Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T07:04:49.311Z Has data issue: false hasContentIssue false
  • English
  • Français

Economic evaluation of screening for open-angle glaucoma

Published online by Cambridge University Press:  09 April 2008

Rodolfo A. Hernández ,
Jennifer M. Burr  and
Luke D. Vale
Rodolfo A. Hernández
Affiliation:
University of Aberdeen
Jennifer M. Burr
Affiliation:
University of Aberdeen
Luke D. Vale
Affiliation:
University of Aberdeen
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: The aim of this study was to assess the cost-effectiveness of screening for open-angle glaucoma (OAG) in the United Kingdom, given that OAG is an important cause of blindness worldwide.

Methods: A Markov model was developed to estimate lifetime costs and benefits of a cohort of patients facing, alternatively, screening or current opportunistic case finding strategies. Strategies, varying in how screening would be organized (e.g., invitation for assessment by a glaucoma-trained optometrist [GO] or for simple test assessment by a technician) were developed, and allowed for the progression of OAG and treatment effects. Data inputs were obtained from systematic reviews. Deterministic and probabilistic sensitivity analyses were performed.

Results: Screening was more likely to be cost-effective as prevalence increased, for 40 year olds compared with 60 or 75 year olds, when the re-screening interval was greater (10 years), and for the technician strategy compared with the GO strategy. For each age cohort and at prevalence levels of ≤1 percent, the likelihood that either screening strategy would be more cost-effective than current practice was small. For those 40 years of age, “technician screening” compared with current practice has an incremental cost-effectiveness ratio (ICER) that society might be willing to pay when prevalence is 6 percent to 10 percent and at over 10 percent for 60 year olds. In the United Kingdom, the age specific prevalence of OAG is much lower. Screening by GO, at any age or prevalence level, was not associated with an ICER < £30,000.

Conclusions: Population screening for OAG is unlikely to be cost-effective but could be for specific subgroups at higher risk.

Keywords

Economic evaluationGlaucomaScreeningCost-effectiveness analysisCost-utility analysis
Type
GENERAL ESSAYS
Information
International Journal of Technology Assessment in Health Care , Volume 24 , Issue 2 , April 2008 , pp. 203 - 211
Copyright
Copyright © Cambridge University Press 2008

