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Jameda Doctor Extractor

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from $2.99 / 1,000 results

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Jameda Doctor Extractor

Jameda Doctor Extractor

Jameda scraper that extracts doctor profiles, specializations, reviews, and coordinates from jameda.de, so you can build accurate provider directories without getting blocked.

Pricing

from $2.99 / 1,000 results

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0.0

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Developer

Kawsar

Kawsar

Maintained by Community

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0

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2

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1

Monthly active users

5 days ago

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Jameda Doctor Extractor is a professional, high-fidelity scraping agent built to harvest comprehensive physician, clinical, and healthcare provider directories from Germany's premier medical portal, jameda.de.

This high-performance scraping solution extracts complete provider profiles, medical specialties, patient ratings, feedback volume, and highly precise geographical coordinates (including physical address details and exact latitude/longitude GPS coordinates).


🌟 The Value of Jameda Data (Why Jameda?)

Jameda is the largest and most trusted healthcare review and search portal in Germany, housing detailed records for over 275,000 physicians, dentists, psychotherapists, and clinical practices.

Scraping Jameda provides unparalleled advantages over general business registries:

  • Verified Medical Designations: Access highly specialized medical titles, clinical sub-specialties, and focused designations that are rarely structured in standard business directories.
  • Patient-Driven Ratings & Sentiments: Capture authentic patient feedback scores and aggregate recommendation counts representing direct public sentiment and local reputation.
  • Advanced Geo-Intelligence: Extract coordinate-mapped practice locations which allow businesses to perform precise distance-based mapping and drive localized analysis.
  • Up-to-Date Medical Directory: Unlike static governmental databases, Jameda’s records are continually updated by the practitioners and active patients, ensuring fresh, live listings.

📈 Key Business & Strategic Benefits

  • Market Density & Coverage Analysis: Evaluate regional healthcare coverage, analyze localized physician density, and discover gaps in medical specialties across metropolitan and rural postal codes in Germany.
  • B2B Healthcare Lead Generation: Build clean, highly targeted leads of specific medical practices, dental offices, and therapists for therapeutic, laboratory, or dental equipment supplies.
  • Competitive Benchmarking: Track competitors' patient ratings, practice sizes, and service listings to analyze clinical positioning and market share in key cities.
  • Localized Directory Building: Easily populate localized medical directory search apps, maps, or research platforms with structured, schema-compliant medical provider profiles.

🚀 Key Extractor Features

  • Smart Pagination Limits: Set individual query-specific limit thresholds (maxItemsPerQuery) to perfectly control your runtime budget per search query or URL.
  • Automatic Keyword Cross-Matching: Simply provide a list of medical queries (e.g. Hausarzt, Zahnarzt) and location regions or postcodes (e.g. Berlin, 80331), and the extractor will automatically combine and crawl them.
  • Direct Search & Profile URL Processing: Input direct links to pre-filtered search results or individual doctor profiles on Jameda to extract exact subsets.
  • Clean Schema Outputs: Features a recursive, built-in data sanitizer that automatically cleans and strips missing elements (like missing review fields or coordinates) before pushing to your dataset, completely eliminating validation errors.
  • Highly Reliable Pagination: Automatically navigates through search result pages to retrieve extensive datasets up to your exact limit per query.

⚙️ Configuration & Input Parameters

ParameterTypeDefaultDescription
queriesArray of strings["Internist"]List of specialties, doctor names, or symptoms to search.
locationsArray of strings["Berlin"]List of German cities, postal codes, or regions.
startUrlsArray of objects[]Direct search or profile URLs from the portal to process.
maxItemsPerQueryInteger20Maximum records to extract per individual search query combination or start URL.
requestTimeoutSecsInteger30Network request timeout per page in seconds.

📊 Extracted Data Properties

Each record stored in your dataset represents a unique medical provider listing containing:

  • name (String): Full name of the medical professional, clinical team, or facility.
  • url (String - URI): Direct portal URL to the provider's profile.
  • imageUrl (String - URI): Practitioner's portrait photo or facility logo URL (when available).
  • specializations (Array of Strings): Extracted list of medical specialties and professional focus areas.
  • ratingScore (Number): Patient rating score out of 5.0.
  • reviewsCount (Integer): Total recommendation and patient review volume.
  • addresses (Array of Objects): List of address entries, with each object containing:
    • addressId (String): Portal's internal address identifier.
    • street (String): Street name and physical practice house number.
    • city (String): Local city.
    • region (String): Local region or federal state.
    • entityName (String): Name of the practice office, healthcare group, or clinic.
    • latitude (Number): Exact GPS latitude coordinate.
    • longitude (Number): Exact GPS longitude coordinate.
  • scrapedAt (String - DateTime): ISO-8601 UTC timestamp of when the record was successfully scraped.

💾 Dataset Output Example

Here is a sample JSON record output from the dataset:

{
"name": "Dr. med. Philipp Lindemann",
"url": "https://www.jameda.de/philipp-lindemann-2/allgemeinmediziner-hausarzt-internist-hausarzt/berlin",
"imageUrl": "https://s3-eu-west-1.amazonaws.com/jamedade/doctor/80e029/80e02907cc779c05acb8962f13382db4_medium_square.jpg",
"specializations": [
"Internist",
"Allgemeinmediziner",
"Hausarzt"
],
"ratingScore": 5.0,
"reviewsCount": 126,
"addresses": [
{
"addressId": "482583",
"street": "Räuschstr. 57 a",
"city": "Berlin",
"region": "Berlin",
"entityName": "Hausarztpraxis Dr.med. Philipp Lindemann Facharzt für Innere Medizin",
"latitude": 52.583416,
"longitude": 13.3012094
}
],
"scrapedAt": "2026-06-06T05:22:50.123456+00:00"
}