Remote diagnostic imaging using artificial intelligence for diagnosing hip dysplasia in infants: Results from a mixed-methods feasibility pilot study

Abstract

Abstract Objectives Infant hip dysplasia or Developmental Dysplasia of the Hip (DDH) occurs in 1–2% of births worldwide and leads to hip arthritis if untreated. We sought to evaluate the feasibility of implementing an artificial intelligence-enhanced portable ultrasound tool for infant hip dysplasia (DDH) screening in primary care, through determining its effectiveness in practice and evaluating patient and provider feedback. Methods A US-FDA-cleared artificial intelligence (AI) screening device for DDH (MEDO-Hip) was added to routine well-child visits from age 6 to 10 weeks. A total of 306 infants were screened during a 1-year pilot study within three family medicine clinics in Alberta, Canada. Patient and provider satisfaction were quantified using the System Usability Survey (SUS), while provider perceptions were further investigated through semi-structured interviews. Results Provider and user surveys commonly identified best features of the tool as immediate diagnosis, offering reassurance/knowledge and avoiding travel, and noted technical glitches most frequently as a barrier. A total of 369 scans of 306 infants were performed from Feb 1, 2021 until Mar 31, 2022. Eighty percent of hips scanned were normal on initial scans, 14% of scans required a follow-up study in the primary care clinic, and DDH cases were identified and treated at the expected 2% rate (6 infants). Conclusions It is feasible to implement a point-of-care ultrasound AI screening tool in primary care to screen for infants with DDH. Beyond improved screening and detection, this innovation was well accepted by patients and fee-for-service providers with a culture and history of innovation.