CMS Data Feeds Dataset
About the Dataset
The CMS Data Feeds Dataset is a comprehensive collection of all current and future CMS data feeds available on cms.data.gov. This dataset transforms each feed into a view, aligning all feed file attributes and casting them to appropriate datatypes. The views are automatically updated when new feed files arrive, and new views are included as CMS publishes new data feeds.
As of February 2026, the dataset encompasses 233 feeds and 3,096 feed files.
See the full list of feeds in the CMS Data Feeds Catalog.
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Dataset Features
137 billion records and growing
233 feeds with automatic addition of new feeds
9,583 feed attributes
19 years of historical data
1.2 TB of data, continuously expanding
Daily updates to ensure data freshness
Automatic quality checks and active monitoring
Designed for seamless ingestion
Data Quality and Maintenance
Dataplex Consulting & Data Products prioritizes data quality through:
Automated data quality checks in all pipelines
Daily monitoring of ingestion and ETL jobs
Timely updates whenever CMS publishes new data
Rigorous processes to ensure data integrity and reliability
Business Applications
Users can leverage this dataset for various purposes, including:
Enriching or augmenting existing datasets
Analyzing published feed metrics over time
Performing segmentation analysis
Training machine learning models
Conducting geospatial analysis
Tracking healthcare trends and performance metrics
Example Use Cases
Analyze telehealth adoption trends across different states
Evaluate the financial performance of home health agencies
Track Medicare spending patterns by drug or geography
Assess hospital performance metrics and patient satisfaction scores
Monitor healthcare-associated infections across facilities
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Data Structure
The dataset consists of three main components:
FEEDS: Contains metadata about each CMS data feed
FEEDS_FILES: Stores information about individual files within each feed
Feed-specific views: Separate views for each feed (e.g., PatientReported_Outcomes, Medicare_Spending)
Entity Relationship Diagram
Sample Queries
Get CMS Feeds to Table Mapping
Find all Feed Views Related to Medicare
Query All 2021 File Records for Medicare Inpatient Hospitals
Get CMS Feeds to Table Mapping
Find all Feed Views Related to Medicare
Query All 2021 File Records for Medicare Inpatient Hospitals
📊 Recent Feed File Updates
Recent CMS feed file updates (last 30 days)
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10/1/2025 to 12/31/2025
1/12/2026
10/1/2025 to 12/31/2025
🆕 Recently Added Feeds
Ambulatory Specialty Model Participants (Added: February 2026)
What's in this data: The Ambulatory Specialty Model (ASM) Participants dataset provides essential information on clinicians required to participate in the ASM. It includes their names, National Provider Identifiers (NPI), their cohort, and the performance years for which they must meet ASM's requirements, making it a crucial resource for analyzing healthcare participation trends.
How you can use it:
Identifying clinicians participating in the ASM across various states and cohorts.
Analyzing trends in participation among small practices versus larger organizations.
Evaluating the distribution of ASM participants by state to inform regional healthcare strategies.
Example Queries:
This query shows the count of ASM participants by state and their associated cohort.
This query shows the number of participants from small practices versus larger organizations in the ASM across performance years.
Medicare Quarterly Part B Spending by Drug (Added: December 2025)
What's in this data: This dataset provides insights into the spending on drugs administered in outpatient settings under Medicare Part B. It includes essential metrics such as total beneficiaries, total claims, and spending per beneficiary, making it a crucial resource for analyzing drug utilization and costs.
How you can use it:
Analyzing trends in drug spending over different quarters to identify cost increase patterns.
Evaluating the average spending per beneficiary for specific drugs to inform healthcare policy decisions.
Comparing drug expenditures across different regions to assess disparities in healthcare spending.
Example Queries:
This query retrieves the total spending and average spending per beneficiary for each drug over the most recent quarter.
This query provides the total number of claims and beneficiaries for drugs with significant spending increases compared to the previous quarter.
Medicare Quarterly Part D Spending by Drug (Added: December 2025)
What's in this data: This dataset provides insights into the spending patterns for drugs prescribed to Medicare beneficiaries enrolled in Part D. It captures crucial metrics such as total spending and average spending per beneficiary, which can help stakeholders understand drug usage and costs in the Medicare program.
How you can use it:
Analyze trends in drug spending over multiple quarters to identify high-cost medications.
Evaluate the effectiveness of cost containment strategies by comparing spending per beneficiary across different medications.
Identify the most prescribed drugs and their respective spending to inform formulary decisions for Medicare Part D plans.
Example Queries:
This query shows total spending and average spending per beneficiary for each drug brand in the latest quarter.
This query shows the total number of beneficiaries and claims for each generic drug name in the latest available data.
📋 View the complete CMS Data Feeds Catalog
Get Started
CMS Medicare/Medicaid Data Access
Includes
All 232 feeds, daily updates, full documentation
Support
Email support included
Cancellation
Cancel anytime, no long-term commitment
Support and Contact
For questions or assistance with the CMS Data Feeds Dataset, please contact:
Email: [email protected]
The Dataplex Consulting & Data Products team monitors ingestion and ETL jobs daily to ensure quality and timely delivery.
About Dataplex
Dataplex Consulting & Data Products delivers turnkey, analytics-ready data products that make complex public and commercial data easy to use across modern data platforms. Our data pipelines include automated quality checks and active monitoring to ensure timely, reliable, and well-structured data that is ready for downstream analytics, machine learning, and operational use.
In addition to data products, Dataplex provides data engineering and analytics consulting services to organizations of all sizes. We bring deep, hands-on experience supporting both early-stage companies and large enterprises, helping teams build scalable data platforms, improve data reliability, and become more data-driven.
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