A predictive model for increased hospital length of stay following geriatric hip fracture

Olivia M Knoll; Nikita Lakomkin; Michelle S Shen; Moses Adebayo; Parth Kothari; Ashley C Dodd; Basem Attum; Nathan Lee; Deepak Chona; Manish K Sethi

doi:10.1016/j.jcot.2019.03.024

A predictive model for increased hospital length of stay following geriatric hip fracture

J Clin Orthop Trauma. 2019 Oct;10(Suppl 1):S84-S87. doi: 10.1016/j.jcot.2019.03.024. Epub 2019 Apr 1.

Authors

Affiliations

¹ The Vanderbilt Orthopaedic Institute Center for Health Policy, 1215 21st Avenue South, Suite 4200 Medical Center East, South Tower Nashville, TN, 37232, USA.
² Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
³ New York University School of Medicine, New York, NY, USA.
⁴ Department of Orthopaedic Surgery, Howard University, Washington, D.C., USA.
⁵ Department of Orthopaedics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁶ University of Tennessee Health Science Center, Memphis, TN, USA.
⁷ Department of Orthopaedic Surgery, University of California San Diego School of Medicine, San Diego, CA, USA.
⁸ Department of Orthopaedic Surgery, Stanford University School of Medicine, Redwood City, CA, USA.

Abstract

Background: The purpose of this study was to identify the risk factors that are significantly associated with hospital length of stay (LOS) following geriatric hip fracture and to use these significant variables to develop a LOS calculator.

Materials and methods: This was a retrospective study examining 614 patients treated for geriatric hip fracture between January 2000 and December 2009 at an urban, Level 1 trauma center. A negative binomial regression analysis was used to identify perioperative variables associated with hospital LOS.

Results: 614 patients met the inclusion criteria, presenting with a mean age of 78 (±10) years. The most common pre-operative comorbidity was hypertension, followed by diabetes and COPD. After controlling for all collected comorbidities as well as demographics and operative variables, hypertension (IRR: 1.10, p = 0.029) and disseminated cancer (IRR: 1.24, p = 0.007) were found to be significantly associated with LOS. In addition, two demographic/presenting variables, admission to the medicine service (IRR: 1.48, p < 0.001) and male sex (IRR: 1.09, p = 0.034), were shown to be independent risk factors for prolonged LOS. These variables were synthesized into a LOS formula, which estimated LOS to within 3 days of the true length of stay for 0.758 of the series (95% confidence interval: 0.661 to 0.855).

Conclusions: This study identified several comorbidity and perioperative variables that were significantly associated with LOS following geriatric hip fracture surgery. The resulting LOS model may have utility in the risk stratification of orthopaedic trauma patients presenting with hip fracture.

Keywords: Hip fractures; Length of stay; Risk factors.