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

OBJECTIVES

Efforts to safely reduce hospital LOS while maintaining quality outcomes and patient satisfaction are paramount. The primary goal of this study was to assess trends in LOS at a high-volume quaternary care spine center. Secondary goals were to assess trends in factors most associated with prolonged LOS.

METHODS

This is a prospective study of all consecutive patients admitted from January 2006 to December 2019. Data included demographics, diagnostic category (degenerative, oncology, deformity, trauma, other), LOS (mean, median, interquartile range, standard deviation, defined as days from admission to discharge), and in-hospital adverse events.

RESULTS

A total of 13,493 patients were included. Overall LOS has not changed over time with an overall median of 6.3 days (p = 0.451). Median LOS significantly increased for patients treated for degenerative pathology from 2.2 days in 2006 to 3.2 days in 2019 (p = 0.019). LOS has not changed for patients treated for deformity (overall median 6.8 days, p = 0.411), oncology (overall median 11.0 days, p = 0.051), or trauma (overall median 11.8 days, p = 0.582). Emergency admissions increased 3.2%/year for degenerative pathologies (p =  < 0.001). Mean age has increased from 48.4 years in 2006 to 58.1 years in 2019 (p =  < 0.001). This trend was observed in the deformity, degenerative and trauma group, not for patients treated for oncological disease. More adverse events were significantly associated with increasing age.

CONCLUSION

This is the first North American study to comprehensively analyze trends in LOS for spinal surgery overtime in an academic center. Overall, LOS has not changed from 2006-2019. Various factors that influence LOS appear to have balanced each other. It may also be explained by the changing epidemiology of both elective and emergency surgeries. These findings provide opportunities for intervention and improvement, targeted at the geriatric population, to reduce length of hospitalization.