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Reliability and Validity of the Contingent Valuation Method for Estimating Willingness to Pay: A Case of In Vitro Fertilisation

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Abstract

Background

The contingent valuation (CV) method is an alternative approach to typical health economic methods for valuing interventions that have both health and non-health outcomes. Fertility treatment, such as in vitro fertilisation (IVF), fall into this category because of the significant non-health outcomes associated with having children.

Aim

To estimate the general population’s willingness to pay (WTP) for one cycle of IVF and one year of IVF treatment, and to test the reliability and validity of a CV instrument.

Methods

Three online CV surveys were administered to a total of 1870 participants from the Australian general population using an ex-post perspective, that is, they assumed they were infertile and needed IVF to conceive a child. Participants answered questions with starting point WTP bids of 2018 Australian dollars (AU$) 4000 or $10,000 for the cost of one IVF cycle, and treatment success rates of 10%, 20% and 50% per IVF cycle. Tests for reliability, internal construct validity, starting point bias, and external validity were performed.

Results

Depending on the success rate and the starting point WTP bid, the mean WTP for one IVF cycle ranged from $6135 to $13,561, while the mean WTP for one year of IVF treatment varied from $17,080 to $31,006. The CV method was reliable and satisfied internal construct and external criterion validity. However strong starting point bias was evident, rendering the mean WTP values highly imprecise.

Conclusion

The CV method holds promise for eliciting the value of interventions, such as fertility treatment, that have significant health and non-health outcomes. Survey instruments that prevent starting point bias are essential. Comparing the results of CV methods to other value elicitation methods is needed to confirm convergent validity.

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Data Availability Statement

The data are not publicly available due to ongoing studies using the data under licence from Survey Sampling International but may be available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. National Perinatal Epidemiology and Statistics Unit, Centre for Big Data Research in Health and School of Women’s and Children’s Health, University of New South Wales, Sydney, Australia

    Stella Nalukwago Settumba, Willings Botha, Muhammad Zulilhaam Ramli & Georgina Mary Chambers

  2. National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia

    Marian Shanahan

Authors
  1. Stella Nalukwago Settumba
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  2. Marian Shanahan
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  3. Willings Botha
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  4. Muhammad Zulilhaam Ramli
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  5. Georgina Mary Chambers
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Contributions

GMC and MS conceived the study. GMC, MS, MZR, SNS, WB designed the study. MZR, SNS and WB analysed the data. All authors contributed to the drafting and revision of the paper.

Corresponding author

Correspondence to Georgina Mary Chambers.

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Funding

This study was funded by the Australian National Health and Medical Research Council (NHMRC), Project Grant APP1104543.

Conflict of interest

Stella Nalukwago Settumba (SNS), Marian Shanahan (MS), Willings Botha (WB), and Muhammad Zulilhaam Ramli (MZR) do not declare any conflicts of interest. Georgina Mary Chambers (GMC) is employed by University of New South Wales (UNSW) and is Director of the National Perinatal Epidemiology and Statistics Unit (NPESU), UNSW. The Fertility Society of Australia funds the NPESU to manage the Australian and New Zealand Assisted Reproduction Database and conduct national reporting of assisted reproductive technology in Australia and New Zealand.

Ethical Approval

This study was approved by the Human Research Ethics Committee, Health and Social Science Panel, University of New South Wales, Sydney. Participants provided consent to participate in the study.

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Settumba, S.N., Shanahan, M., Botha, W. et al. Reliability and Validity of the Contingent Valuation Method for Estimating Willingness to Pay: A Case of In Vitro Fertilisation. Appl Health Econ Health Policy 17, 103–110 (2019). https://doi.org/10.1007/s40258-018-0433-3

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  • DOI: https://doi.org/10.1007/s40258-018-0433-3

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