Medicaid is associated with increased readmission and resource utilization after primary total knee arthroplasty: a propensity score–matched analysis

• Authors: David Shau, Emory University; Neeta Shenvi, Emory University; Kirk Easley, Emory University; Melissa Smith, Emory University; III, George N. Guild, Emory University
• Journal Title: Arthroplasty Today
• Volume: Volume 4, Number 3
• Publisher: Elsevier | 2018-09-01, Pages 354-358
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1016/j.artd.2018.05.001
• Subjects: Biology, Biostatistics; Health Sciences, Medicine and Surgery
• Keywords: Insurance status; Medicaid; Primary total knee arthroplasty; Readmission; Resource utilization

Abstract

Background: Medicaid payer status has been shown to affect resource utilization across multiple medical specialties. There is no large database assessment of Medicaid and resource utilization in primary total knee arthroplasty (TKA), which this study sets out to achieve. Methods: The Nationwide Readmissions Database was used to identify patients who underwent TKA in 2013 and corresponding “Medicaid” or “non-Medicaid” payer statuses. Demographics, 15 individual comorbidities, readmission rates, length of stay, and direct cost were evaluated. A propensity score–based matching model was then used to control for baseline confounding variables between payer groups. A chi-square test for paired proportions was used to compare readmission rates between the 2 groups. Length of stay and direct cost comparisons were evaluated using the Wilcoxon signed-rank test. Results: A total of 8372 Medicaid and 268,261 non-Medicaid TKA patients were identified from the 2013 Nationwide Readmissions Database. A propensity score was estimated for each patient based on the baseline demographics, and 8372 non-Medicaid patients were propensity score matched to the 8372 Medicaid patients. Medicaid payer status yielded a statistically significant increase in overall readmission rates of 18.4% vs 14.0% (P <.0001, relative risk = 1.31, 95% confidence interval [1.23-1.41]) with non-Medicaid status and 90-day readmission rates of 10.0% vs 7.4%, respectively (P <.001, relative risk = 1.35, 95% confidence interval [1.22-1.48]). The mean length of stay was longer in the Medicaid group compared with the non-Medicaid group at 4.0 days vs 3.3 days (P <.0001) as well as the mean total cost of $64,487 vs $61,021 (P <.0001). Conclusions: This study demonstrates that Medicaid payer status is independently associated with increased resource utilization, including readmission rates, length of stay, and total cost after TKA.