Health state descriptions, valuations and individuals’ capacity to walk: a comparative evaluation of preference-based instruments in the context of spinal cord injury
This study explores variation in health state descriptions and valuations derived from preference-based health-related quality of life instruments in the context of spinal cord injury (SCI).
Individuals living with SCI were invited to complete a web-based, cross-sectional survey. The survey comprised questions regarding demographics, SCI classifications and characteristics, secondary health complications and conditions, quality of life and SCI-specific functioning in activities of daily living. Four preference-based health status classification systems were included; Assessment of Quality of Life 8-dimension questionnaire (AQoL-8D), EQ-5D-5L, Health Utilities Index (HUI) and SF-6D (derived from the SF-36v2). In addition to descriptive comparisons of index scores and item/dimension responses, analyses explored dimension-level correlation and absolute agreement (intraclass correlation coefficient (ICC)). Subgroup analyses examined the influence of individuals’ self-reported ability to walk.
Of 609 invitations, 364 (60 %) individuals completed the survey. Across instruments, convergent validity was seen between pain and mental health dimensions, while sizeable variation pertaining to issues of mobility was observed. Mean index scores were 0.248 (HUI-3), 0.492 (EQ-5D-5L), 0.573 (AQoL-8D) and 0.605 (SF-6D). Agreement ranged from ‘slight’ (HUI-3 and SF-6D; ICC = 0.124) to ‘moderate’ (AQoL-8D and SF-6D; ICC = 0.634). Walking status had a markedly different impact on health state valuations across instruments.
Variation in the way that individuals are able to describe their health state across instruments is not unique to SCI. Further research is necessary to understand the significant differences in index scores and, in particular, the implications of framing mobility-related questions in the context of respondents’ ability to walk.
KeywordsHealth-related quality of life Quality-adjusted life years Spinal cord injury Disability Utility measurement Health state valuation
Financial support for this study was provided entirely by a grant from the Rick Hansen Institute (Rick Hansen Institute Translational Research Program, Grant #2012-29: Spinal Cord Injury and Secondary Complications: A Mixed-Methods Evaluation of Preference-Based Instruments). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing and publishing the report. We would also like to thank Health Utilities Inc. for the New Investigator Grant awarded to Dr. David Whitehurst, Dr. Davene Wright for her discussion of an early draft of this paper at the 2015 Vancouver Health Economics Methodology (VanHEM) meeting, Lidia Engel for her assistance with generating Fig. 1, and the two anonymous reviewers for their constructive and comprehensive comments.
Compliance with ethical standards
The study was approved by the University of British Columbia Behavioural Research Ethics Board (H12-01138) and Vancouver Coastal Health Authority (Research Study #V12-01138).
Conflict of interest
The authors declare that they have no conflict of interest.
- 2.Canadian Agency for Drugs and Technologies in Health. (2006). Guidelines for the economic evaluation of health technologies: Canada (3rd ed.). Ottawa, Ontario: Canadian Agency for Drugs and Technologies in Health.Google Scholar
- 3.National Institute for Health and Care Excellence. (2013). Guide to the methods of technology appraisal 2013. London: National Institute for Health and Care Excellence.Google Scholar
- 4.Statistics Canada. (2011). Canadian Community Health Survey (CCHS), 2010 Annual Component surveys. Ottawa, Ontario: Statistics Canada.Google Scholar
- 5.Richardson, J., McKie, J., & Bariola, E. (2014). Multiattribute Utility instruments and their use. In A. J. Culyer (Ed.), Encyclopedia of health economics (pp. 41–57). San Diego, CA: Elsevier.Google Scholar
- 13.The Assessment of Quality of Life (AQoL) instruments. Melbourne (Australia): Centre for Health Economics. Accessed August 31, 2015. http://www.aqol.com.au/index.php/aqolinstruments.
- 18.Richardson, J., Khan, M. A., Iezzi, A., & Maxwell, A. (2015). Comparing and explaining differences in the magnitude, content, and sensitivity of utilities predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB, and AQoL-8D multiattribute utility instruments. Medical Decision Making, 35(3), 276–291.PubMedCrossRefGoogle Scholar
- 26.Engel, L., Bryan, S., Evers, S. M., Dirksen, C. D., Noonan, V. K., & Whitehurst, D. G. (2014). Exploring psychometric properties of the SF-6D, a preference-based health-related quality of life measure, in the context of spinal cord injury. Quality of Life Research, 23(8), 2383–2393.PubMedCrossRefGoogle Scholar
- 30.Seiber WJ, Groessl EJ, David KM, Ganiats TG, Kaplan RM (2008) Quality of well being self-administered (QWB-SA) scale user’s manual. San Diego, CA: Health Services Research Center. Accessed August 31, 2015. https://hoap.ucsd.edu/qwb-info/QWB-Manual.pdf.
- 31.Ware, J. E., Kosinski, M., Bjorner, J. B., Turner-Bowker, D. M., Gandek, B., & Maruish, M. E. (2007). User’s manual for the SF-36v2TM health survey (2nd ed.). Lincoln, RI: QualityMetric.Google Scholar
- 32.Whitehurst, D. G., Suryaprakash, N., Engel, L., Mittmann, N., Noonan, V. K., Dvorak, M. F., et al. (2014). Perceptions of individuals living with spinal cord injury toward preference-based quality of life instruments: A qualitative exploration. Health Qual Life Outcomes, 12, 50.PubMedPubMedCentralCrossRefGoogle Scholar
- 33.Noreau, L., Noonan, V. K., Cobb, J., Leblond, J., & Dumont, F. S. (2014). Spinal cord injury community survey: A national, comprehensive study to portray the lives of Canadians with spinal cord injury. Topics in Spinal Cord Injury Rehabilitation, 20(4), 249–264.PubMedPubMedCentralCrossRefGoogle Scholar
- 34.Brazier, J. E., Rowen, D., & Hanmer, J. (2008). Revised SF-6D scoring programmes: A summary of improvements. PRO Newsletter, 40, 14–15.Google Scholar
- 42.Joore, M., Brunenberg, D., Nelemans, P., Wouters, E., Kuijpers, P., Honig, A., et al. (2010). The impact of differences in EQ-5D and SF-6D utility scores on the acceptability of cost-utility ratios: Results across five trial-based cost-utility studies. Value Health, 13(2), 222–229.PubMedCrossRefGoogle Scholar
- 43.Mihalopoulos, C., Chen, G., Iezzi, A., Khan, M. A., & Richardson, J. (2014). Assessing outcomes for cost-utility analysis in depression: comparison of five multi-attribute utility instruments with two depression-specific outcome measures. British Journal of Psychiatry, 205(5), 390–397.PubMedCrossRefGoogle Scholar