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Consumer preference to utilise a mobile health app: A stated preference experiment

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  • David Lim
  • Richard Norman
  • Suzanne Robinson

Abstract

Background: One prominent barrier faced by healthcare consumers when accessing health services is a common requirement to complete repetitive, inefficient paper-based documentation at multiple registration sites. Digital innovation has a potential role to reduce the burden in this area, through the collection and sharing of data between healthcare providers. While there is growing evidence for digital innovations to potentially improve the effectiveness and efficiency of health systems, there is less information on the willingness of healthcare consumers to embrace and utilise technology to provide data. Aim: The study aims to improve understanding of consumers’ preference for utilising a digital health administration mobile app. Methods: The online study used a stated preference experiment design to explore aspects of consumers’ preference for a mobile health administration app and its impact on the likelihood of using the app. The survey was answered by a representative sample (by age and gender) of Australian adults, and sociodemographic factors were also recorded for analysis. Each participant answered eight choice sets in which a hypothetical app (defined by a set of dimensions and levels) was presented and the respondent was asked if they would be willing to provide data using that app. Analysis was conducted using bivariate logistic regression. Results: For the average respondent, the two most important dimensions were the time it took to register on the app and the electronic governance arrangements around their personal information. Willingness to use any app was found to differ based on respondent characteristics: people with higher education, and women, were relatively more willing to utilise the mobile health app. Conclusion: This study investigated consumers’ willingness to utilise a digital health administration mobile app. The identification of key characteristics of more acceptable apps provide valuable insight and recommendations for developers of similar digital health administration technologies. This would increase the likelihood of achieving successful acceptance and utilisation by consumers. The results from this study provide evidence-based recommendations for future research and policy development, planning and implementation of digital health administration mobile applications in Australia.

Suggested Citation

  • David Lim & Richard Norman & Suzanne Robinson, 2020. "Consumer preference to utilise a mobile health app: A stated preference experiment," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-12, February.
  • Handle: RePEc:plo:pone00:0229546
    DOI: 10.1371/journal.pone.0229546
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    References listed on IDEAS

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    1. Vikas Soekhai & Esther W. Bekker-Grob & Alan R. Ellis & Caroline M. Vass, 2019. "Discrete Choice Experiments in Health Economics: Past, Present and Future," PharmacoEconomics, Springer, vol. 37(2), pages 201-226, February.
    2. Esther W. de Bekker‐Grob & Mandy Ryan & Karen Gerard, 2012. "Discrete choice experiments in health economics: a review of the literature," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 145-172, February.
    3. Julia A Dalton & Dianne Rodger & Michael Wilmore & Sal Humphreys & Andrew Skuse & Claire T Roberts & Vicki L Clifton, 2018. "The Health-e Babies App for antenatal education: Feasibility for socially disadvantaged women," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-18, May.
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