🏥 CMS Hospital Quality Scraper: Star Ratings (No Key)

Overview

CMS Hospital Quality Scraper pulls the official CMS Hospital Compare dataset from Medicare.gov as clean, structured JSON: overall star rating (1 to 5), hospital name, type, ownership, location, contact details, and emergency-services flag. Coverage runs to 4,500+ Medicare-certified acute-care hospitals across every US state. Built for healthcare analytics, site selection, quality benchmarking, and investment due diligence.

The Centers for Medicare & Medicaid Services publishes this dataset as the federal government's official hospital quality benchmark. It powers Medicare.gov's hospital finder and drives decisions at insurers, health systems, investors, and researchers. The underlying Socrata API is open but demands dataset IDs and SODA query syntax, so this actor handles the plumbing and returns one clean record per hospital.

Reliability posture: blocked, empty, or failed runs are never charged. You only pay for a hospital record that was actually delivered.

✅ No API key | ✅ Official CMS Provider Data Catalog | ✅ Zero charge on empty runs | ✅ First 10 hospitals free | ✅ MCP-ready for AI agents

Features

Overall star rating (1 to 5) plus name, type, ownership, address, phone, and emergency-services flag on every record. Filter by state, city, hospital name (partial match), or minimum star rating to narrow to a target set. Full coverage: about 4,500 Medicare-certified acute-care hospitals across all 50 states plus DC. Direct pulls from the official CMS Provider Data Catalog, so there is no key, no cookies, and no anti-bot friction. One flat JSON record per hospital, ready for BI dashboards, network-adequacy models, or LLM ingestion.

How it works

The actor queries the CMS Provider Data Catalog's Socrata endpoint for the Hospital General Information dataset, applies your state, city, name, or star-rating filters server-side, and flattens the response into one record per facility. Pagination is handled internally so you can pull anywhere from 1 to 5,000 hospitals in a single run.

Empty searches (an unusual state code, a strict star threshold, a name that matches nothing) are recognized before charging: no matches, no charge.

🧾 Input configuration

{
  "state": "NY",
  "minStars": 4,
  "maxResults": 100
}

📤 Output format

{
  "hospital_name": "PROVIDENCE ST JOSEPH HOSPITAL",
  "facility_id": "050006",
  "address": "2700 DOLBEER ST",
  "city": "EUREKA",
  "state": "CA",
  "zip_code": "95501",
  "county_name": "HUMBOLDT",
  "phone_number": "(707) 445-8121",
  "hospital_type": "Acute Care Hospitals",
  "hospital_ownership": "Voluntary non-profit - Private",
  "overall_star_rating": "4",
  "emergency_services": "Yes",
  "scraped_at": "2026-07-15T04:15:15.503Z"
}

Every hospital record contains these fields:

Field	Description
🏥 hospital_name	Facility name as filed with CMS
🆔 facility_id	CMS Certification Number (CCN)
🏠 address	Street address
🌆 city	City
🗺️ state	Two-letter state code
📮 zip_code	ZIP code
📍 county_name	County
📞 phone_number	Main phone number
🩺 hospital_type	CMS facility type (e.g. Acute Care)
🏛️ hospital_ownership	Ownership category (non-profit, government, proprietary)
⭐ overall_star_rating	CMS overall star rating (1 to 5)
🚑 emergency_services	Yes or No
🕒 scraped_at	ISO timestamp of capture

💼 Common use cases

Healthcare investment and diligence Benchmark acquisition targets against state and national peers on star rating and ownership type. Screen for high-performing hospitals (4 or 5 stars) in a target metro before an outreach cycle.

Payer network adequacy and benchmarking Build network-adequacy models with facility-level counts by state and ownership. Compare star ratings across contracted vs. non-contracted hospitals to prioritize renegotiation.

Health-system strategy and site selection Map competitive density and star distribution in a candidate expansion market. Identify referral targets by county, star rating, and emergency-services capability.

Research and journalism Study quality variation across states, ownership types, or metros using a consistent CMS dataset. Automate quarterly refreshes to catch new star-rating publications.

🚀 Getting started

1. Open the actor and enter a State code (e.g. CA), or leave blank for all 50 states.
2. Optionally add a City or partial Hospital name to narrow further.
3. Set Minimum star rating (1 to 5) if you only want top performers.
4. Set Max hospitals (default 200) to cap the run.
5. Click Save & Start, then download as JSON, CSV, or Excel, or pull via API or MCP.

FAQ

Do I need an API key? No. The CMS Provider Data Catalog is fully open. No login, no key, no rate-limit paperwork.

How current is the data? CMS updates the Hospital Compare dataset quarterly. The actor always queries the live endpoint, so you get the latest release.

How many hospitals are covered? Roughly 4,500 Medicare-certified acute-care hospitals across all 50 states plus DC and territories.

What is the star rating based on? CMS calculates the overall star rating from up to five care areas: mortality, safety of care, readmission, patient experience, and timely and effective care. Hospitals with fewer than three scored groups receive no rating.

Can I get raw HCAHPS scores? The overall star rating already incorporates HCAHPS. For raw HCAHPS survey scores by domain (communication with nurses, responsiveness, quietness), contact us and we can build a companion actor on the HCAHPS-specific CMS dataset.

Use in Claude, ChatGPT & any MCP agent

https://mcp.apify.com/?tools=themineworks/cms-hospital-quality

Or call it programmatically with the Apify client:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('themineworks/cms-hospital-quality').call({
  state: 'NY',
  minStars: 4,
  maxResults: 100,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

🛠️ Complete your healthcare data pipeline

Hospital ratings are one signal. Layer in the rest of the healthcare stack:

• Medicare Part D Drug Spending: total spend, claims, beneficiaries, and unit cost for every drug in Medicare Part D.
• openFDA Scraper: drug adverse events (FAERS), recalls, labels, device 510k, and food enforcement.
• Socrata Open Data Scraper: any US federal, state, or city Socrata portal (CDC, HHS, CMS, NYC, more).

Typical flow: benchmark hospitals with this actor, pair with Part D pricing for payer economics, and pull FAERS for the safety signal on prescribed drugs.

Found a bug or have a feature request? Open an issue on the actor's Apify Console page or reach out through the Apify profile.