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Estimating the Reference Incremental Cost-Effectiveness Ratio for the Australian Health System

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Abstract

Background

Spending on new healthcare technologies increases net population health when the benefits of a new technology are greater than their opportunity costs—the benefits of the best alternative use of the additional resources required to fund a new technology.

Objective

The objective of this study was to estimate the expected incremental cost per quality-adjusted life-year (QALY) gained of increased government health expenditure as an empirical estimate of the average opportunity costs of decisions to fund new health technologies. The estimated incremental cost-effectiveness ratio (ICER) is proposed as a reference ICER to inform value-based decision making in Australia.

Methods

Empirical top-down approaches were used to estimate the QALY effects of government health expenditure with respect to reduced mortality and morbidity. Instrumental variable two-stage least-squares regression was used to estimate the elasticity of mortality-related QALY losses to a marginal change in government health expenditure. Regression analysis of longitudinal survey data representative of the general population was used to isolate the effects of increased government health expenditure on morbidity-related, QALY gains. Clinical judgement informed the duration of health-related quality-of-life improvement from the annual increase in government health expenditure.

Results

The base-case reference ICER was estimated at AUD28,033 per QALY gained. Parametric uncertainty associated with the estimation of mortality- and morbidity-related QALYs generated a 95% confidence interval AUD20,758–37,667.

Conclusion

Recent public summary documents suggest new technologies with ICERs above AUD40,000 per QALY gained are recommended for public funding. The empirical reference ICER reported in this article suggests more QALYs could be gained if resources were allocated to other forms of health spending.

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References

  1. AIHW. National health expenditure data cube, 1985–86 to 2014–15. Canberra: AIHW; 2016.

    Google Scholar 

  2. Pharmaceutical Benefits Scheme Information Management Section Pharmaceutical Policy Branch. Expenditure and prescriptions twelve months to 30 June 2015.

  3. Pharmaceutical Benefits Scheme Information Management Section Pharmaceutical Policy Branch. Expenditure and prescriptions twelve months to 30 June 2016.

  4. Woods B, Revill P, Sculpher M, Claxton K. Country-level cost-effectiveness thresholds: initial estimates and the need for further research. Value Health. 2016;19:929–35.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Shiroiwa T, Sung Y, Fukuda T, Lang H, Bae S, Tsutani K. International survey on willingness-to-pay (WTP) for one additional QALY gained: what is the threshold of cost effectiveness? Health Econ. 2010;19:422–37.

    Article  PubMed  Google Scholar 

  6. Weinstein M, Zeckhauser R. Critical ratios and efficient allocation. J Public Econ. 1973;2:147–57.

    Article  Google Scholar 

  7. Eichler H-G, Kong SX, Gerth WC, Mavros P, Jönsson B. Use of cost-effectiveness analysis in health-care resource allocation decision-making: how are cost-effectiveness thresholds expected to emerge? Value Health. 2004;7:518–28.

    Article  PubMed  Google Scholar 

  8. Appleby J, Devlin N, Parkin D, Buxton M, Chalkidou K. Searching for cost effectiveness thresholds in the NHS. Health Policy. 2009;91:239–45.

    Article  PubMed  Google Scholar 

  9. O’Mahony JF, Coughlan D. The Irish cost-effectiveness threshold: does it support rational rationing or might it lead to unintended harm to Ireland’s health system? Pharmacoeconomics. 2016;34:5–11.

    Article  PubMed  Google Scholar 

  10. Schaffer SK, Sussex J, Devlin N, Walker A. Local health care expenditure plans and their opportunity costs. Health Policy. 2015;119:1237–44.

    Article  Google Scholar 

  11. Claxton K, Martin S, Soares M, Rice N, Spackman E, Hinde S, et al. Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold. Health Technol Assess. 2015;19:1–503.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Martin S, Rice N, Smith PC. Does health care spending improve health outcomes? Evidence from English programme budgeting data. J Health Econ. 2008;27:826–42.

    Article  PubMed  Google Scholar 

  13. Martin S, Rice N, Smith PC. Comparing costs and outcomes across programmes of health care. Health Econ. 2012;21:316–37.

    Article  PubMed  Google Scholar 

  14. Vallejo-Torres L, García-Lorenzo B, Serrano-Aguilar P. Estimating a cost-effectiveness threshold for the Spanish NHS. Spanish Health Economics Study Group Meeting, Gran Canaria. 2016.

  15. Taylor A, Dal Grande E, Wilson D. The South Australian Health Omnibus Survey 15 years on: has public health benefited. Public Health Bull. 2006;3:30–2.

    Google Scholar 

  16. Australian Bureau of Statistics. Disability, ageing and carers, Australia: summary of findings, 2015. Cat No. 44300 2016.

