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BioMed Research International
Volume 2017, Article ID 4543610, 11 pages
https://doi.org/10.1155/2017/4543610
Research Article

Computer-Assessed Preference-Based Quality of Life in Patients with Spinal Cord Injury

1Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
2ICS Maugeri, Nervi, Italy
3ICS Maugeri, Pavia, Italy
4CERGAS, Bocconi University, Milan, Italy

Correspondence should be addressed to Enea Parimbelli; moc.liamg@illebmirap.aene

Received 18 April 2017; Revised 27 June 2017; Accepted 16 July 2017; Published 30 August 2017

Academic Editor: Ashraf S. Gorgey

Copyright © 2017 Enea Parimbelli et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objectives. Our aims were to (1) measure quality of life (QoL) in spinal cord injury (SCI) patients using different methods and analyze differences; (2) enable targeted treatments by identifying variables that affect QoL; and (3) provide decision-makers with useful data for cost-utility analyses in SCI population. Methods. Seventy-one participants were enrolled. The computer-based tool UceWeb was used to elicit QoL in terms of utility coefficients, through the standard gamble, time trade-off, and rating scale methods. The SF36 questionnaire was also administered. Statistical analyses were performed to find predictors of QoL among collected variables. Results. Median values for rating scale, time trade-off, and standard gamble were 0.60, 0.82, and 0.85, respectively. All scales were significantly correlated. Rating scale and SF36 provided similar values, significantly lower than the other methods. Impairment level, male gender, older age, living alone, and higher education were correlated with lower QoL but accounted for only 20% of the variation in utility coefficients. Conclusions. Demographic and clinical variables are useful to predict QoL but do not completely capture utility coefficients variability. Therefore, direct preference-based utility elicitation should be strengthened. Finally, this is the first study providing data that can be used as a reference for cost-utility analyses in the Italian SCI population.