Matched Analysis of the Risk Assessment and Prediction Tool for Discharge Planning Following Single-Level Posterior Lumbar Fusion

Ali S Farooqi; Austin J Borja; Sonia Ajmera; Gregory Glauser; Krista Strouz; Ali K Ozturk; Dmitriy Petrov; H Isaac Chen; Scott D McClintock; Neil R Malhotra

doi:10.1016/j.wneu.2022.03.069

Matched Analysis of the Risk Assessment and Prediction Tool for Discharge Planning Following Single-Level Posterior Lumbar Fusion

World Neurosurg. 2022 Jul:163:e113-e123. doi: 10.1016/j.wneu.2022.03.069. Epub 2022 Mar 18.

Authors

Affiliations

¹ Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
² McKenna EpiLog Fellowship in Population Health at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
³ West Chester University, The West Chester Statistical Institute and Department of Mathematics, West Chester, Pennsylvania, USA.
⁴ Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA; McKenna EpiLog Fellowship in Population Health at the University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: neil.malhotra@pennmedicine.upenn.edu.

PMID: 35314405
DOI: 10.1016/j.wneu.2022.03.069

Abstract

Objectives: Predicting patient needs for extended care after spinal fusion remains challenging. The Risk Assessment and Prediction Tool (RAPT) was externally developed to predict discharge disposition after nonspine orthopedic surgery but remains scarcely used in neurosurgery. The present study is the first to use coarsened exact matching-which incorporated patient characteristics known to independently affect outcomes-for 1:1 matching across a large population of single-level, posterior lumbar fusions, to isolate the predictive value of preoperative RAPT score on postoperative discharge disposition.

Methods: Preoperative RAPT scores were prospectively calculated for 1066 patients undergoing consecutive single-level, posterior-only lumbar fusion within a single, university healthcare system. The primary outcome was discharge disposition. Logistic regression was executed across all patients, evaluating the RAPT score as a continuous variable to predict home discharge. Subsequently, patients were retrospectively clustered into predicted risk cohorts-validated within prior orthopedic joint research-based on the RAPT score (Lowest, Intermediate, and Highest Risk). Coarsened exact matching was performed among predicted risk cohorts, and outcomes were compared between exact-matched groups.

Results: Among all patients, single-point increases in the RAPT score (i.e., decrease in predicted risk) were associated a 75% increased odds of home discharge (P < 0.001). Exact-matched analysis demonstrated increased odds of home discharge by 400% when comparing the Lowest versus Highest Risk cohorts (P = 0.004), by 750% when comparing the Intermediate versus Highest Risk cohorts (P < 0.001), and by 200% when comparing the Lowest versus Intermediate Risk cohorts (P < 0.001).

Conclusions: The RAPT score, captured in preoperative evaluations, can be highly predictive of discharge disposition following single-level, posterior lumbar fusion.

Keywords: Coarsened exact matching; Discharge planning; Lumbar fusion; RAPT; Spine; Value-based care.

MeSH terms

Humans
Lumbar Vertebrae / surgery
Patient Discharge*
Postoperative Complications
Retrospective Studies
Risk Assessment
Risk Factors
Spinal Fusion*