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The Risk Assessment and Prediction Tool (RAPT) for Discharge Planning in a Posterior Lumbar Fusion Population.

Publication ,  Journal Article
Glauser, G; Piazza, M; Berger, I; Osiemo, B; McClintock, SD; Winter, E; Chen, HI; Ali, ZS; Malhotra, NR
Published in: Neurosurgery
February 2020

As the use of bundled care payment models has become widespread in neurosurgery, there is a distinct need for improved preoperative predictive tools to identify patients who will not benefit from prolonged hospitalization, thus facilitating earlier discharge to rehabilitation or nursing facilities.To validate the use of Risk Assessment and Prediction Tool (RAPT) in patients undergoing posterior lumbar fusion for predicting discharge disposition.Patients undergoing elective posterior lumbar fusion from June 2016 to February 2017 were prospectively enrolled. RAPT scores and discharge outcomes were recorded for patients aged 50 yr or more (n = 432). Logistic regression analysis was used to assess the ability of RAPT score to predict discharge disposition. Multivariate regression was performed in a backwards stepwise logistic fashion to create a binomial model.Escalating RAPT score predicts disposition to home (P < .0001). Every unit increase in RAPT score increases the chance of home disposition by 55.8% and 38.6% than rehab and skilled nursing facility, respectively. Further, RAPT score was significant in predicting length of stay (P = .0239), total surgical cost (P = .0007), and 30-d readmission (P < .0001). Amongst RAPT score subcomponents, walk, gait, and postoperative care availability were all predictive of disposition location (P < .0001) for both models. In a generalized multiple logistic regression model, the 3 top predictive factors for disposition were the RAPT score, length of stay, and age (P < .0001, P < .0001 and P = .0001, respectively).Preoperative RAPT score is a highly predictive tool in lumbar fusion patients for discharge disposition.

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Published In

Neurosurgery

DOI

EISSN

1524-4040

ISSN

0148-396X

Publication Date

February 2020

Volume

86

Issue

2

Start / End Page

E140 / E146

Related Subject Headings

  • Spinal Fusion
  • Risk Assessment
  • Prospective Studies
  • Predictive Value of Tests
  • Patient Discharge
  • Neurology & Neurosurgery
  • Middle Aged
  • Male
  • Lumbar Vertebrae
  • Length of Stay
 

Citation

APA
Chicago
ICMJE
MLA
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Glauser, G., Piazza, M., Berger, I., Osiemo, B., McClintock, S. D., Winter, E., … Malhotra, N. R. (2020). The Risk Assessment and Prediction Tool (RAPT) for Discharge Planning in a Posterior Lumbar Fusion Population. Neurosurgery, 86(2), E140–E146. https://doi.org/10.1093/neuros/nyz419
Glauser, Gregory, Matthew Piazza, Ian Berger, Benjamin Osiemo, Scott D. McClintock, Eric Winter, H Isaac Chen, Zarina S. Ali, and Neil R. Malhotra. “The Risk Assessment and Prediction Tool (RAPT) for Discharge Planning in a Posterior Lumbar Fusion Population.Neurosurgery 86, no. 2 (February 2020): E140–46. https://doi.org/10.1093/neuros/nyz419.
Glauser G, Piazza M, Berger I, Osiemo B, McClintock SD, Winter E, et al. The Risk Assessment and Prediction Tool (RAPT) for Discharge Planning in a Posterior Lumbar Fusion Population. Neurosurgery. 2020 Feb;86(2):E140–6.
Glauser, Gregory, et al. “The Risk Assessment and Prediction Tool (RAPT) for Discharge Planning in a Posterior Lumbar Fusion Population.Neurosurgery, vol. 86, no. 2, Feb. 2020, pp. E140–46. Epmc, doi:10.1093/neuros/nyz419.
Glauser G, Piazza M, Berger I, Osiemo B, McClintock SD, Winter E, Chen HI, Ali ZS, Malhotra NR. The Risk Assessment and Prediction Tool (RAPT) for Discharge Planning in a Posterior Lumbar Fusion Population. Neurosurgery. 2020 Feb;86(2):E140–E146.
Journal cover image

Published In

Neurosurgery

DOI

EISSN

1524-4040

ISSN

0148-396X

Publication Date

February 2020

Volume

86

Issue

2

Start / End Page

E140 / E146

Related Subject Headings

  • Spinal Fusion
  • Risk Assessment
  • Prospective Studies
  • Predictive Value of Tests
  • Patient Discharge
  • Neurology & Neurosurgery
  • Middle Aged
  • Male
  • Lumbar Vertebrae
  • Length of Stay