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Author Notes:

Daniel Pinto, PT, PhD (corresponding author: 414.288.4495 phone, d.pinto@marquette.edu), Assistant Professor, Department of Physical Therapy, Marquette University.

DP, AJ, AWH conceived of the study, JB, SHC, SC, EFF, CF, CT, CKM, HT, AJ provided site specific data on utilization and costs, DP and MG performed all analyses and data interpretation, DP wrote initial draft of manuscript, All authors provided critical feedback on the manuscript. All authors read and provided approval of the final manuscript.

The authors declare that they have no competing interests.


Research Funding:

The National Institute on Disability, Independent Living, and Rehabilitation Research provided funding through the Midwest Regional SCI Model System (90SI5009), the Rocky Mountain Regional Spinal Injury System (90SI5015), the Southeastern Regional Spinal Cord Injury Model System at Shepherd Center (90SI5016), and the Texas Model Spinal Cord Injury System at TIRR Memorial Hermann (90SI5027).


  • Science & Technology
  • Technology
  • Life Sciences & Biomedicine
  • Engineering, Biomedical
  • Neurosciences
  • Rehabilitation
  • Engineering
  • Neurosciences & Neurology
  • Economic
  • Budget impact analysis
  • Spinal cord injury
  • Robotics
  • Locomotor training
  • GAIT

Budget impact analysis of robotic exoskeleton use for locomotor training following spinal cord injury in four SCI Model Systems

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Journal Title:



Volume 17, Number 1


, Pages 4-4

Type of Work:

Article | Final Publisher PDF


Background: We know little about the budget impact of integrating robotic exoskeleton over-ground training into therapy services for locomotor training. The purpose of this study was to estimate the budget impact of adding robotic exoskeleton over-ground training to existing locomotor training strategies in the rehabilitation of people with spinal cord injury. Methods: A Budget Impact Analysis (BIA) was conducted using data provided by four Spinal Cord Injury (SCI) Model Systems rehabilitation hospitals. Hospitals provided estimates of therapy utilization and costs about people with spinal cord injury who participated in locomotor training in the calendar year 2017. Interventions were standard of care walking training including body-weight supported treadmill training, overground training, stationary robotic systems (i.e., treadmill-based robotic gait orthoses), and overground robotic exoskeleton training. The main outcome measures included device costs, training costs for personnel to use the device, human capital costs of locomotor training, device demand, and the number of training sessions per person with SCI. Results: Robotic exoskeletons for over-ground training decreased hospital costs associated with delivering locomotor training in the base case analysis. This analysis assumed no difference in intervention effectiveness across locomotor training strategies. Providing robotic exoskeleton overground training for 10% of locomotor training sessions over the course of the year (range 226-397 sessions) results in decreased annual locomotor training costs (i.e., net savings) between $1114 to $4784 per annum. The base case shows small savings that are sensitive to parameters of the BIA model which were tested in one-way sensitivity analyses, scenarios analyses, and probability sensitivity analyses. The base case scenario was more sensitive to clinical utilization parameters (e.g., how often devices sit idle and the substitution of high cost training) than device-specific parameters (e.g., robotic exoskeleton device cost or device life). Probabilistic sensitivity analysis simultaneously considered human capital cost, device cost, and locomotor device substitution. With probabilistic sensitivity analysis, the introduction of a robotic exoskeleton only remained cost saving for one facility. Conclusions: Providing robotic exoskeleton for over-ground training was associated with lower costs for the locomotor training of people with SCI in the base case analyses. The analysis was sensitive to parameter assumptions.

Copyright information:

© 2020 The Author(s).

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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