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. Organisation of services for diabetic retinopathy screening. HTA Report 1. Glasgow: NHS Quality Improvement Scotland (Health Technology Board for Scotland [HTBS]); 2002.Google Scholar
2. General ophthalmic services. Primary Care Circular PCA 2005(0)03 [document on the Internet]. Scottish Executive; 2005. Accessed October 2007.Google Scholar
3. General ophthalmic services. Primary Care Circular 2005 PCA(0)1 [document on the Internet]. Scottish Executive; 2005. Accessed October 2007.Google Scholar
4. British Household Panel Survey (BHPS) [website on the Internet]. Institute for Social & Economic Research, University of Essex; 2006. Accessed October 2007.Google Scholar
5. General Ophthalmic Services [webpage on the Internet]. ISD Scotland; 2007. Accessed October 2007.Google Scholar
6. Guide to the methods of technology appraisal [document on the Internet]. London: National Institute for Clinical Excellence; 2004. Accessed October 2007]. Available from: URL: http://www.nice.org.uk/page.aspx?o=201974.Google Scholar
7. Azuara-Blanco, A, Burr, J, Thomas, R, MacLennan, G, McPherson, S. The accuracy of accredited glaucoma optometrists in the diagnosis and treatment recommendation for glaucoma. Br J Ophthalmol. 2007;91:1639–1643.CrossRefGoogle ScholarPubMed
8. Briggs, AH, Sculpher, MJ. An introduction to Markov modelling for economic evaluation. Pharmacoeconomics. 1998;13:397–409.CrossRefGoogle ScholarPubMed
9. Briggs, A, Sculpher, M, Claxton, K. Decision modelling for health economic evaluation. Oxford: Oxford University Press; 2006.CrossRefGoogle Scholar
10. Burr, JM, Kilonzo, M, Vale, L, Ryan, M. Developing a preference-based Glaucoma Utility Index using a discrete choice experiment. Optom Vis Sci. 2007;84:797–808.CrossRefGoogle ScholarPubMed
11. Burr, JM, Mowatt, G, Hernandez, R, et al. . The clinical effectiveness and cost-effectiveness of screening for open angle glaucoma: A systematic review and economic evaluation. Health Technol Assess. 2007;11:iii–iv, ix-x, 1-190.CrossRefGoogle ScholarPubMed
12. Crabb, DP, Fitzke, FW, Hitchings, RA, Viswanathan, AC. A practical approach to measuring the visual field component of fitness to drive. Br J Ophthalmol. 2004;88:1191–1196.CrossRefGoogle ScholarPubMed
13. Gooder, P. Development and Evaluation Committee (DEC) Report No 38. Screening for glaucoma. Bristol: Research & Development Directorate South and West; 1995.Google Scholar
14. Gupta, V, Srinivasan, G, Mei, SS, et al. . Utility values among glaucoma patients: An impact on the quality of life. Br J Ophthalmol. 2005;89:1241–1244.CrossRefGoogle ScholarPubMed
15. Hernandez, R, Rabindranath, K, Fraser, C, et al. . Screening for open angle glaucoma: Systematic review of cost-effectiveness studies. J Glaucoma. In press.Google Scholar
16. Hollows, FC, Graham, PA. Intra-ocular pressure glaucoma and glaucoma suspects in a defined population. Br J Ophthalmol. 1966;50:570–586.CrossRefGoogle Scholar
17. Iversen, GR. Bayesian statistical inference. Thousand Oaks, CA: Sage Publications; 1984.CrossRefGoogle Scholar
18. Lee, AJ, Wang, JJ, Rochtchina, E, et al. . Patterns of glaucomatous visual field defects in an older population: The Blue Mountains Eye Study. Clin Experiment Ophthalmol. 2003;31:331–335.CrossRefGoogle Scholar
19. Maier, PC, Funk, J, Schwarzer, G, Antes, G, Falck-Ytter, YT. Treatment of ocular hypertension and open angle glaucoma: Meta-analysis of randomised controlled trials. BMJ. 2005;331:134–136.CrossRefGoogle ScholarPubMed
20. Meads, C, Hyde, C. How much is the cost of visual impairment: Caveat emptor. Pharmacoeconomics. 2006;24:207–209.CrossRefGoogle ScholarPubMed
21. Philips, Z, Ginnelly, L, Sculpher, M, Claxton, K, Golder, S, Riemsma, R, Woolacoot, N, Glanville, J. Review of guidelines for good practice in decision analytic modelling in health technology assessment. Health Technol Assess 2004;8 (36).CrossRefGoogle ScholarPubMed
22. Quigley, HA, Broman, AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90:262–267.CrossRefGoogle ScholarPubMed
23. Sommer, A, Tielsch, JM, Katz, J, et al. . Relationship between intraocular pressure and primary open angle glaucoma among white and black Americans: The Baltimore Eye Survey. Arch Ophthalmol. 1991;109:1090–1095.CrossRefGoogle ScholarPubMed
24. Sonnenberg, FA, Beck, JR. Markov models in medical decision making: A practical guide. Med Decis Making. 1993;13:322–336.CrossRefGoogle ScholarPubMed
25. Tielsch, JM, Katz, J, Singh, K, et al. . A population-based evaluation of glaucoma screening: The Baltimore Eye Survey. Am J Epidemiol. 1991;134:1102–1110.CrossRefGoogle ScholarPubMed
26. Traverso, CE, Walt, JG, Kelly, SP, et al. . Direct costs of glaucoma and severity of the disease: A multinational long term study of resource utilisation in Europe. Br J Ophthalmol. 2005;89:1245–1249.CrossRefGoogle ScholarPubMed
27. Tuck, MW. Referrals for suspected glaucoma: An International Glaucoma Association survey. Ophthalmic Physiol Opt. 1991;11:22–26.CrossRefGoogle ScholarPubMed
28. Vaahtoranta-Lehtonen, H, Tuulonen, A, Aronen, P, et al. . Cost effectiveness and cost utility of an organized screening programme for glaucoma. Acta Ophthalmol Scand. 2007;85:508–518.CrossRefGoogle ScholarPubMed
29. Wolfs, RC, Ramrattan, RS, Hofman, A, de Jong, PT. Cup-to-disc ratio: Ophthalmoscopy versus automated measurement in a general population: The Rotterdam Study. Ophthalmology. 1999;106:1597–1601.CrossRefGoogle Scholar
Supplementary material: File

Hernandez supplementary material

Supplementary tables

Download Hernandez supplementary material(File)
File 50.2 KB
Supplementary material: File

Hernandez supplementary material

Supplementary figures

Download Hernandez supplementary material(File)
File 50.7 KB
Supplementary material: File

Hernandez supplementary material

Supplementary tables

Download Hernandez supplementary material(File)
File 114.7 KB