Learning Curves Associated With Robotic Total Hip Arthroplasty: A Scoping Review.

Introduction: Robotic total hip arthroplasty (rTHA) is gaining widespread adoption, yet the learning curve (LC) associated with its implementation remains uncertain. Understanding LCs is crucial to optimizing training protocols and improving patient outcomes. This scoping review assesses LCs in rTHA by evaluating operative time, leg length discrepancy (LLD), and acetabular component inclination (ACI).

Methods: A systematic search was conducted across PubMed, MEDLINE, Embase, Scopus, and Web of Science following PRISMA guidelines. Studies assessing the LC of rTHA based on operative efficiency, radiographic accuracy, and surgical outcomes were included.

Results: A total of 12 studies were included. Improvements in operative time were observed at a median of 13 cases, ranging from 7 to 35 cases. Both LLD and ACI findings were inconsistent, with little evidence of a LC found in the literature.

Conclusion: This review highlights the learning curve in rTHA, with proficiency improving after early cases. Standardized benchmarks and training models could enhance learning and enable comparisons across robotic systems. Future research should refine proficiency thresholds, assess system differences, and develop structured training for optimal rTHA adoption.