Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-20T03:45:20.746Z Has data issue: false hasContentIssue false
  • English
  • Français

COST-UTILITY OF SELF-MANAGED COMPUTER THERAPY FOR PEOPLE WITH APHASIA

Published online by Cambridge University Press:  02 December 2013

Nicholas R. Latimer ,
Simon Dixon  and
Rebecca Palmer
Nicholas R. Latimer
Affiliation:
School of Health and Related Research, University of Sheffield
Simon Dixon
Affiliation:
School of Health and Related Research, University of Sheffield
Rebecca Palmer
Affiliation:
School of Health and Related Research, University of Sheffield
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: The aim of this study was to examine the potential cost-effectiveness of self-managed computer therapy for people with long-standing aphasia post stroke and to estimate the value of further research.

Methods: The incremental cost-effectiveness ratio of computer therapy in addition to usual stimulation compared with usual stimulation alone was considered in people with long-standing aphasia using data from the CACTUS trial. A model-based approach was taken. Where possible the input parameters required for the model were obtained from the CACTUS trial data, a United Kingdom-based pilot randomized controlled trial that recruited thirty-four people with aphasia and randomized them to computer treatment or usual care. Cost-effectiveness was described using an incremental cost-effectiveness ratio (ICER) together with cost-effectiveness acceptability curves. A value of information analysis was undertaken to inform future research priorities.

Results: The intervention had an ICER of £3,058 compared with usual care. The likelihood of the intervention being cost-effective was 75.8 percent at a cost-effectiveness threshold of £20,000 per QALY gained. The expected value of perfect information was £37 million.

Conclusions: Our results suggest that computer therapy for people with long-standing aphasia is likely to represent a cost-effective use of resources. However, our analysis is exploratory given the small size of the trial it is based upon and therefore our results are uncertain. Further research would be of high value, particularly with respect to the quality of life gain achieved by people who respond well to therapy.

Keywords

AphasiaComputer-assisted therapySelf-managementCost-effectiveness analysis
Type
Assessments
Information
International Journal of Technology Assessment in Health Care , Volume 29 , Issue 4 , October 2013 , pp. 402 - 409
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Department of Health. National stroke strategy. London: Department of Health; 2007.Google Scholar
2.Royal College of Speech and Language Therapists. RCSLT resource manual for commissioning and planning services for SLCN: Aphasia. Royal College of Speech and Language Therapists; 2009. http://www.rcslt.org/speech_and_language_therapy/commissioning/aphasia_plus_intro. (accessed May 2, 2012).Google Scholar
3.Kurland, J, Baldwin, K, Tauer, C. Treatment-induced neuroplasticity following intensive naming therapy in a case of chronic Wernicke's aphasia. Aphasiology. 2010;24:737–751.CrossRefGoogle Scholar
4.Meinzer, M, Djundja, D, Barthel, G, Elbert, T, Rockstroh, B. Long term stability of improved language functions in chronic aphasia after constraint-induced aphasia therapy. Stroke. 2005;36:1462–1466.CrossRefGoogle ScholarPubMed
5.Raymer, A, Beeson, P, Holland, A, et al.Translational research in aphasia: From neuroscience to neurorehabilitation. J Speech Lang Hear Res. 2008;51:259–275.CrossRefGoogle ScholarPubMed
6.Katz, R, Wertz, R. The efficacy of computer-provided reading treatment for chronic aphasic adults. J Speech Lang Hear Res. 1997;40:493–1507.CrossRefGoogle ScholarPubMed
7.Lee, J, Kaye, R, Cherney, L. Conversational script performance in adults with non-fluent aphasia: Treatment intensity and aphasia severity. Aphasiology. 2009;23:885–897.CrossRefGoogle Scholar
8.van de Sandt-Koenderman, M. Aphasia rehabilitation and the role of computer technology: Can we keep up with modern times? Int J Speech Lang Pathol. 2011;13:21–27.CrossRefGoogle ScholarPubMed
9.Palmer, R, Enderby, P, Cooper, C, et al.Computer therapy compared with usual care for people with long-standing aphasia post stroke: a pilot randomized controlled trial. Stroke. 2012;43;7:1904–1911.CrossRefGoogle Scholar
10.Swinburn, K, Porter, G, Howard, D. Comprehensive aphasia test. London: Psychology Press; 2004.Google Scholar
11.Druks, J, Masterson, J. An object and action naming battery. London: Psychology Press; 2000.Google Scholar
12.StepbyStep© software. Steps Consultancy Ltd website. http://www.aphasia-software.com (accessed May 2, 2012).Google Scholar
13.Annemans, L, Geneste, B, Jolain, B. Early modelling for assessing health and economic outcomes of drug therapy. Value Health. 2000;3:427–434.CrossRefGoogle ScholarPubMed
14.Hartz, S, John, J. Contribution of economic evaluation to decision making in early phases of product development: A methodological and empirical review. Int J Technol Assess Health Care. 2008;24:465–472.CrossRefGoogle ScholarPubMed
15.National Institute for Health and Clinical Excellence. Guide to the methods of technology appraisal. London: NICE; 2008.Google Scholar
16.Brønnum-Hansen, H, Davidsen, M, Thorvaldsen, P. Long-term survival and causes of death after stroke. Stroke. 2001;32:2131–2136.CrossRefGoogle ScholarPubMed
17.Office for National Statistics. Interim Life tables, United Kingdom, Based on data for the years 2007–2009. http://www.ons.gov.uk/ons/rel/lifetables/interim-life-tables/interim-life-tables/index.html (accessed September 18, 2011).Google Scholar
18.Dolan, P. Modeling valuations for EuroQol health states. Med Care. 1997;35:1095–1108.CrossRefGoogle ScholarPubMed
19.Ara, R, Brazier, JE. Populating an economic model with health state utility values: Moving toward better practice. Value Health. 2010;13:509–518.CrossRefGoogle ScholarPubMed
20.Curtis, L.Unit costs of health and social care 2010. Kent, UK: Personal Social Services Research Unit, University of Kent; 2011.Google Scholar
21.Pharmaceutical Press. British National Formulary 61 – March 2011. London: Pharmaceutical Press; 2011.Google Scholar
22.Department of Health. NHS reference costs 2009–10. London: Department of Health; 2011.Google Scholar
23.Griffin, S, Welton, NJ, Claxton, K. Exploring the research decision space: the expected value of information for sequential research designs. Med Decis Making. 2010;30:155–162.CrossRefGoogle ScholarPubMed
24.Brennan, A, Kharroubi, S, O'Hagan, A, et al.Calculating partial expected value of perfect information via Monte Carlo sampling algorithms. Med Dec Making. 2007;27:448.CrossRefGoogle ScholarPubMed
25.Latimer, N, Lord, J, Grant, RL, et al.Value of information in the osteoarthritis setting: Cost-effectiveness of COX-2 selective inhibitors, traditional NSAAIDs and proton pump inhibitors. Pharmacoeconomics. 2011;29:225–237.CrossRefGoogle ScholarPubMed
Supplementary material: File

Latimer et al. supplementary material

Appendix

Download Latimer et al. supplementary material(File)
File 23 KB