Extract publicly available drug databases, clinical trial registries, provider directories, insurance formularies, hospital quality metrics, and published medical research — normalised against standard medical ontologies and delivered with the accuracy healthcare applications demand.
Healthcare data scraping is the automated collection of structured information from publicly available healthcare databases — provider directories, clinical trial registries, drug approval databases, insurance plan formularies, hospital quality rating portals, and published medical research. We collect only what is publicly accessible: never patient records, protected health information, or HIPAA-covered data.
For pharma intelligence teams, health tech companies, insurance analysts, and healthcare investors, this public data is enormously valuable but deeply fragmented across hundreds of government portals, regulatory databases, and institutional websites. NPI registries, ClinicalTrials.gov, FDA.gov, CMS datasets, PubMed, and state Medicaid formularies each have their own format, update cadence, and access quirks. DataFlirt aggregates them into a unified, normalised data layer.
Our healthcare data pipelines normalise against standard medical ontologies — NPI for providers, RxNorm for drugs, ICD-10 for diagnoses, and CPT for procedures — so the data integrates cleanly with clinical systems, analytics platforms, and health tech products without requiring manual mapping.
Comprehensive extraction built for reliability, accuracy, and scale.
Scrape drug databases, formulary coverage tiers, pricing, availability, and NDA/ANDA approval status from FDA and payer sources.
Extract physician, specialist, and facility NPI records — including specialty, location, credentials, and insurance accepted.
Track ClinicalTrials.gov and international registries for trial status, phase changes, enrollment updates, and results.
Collect plan summaries, network rosters, formulary tiers, and benefit structures from CMS and payer portals.
Extract structured abstracts, author lists, citations, and MeSH tags from PubMed and medical journal databases.
Pull CMS star ratings, HCAHPS scores, readmission rates, and procedure volume data for hospitals and facilities.
Every field you need, structured and ready to use downstream.
A proven process that turns any source into clean structured data — reliably.
{ "source": "clinicaltrials.gov", "nct_id": "NCT05812483", "title": "Phase 3 Study of XYZ-001 in Type 2 Diabetes", "phase": "Phase 3", "status": "Recruiting", "sponsor": "Novartis Pharmaceuticals", "enrollment": 1200, "primary_completion": "2026-03-01", "conditions": ["Type 2 Diabetes Mellitus"], "mesh_terms": ["Diabetes Mellitus, Type 2", "Hypoglycemic Agents"], "last_updated": "2025-05-28" }
Built on proven open-source tools and cloud infrastructure — no vendor lock-in.
All pipelines designed around publicly available data only. No scraping of patient portals, EHR systems, or login-protected records.
Automatic cross-referencing against NPI, RxNorm, ICD-10, CPT, and MeSH — data arrives pre-normalised for clinical system integration.
FDA.gov, CMS.gov, NIH, EMA, and CDSCO (India) monitored for new approvals, safety communications, and policy updates.
We track changes between crawls and deliver only new or updated records — minimising processing overhead on large provider databases.
US, EU (EMA), UK (MHRA), India (CDSCO), and Australia (TGA) regulatory data sources covered for global pharma intelligence.
All healthcare-adjacent data delivered over encrypted channels with configurable access controls and audit logging.
From solo analysts to enterprise data teams — here's how organizations use this data.
In healthcare, data quality isn't optional — it's critical. A mis-mapped NPI, a stale formulary tier, or a missed trial status change can undermine a product, a compliance review, or an investment decision. DataFlirt delivers structured, ontology-normalised healthcare data with the accuracy, recency, and traceability that healthcare organisations and health tech platforms depend on.
Start free and scale as your data needs grow.
For small teams and projects getting started with data.
For growing teams with serious data requirements.
For large organizations with custom requirements.
Everything you need to know before getting started.
Join data teams worldwide using DataFlirt to power products, research, and operations with reliable, structured web data.
