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A cost utility analysis of mammography screening in Australia

Author

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  • Hall, Jane
  • Gerard, Karen
  • Salkeld, Glenn
  • Richardson, Jeff

Abstract

Cost utility analysis is the preferred method of analysis when quality of life instead is an important outcome of the project being appraised. However, there are several methodological issues to be resolved in implementing cost utility analysis, including whether to use generalised measures or direct disease specific outcome assessment, the choice of measurement technique, and the combination of different health states. Screening for breast cancer meets this criterion as mammographic screening has been shown to reduce mortality; and it is said that earlier treatment frequently results in less radical surgery so that women are offered the additional benefit of improved quality of life. Australia, like many other countries, has been debating whether to introduce a national mammographic screening programme. This paper presents the results of a cost utility analysis of breast cancer screening using an approach to measuring outcome, Healthy Year Equivalents, developed within this study to resolve these problems. Descriptions of breast cancer quality of life were developed from surveys of women with breast cancer, health professionals and the published literature. The time trade off technique was then used to derive values for breast cancer treatment outcomes in a survey of women in Sydney, Australia. Respondents included women with breast cancer and women who had not had breast cancer. Testing of (i) the effect of prognosis on the value attached to a health scenario; and (ii) whether the value attached to a health scenario remains constant over time has been reported. The estimate of the net costs of screening are reported. The costs of breast cancer screening include the screening programme itself, the further investigations and the subsequent treatment of breast cancer cases. Breast cancer is treated in the absence of screening, many commentators claim earlier treatment is costly but there is little evidence. Therefore we have investigated current patterns of breast cancer treatment, current use of investigations for women presenting with symptoms and current use of covert mammography screening. The results are extrapolated to obtain estimates of the costs and outcomes presented as cost per healthy year equivalent. This analysis produces important information for the Australian policy debate over mammography. It also contributes to the development of cost utility analysis and the approach developed here can be applied more generally.

Suggested Citation

  • Hall, Jane & Gerard, Karen & Salkeld, Glenn & Richardson, Jeff, 1992. "A cost utility analysis of mammography screening in Australia," Social Science & Medicine, Elsevier, vol. 34(9), pages 993-1004, May.
  • Handle: RePEc:eee:socmed:v:34:y:1992:i:9:p:993-1004
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    Cited by:

    1. Jonathan R. Treadwell, 1998. "Tests of Preferential Independence in the QALY Model," Medical Decision Making, , vol. 18(4), pages 418-428, October.
    2. Attema, Arthur E. & Brouwer, Werner B.F., 2012. "A test of independence of discounting from quality of life," Journal of Health Economics, Elsevier, vol. 31(1), pages 22-34.
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    4. Carmen Herrero Blanco, 2001. "Individual Evidence Of Independence In Health Profiles Evaluation," Working Papers. Serie AD 2001-20, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    5. Irmgard C. Schiller-Frühwirth & Beate Jahn & Marjan Arvandi & Uwe Siebert, 2017. "Cost-Effectiveness Models in Breast Cancer Screening in the General Population: A Systematic Review," Applied Health Economics and Health Policy, Springer, vol. 15(3), pages 333-351, June.
    6. Cam Donaldson & Stephen Birch & Amiram Gafni, 2002. "The distribution problem in economic evaluation: income and the valuation of costs and consequences of health care programmes," Health Economics, John Wiley & Sons, Ltd., vol. 11(1), pages 55-70, January.
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    8. Bromley, Hannah L. & Petrie, Dennis & Mann, G.Bruce & Nickson, Carolyn & Rea, Daniel & Roberts, Tracy E., 2019. "Valuing the health states associated with breast cancer screening programmes: A systematic review of economic measures," Social Science & Medicine, Elsevier, vol. 228(C), pages 142-154.
    9. John Cairns & Phil Shackley, 1993. "Sometimes sensitive, seldom specific: A review of the economics of screening," Health Economics, John Wiley & Sons, Ltd., vol. 2(1), pages 43-53, April.
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    13. John Brazier & Mark Deverill, 1999. "A checklist for judging preference‐based measures of health related quality of life: Learning from psychometrics," Health Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 41-51, February.
    14. Richard Milne & Kathy Heaton-Brown & Paul Hansen & David Thomas & Vernon Harvey & Alison Cubitt, 2006. "Quality-of-Life Valuations of Advanced Breast Cancer by New Zealand Women," PharmacoEconomics, Springer, vol. 24(3), pages 281-292, March.
    15. Ariel Beresniak & Antonieta Medina-Lara & Jean Auray & Alain Wever & Jean-Claude Praet & Rosanna Tarricone & Aleksandra Torbica & Danielle Dupont & Michel Lamure & Gerard Duru, 2015. "Validation of the Underlying Assumptions of the Quality-Adjusted Life-Years Outcome: Results from the ECHOUTCOME European Project," PharmacoEconomics, Springer, vol. 33(1), pages 61-69, January.
    16. Tammy O. Tengs & Eric P. Winer & Susan Paddock & Omar Aguilar-Chavez & Donald A. Berry, 1998. "Testing for the BRCA1 and BRCA2 Breast-Ovarian Cancer Susceptibility Genes," Medical Decision Making, , vol. 18(4), pages 365-375, October.
    17. Angela Robinson & Anne Spencer, 2006. "Exploring challenges to TTO utilities: valuing states worse than dead," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 393-402, April.
    18. Szeto, Kam Leong & Devlin, Nancy J., 1996. "The cost-effectiveness of mammography screening: evidence from a microsimulation model for New Zealand," Health Policy, Elsevier, vol. 38(2), pages 101-115, November.
    19. Karen Gerard & Katharine Johnston & Jackie Brown, 1999. "The role of a pre‐scored multi‐attribute health classification measure in validating condition‐specific health state descriptions," Health Economics, John Wiley & Sons, Ltd., vol. 8(8), pages 685-699, December.
    20. Peep F. M. Stalmeier & Jan J. V. Busschbach & Leida M. Lamers & Paul F. M. Krabbe, 2005. "The gap effect: discontinuities of preferences around dead," Health Economics, John Wiley & Sons, Ltd., vol. 14(7), pages 679-685, July.
    21. Peasgood, T & Ward, S & Brazier, J, 2010. "A review and meta-analysis of health state utility values in breast cancer," MPRA Paper 29950, University Library of Munich, Germany.
    22. G. Ardine De Wit & Jan J.V. Busschbach & Frank Th. De Charro, 2000. "Sensitivity and perspective in the valuation of health status: whose values count?," Health Economics, John Wiley & Sons, Ltd., vol. 9(2), pages 109-126, March.
    23. Amiram Gafni, 1995. "Time in Health," Medical Decision Making, , vol. 15(1), pages 31-37, February.
    24. José Mª Abellán & José Luis Pinto & Ildefonso Méndez & Xabier Badía, 2004. "A test of the predictive validity of non-linear QALY models using time trade-off utilities," Economics Working Papers 741, Department of Economics and Business, Universitat Pompeu Fabra.

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