  17. Watson N, Wooden MP. The HILDA survey: a case study in the design and development of a successful household panel survey. Longit Life Course Stud. 2012;3:369–81.

    Google Scholar 

  18. Walters SJ, Brazier JE. What is the relationship between the minimally important difference and health state utility values? The case of the SF-6D. Health Qual Life Outcomes. 2003;1:4.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Rohde N, Tang KK, Osberg L, Rao P. The effect of economic insecurity on mental health: recent evidence from Australian panel data. Soc Sci Med. 2016;151:250–8.

    Article  PubMed  Google Scholar 

  20. Davidson R, MacKinnon JG. Estimation and inference in econometrics. New York: Oxford University Press; 1993.

    Google Scholar 

  21. Pharmaceutical Benefits Advisory Committee. Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee, Version 4.5; 2015.

  22. Sullivan DF. A single index of mortality and morbidity. HSMHA Health Rep. 1971;86:347.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Clemens S, Begum N, Harper C, Whitty JA, Scuffham PA. A comparison of EQ-5D-3L population norms in Queensland, Australia, estimated using utility value sets from Australia, the UK and USA. Qual Life Res. 2014;23:2375–81.

    Article  PubMed  Google Scholar 

  24. Engel GL. The need for a new medical model: a challenge for biomedicine. Science. 1977;196:129–36.

    Article  CAS  PubMed  Google Scholar 

  25. Havelka M, Despot Lučanin J, Lučanin D. Biopsychosocial model: the integrated approach to health and disease. Coll Antropol. 2009;33:303–10.

    PubMed  Google Scholar 

  26. Dahlgren G, Whitehead M. Policies and strategies to promote social equity in health Background document to WHO — Strategy paper for Europe. Stockholm: Institute for Futures Studies; 1991.

  27. Carter D, Vogan A, Afzali HHA. Governments need better guidance to maximise value for money: the case of Australia’s Pharmaceutical Benefits Advisory Committee. Appl Health Econ Health Policy. 2016;14:401–7.

    Article  PubMed  Google Scholar 

  28. Australian Government Department of Health. Application No. 1428: mechanical thrombectomy for acute ischaemic stroke. November 2016: public summary document.

  29. Australian Government Department of Health. Idelalisib oral tablet, 100 mg, 150 mg Zydelig®, Gilead Sciences Pty Ltd. March 2016: public summary document.

  30. Raftery JP. Paying for costly pharmaceuticals: regulation of new drugs in Australia, England and New Zealand. Med J Aust. 2008;188:26.

    PubMed  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge the cooperation and effort of the data providers (Independent Hospital Pricing Authority, Department of Human Services, Department of Veterans’ Affairs, Australian Coordinating Registry) in the health authorities of the States and Territories and the Australian Government; the Australian Bureau of Statistics for access to the Census of Population and Housing 2011 through Tablebuilder; and the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this article, however, are those of the authors and should not be attributed to either the Department of Social Services or the Melbourne Institute. The authors thank Prof. Mark Sculpher for his conceptual input and Dr. James Lomas for useful comments on the statistical methods. The authors also acknowledge the members of their advisory group; Prof. Rosalie Viney, Prof. Robyn Ward, Prof. Catherine Cole, Prof. Jonathan Craig and Associate Prof. Rachael Moorin for their input to the overall research methodology.

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Authors and Affiliations

Authors

Contributions

Jonathan Karnon, Hossein Haji Ali Afzali and Terence C. Cheng conceptualised the study, all authors contributed to the development of the methods used and approved the analyses. Laura C. Edney wrote the first draft of the manuscript. All authors contributed to subsequent drafts, responses to the peer reviewers and approved the final version.

Corresponding author

Correspondence to Laura Catherine Edney.

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Funding

This study was funded by a National Health and Medical Research Council Project Grant (No. 108-4387).

Conflict of interest

Jonathan Karnon is a member of the Economic Sub-Committee of the Pharmaceutical Benefits Advisory Committee and Hossein Haji Ali Afzali is a member of the Evaluation Sub-Committee of the Medical Services Advisory Committee. Terence C. Cheng and Laura C. Edney have no conflicts of interest directly relevant to the contents of this article.

Ethics approval

Ethics approval was granted by the South Australian Health Human Research Ethics Committee (Ethics Reference No. HREC/14/SAH/159).

Data availability statement

The datasets generated and analysed during the current study are not publicly available owing to strict confidentiality requirements imposed by the data custodians.

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Edney, L.C., Haji Ali Afzali, H., Cheng, T.C. et al. Estimating the Reference Incremental Cost-Effectiveness Ratio for the Australian Health System. PharmacoEconomics 36, 239–252 (2018). https://doi.org/10.1007/s40273-017-0585-2

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