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Developing an Australian utility value set for MacNew-7D health states

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Abstract

Background

A new preference-based measure (MacNew-7D) has recently been developed to allow condition-specific data to be used to capture the quality of life in health economic evaluations in cardiology; however, a general population value set has not yet been developed. This study developed a population utility value set for the MacNew-7D heart disease-specific instrument.

Methods

The discrete choice experiments (DCE) technique was chosen as the preference-elicitation method. The DCE asked respondents to compare two options and to state their preferences. The survey was conducted using an online panel of respondents, with quota sampling using age groups, sex and jurisdictions to achieve representativeness of the Australian population. The total design consisted of 200 choice sets, of which each respondent answered eight. Additionally, each respondent answered two quality control choice sets. The best-fitting models were selected on the basis of consistency, parsimony, and goodness of fit.

Results

In total, 1903 respondents were included in the analyses. The MacNew-7D utility value set ranged from −0.4456 to 1.000 for health states defined by the classification system. The best-fitting model retained all levels for five dimensions and collapsed one adjacent level for the other two dimensions. Findings were robust to sensitivity analyses related to the inclusion or exclusion of dominancy and repeat tasks.

Conclusion

Findings indicated that the MacNew-7D utility value set is likely suitable for estimating quality-adjusted life years derived from the MacNew heart disease health-related quality–of-life questionnaire. This value set was derived from an Australian population-based sample and may not be generalisable to dissimilar populations.

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Data availability

The datasets are not publicly available as publications are planned but are available from the corresponding author upon reasonable request.

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Acknowledgements

School of Health and Related Research, The University of Sheffield, hosted Dr. Kularatna and facilitated the exchange of ideas between academic groups.

Funding

This study was funded by an Australian Heart Foundation Vanguard grant (2016/101407) and Heart Foundation post-doctoral fellowship for Dr. Kularatna. Centre for Healthcare Transformation, Queensland University of Technology, funded the DCE data collection. SMM is supported by an NHMRC administered fellowship #1161138.

Author information

Authors and Affiliations

  1. Australian Centre for Health Services Innovation, Centre for Healthcare Transformation, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Qld, Australia

    Sanjeewa Kularatna, Sameera Senanayake, Ruvini Hettiarachchi, Katie Fozzard, William Parsonage & Steven M. MacPhail

  2. Monash Business School, Centre for Health Economics, Monash University, Melbourne, VIC, 3145, Australia

    Gang Chen

  3. School of Population Health, Curtin University, Bentley, WA, Australia

    Richard Norman

  4. School of Health and Related Research, University of Sheffield, Sheffield, UK

    Clara Mukuria & Donna Rowen

  5. Centre for Health Economics Research and Evaluation, University of Technology, Sydeny, NSW, Australia

    Brendan Mulhern

  6. Digital Health and Informatics, Metro South Health, Brisbane, Qld, 4102, Australia

    Steven M. MacPhail

Authors
  1. Sanjeewa Kularatna
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  2. Gang Chen
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  3. Richard Norman
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  4. Clara Mukuria
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  5. Donna Rowen
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  10. William Parsonage
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  11. Steven M. MacPhail
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Contributions

SK developed the idea, conducted the analysis and wrote the first draft of the paper. GC, RN, CM, DR and BM contributed to the plan of data collection, DCE design and contributed to the writing of the manuscript. SS, RH and KF did the data collection, assisted the data analysis and contributed to the manuscript. WP and SM assisted in developing the idea, data collection and writing the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sanjeewa Kularatna.

Ethics declarations

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

This study received ethical approval from the Queensland University of Technology Human Research Ethics Committee (Reference No. #2000000573).

Consent to participate

Survey respondents were sourced from an existing Australian online panel administered by Pureprofile (www.pureprofile.com). This panel was drawn from volunteers (aged 18 and above, be able to give consent and understand English) in the general population who were paid a small amount by the panel administrators for completion of the survey.

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Kularatna, S., Chen, G., Norman, R. et al. Developing an Australian utility value set for MacNew-7D health states. Qual Life Res 32, 1151–1163 (2023). https://doi.org/10.1007/s11136-022-03325-6

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