Patient Characteristics Associated With Loss to Follow-Up After Total Joint Arthroplasty.

Abstract

Maintaining follow up after total joint arthroplasty (TJA) is critical to monitor patient outcomes and complications. However, patient factors associated with follow-up compliance have not been described previously. This study aimed to characterize demographic and perioperative characteristics associated with TJA follow-up compliance. This was a retrospective review of all primary, elective total hip and knee arthroplasty (THA and TKA) procedures at an urban, tertiary care center from 2011 to 2022. Patient follow ups were categorized as early (0 to 90 days), mid-term (91 days to 2 years), and late-term (greater than 2 years) follow ups. Patient characteristics, including age, sex, race, smoking status, spoken language, body mass index, income class, insurance type, distance from hospital, 90-day readmission, American Society of Anesthesia Status, and Charlson Comorbidity Index, were compared at each period, and logistic regression identified predictors of follow up. In total, 2,836 TKA and 3,056 THA procedures were analyzed, with overall follow-up rates of 78.9 and 76.8%, respectively. Among all TJA patients, those who did not have follow ups were more likely to be younger, men, White, active smokers, live further from the hospital, and have lower Charlson Comorbidity Indices. Uniquely, for TKA patients, higher income status predicted lower overall and early follow-up rates, while English-speaking status predicted lower early and higher late follow-up rates in this subgroup. Differences between groups based on follow-up status decreased as follow-up time increased. Regression analyses showed loss to follow up increased with increased distance from the hospital and current smoking. Uniquely, for THA, men predicted loss to follow up. Younger age, men, White race, higher income, current smoking, and increased distance from the hospital are associated with increased early, but not late, loss to follow up after TJA. Future studies should assess the influence of other factors, including home support and telemedicine use, on follow-up rates.