Evaluation of the Risk Assessment and Prediction Tool for Postoperative Disposition Needs After Cervical Spine Surgery


Journal Article

Abstract BACKGROUND Bundled care payment models are becoming more prevalent in neurosurgery. Such systems place the cost of postsurgical facilities in the hands of the discharging health system. Opportunity exists to leverage prediction tools for discharge disposition by identifying patients who will not benefit from prolonged hospitalization and facilitating discharge to post-acute care facilities. OBJECTIVE To validate the use of the Risk Assessment and Predictive Tool (RAPT) along with other clinical variables to predict discharge disposition in a cervical spine surgery population. METHODS Patients undergoing cervical spine surgery at our institution from June 2016 to February 2017 and over 50 yr old had demographic, surgical, and RAPT variables collected. Multivariable regression analyzed each variable's ability to predict discharge disposition. Backward selection was used to create a binomial model to predict discharge disposition. RESULTS A total of 263 patients were included in the study. Lower RAPT score, RAPT walk subcomponent, older age, and a posterior approach predicted discharge to a post-acute care facility compared to home. Lower RAPT also predicted an increased risk of readmission. RAPT score combined with age increased the predictive capability of discharge disposition to home vs skilled nursing facility or acute rehabilitation compared to RAPT alone (P < .001). CONCLUSION RAPT score combined with age is a useful tool in the cervical spine surgery population to predict postdischarge needs. This tool may be used to start early discharge planning in patients who are predicted to require post-acute care facilities. Such strategies may reduce postoperative utilization of inpatient resources.

Full Text

Duke Authors

Cited Authors

  • Berger, I; Piazza, M; Sharma, N; Glauser, G; Osiemo, B; McClintock, SD; Lee, JYK; Schuster, JM; Ali, Z; Malhotra, NR

Published Date

  • November 1, 2019

Published In

Volume / Issue

  • 85 / 5

Start / End Page

  • E902 - E909

Published By

Electronic International Standard Serial Number (EISSN)

  • 1524-4040

International Standard Serial Number (ISSN)

  • 0148-396X

Digital Object Identifier (DOI)

  • 10.1093/neuros/nyz161


  • en