Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Machine learning has the potential to improve clinical decision-making and patient care by helping to prioritize resources for postsurgical monitoring and informing presurgical discussions of likely outcomes of TJA. Applied to presurgical registry data, such models can predict, with fair-to-good ability, 2-year postsurgical MCIDs. Although we report all parameters of our best-performing models, they cannot simply be applied off-the-shelf without proper testing. Our analyses indicate that machine learning holds much promise for predicting orthopaedic outcomes. LEVEL OF EVIDENCE: Level III, diagnostic study.