Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-23T14:52:07.743Z Has data issue: false hasContentIssue false
  • English
  • Français

Using information graphics in health technology assessment: Toward a structured approach

Published online by Cambridge University Press:  22 October 2009

Martin Pitt ,
Will Stahl-Timmins ,
Rob Anderson  and
Ken Stein
Martin Pitt
Affiliation:
Peninsula Medical School, University of Exeter, UK
Will Stahl-Timmins
Affiliation:
Peninsula Medical School, University of Exeter, UK
Rob Anderson
Affiliation:
Peninsula Medical School, University of Exeter, UK
Ken Stein
Affiliation:
Peninsula Medical School, University of Exeter, UK
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: This study investigates the use of information graphics to display the outputs of health technology assessment (HTA) in the United Kingdom and proposes a more structured approach founded in an analysis of the decision-making requirements of the key stakeholders.

Methods: A scoping review of HTA reports was conducted to investigate current practice in the use of information graphics in HTA literature. A classification framework using dimensions of report section, graphical type, and originating research center was devised and used for a full content analysis of the graphical figures in the fifty most recent reports produced for the UK National Health Service's HTA process.

Results: Our survey shows that graphical tools are used extensively in HTA reports although less frequently than tables. Use of information graphics varies widely between different report sections and tends to follow conventional lines with little evidence of variance from established practice. The largest variance was found between the quantities of graphics used by different research centers responsible for authoring the reports.

Conclusions: HTA makes extensive use of graphics; however, there is little evidence of a systematic or standardized approach, or of much innovation. Significant potential exists to explore the application of information graphics in this field, but there are many research challenges. A contextually based, structured approach to the design of effective information graphics in HTA is proposed as a basis both to investigate the application of existing graphical tools in HTA, and to explore the considerable scope for innovation.

Keywords

Health technology assessmentInformation graphicsInformation visualizationDecision support
Type
General Essays
Information
International Journal of Technology Assessment in Health Care , Volume 25 , Issue 4 , October 2009 , pp. 555 - 563
Copyright
Copyright © Cambridge University Press 2009

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. Ades, AE, Sculpher, M, Sutton, A, Abrams, K, Cooper, N, Welton, N, Lu, G. Bayesian methods for evidence synthesis in cost-effectiveness analysis. Pharmacoeconomics. 2006;24:1–19.CrossRefGoogle ScholarPubMed
2. Bell, J. The effect of presentation form on the use of information in annual reports. Manage Sci. 1984;30:169–185.CrossRefGoogle Scholar
3. Benbasat, I, Dexter, AS. An experimental evaluation of graphical and color-enhanced information presentation. Manage Sci. 1985;31:1348–1364.CrossRefGoogle Scholar
4. Claxton, K, Sculpher, M, McCabe, C, et al. Probabilistic sensitivity analysis for NICE technology assessment: Not an optional extra. Health Econ. 2000;14:1–20.Google Scholar
5. Drummond, M, Schwartz, JS, Jönsson, B, et al. Key principles for the improved conduct of health technology assessments for resource allocation decisions. Int J Technol Assess Health Care. 2008;24:244–258.CrossRefGoogle ScholarPubMed
6. Elting, L, Martin, CG, Cantor, SB, Rubinstein, EB. Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures. BMJ. 1999;318:1527–1531.CrossRefGoogle ScholarPubMed
7. Fenwick, E, Claxton, K, Sculpher, M. Representing uncertainty: the role of cost-effectiveness acceptability curves. Health Econ. 2001;10:779–787.CrossRefGoogle ScholarPubMed
8. Granados, A, Jonsson, E, Banta, HD, et al. EUR-ASSESS Project Subgroup Report on Dissemination and Impact. Int J Technol Assess Health Care. 1997;13:220–286.CrossRefGoogle ScholarPubMed
9. Information Graphics in HTA. 2008. http://www.pms.ac.uk/infographics/HTAsurvey (accessed November 27, 2007).Google Scholar
10. Irani, P, Ware, C. Diagramming information structures using 3D perceptual primitives. ACM Trans Comput-Human Interact. 2003;10:1–19.CrossRefGoogle Scholar
11. Jarvenpaa, SL. The effect of task demands and graphical format on information processing strategies. Manage Sci. 1989;35:285–303.CrossRefGoogle Scholar
12. Lewis, S, Clarke, M. Forest plots: Trying to see the wood and the trees. BMJ. 2001;322:1479–1480.CrossRefGoogle ScholarPubMed
13. Lurie, NH, Mason, CH. Visual representation: Implications for decision making. J Mark. 2007;71:160–177.CrossRefGoogle Scholar
14. National Institute for Clinical Excellence. Methods for the development of NICE public health guidance consultation draft. London: National Institute for Clinical Excellence; 2008.Google Scholar
15. National Institute for Clinical Excellence. Guide to the methods of technology appraisal 2008. London: National Institute for Clinical Excellence; 2008.Google Scholar
16. Perera, R, Heneghan, C, Yudkin, P. A graphical method for depicting randomised trials of complex interventions. BMJ. 2007;334:127–129.CrossRefGoogle ScholarPubMed
17. Piaggio, G, Elbourne, DR, Altman, DG, Pocock, SJ, Evans, SJW, for the CONSORT Group. Reporting of noninferiority and equivalence randomized trials: An extension of the CONSORT statement. JAMA. 2006;295:1152–1160.CrossRefGoogle ScholarPubMed
18. Pieczkiewicz, DS, Finkelstein, SM, Hertz, MI. Design and evaluation of a web-based interactive visualization system for lung transplant home monitoring data. AMIA Annu Symp Proc. 2007;598–602.Google Scholar
19. Plaisant, C. The challenge of information visualization evaluation. In: Dragecevic, P, Fekete, J, eds. Proceedings of the IEEE Working Conference on Advanced Visual Interfaces. 2004:109–116.CrossRefGoogle Scholar
20. Powsner, SM, Tufte, ER. Graphical summary of patient status. Lancet. 1994;344:386–390.CrossRefGoogle ScholarPubMed
21. Remus, W. A study of graphical and tabular displays and their interaction with environmental complexity. Manage Sci. 1987;33:1200–1204.CrossRefGoogle Scholar
22. Spence, R. Information visualization: Design for interaction. Harlow: Pearson Prentice Hall; 2007.Google Scholar
23. Thomas, JJ, Cook, KA. Illuminating the path: The research and development agenda for visual analytics. Washington, DC: IEEE Computer Society; 2005.Google Scholar
24. Tufte, ER. The visual display of quantitative information. Cheshire, CN: Graphics Press; 2001.Google Scholar
25. Ware, C. Information visualization: Perception for design. San Francisco: Morgan Kaufman; 2004.Google Scholar