Prediction calculator for nonroutine discharge and length of stay after spine surgery

BACKGROUND CONTEXT: Following spine surgery, delays in referral to rehabilitation facilities leads to increased length of hospital stay (LOS), increases costs, more risk of hospital acquired complications, and decreased patient satisfaction. PURPOSE: We sought to create a prediction calculator to determine the expected LOS after spine surgery and identify patients most likely to need postoperative nonhome discharge. The goal would be to facilitate earlier referral to rehabilitation and thereby ultimately shorten LOS, reduce costs, and improve patient satisfaction. STUDY DESIGN: Retrospective. PATIENT SAMPLE: We retrospectively reviewed all adult patients who underwent spine surgery for all indications between January and June 2018. OUTCOME MEASURES: Length of stay and discharge disposition. METHODS: Demographic variables, insurance status, baseline comorbidities, narcotic use, operative characteristics, as well as postoperative length of stay and discharge disposition data were collected. Univariable and multivariable analyses were performed to identify independent predictors of LOS and discharge disposition. RESULTS: Two hundred fifty-seven patients were included. Mean age was 59 years, 46% were females, and 52% had private insurance vs 7% with Medicaid and 41% with Medicare. The most commonly performed procedure was lumbar fusion (31.9%). Mean LOS after surgery was 4.8 days and 18% had prolonged LOS >7 days. Age, insurance type, marriage status, and surgical procedure were significantly associated with LOS and discharge disposition. The final model had an area under the curve of 89% with good discrimination. A web based calculator was developed: https://jhuspine1.shinyapps.io/RehabLOS/ CONCLUSIONS: This study established a novel pilot calculator to identify those patients most likely to be discharged to rehabilitation facilities and to predict LOS after spine surgery. Our calculator had a high predictive accuracy of 89% compared to others in the literature. With validation this tool may ultimately facilitate streamlining of the postoperative period to shorten LOS, optimize resource utilization, and improve patient care.