Zocdoc Scraper: Doctors, Reviews & Availability Data in 2026

A public window into healthcare supply

Zocdoc is the largest consumer marketplace for medical appointments in the US, and that makes it an unusual dataset: which providers practice where, what insurance they accept, how patients rate them — and, uniquely, when they’re actually available. No industry survey captures appointment lead times the way live booking calendars do.

For healthcare analysts, networks and researchers, that’s measurable access-to-care data hiding in plain sight.

What you can extract

Three data types per run:

• Doctor name and specialties
• Practice locations and contact details
• Education and certifications
• Languages spoken
• Accepted insurances
• Ratings and review counts
• Patient reviews — rating, text, date, verification status
• Appointment availability — dates, times, in-person or telehealth

The technical challenge

Zocdoc renders search results and booking calendars dynamically, and availability data is the most volatile content there is — it changes by the hour. Reliable extraction needs:

• Coverage strategy — search pages for breadth, profile pages for depth, calendars for availability, each with its own structure. Dynamic rendering sometimes calls for a headless browser.
• Residential proxies for sustained volume.
• Freshness discipline — availability snapshots are only meaningful with timestamps and regular re-runs.

DIY or a ready-made Actor?

Our Zocdoc Scraper on Apify extracts all three data types — profiles, reviews, availability — from searches by specialty and location, with filters for insurance, gender, telehealth and new-patient acceptance. No login required. Pay-per-result at about $0.005 per item (doctors, reviews and availability slots each count as items).

A practical workflow

1. Define the market — specialties × cities, or direct Zocdoc URLs.
2. Snapshot on a schedule — weekly profile runs, daily availability runs for lead-time tracking.
3. Structure the text — patient reviews are free text; LLM-powered extraction turns them into themes and sentiment at scale.
4. Analyze — provider density, insurance acceptance maps, appointment lead times by specialty and region.

Use cases that pay off

• Provider network research — map doctors by specialty, location and accepted insurance.
• Market analysis — provider density and ratings by region for expansion planning.
• Reputation monitoring — track reviews across practices and competitors.
• Access-to-care studies — appointment availability as a hard metric, not an estimate.

The legal boundaries

Healthcare deserves extra care, even with public data:

• Public professional data — provider profiles describe professionals in their public capacity; extraction for analysis is defensible.
• Reviews are personal expression — store them minimally, anonymize authors, and never republish wholesale.
• No patient data, ever — the scraper touches only what any anonymous visitor sees; keep it that way in your pipeline too.

Getting started

Run the Zocdoc Scraper on one specialty in one city and compare availability across neighborhoods — the lead-time differences are usually striking. To enrich the practices behind the profiles, pair it with the LinkedIn Profiles & Companies scraper. Healthcare data pipelines with monitoring and dashboards are what we build at SilentFlow.