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Brown University’s free Private Equity State Tracker maps more than 6,000 documented private equity investments in U.S. health care across all 50 states from 2015 through 2023. It lets readers explore activity by state, county, ZIP code, and selected physician specialties. It is a historical research tool—not a real-time monitor or a complete census of every deal.
What the Brown Private Equity State Tracker shows
The interactive tracker was created by researchers at Brown University’s School of Public Health to make information about private equity in health care easier to explore. Its coverage includes investments involving physician practices and short-term acute care hospitals. Brown describes the dataset as containing more than 6,000 investments during 2015–2023; that figure describes the tracker’s documented coverage, not every transaction that occurred.
Users can examine activity at state, county, and ZIP-code levels, compare activity over time, and view physician specialties such as primary care, orthopedics, and oncology. The tracker is free to use and intended for policymakers, researchers, journalists, and the public. Brown offers the underlying data through a brief form. Open the Brown Private Equity State Tracker.
How to use the tracker without mixing unlike measures
- Choose the geography. Select a state, county, or ZIP code, depending on the question you want to investigate.
- Set the time period. The investment coverage runs from 2015 through 2023. The tracker should not be read as showing deals after that period.
- Keep the provider category consistent. For physician-practice views, select a specialty available in the tracker; for hospital activity, note that the included hospitals are short-term acute care hospitals.
- Check what the displayed measure represents. A transaction count, an estimate of physician affiliation, and an estimate of hospital affiliation describe different things. Brown’s physician affiliation estimates use 2023 data, so they are not the same as the 2015–2023 investment timeline.
- Interpret comparisons as descriptive. State or specialty differences can help frame questions for reporting and policy, but the comparison alone does not show why the differences arose or establish cause and effect.
How Brown assembled the data
Physician-practice investments
Brown combines PitchBook records with Medicare Data on Provider Practice and Specialty (MD-PPAS), then manually reviews sources such as press releases, industry reports, and current and archived websites. The mixture of a commercial database, provider records, and manual source review is intended to identify and characterize investments; it does not eliminate gaps in public reporting.
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Hospital acquisitions
The hospital acquisition data for 2015–2023 are based on publicly available data compiled by Kim and colleagues. This is a separate source from the physician-practice investment data and covers short-term acute care hospitals.
Affiliation estimates
Brown estimates physician affiliation using 2023 data by linking investment records to MD-PPAS. For hospital affiliation, it links the Agency for Healthcare Research and Quality’s Compendium of U.S. Health Systems to MD-PPAS. These affiliation estimates are a snapshot based on those data, not a complete account of every provider’s ownership history over the tracker’s full investment period.
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Brown’s formal citation is: Singh Y, Reddy M, Shroff J, Whaley C, Hostert N, Fuse Brown E. Private Equity State Tracker. Brown University School of Public Health; 2026. doi:10.26300/xfj4-s836. See the official tracker page for methodology and access details.
What the tracker leaves out
Brown cautions that its totals should be treated as underestimates. There are no systematic reporting or disclosure requirements for private equity investments in health care, so smaller or otherwise unreported transactions are likely missing.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →- Some provider types: The Medicare-based physician data omit some specialties, including obstetrics and gynecology, pediatrics, and dentistry. Non-physician providers such as advanced practice providers are also outside this coverage.
- Some hospital settings: The hospital acquisition data cover short-term acute care hospitals, not psychiatric, rehabilitation, or long-term acute care hospitals.
- Some specialty staffing arrangements: Estimates for anesthesiology and emergency medicine may omit staffing-firm arrangements.
- Deal structure and ownership changes: Brown cannot systematically track whether a deal involved a leveraged buyout, joint venture, or a management services organization. It also cannot track exits; an entity still classified as private equity-affiliated may have changed ownership through an exit, sale, or divestiture.
What state examples can—and cannot—tell you
Brown’s launch announcement highlights several state-level observations: fewer than half of Texas oncologists are affiliated with hospitals; one-third of independent doctors in Texas are employed by private equity-backed entities; and a majority of Indiana oncologists are employed by hospitals and health systems. These examples illustrate how hospital employment and private equity affiliation can vary across settings. They do not establish that one pattern caused another, or that a state’s figures apply to specialties and provider types the tracker does not cover.
Brown assistant professor Yashaswini Singh said the tracker is intended to support evidence-based policymaking about health-care corporatization more broadly, rather than focusing on private equity in isolation. That framing matters when interpreting the maps: they document selected activity and affiliations, not every ownership channel in health care.
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Who may find it useful
The tracker can help a reader locate reported activity in a particular area, identify patterns worth investigating, or find a starting point for policy and research questions. A journalist might compare the same specialty across two states; a researcher might use the downloadable data for further analysis; a resident might check which types of activity Brown has documented locally. In each case, the result should be described with its geography, period, provider scope, and measure so readers do not mistake an estimate for a complete count.
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