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Private equity owned dentists, eye doctors and vets in Wisconsin
44 Wisconsin cities, with the share of each city’s dental and eye care practices that are PE-backed or lender-controlled. Vets are locations of the chains we track.
| City | Dental | PE share | Eye care | PE share | Vet chains |
|---|---|---|---|---|---|
| Milwaukee | 205 | 6% | 67 | 1% | 5 |
| Madison | 129 | 18% | 77 | 1% | 14 |
| Green Bay | 93 | 15% | 46 | 4% | 8 |
| Appleton | 75 | 19% | 35 | 0% | 3 |
| Brookfield | 62 | 8% | 33 | 3% | 5 |
| Kenosha | 55 | 9% | 31 | 3% | 3 |
| Waukesha | 55 | 15% | 22 | 14% | 2 |
| Eau Claire | 52 | 10% | 21 | 0% | 1 |
| Wausau | 52 | 12% | 19 | 0% | 1 |
| Wauwatosa | 45 | 7% | 17 | 6% | 3 |
| Racine | 41 | 15% | 21 | 5% | 1 |
| Janesville | 42 | 19% | 17 | 0% | 3 |
| Oshkosh | 41 | 17% | 20 | 0% | 1 |
| West Allis | 45 | 7% | 11 | 9% | 2 |
| Sheboygan | 34 | 15% | 16 | 6% | 1 |
| Glendale | 29 | 17% | 11 | 0% | 2 |
| Mequon | 27 | 11% | 13 | 0% | 2 |
| Greenfield | 29 | 7% | 8 | 0% | 4 |
| Stevens Point | 31 | 6% | 8 | 0% | 2 |
| La Crosse | 29 | 14% | 10 | 0% | 1 |
| Fond Du Lac | 22 | 23% | 15 | 0% | 1 |
| Onalaska | 26 | 12% | 10 | 0% | 2 |
| Sun Prairie | 27 | 15% | 8 | 0% | 2 |
| West Bend | 26 | 19% | 11 | 0% | – |
| Hudson | 24 | 4% | 6 | 33% | 1 |
| Oconomowoc | 22 | 14% | 9 | 0% | 1 |
| Manitowoc | 22 | 18% | 7 | 0% | 2 |
| New Berlin | 14 | 14% | 15 | 7% | 2 |
| Pewaukee | 21 | 24% | 8 | 0% | 2 |
| Neenah | 19 | 11% | 10 | 0% | 1 |
| Menomonee Falls | 18 | 39% | 8 | 0% | 2 |
| Middleton | 19 | 16% | 7 | 0% | 2 |
| Wisconsin Rapids | 17 | 12% | 10 | 0% | 1 |
| Chippewa Falls | 18 | 6% | 9 | 0% | – |
| Mount Pleasant | 18 | 33% | 4 | 0% | 1 |
| Hales Corners | 18 | 6% | 3 | 0% | 1 |
| Marshfield | 11 | 0% | 10 | 0% | 1 |
| Franklin | 17 | 18% | 4 | 0% | – |
| Superior | 15 | 13% | 5 | 0% | 1 |
| Beloit | 14 | 14% | 5 | 0% | 1 |
| Fitchburg | 10 | 10% | 8 | 0% | 2 |
| Menomonie | 15 | 20% | 5 | 0% | – |
| Rice Lake | 12 | 0% | 8 | 0% | – |
| Watertown | 12 | 8% | 8 | 0% | – |
Cities with at least 20 practices in our data. How we label