We extract verified medical professional profiles, clinical affiliations, NPI numbers, board certifications, and publication histories from Doximity. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Physician Profiles objects from doximity.com. All fields typed and schema-versioned.
"profile_id": "dr-jane-smith-md", "full_name": "Dr. Jane Smith, MD", "primary_specialty": "Cardiology", "npi_number": "1932485721", "city": "Boston", "state": "MA", "verified_status": true, "languages_spoken": "['English', 'Spanish']"
| # | profile_id | full_name | first_name | last_name | title | primary_specialty |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Education & Training objects from doximity.com. All fields typed and schema-versioned.
"profile_id": "dr-jane-smith-md", "medical_school": "Harvard Medical School", "graduation_year": 2012, "residency_program": "Massachusetts General Hospital", "residency_years": "2012-2015", "fellowship_program": "Brigham and Women's Hospital", "degrees_earned": "['MD', 'PhD']"
| # | profile_id | medical_school | graduation_year | residency_program | residency_years | fellowship_program |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Certifications & Licensure objects from doximity.com. All fields typed and schema-versioned.
"profile_id": "dr-jane-smith-md", "board_name": "American Board of Internal Medicine", "specialty_certified": "Cardiovascular Disease", "year_certified": 2016, "state_licenses": "['MA', 'NY']", "license_status": "Active", "npi_registry_match": true
| # | profile_id | board_name | specialty_certified | year_certified | state_licenses | license_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hospital Affiliations objects from doximity.com. All fields typed and schema-versioned.
"profile_id": "dr-jane-smith-md", "hospital_name": "Massachusetts General Hospital", "health_network_name": "Mass General Brigham", "location": "Boston, MA", "department": "Cardiology", "primary_affiliation": true, "admitting_privileges": true
| # | profile_id | hospital_name | health_network_name | location | department | role |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Publications objects from doximity.com. All fields typed and schema-versioned.
"profile_id": "dr-jane-smith-md", "article_title": "Novel Biomarkers in Heart Failure", "journal_name": "Journal of the American College of Cardiology", "publication_date": "2023-04-12", "pubmed_id": "36789123", "doi": "10.1016/j.jacc.2023.02.015", "citation_count": 42
| # | profile_id | article_title | journal_name | publication_date | authors | pubmed_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Doximity pipeline captures verified physician credentials, clinical networks, and academic histories — bypassing aggressive rate limits and navigating complex directory structures.
Extract National Provider Identifier (NPI) numbers, board certifications, and state licensure data directly from physician profiles.
Map primary and secondary hospital affiliations, identifying which providers admit patients to specific regional health systems.
Capture medical school alma maters, graduation years, residency programs, and fellowship details to build academic pedigrees.
Extract linked medical publications, clinical trial participation, PubMed IDs, and co-author networks.
Track provider locations down to the city and state level, useful for evaluating regional specialty coverage and care deserts.
Normalise primary specialties and sub-specialties across thousands of profiles into standard medical taxonomies.
Navigate Doximity's aggressive rate-limiting and IP bans using residential proxy pools and TLS fingerprint spoofing.
Systematically paginate through Doximity's alphabetical state and specialty directories to ensure total catalogue coverage.
Monitor known profiles for updates to affiliations, newly published research, or changes in licensure status.
Brief in. Clean data out.
Provide target specialties, geographic regions, or specific hospital networks. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and directory traversal logic for doximity.com.
Schema validation, null-rate checks, and data type normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Doximity restricts automated access to protect its proprietary physician graph. Here is how our infrastructure maintains extraction stability.
Doximity monitors request velocity and IP reputation aggressively. Our crawlers use US-based residential ISP proxies, randomise request timing, and limit concurrency per subnet to avoid triggering automated blocks.
Extracting the full provider directory requires navigating complex nested pagination across states, cities, and specialties. Our spiders map the directory tree and maintain state to ensure no profiles are dropped.
Physician bios and affiliation lists often contain free-text variations of the same hospital or specialty. We extract the raw text and apply normalisation rules to align with standard healthcare taxonomies.
Doximity frequently updates its profile UI. We use multiple fallback chains per field — CSS selectors, XPath, and JSON-LD structured data extraction — so layout changes do not break your data feed.
For ongoing monitoring, we maintain a hash index of last-seen values per physician. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Life sciences commercial teams identify Key Opinion Leaders (KOLs) based on publication history, specialty, and clinical trial participation.
Medical recruiting firms build talent pools by extracting physician credentials, residency completion dates, and current affiliations.
Health insurance payers analyse hospital affiliations and geographic density to evaluate network adequacy and identify out-of-network providers.
Sales operations teams map hospital networks and physician specialties to route leads and define sales territories.
Digital health startups verify state licensure and board certifications to quickly onboard qualified providers into their telemedicine platforms.
Healthcare data teams use Doximity profiles to enrich internal CRM records, cross-referencing NPI numbers with up-to-date clinical affiliations.
"Doximity holds the most accurate, professionally maintained graph of US medical professionals — but extracting that graph requires navigating strict directory protections."
Building a healthcare provider dataset requires more than basic HTTP requests. Doximity deploys advanced fingerprinting and rate-limiting to prevent scraping. DataFlirt handles the proxy rotation, session spoofing, and directory traversal so your data engineering team can focus on entity resolution and analysis.
Everything supported by our doximity.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of US residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About doximity.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Doximity is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated provider profile data. We do not extract personal patient data, circumvent authentication walls, or violate HIPAA. Clients should review Doximity's ToS and consult legal counsel for specific use cases.
We use US-based residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 429/CAPTCHA rate spikes in real time and trigger pool rotation automatically.
Standard extraction includes name, title, primary specialty, sub-specialty, NPI number, city, state, hospital affiliations, education history, board certifications, and publication links.
No. We only extract data visible on the public-facing provider profiles and directories. We do not log into accounts to scrape private peer connections or direct messages.
Pipelines can be configured for monthly, weekly, or daily runs depending on your requirements. For large directories, we recommend a rolling update schedule where a subset of profiles is refreshed daily.
Yes. We can enrich the extracted Doximity profiles by joining them against the NPPES NPI registry to append official taxonomy codes, practice locations, and Medicare enrollment status.
Absolutely. We provide a sample run of up to 500 profiles for your target specialty as part of the pre-engagement scoping process — so you can validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a specific specialty export or a continuous monitoring feed across the entire US provider network — we scope, build, and operate the pipeline. Tell us what you need.
