Background: Developmental dysplasia of the hip (DDH) is a common cause of premature osteoarthritis. This osteoarthritis can be prevented if DDH is detected by ultrasound and treated in infancy, but universal DDH screening is generally not cost-effective due to the need for experts to perform the scans. Questions/purposes: The purpose of our study was to evaluate the feasibility of having non-expert primary care clinic staff perform DDH ultrasound using handheld ultrasound with artificial intelligence (AI) decision support. Patients and Methods: We performed an implementation study evaluating the FDA-cleared MEDO-Hip AI app interpreting cine-sweep images obtained from handheld Philips Lumify probe to detect DDH. Initial scans were done by nurses or family physicians in 3 primary care clinics, trained by video, powerpoint slides and brief in-person. When the AI app recommended follow-up, we first performed internal follow-up by a sonographer using the AI app; cases still considered abnormal by AI were referred to pediatric orthopedic clinic for assessment. Results: We performed 369 scans in 306 infants. Internal follow-up rates were initially 40% for nurses and 20% for physicians, declining steeply to 14% after ~60 cases/site: 4% technical failure, 8% normal at sonographer follow-up using AI, and 2% confirmed DDH. Of 6 infants referred to pediatric orthopedic clinic, all were treated for DDH (100% specificity); 4 had no risk factors and may not have otherwise been identified. Conclusions: Real-time AI decision support and a simplified portable ultrasound protocol enabled lightly trained primary care clinic staff to perform hip dysplasia screening with follow-up and case detection rates similar to costly conventional ultrasound screening performed by experts. This highlights the potential utility of AI-supported portable ultrasound in primary care. Level of Evidence: This study uses data from consecutive patients and would be classified as Level 3 evidence