We extract condition profiles, drug information, symptom schemas, and editorial review networks from Verywell Health. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery on your defined cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Medical Articles objects from verywellhealth.com. All fields typed and schema-versioned.
"article_id": "VH-982341", "url": "https://www.verywellhealth.com/type-2-diabetes-overview", "title": "Type 2 Diabetes: Symptoms, Causes, and Treatment", "primary_category": "Diabetes", "published_date": "2023-11-14", "author_name": "Dr. Sarah Jenkins"
| # | article_id | url | title | primary_category | sub_category | published_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Conditions & Symptoms objects from verywellhealth.com. All fields typed and schema-versioned.
"condition_name": "Type 2 Diabetes", "overview": "A chronic condition that affects the way the body processes blood sugar.", "common_symptoms": "['Increased thirst', 'Frequent urination', 'Fatigue']", "causes": "['Insulin resistance', 'Genetics', 'Lifestyle factors']", "risk_factors": "['Obesity', 'Age over 45', 'Family history']", "related_conditions": "['Hypertension', 'Neuropathy']"
| # | condition_name | icd_code_reference | overview | common_symptoms | rare_symptoms | causes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Drug Information objects from verywellhealth.com. All fields typed and schema-versioned.
"generic_name": "Metformin", "brand_names": "['Glucophage', 'Fortamet', 'Glumetza']", "drug_class": "Biguanides", "common_side_effects": "['Nausea', 'Stomach upset', 'Diarrhea']", "interactions": "['Alcohol', 'Contrast dyes', 'Certain blood pressure medications']", "fda_approval_status": "Approved"
| # | generic_name | brand_names | drug_class | indications | dosage_forms | common_side_effects |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Editorial & Review Board objects from verywellhealth.com. All fields typed and schema-versioned.
"name": "Dr. Richard Thompson", "credentials": "MD, FACP", "specialty": "Endocrinology", "board_certifications": "['American Board of Internal Medicine']", "total_articles_reviewed": 142, "education": "Harvard Medical School"
| # | profile_id | name | credentials | specialty | board_certifications | education |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Citations & References objects from verywellhealth.com. All fields typed and schema-versioned.
"article_url": "https://www.verywellhealth.com/type-2-diabetes-overview", "citation_index": 3, "source_journal": "Journal of Clinical Endocrinology", "publication_year": 2022, "doi": "10.1210/clinem/dgac123", "pmid": "35123456"
| # | article_url | citation_index | citation_text | source_title | source_authors | source_journal |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Verywell Health relies on complex editorial layouts and deep categorical hierarchies. Our scraper parses unstructured text into structured medical entities, mapping conditions, symptoms, and author credentials with absolute precision.
Extract symptoms, causes, and treatments into discrete JSON arrays.
Scrape reviewer credentials, board certifications, and update timestamps to verify content authority.
Parse dosages, contraindications, and side effect profiles from pharmaceutical content.
Extract DOI, PMID, and academic journal references from article footnotes.
Map the full category tree from broad topics down to specific sub-conditions.
Monitor last-updated timestamps to only scrape articles that underwent editorial review since the last run.
Clean conversion of complex medical tables and body text into structured markdown for LLM ingestion.
Capture medical illustrations, diagrams, and alt-text metadata.
Configure daily or weekly runs to maintain an up-to-date medical knowledge base.
Brief in. Clean data out.
Provide category URLs, condition lists, or author profiles. We map the target schema.
We configure Scrapy / Playwright crawlers, handle pagination, and parse editorial DOM structures.
Schema validation, null-rate checks, and markdown formatting verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or API webhook on schedule.
Health publishers use dynamic layouts and heavily tested article structures. Here is how we ensure schema stability across millions of words.
Editorial sites frequently change article templates. We use multi-layer XPath and text-pattern matching to extract core content regardless of presentation layer.
We strip ads, tracking pixels, and navigation elements, converting raw HTML into clean, structured markdown.
Medical content is updated frequently for accuracy. We track 'last medically reviewed' timestamps to trigger delta updates.
We parse unstructured text blocks to isolate discrete data points like specific side effects or ICD-10 references.
We use polite crawl delays and US residential proxies to prevent IP bans and maintain reliable pipeline execution.
Feed clean, board-reviewed medical text into vector databases for healthcare AI models.
Populate clinical decision support systems with structured symptom and condition data.
Analyse topic coverage, word counts, and citation density to inform health content strategy.
Monitor drug information updates, side effect reporting, and consumer-facing medication guidance.
Map the network of board-certified reviewers and authors across the digital health landscape.
Extract structured relationships between conditions, risk factors, and symptoms for diagnostic tools.
"Verywell Health represents one of the largest repositories of board-reviewed medical content on the internet, but parsing editorial layouts into structured data requires precision engineering."
Extracting medical literature is fundamentally different from scraping eCommerce. The value lies in the relationships between conditions, symptoms, and the verified credentials of the reviewing physicians. DataFlirt builds pipelines that normalise unstructured text into highly relational schemas, providing clean data for LLMs and clinical applications without the engineering overhead.
Everything supported by our verywellhealth.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 and deduplication. Playwright renders complex editorial layouts and dynamic citation loaders.
US-based residential ISP proxies ensure high success rates and prevent algorithmic blocking during deep historical crawls.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, delta detection, and SLA alerting. State stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About verywellhealth.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available, non-authenticated editorial content is generally permissible. We do not extract personal health information or violate HIPAA.
We maintain resilient selector chains and use text-pattern matching to isolate content blocks regardless of DOM changes.
Yes. We strip boilerplate HTML and deliver clean markdown, optimised for LLM ingestion and RAG architectures.
We monitor the 'last medically reviewed' and 'updated' timestamps on articles, enabling efficient delta crawls.
Yes. We scrape the full author and medical review board profiles, including board certifications and academic affiliations.
Yes. We parse structured lists within articles to build relational mapping between diseases, symptoms, and treatments.
We typically start with category-specific extractions or full-site historical dumps, followed by weekly delta updates.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off corpus for LLM training or continuous updates for a clinical knowledge base — we scope, build, and operate the pipeline. Tell us what you need.
