Retrospective cohort study.
The aim of this study was to assess 90-day readmission and evaluate risk factors associated with readmission after lumbar fusion in New York State.
Summary of Background Data.
Readmission is becoming an important metric for quality and efficiency of health care. Readmission and its predictors following spine surgery are overall poorly understood and limited evidence is available specifically in lumbar fusion.
The New York Statewide Planning and Research Cooperative System (SPARCS) was utilized to capture patients undergoing lumbar fusion from 2005 to 2014. Temporal trend of 90-day readmission was assessed using Cochran-Armitage test. Logistic regression was used to examine predictors associated with 90-day readmission.
There were 86,869 patients included in this cohort study. The overall 90-day readmission rate was 24.8%. On a multivariable analysis model, age (odds ratio [OR] comparing ≥75 versus <35 years: 1.24, 95% confidence interval [CI]: 1.13–1.35), sex (OR female to male: 1.19, 95% CI: 1.15–1.23), race (OR African-American to white: 1.60, 95% CI: 1.52–1.69), insurance (OR Medicaid to Medicare: 1.42, 95% CI: 1.33–1.53), procedure (OR comparing thoracolumbar fusion, combined [International Classification of Disease, Ninth Revision, ICD-9: 81.04] to posterior lumbar interbody fusion/transforaminal lumbar spinal fusion [ICD-9: 81.08]: 2.10, 95% CI: 1.49–2.97), number of operated spinal levels (OR comparing four to eight vertebrae to two to three vertebrae: 2.39, 95% CI: 2.07–2.77), health service area ([HSA]; OR comparing Finger Lakes to New York-Pennsylvania border: 0.67, 95% CI: 0.61-0.73), and comorbidity, i.e., coronary artery disease (OR: 1.26, 95% CI: 1.19–1.33) were significantly associated with 90-day readmission. Directions of the odds ratios for these factors were consistent after stratification by procedure type.
Age, sex, race, insurance, procedure, number of operated spinal levels, HSA, and comorbidities are major risk factors for 90-day readmission. Our study allows risk calculation to determine high-risk patients before undergoing spinal fusion surgery to prevent early readmission, improve quality of care, and reduce health care expenditures.
Level of Evidence: 3