Factors Associated With Short Length of Stay After Long Fusions for Adult Spinal Deformity: Initial Steps Toward Developing an Enhanced Recovery Pathway

Abstract

Study Design: Retrospective cohort study. Objectives: The identification of case types and institutional factors associated with reduced length of stay (LOS) is a key initial step to inform the creation of clinical care pathways that can assist hospitals to maximize the benefit of value-based payment models. The objective of this study was to identify preoperative, intraoperative, and postoperative factors associated with shorter than expected LOS after adult spinal deformity (ASD) surgery. Methods: A retrospective cohort study was performed of 82 patients with ASD who underwent ≥5 levels of fusion to the pelvis between 2013 and 2018. A LOS <6 days was determined as a basis for comparison, as 5.7 days was the “expected LOS” generated through Poisson regression modeling of the sample. Clinical, radiographic, surgical, and postoperative factors were compared between those staying ≥6 days (L group) and <6 days (S group). Logistic regression was used to identify factors associated with LOS <6 days. Results: A total of 35 patients were in group S (42.7%). Gender, age, body mass index, ASA (American Society of Anesthesiologists) class, and use of preoperative narcotics, revision surgery, day of admission, and surgical complications did not vary between the cohorts ( P > .05). Mild-moderate preoperative sagittal deformity (sagittal Schwab modifiers 0 or +), lower estimated blood loss (<1200 mL), fewer levels fused (7 vs 10 levels), shorter operating room time, procedure end time before 15:00, and no intensive care unit stay, were associated with short LOS ( P < .05). Only 1 major medical complication occurred in the short LOS group ( P < .05). Conclusions: This study identifies the ASD “case phenotype,” intra-, and postoperative benchmarks associated with shorter LOS, providing targets for pathways designed to reduce LOS.

COVID-19 Significantly Impacted Hospital Length of Stay and Discharge Patterns for Adult Spinal Deformity Patients

“…This could be explained by the fact that ASD patients with the most severe deformity or clinical presentation could have been prioritized during the pandemic. Although our study rigorously controlled for various factors that have been shown to influence LOS and discharge disposition such as age, ASA class, the number of levels fused, revision surgery, and three-column osteotomy, 10 , 29 our analysis did not control for spinal alignment or preoperative health-related quality of life (HRQoL) scores.…”

Variations in LOS and its main determinants overtime at an academic spinal care center from 2006–2019

“…In the last 15 years, many efforts have been made to decrease LOS while ensuring high-quality care for patients via clinical care pathways [ 9 ]. Many studies have reported on factors associated with increased LOS [ 1 , 6 – 8 , 10 ].…”

“…Presurgical physiotherapy, so-called «prehabilitation», has not yet been shown to impact postoperative outcomes [ 20 , 21 ]. Despite these numerous technological and organizational advances among others, the reductions in LOS have been inconsistently reported [ 9 ].…”

Predictive Models for Length of Stay and Discharge Disposition in Elective Spine Surgery: Development, Validation, and Comparison to the ACS NSQIP Risk Calculator

“…Accurate preoperative identification of patients at risk for extended LOS and discharge to rehabilitation can provide substantial benefit, including more transparent communication on expected benefits and risks of surgery, postoperative planning, cost savings, preemptive administrative action, and optimization of modifiable patient risk factors 11–13. Many studies have determined significant risk factors in spine surgery, but most have been unable to create robust predictive models due to small cohort sizes and limited granularity of patient data 14,15. Of the reported predictive models, few capture the breadth of elective spinal cases, normally focusing on single types of procedures, diagnosis, or patient groups 16.…”

“…[11][12][13] Many studies have determined significant risk factors in spine surgery, but most have been unable to create robust predictive models due to small cohort sizes and limited granularity of patient data. 14,15 Of the reported predictive models, few capture the breadth of elective spinal cases, normally focusing on single types of procedures, diagnosis, or patient groups. 16 A notable tool used for all types of surgeries is the American College of Surgeon's National Surgical Quality Improvement Program's (ACS NSQIP) online calculator, which utilizes 21 inputted preoperative factors to predict both LOS and discharge status.…”