Abstract
Objective
A comparison of the implications of the application of the principles of equity and efficiency as two desirable but competing attributes of the organ allocation system. Efficiency is defined in economic terms as the standard cost per QALY model and equity considerations are included in a model based on public preferences generated from a discrete choice experiment in determining priority for donor liver graft allocation.
Methods
A survey of the general public (n = 303) using a discrete choice experiment was undertaken. The results enabled estimation of the relative weights attached to several key factors which might be used to prioritise patients on the waiting list for liver transplantation. These weights were then used to develop a patient-specific index (PSI) for all patients diagnosed with one of three main chronic liver diseases who had received a liver transplant during an 18-month period at all Department of Health designated liver transplant centres in England and Wales (n = 207). The cost per QALY model comprised net total costs from assessment to 27 months following assessment as the numerator of the ratio. Net survival over the same time period, adjusted for HR-QOL using population values for the EQ-5D descriptive system, formed the denominator.
Results
Priority for liver transplantation differed markedly according to whether patients were ranked according to efficiency (net cost per QALY) or equity considerations (PSI) and the differences in ranks were found to be statistically significant (Wilcoxon signed rank test p < 0.001).
Conclusions
This study emphasises that the priorities of the general public may not accord with those arising from a pure efficiency objective and quantifies the extent of the efficiency loss in terms of lost QALYs and increased net programme costs associated with the incorporation of equity concerns as reflected in public preferences for the allocation of donor livers for transplantation.
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Notes
1A choice between the random effects linear regression model and a fixed effects model was made using the Hausman test, which indicated that the random effects model was superior (chi-squared 7.3, p chi-squared 0.1994). The data were also analysed using a tobit regression model. The results of this analysis were very similar to those of the random effects model.
References
Neuberger J. Developments in liver transplantation. Gut 2004; 53: 759–68
2001 annual report of the US Organ Procurement and Transplantation Network and the Scientific Registry for Transplant Recipients: Transplant Data 1991–2000. Rockville (MD): Department of Health and Human Services, Health Resources and Services Administration, Office of Special Programs, Division of Transplantation; Richmond (VA): United Network for Organ Sharing; Ann Arbor (MI): University Renal Research and Education Association, 2001
National Health Service (NHS) UK Transplant. Transplant activity in the UK 2002–2003. Stoke Gifford: UK Transplant, 2003
Ghent CN. Overall evaluation: screening and assessment of risk factors. Liver Transpl Surg 1996; 2: 2–8
Neuberger J, Adams D, McMaster P, et al. Assessing priorities for allocation of donor liver grafts: survey of public and clinicians. BMJ 1998; 317: 172–5
Ubel P, Loewenstein G. The efficacy and equity of retransplantation: an experimental survey of public attitudes. Health Policy 1995; 34: 145–51
Ubel P, Loewenstein G. Distributing scarce livers: the moral reasoning of the general public. Soc Sci Med 1996; 42: 1049–55
Peters TG. Organ donors and non-donors. Arch Intern Med 1996; 156: 2419–24
Haustein SV, Sellers MT. Factors associated with (un)willingness to be an organ donor: importance of public exposure and knowledge. Clin Transplant 2004; 18: 193–200
Ratcliffe J. Public preferences for the allocation of donor liver grafts for transplantation. Health Econ 2000; 9: 137–48
Longworth L, Young T, Buxton M, et al. Mid term cost effectiveness of the liver transplantation programme of England and Wales for three liver disease groups. Liver Transpl 2003; 9: 1295–307
Dolan P. Modelling valuations for Euroqol health states. Med Care 1997; 35(11): 1095–108
Young T, Longworth L, Ratcliffe J. Survival on the waiting list, post transplant and estimated survival in the absence of transplantation: final report to the Department of Health. Uxbridge: Brunel University, 2000
StataCorp. Stata statistical software: release 8.0. College Station (TX): Stata Corporation, 2003
Great Britain HM Treasury. The green book appraisal and evaluation in central government. London: Her Majesty’s Stationery Office (HMSO), 2003
Neuberger J, Ubel PA. Finding a place for public preferences in liver allocation decisions. Transplantation 2000; 70: 1411–3
Neuberger J, Lucey M. Liver transplantation practice and management. London: BMJ Publishing Group, 1994
Dolan P, Cookson R, Ferguson B. Effect of discussion and deliberation on the public’s views of priority setting in health care: focus group study. BMJ 1999; 318: 916–9
Acknowledgements
We would like to acknowledge the assistance of the cost effectiveness of liver transplantation (CELT) study team in the collection of the cost per QALY data. We thank colleagues in ScHARR, in particular Aki Tsuchiya for helpful comments upon earlier drafts of this paper. The research was financially supported by the Department of Health’s Policy Research Programme. The views expressed and any errors or omissions are the responsibility of the authors alone.
The authors have no conflicts of interest that are directly relevant to the content of this study.
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Ratcliffe, J., Buxton, M., Young, T. et al. Determining priority for liver transplantation. Appl Health Econ Health Policy 4, 249–255 (2005). https://doi.org/10.2165/00148365-200504040-00007
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DOI: https://doi.org/10.2165/00148365-200504040-00007