Predictive Model for Medical and Surgical Readmissions Following Elective Lumbar Spine Surgery A National Study of 33,674 Patients

Study Design. This study retrospectively analyzes prospectively collected data. Objective. Here we aim to develop predictive models for 3month medical and surgical readmission after elective lumbar surgery, based on a multi-institutional, national spine registry. Summary of Background Data. Unplanned readmissions place considerable stress on payers, hospitals, and patients. Medicare data reveals a 30-day readmission rate of 7.8% for lumbar-decompressions and 13.0% for lumbar-fusions, and hospitals are now being penalized for excessive 30-day readmission rates by virtue of the Hospital Readmissions Reduction Program. Methods. The Quality and Outcomes Database (QOD) was queried for patients undergoing elective lumbar surgery for degenerative diseases. The QOD prospectively captures 3-month readmissions through electronic medical record (EMR) review and self-reported outcome questionnaires. Distinct multivariable logistic regression models were fitted for surgery-related and medical readmissions adjusting for patient and surgery-specific variables. Results. Of the total 33,674 patients included in this study 2079 (6.15%) reported at least one readmission during the 90day postoperative period. The odds of medical readmission were significantly higher for older patients, males versus females, African Americans versus Caucasion, those with higher American Society of Anesthesiologists (ASA) grade, diabetes, coronary artery disease, higher numbers of involved levels, anterior only or anterior-posterior versus posterior approach; also, for patients who were unemployed compared with employed patients and those with high baseline Oswestry Disability Index (ODI). The odds of surgery-related readmission were significantly greater for patients with a higher body mass index (BMI), a higher ASA grade, female versus male, and African Americans versus Caucasians; also, for patients with severe depression, more involved spinal levels, anterior-only surgical approaches and higher baseline ODI scores. Conclusion. In this study we present internally validated predictive models for medical and surgical readmission after elective lumbar spine surgery. These findings set the stage for targeted interventions with a potential to reduce unnecessary readmissions, and also suggest that medical and surgical readmissions be treated as distinct clinical events.