We extract doctor profiles, clinic details, availability slots, and patient reviews from Docplanner. 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 Doctor Profiles objects from docplanner.com. All fields typed and schema-versioned.
"doctor_id": "DP-847291", "full_name": "Dr. Elena Rossi", "specialty": "Cardiologist", "experience_years": 14, "languages_spoken": "['Italian', 'English']", "teleconsultation_offered": true, "average_rating": 4.8, "total_reviews": 142
| # | doctor_id | full_name | specialty | education | experience_years | languages_spoken |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Clinic Data objects from docplanner.com. All fields typed and schema-versioned.
"clinic_id": "CL-39201", "clinic_name": "Milano Heart Clinic", "city": "Milan", "postal_code": "20122", "latitude": 45.4642, "longitude": 9.19, "wheelchair_accessible": true
| # | clinic_id | doctor_id | clinic_name | address_line | city | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Availability & Pricing objects from docplanner.com. All fields typed and schema-versioned.
"doctor_id": "DP-847291", "consultation_fee": 150.0, "currency": "EUR", "service_type": "First Visit Cardiology", "insurance_accepted": "['Allianz', 'Generali']", "next_available_date": "2026-05-14", "available_slots_count": 4
| # | doctor_id | clinic_id | consultation_fee | currency | service_type | insurance_accepted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Patient Reviews objects from docplanner.com. All fields typed and schema-versioned.
"review_id": "RV-992831", "doctor_id": "DP-847291", "rating": 5, "verified_visit": true, "date_posted": "2026-04-10", "wait_time_rating": 4, "review_text": "Very thorough examination and clear explanations."
| # | review_id | doctor_id | patient_name | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from docplanner.com. All fields typed and schema-versioned.
"keyword": "Cardiologist", "location": "Milan", "position": 2, "sponsored_listing": false, "doctor_name": "Dr. Elena Rossi", "average_rating": 4.8, "scraped_at": "2026-05-12T10:15:22Z"
| # | keyword | location | position | doctor_name | specialty | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Docplanner scraper handles every layer of the platform: doctor profiles, dynamic availability calendars, consultation pricing, and verified patient reviews — with JavaScript rendering and regional circumvention built in.
Extract doctor names, education, experience, languages spoken, and professional statements across all specialisations.
Render dynamic JavaScript calendars to extract next available dates and precise slot timestamps per clinic.
Capture clinic names, exact addresses, GPS coordinates, and accessibility features for every associated practice.
Extract full review text, star ratings, verified visit flags, and sub-ratings for wait times and bedside manner.
Track consultation costs, service-specific pricing, and lists of accepted private insurance networks.
Identify doctors offering online consultations versus strictly in-person appointments.
Unified schema mapping across Docplanner's regional domains including Doctoralia, MioDottore, and ZnanyLekarz.
Monitor organic versus sponsored visibility for specific medical keywords and city locations.
Run continuous pipelines that only emit diffs when availability slots open or consultation fees change.
Brief in. Clean data out.
Provide target cities, specialisations, or specific clinic URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for Docplanner domains.
Schema validation, null-rate checks, and availability slot verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Docplanner protects its availability data and doctor directories with rate limits and heavy client-side rendering. Here is how we maintain reliable extraction.
Docplanner's regional sites (Doctoralia, MioDottore) enforce strict geo-blocking and rate limits. We route requests through residential ISP proxies specific to the target country, maintaining realistic session fingerprints to avoid IP bans.
Availability slots and pricing details are loaded asynchronously via JavaScript. We deploy full Playwright browser sessions to trigger API calls and hydrate the calendar widgets, capturing data that static HTML parsers miss.
Doctor profiles often contain multiple clinic locations, each with its own pricing and calendar. Our extraction logic maps these nested relationships accurately, using fallback selectors to handle inconsistent profile layouts.
Extracting a complete city directory requires traversing hundreds of paginated search results. Our crawlers manage state and deduplicate records across pages to ensure complete coverage without infinite loops.
For continuous availability monitoring, we maintain a hash index of last-seen calendar states. Subsequent runs only push diffs when new slots appear or are booked, reducing your downstream processing load.
Telehealth platforms monitor doctor availability, pricing, and geographic coverage to benchmark their own networks.
Insurtech firms verify in-network provider directories and track which private insurances are accepted by top specialists.
B2B sales teams generate high-intent leads for practice management software by targeting clinics with specific characteristics.
Healthcare analysts track consultation fees across regions and specialisations to identify pricing trends and market gaps.
Agencies monitor verified patient reviews and ratings to help clinics manage their online presence and patient sentiment.
Researchers map wait times and availability gaps across cities to study patient access to specialised care.
"Docplanner holds the most comprehensive map of private healthcare availability and pricing in Europe and LatAm — but it requires complex infrastructure to extract at scale."
Extracting availability calendars and verified reviews requires bypassing strict rate limits, rendering heavy SPA components, and mapping nested clinic-to-doctor relationships. DataFlirt manages the proxy rotation, session handling, and schema maintenance so you receive structured healthcare intelligence directly in your warehouse.
Everything supported by our docplanner.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 the heavy JavaScript components required for dynamic calendar slots and pricing modules.
We maintain pools of residential ISP proxies across Europe and LatAm. Rotation happens per-request to bypass regional rate limits without triggering bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling for daily availability checks, ensuring data is delivered precisely on time.
Data delivered to where your team already works — no new tooling required.
About docplanner.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available doctor profiles, clinic addresses, and public reviews is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal patient health records (PHI), circumvent authentication walls, or violate GDPR. Clients should review Docplanner's ToS and consult legal counsel for specific use cases.
Docplanner's calendars are dynamically loaded via JavaScript. We use Playwright to execute the necessary scripts and trigger the API calls that populate the available time slots, capturing the exact timestamps and consultation types.
Yes. Docplanner operates under various regional brands including Doctoralia (Spain, LatAm), MioDottore (Italy), and ZnanyLekarz (Poland). Our pipelines normalise data from all these domains into a single, unified schema.
For pipelines tracking specific clinics or highly sought-after specialists, we can configure sub-daily runs to capture availability changes. Full city or country directories are typically refreshed weekly or monthly depending on your requirements.
Yes. We extract the full review text, star rating, date, and specific tags such as 'Verified Visit'. We also capture sub-ratings for wait times and bedside manner where available.
Our minimum engagement covers a defined set of specialisations or cities with regular delivery cadences. Pricing scales based on the volume of profiles and the frequency of calendar updates required. Contact us for a precise quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of specialists in Spain or continuous tracking of consultation fees across LatAm — we scope, build, and operate the pipeline. Tell us what you need.
