Characterization of Re-admission and Emergency Department Visits within 90 Days Following Lower-Extremity Arthroplasty. Issue 3 (October 2018) - Huerfano, Elina; Gonzalez Della Valle, Alejandro; Shanaghan, Kate; Girardi, Federico; Memtsoudis, Stavros; Liu, Jiabin
Background: Acute care events including emergency department (ED) visits and unscheduled inpatient re-admissions following lower-extremity arthroplasty are not fully understood. Question/Purposes: The purpose of this study was to characterize acute care events occurring after discharge in patients who received a lower-extremity arthroplasty: the incidence, timing, and risk factors of inpatient admission and ED visits within 90 days of discharge. Methods: The New York State Inpatient and Emergency Department Databases were used to identify patients who underwent elective total knee arthroplasty (TKA) or total hip arthroplasty (THA) from 2009 to 2013 (124, 234 and 76, 411 patients, respectively). Multivariate logistic regression analysis was used to determine the predictors of and the most frequent reasons for unscheduled acute care within 90 days of discharge. Results: Unscheduled acute care was needed in 13.79% of patients (8.81% of inpatient re-admissions and 4.98% of ED visits), most often in the first week after discharge (61.05% of all inpatient re-admissions and 20.46% of all ED visits). Most of these visits were for musculoskeletal pain, peri-prosthetic joint or wound infection, cardiac complications, blood transfusion, psychiatric events, mechanical complications, and deep vein thrombosis. Predictors for the need for acute care after TKA included African American and Hispanic race or ethnicity, Medicaid coverage, and neuraxial anesthesia. Predictors for the need for acute care after THA included older age (over 85 years), African American race, and Medicaid coverage. Conclusion: We identified demographic and procedure-related variables associated with an increased risk of ED visits and inpatient re-admissions after TKA or THA. Understanding these variables will contribute to improved care quality.