000Z"
}

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✨ Why choose this Actor

	Capability
🎯	Built for the job. Scoped specifically to Doximity so you skip the parser engineering entirely.
🔖	Structured output. Clean, typed fields ready for analysis, dashboards, or downstream pipelines.
⚡	Fast. Optimized request patterns return results in seconds, not minutes.
🔁	Always fresh. Every run pulls live data, so the dataset reflects Doximity as of run time.
🌐	No infra to manage. Apify handles proxies, retries, scaling, scheduling, and storage.
🛡️	Reliable. Battle-tested across many runs and edge cases, with graceful error handling.
🚫	No code required. Configure in the UI, run from CLI, schedule via cron, or call from any language with the Apify SDK.

📊 Production-grade structured physician data without the engineering overhead of building and maintaining your own scraper.

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📈 How it compares to alternatives

Approach	Cost	Coverage	Refresh	Filters	Setup
⭐ Doximity Scraper (this Actor)	$5 free credit, then pay-per-use	Public Doximity directory	Live per run	Specialty, state	⚡ 2 min
Build your own scraper	Engineering hours	Full once built	Whenever you maintain it	Custom code	🐢 Days to weeks
Paid medical-data platforms	$$$ monthly per seat	Vendor-defined	Periodic	Vendor-defined	⏳ Hours
Manual searches	Hours per check	Limited	Stale	Manual	🕒 Variable

Pick this Actor when you want broad coverage, source-native filtering, and no pipeline maintenance.

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🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Doximity Physician Directory Scraper page on the Apify Store.
3. 🎯 Set filters. Pick a specialty and optional state.
4. 🚀 Run it. Click Start and let the Actor collect your data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

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💼 Business use cases

📊 Healthcare recruiting Find specialists by training and affiliation Build recruitment pipelines for hospitals Track competitor faculty and hospital systems Power lateral-hire outreach campaigns	🏢 Pharma and medical device sales Build prescriber prospect lists by specialty Identify KOLs by publication record Power CRM enrichment with credentials Track decision-makers at target accounts
🎯 Medical affairs and research Identify KOLs for advisory boards Map physician networks by specialty Build publication-tracking dashboards Power CME audience research	🛠️ Engineering and product Power physician-directory products without owning a crawler Replace fragile in-house Doximity scrapers Wire datasets into your apps via the Apify API or webhooks Skip the proxy, retry, and parsing maintenance entirely

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🌟 Beyond business use cases

Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.

🎓 Research and academia Empirical datasets for papers, thesis work, and coursework Longitudinal studies tracking changes across snapshots Reproducible research with cited, versioned data pulls Classroom exercises on data analysis and ethical scraping	🎨 Personal and creative Side projects, portfolio demos, and indie app launches Data visualizations, dashboards, and infographics Content research for bloggers, YouTubers, and podcasters Hobbyist collections and personal trackers
🤝 Non-profit and civic Transparency reporting and accountability projects Advocacy campaigns backed by public-interest data Community-run databases for local issues Investigative journalism on public records	🧪 Experimentation Prototype AI and machine-learning pipelines with real data Validate product-market hypotheses before engineering spend Train small domain-specific models on niche corpora Test dashboard concepts with live input

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🔌 Automating Doximity Physician Directory Scraper

This Actor exposes a REST endpoint, so you can drive it from any language or workflow tool.

• Node.js - call it via the Apify JS SDK.
• Python - call it via the Apify Python SDK.
• REST - hit it directly through the Apify v2 API.

Schedules. Use Apify Scheduler to capture daily snapshots of physician directory changes. Combine with the Apify dataset diff tools to track new physicians and affiliation changes between runs.

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❓ Frequently Asked Questions

🔌 Integrate with any app

Doximity Physician Directory Scraper connects to any cloud service via Apify integrations:

• Make - Automate multi-step workflows
• Zapier - Connect with 5,000+ apps
• Slack - Get run notifications in your channels
• Airbyte - Pipe results into your warehouse
• GitHub - Trigger runs from commits and releases
• Google Drive - Export datasets straight to Sheets

You can also use webhooks to trigger downstream actions when a run finishes.

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🔗 Recommended Actors

• 🏥 Healthgrades Scraper - US doctor and provider directory
• 🩺 ClinicalTrials.gov Scraper - U.S. clinical trial database
• 💊 Cost Plus Drugs Scraper - Cost Plus Drugs catalog
• 🏥 Florida MQA Licensee Scraper - Florida medical license records
• 📋 FDA 510(k) Scraper - FDA medical-device clearance database

💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.

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🆘 Need Help? Open our contact form to request a new scraper, propose a custom project, or report an issue.

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⚠️ Disclaimer. This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Doximity. All trademarks mentioned are the property of their respective owners. The scraper accesses only publicly available pages and is intended for legitimate research, analytics, and lead-generation use. Users are responsible for compliance with the source site's Terms of Service, applicable privacy laws (such as HIPAA), and any data-protection rules that apply.