License Healthcare Pricing Data or Access It via API

Gigasheet licenses nationwide healthcare price transparency data as bulk datasets and provides an API for teams that need negotiated rates inside applications, analytics workflows, and AI agents. Use bulk licensing when you need large-scale ingestion into a warehouse or model pipeline. Use the API when a product or agent needs programmatic access. Use the Price Transparency Explorer when analysts need answers without building data infrastructure.

The data covers payer Transparency in Coverage files and hospital price transparency files nationwide: more than 150 billion negotiated rates across payers and providers, with commercial negotiated rates alongside geographically adjusted Medicare benchmarks.

Where can you license healthcare pricing datasets or access them through an API?

Gigasheet provides licensed nationwide healthcare price transparency data through three delivery methods. The right one depends on where the data needs to live and who will use it.

• Load nationwide files into a warehouse or lakehouse: Bulk Data licensing.
• Add pricing data to a product or workflow: the Price Transparency and Analytics API.
• Research rates and compare markets without engineering work: the Price Transparency Explorer.
• Build an AI agent or model workflow: API and MCP access for agents, or bulk delivery for model pipelines.

All three run on the same underlying data, so you can validate rates in the Explorer before you scope an extract or an integration.

What healthcare pricing data can you license from Gigasheet?

Gigasheet licenses normalized negotiated-rate data from payer machine-readable files and hospital price transparency files, joined with provider reference data and Medicare benchmarks.

• Coverage: all payers and all states, from both Transparency in Coverage and Hospital Price Transparency sources. Gigasheet will process a payer or hospital on request if it is not already in the set.
• Rate fields: billing code and modifier, negotiated rate and rate type, negotiation arrangement, payer, plan, network, provider identifiers, and effective dates.
• Billing codes: CPT, HCPCS, DRG, and other code types published in price transparency files.
• Provider reference data: NPI, TIN, taxonomy, and group and health system affiliation, so rates roll up to the entity you actually negotiate with.
• Medicare benchmarks: geographically adjusted Medicare reimbursement as an independent reference point.
• Provider Rate Scores (optional): where a negotiated rate sits relative to the market for the same code and geography. Scores describe negotiated-rate position only, not quality of care or patient cost.
• Source lineage: every record traces back to the original machine-readable file.

Commercial negotiated rates and Medicare benchmarks are different data types. Keep them in separate fields and compare them deliberately, usually as a percentage of Medicare for the same code, setting, and locality.

Should you use a bulk healthcare dataset or a pricing data API?

Use bulk licensing when your team needs to ingest, retain, and combine nationwide data with its own. Use the API when an application, workflow, or AI agent needs answers on demand without moving the data.

Bulk dataset licensing

• Best for: data engineering teams, healthcare data companies, and analytics groups that run their own warehouse.
• Delivery: Amazon S3, Azure Blob, Google Cloud Storage, SFTP, Snowflake, BigQuery, or Redshift.
• Formats: Parquet, CSV, or JSON, partitioned and typed.
• Shape: pivoted or reshaped to your schema instead of a raw dump to reconcile.
• Freshness: refreshed continuously as payers and hospitals post new files.

API access

• Best for: product teams, RCM and repricing applications, BI dashboards, and AI agents.
• How it works: REST endpoints for data retrieval and custom calculations across 150 billion+ negotiated rates. The analysis runs on Gigasheet's infrastructure and returns the answer, not millions of rows.
• Calculations: pre-built aggregations and statistics, plus a formula library for conditional logic, date math, correlation, and grouped aggregations.
• Context: responses arrive enriched with market benchmarks, and you can export the underlying rows any time.
• Developer resources: API documentation with Python examples, and any language works.

Many teams use both: bulk data for the warehouse, and the API for application features that need fast answers.

How can AI agents use licensed healthcare pricing data?

AI agents can use licensed negotiated-rate data as a governed, traceable source for rate research, payer and provider comparisons, benefit analysis, repricing research, and claim benchmarking.

• MCP access: Gigasheet exposes an MCP service, so Claude, ChatGPT, or any MCP-compatible model can query the national dataset directly. The model brings its reasoning. Gigasheet brings the rates and the nuances of healthcare pricing data.
• API as agent tools: wrap API endpoints as tools inside your own agent framework or application.
• Bulk data for model workflows: load licensed data into your warehouse for retrieval, feature engineering, or analysis pipelines.
• Gigasheet's own agent: analysts can ask questions in plain language inside the Explorer and get an intelligence report with the backing data, including structured claim benchmarks for payment integrity teams.

Traceability matters more for agents than for people. Every figure an agent returns should tie back to the published rate and source file behind it, so a reviewer can check the work.

Governance note: before using any dataset in an AI workflow, confirm your license terms, permitted uses (including any model training or fine-tuning), source-data requirements, and data handling process. This is general implementation guidance, not legal advice.

Who uses healthcare pricing datasets and APIs?

Licensed negotiated-rate data is used by organizations that need pricing intelligence inside payment, benefits, navigation, provider, and technology workflows.

• Payment integrity, cost containment, and repricing companies: benchmark high-cost claims and support repricing decisions.
• TPAs, self-insured employers, and benefits consultants: evaluate networks and compare plan pricing.
• Care navigation and patient advocacy companies: steer members toward appropriately priced providers.
• Provider marketplaces and healthcare technology companies: add negotiated-rate data to products.
• Hospitals, physician groups, and MSOs: prepare for payer negotiations with competitor rate context.
• Healthcare data and AI companies: build analytics products and agent workflows on normalized data.

How does negotiated-rate data compare with benchmark-based cost APIs?

Negotiated-rate datasets and benchmark-based cost APIs answer different questions. Pick the source type that matches your use case rather than assuming one replaces the other.

Benchmark APIs are built around percentile estimates. For example, in a 2017 article FAIR Health described API delivery of charge and allowed benchmarks from the 5th to 95th percentile across 493 geozips, based on twelve months of data, updated twice per year, and covering more than 15,000 procedure codes.

• Benchmark APIs: percentile-based estimates of charges or allowed amounts for a code and geography.
• Negotiated-rate datasets: the specific rates payers and providers disclose under federal price transparency rules, by payer, plan, network, and provider.

When evaluating any vendor, compare use-case fit, geography, code coverage, data lineage, refresh cadence, and licensing terms.

How do you get started with Gigasheet healthcare pricing data?

Start by choosing the delivery method that fits your workflow, then scope the data you need.

1. Define the use case. Repricing research, product integration, network benchmarking, or AI agent research.
2. Validate the data. Search a payer, code, or provider in the Price Transparency Explorer to see the rates for yourself.
3. Choose a delivery method. Bulk licensing, API and MCP access, or the Explorer.
4. Confirm scope and permitted use. Geography, payers, code types, Medicare benchmarks, destination, format, and license terms.
5. Set up the integration. Load the extract into your warehouse, connect your application or agent to the API, or give analysts access.

Review our guide to benchmarking negotiated rates for analysis methods once the data is in place. When you are ready, Request a Demo.

Last updated November 2, 2026. Source categories: payer Transparency in Coverage machine-readable files, hospital price transparency files, and Medicare reimbursement data.