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

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.

journal_name

Neurosurgery

journal_title

Neurosurgery

authors

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

doi

10.1093/neuros/nyz161

subject

Has Abstract

pub_date

2019-11-01 00:00:00

pages

E902-E909

issue

5

eissn

0148-396X

issn

1524-4040

pii

5499121

journal_volume

85

pub_type

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