This visualization draws on multiple national data sources to examine how consolidation has reshaped U.S. hospital markets from 2000 to 2025.
Each hospital's local market is defined by a 30-minute travel radius, estimated using 2025 travel times from the HERE Maps API.
Ownership and transaction data are combined with hospital size (bed counts) to assess market concentration and how it has changed over time.

**Hospitals**
The dataset includes all general, short-term, acute-care hospitals operating in the United States between 2000 and 2025. Exclusions were based on national facility classifications. We focus on general, short-term, acute-care hospitals — the facilities that compete directly for inpatient services delivered to the privately insured. Specialty hospitals (psychiatric, rehabilitation, children's, long-term care, VA, or military), urgent-care centers, and facilities without staffed inpatient beds were excluded using Centers for Medicare & Medicaid Services (CMS) and state licensing data.
We identified and verified hospitals using data from CMS, the American Hospital Directory, the American Community Assessment (ACA), and the Health Care Affordability Lab at Yale’s own data collection and validation process, which involved scraping and reconciling state licensing records, system websites, and public filings.

**Hospital Markets**
Each hospital’s market is defined as a 30-minute travel radius around that facility. Within this boundary, we calculate market concentration using the Herfindahl-Hirschman Index (HHI) based on:

the number of hospitals in the area,
their size (measured by bed count), and
who owns those beds.

The HHIs are defined as the sum of squares of the market shares of each hospital in a market. A hospital’s market share is its count of beds divided by the total count of beds in the hospital’s market. This provides a consistent analytical proxy for understanding local hospital market competition, but does not represent a legally defined antitrust market.
Hospitals that relocate over time are recalculated with new isochrones based on their updated coordinates.
All travel times are based on 2025 network data from the HERE Maps API.

**Transactions and “Red Zone” Mergers**
A transaction represents a change in hospital ownership, typically through a merger or acquisition. A single transaction can involve multiple hospitals, as health systems often acquire or merge with several facilities in the same year.
In this tool, all transactions occurring within a selected year or range of years are visualized. Each event includes:

the acquiring system (buyer),
the buyer’s existing hospitals, and
all hospitals purchased during the transaction.

The buyer is identified as the ownership group listed at the end of that calendar year in our harmonized ownership database.
The tool classifies a transaction as a Red Zone Merger when it occurs in a market where:

the post-merger HHI is ≥ 1,800, and
the increase in HHI is > 100 points.

These thresholds are drawn from the FTC/DOJ 2023 Merger Guidelines and are used here as reference benchmarks, not legal classifications. They highlight markets where consolidation may meaningfully reduce local competition or raise prices under conditions similar to those regulators consider concerning.

**Hospital Openings & Closures**
Hospital openings and closures can significantly affect local market concentration. Each hospital appears in the tool beginning in the first year it appears in the dataset. Hospitals that don’t appear in a specific year may be absent due to gaps in reporting, rather than because of a closure. Missing records in subsequent years may be due to a gap in data and may not be definitive evidence of opening or closure.
This approach allows users to see how the competitive landscape of a hospital market changes over time, but does not model service reductions, partial closures, or planned openings prior to operation. Because these events can temporarily increase or decrease a community’s HHI value, users should interpret year-to-year changes in markets with openings or closures as structural shifts rather than merger-driven changes.

**Feedback**
We value and need your feedback. This is a first-of-its-kind database that we built from scratch. We've done our best to gather and validate the data; however, if you notice an error (e.g. a hospital’s name, a merger year) or if you have questions about our methodology, please notify us through the Add Feedback button.