Cost-benefit analysis of intraoperative neuromonitoring for cardiac surgery

Bhav Jain; Faraan O Rahim; Parthasarathy D Thirumala; Michael L McGarvey; Jeffrey Balzer; Raul G Nogueira; David N van der Goes; Adam de Havenon; Ibrahim Sultan; John Ney

doi:10.1016/j.jstrokecerebrovasdis.2024.107576

Cost-benefit analysis of intraoperative neuromonitoring for cardiac surgery

J Stroke Cerebrovasc Dis. 2024 Mar;33(3):107576. doi: 10.1016/j.jstrokecerebrovasdis.2024.107576. Epub 2024 Jan 12.

Authors

Affiliations

¹ Stanford University School of Medicine, Stanford, CA, United States; Massachusetts Institute of Technology, Cambridge, MA, United States.
² Duke University, Durham, NC, United States.
³ Department of Neurological Surgery and Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, United States.
⁴ Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
⁵ Department of Neurological Surgery and Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, United States; UPMC Stroke Institute, Pittsburgh, PA, United States.
⁶ Department of Economics, University of New Mexico, Albuquerque, NM, United States.
⁷ Department of Neurology, Yale University, New Haven, CT, United States.
⁸ Division of Cardiac Surgery, Department of Cardiothoracic Surgery, University of Pittsburgh, Pittsburgh, PA, United States; Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, United States.
⁹ Department of Neurology, Boston University School of Medicine, Boston, MA, United States; West Haven VA Medical Center, West Haven, CT, United States. Electronic address: john.p.ney@gmail.com.

PMID: 38232584
DOI: 10.1016/j.jstrokecerebrovasdis.2024.107576

Abstract

Background: Intraoperative neuromonitoring (IONM) can detect large vessel occlusion (LVO) in real-time during surgery. The aim of this study was to conduct a cost-benefit analysis of utilizing IONM among patients undergoing cardiac surgery.

Methods: A decision-analysis tree with terminal Markov nodes was constructed to model functional outcome, as measured via the modified Rankin Scale (mRS), among 65-year-old patients undergoing cardiac surgery. Our cost-benefit analysis compares the use of IONM (electroencephalography and somatosensory evoked potential) against no IONM in preventing neurological complications from perioperative LVO during cardiac surgery. The study was performed over a lifetime horizon from a societal perspective in the United States. Base case and one-way probabilistic sensitivity analyses were performed.

Results: At a baseline LVO rate of 0.31%, the mean attributable lifetime expenditure for IONM-monitored cardiac surgeries relative to unmonitored cardiac surgeries was $1047.41 (95% CI, $742.12 - $1445.10). At a critical LVO rate of approximately 3.67%, the costs of both monitored and unmonitored cardiac surgeries were the same. Above this critical rate, implementing IONM became cost-saving. On one-way sensitivity analysis, variation in LVO rate from 0% - 10% caused lifetime costs attributable to receiving IONM to range from $1150.47 - $29404.61; variations in IONM cost, percentage of intervenable LVOs, IONM sensitivity, and mechanical thrombectomy cost exerted comparably minimal influence over lifetime costs.

Discussion: We find considerable cost savings favoring the use of IONM under certain parameters corresponding to high-risk patients. This study will provide financial perspective to policymakers, clinicians, and patients alike on the appropriate use of IONM during cardiac surgery.

Keywords: Cardiac surgery; Cost-benefit analysis; Electroencephalography; Health economics; Intraoperative neuromonitoring; Intraoperative stroke; Markov model.

MeSH terms

Aged
Cardiac Surgical Procedures* / adverse effects
Cost-Benefit Analysis
Evoked Potentials, Somatosensory / physiology
Humans
Nervous System Diseases* / etiology
Neurosurgical Procedures / adverse effects
Retrospective Studies