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Predicting the post-operative length of stay for the orthopaedic trauma patient

International Orthopaedics volume 41, pages 859–868 (2017)Cite this article

Abstract

Purpose

Length of stay (LOS) is a major driver of cost and quality of care. A bundled payment system makes it essential for orthopaedic surgeons to understand factors that increase a patient’s LOS. Yet, minimal data regarding predictors of LOS currently exist. Using the ACS-NSQIP database, this is the first study to identify risk factors for increased LOS for orthopaedic trauma patients and create a personalized LOS calculator.

Methods

All orthopaedic trauma surgery between 2006 and 2013 were identified from the ACS-NSQIP database using CPT codes. Patient demographics, pre-operative comorbidities, anatomic location of injury, and post-operative in-hospital complications were collected. To control for individual patient comorbidities, a negative binomial regression model evaluated hospital LOS after surgery. Betas (β), were determined for each pre-operative patient characteristic. We selected significant predictors of LOS (p < 0.05) using backwards stepwise elimination.

Results

49,778 orthopaedic trauma patients were included in the analysis. Deep incisional surgical site infections and superficial surgical site infections were associated with the greatest percent change in predicted LOS (β = 1.2760 and 1.2473, respectively; p < 0.0001 for both). A post-operative LOS risk calculator was developed based on the formula: \( {\mathbf{e}}^{\left(\boldsymbol{intercept}+{\boldsymbol{\beta}}_1{\boldsymbol{X}}_1 + {\boldsymbol{\beta}}_2{\boldsymbol{X}}_2+\dots \right)} \).

Conclusions

Utilizing a large prospective cohort of orthopaedic trauma patients, we created the first personalized LOS calculator based on pre-operative comorbidities, post-operative complications and location of surgery. Future work may assess the use of this calculator and attempt to validate its utility as an accurate model. To improve the quality measures of hospitals, orthopaedists must employ such predictive tools to optimize care and better manage resources.

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Affiliations

  1. Department of Orthopaedics, Vanderbilt Orthopaedic Institute Center for Health Policy, Vanderbilt University Medical Center, 1215 21st Avenue South, Suite 4200, Medical Center East, South Tower, Nashville, TN, 37232, USA

    Deepak Chona, Nikita Lakomkin, Idine Mousavi, Parth Kothari, Ashley C. Dodd, Michelle S. Shen, William T. Obremskey & Manish K. Sethi

  2. Department of Biostatistics, Vanderbilt University, Nashville, TN, USA

    Catherine Bulka

Authors
  1. Deepak Chona
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  2. Nikita Lakomkin
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  3. Catherine Bulka
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  4. Idine Mousavi
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  5. Parth Kothari
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  6. Ashley C. Dodd
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  7. Michelle S. Shen
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  8. William T. Obremskey
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  9. Manish K. Sethi
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Corresponding author

Correspondence to Manish K. Sethi.

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Conflicts of interest

No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.

Informed consent

Obtaining the informed consent from involved patients was waived by the Vanderbilt Institutional Review Board. All procedures involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments. This study was approved by the Vanderbilt Institutional Review Board.

Appendix

Appendix

Table 4 Trauma CPT code descriptions
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Chona, D., Lakomkin, N., Bulka, C. et al. Predicting the post-operative length of stay for the orthopaedic trauma patient. International Orthopaedics (SICOT) 41, 859–868 (2017). https://doi.org/10.1007/s00264-017-3425-2

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  • DOI: https://doi.org/10.1007/s00264-017-3425-2

Keywords

  • Complications
  • Cost
  • Inpatient
  • Resource allocation