Which Factors Predict 30-Day Readmission After Total Hip and Knee Replacement Surgery?

Cynthia L Williams; George Pujalte; Zhuo Li; Rock P Vomer 2nd; Maruoka Nishi; Lisa Kieneker; Cedric J Ortiguera

doi:10.7759/cureus.23093

Which Factors Predict 30-Day Readmission After Total Hip and Knee Replacement Surgery?

Cureus. 2022 Mar 12;14(3):e23093. doi: 10.7759/cureus.23093. eCollection 2022 Mar.

Authors

Cynthia L Williams¹, George Pujalte², Zhuo Li³, Rock P Vomer 2nd⁴, Maruoka Nishi⁵, Lisa Kieneker⁶, Cedric J Ortiguera⁷

Affiliations

¹ Therapeutics, Brooks College of Health, University of North Florida, Jacksonville, USA.
² Department of Family Medicine and Department of Orthopedics, Mayo Clinic, Jacksonville, USA.
³ Biostatistics Unit, Mayo Clinic, Jacksonville, USA.
⁴ Family Medicine, Eastern Virginia Medical School, Norfolk, USA.
⁵ Department of Family and Community Medicine, University of Oklahoma, Tulsa, USA.
⁶ Family Medicine, Mayo Clinic, Jacksonville, USA.
⁷ Orthopedic Surgery, Mayo Clinic, Jacksonville, USA.

Abstract

Background The Centers for Medicare and Medicaid Services enacted the Hospital Readmissions Reduction Program to impose penalties for diagnoses with high readmission rates. Despite several elective orthopedic procedures being included in this program, readmission rates have not declined, and associated costs have reached critical levels for total knee and total hip arthroplasty. Readmissions drastically impact patient outcomes. There are many known contributors to patient readmission rates, including infection, pain, and hematomas. However, evidence is inconclusive regarding other aspects, such as demographics, insurance, and discharge disposition. The purpose of this manuscript is to 1) measure hospital readmission rates for total knee and total hip arthroplasty, 2) evaluate the causes of readmissions, and 3) provide a predictive profile of risk factors associated with hospital readmissions. Methods Patients who underwent total knee or total hip arthroplasty were identified through a retrospective database review. An electronic chart review extracted data concerning patient demographics, comorbidities, surgical information, 30-day outcomes, and reasons for 30-day readmissions. Continuous and categorical variables were assessed with the Wilcoxon rank-sum test and the Chi-square test, respectively. Results A total of 6,065 patients were included, with 269 (4.4%) having at least one surgery-related 30-day readmission. No differences in readmission were noted with age, sex, or ethnicity; however, differences were found in weight and body mass index. Statistically significant comorbidities were heart failure, chronic obstructive pulmonary disease, dialysis, and alcohol use or abuse. Conclusion Our research indicated that surgery type, length of stay, and heart failure most significantly impacted 30-day readmission rates. By assessing readmission rates, we can take steps to optimize care for non-elective surgeries that will improve patient outcomes and cost-effectiveness.

Keywords: arthroplasty; orthopedic; procedures; readmissions; surgeries.