US Veterinary Clinics & Animal Hospitals
U.S. Location Dataset // 38,128

38,128 US veterinary clinics and animal hospitals with street address, phone, website and coordinates, plus the corporate group operating the location where it belongs to one. That corporate column is the reason to buy this rather than scrape a directory: veterinary medicine has been consolidating faster than almost any healthcare sector, and knowing which clinics are already owned by Mars Veterinary Health, Thrive or another group tells you immediately whether purchasing runs through a head office or through the practice owner. The file identifies 2,995 clinics under named corporate groups — Banfield and VCA under Mars, plus National Veterinary Associates and Thrive — and leaves everything else unbranded. Treat unbranded as an owner we have not identified rather than as proof of independence: corporate ownership is proven here from each operator's own hospital list, so a group we have not yet mapped simply does not appear. Animal health pharmaceutical companies, distributors, equipment and diagnostics manufacturers, practice management software vendors, staffing agencies, and the private equity buyers still acquiring practices all segment exactly this way. State veterinary boards license veterinarians rather than clinics, so no register of practices exists and this has to be assembled. It is also cleaned, which matters more than the headline number: an audit removed 1,783 retail pop-up vaccination clinics that mapping data files as veterinarians — 966 of them shared a single call-center phone number, because they are vaccination events held inside pet stores rather than practices — plus 879 groomers, boarding kennels, shelters and trainers, and 425 duplicates caused by a merge defect. Equine and large-animal practices, mobile and house-call vets, and full veterinary hospitals inside retailers were all deliberately kept.

All 38,128 records, as published — the complete set rather than a sample. That matters most for coverage and gap questions: put together the same list from partial searches and every location you miss reads as a gap that is not there, so the answer is wrong rather than merely late. Assembling the U.S.-wide coverage by hand also means one query per area against sources that cap what they return per search.