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Using Eye-Tracking Technology with Older People in Memory Clinics to Investigate the Impact of Mild Cognitive Impairment on Choices for EQ-5D-5L Health States Preferences

Author

Listed:
  • Kaiying Wang

    (Flinders University)

  • Chris Barr

    (Flinders University)

  • Richard Norman

    (Curtin University)

  • Stacey George

    (Flinders University)

  • Craig Whitehead

    (Flinders University)

  • Julie Ratcliffe

    (Flinders University)

Abstract

Background Population ageing is a phenomenon taking place in almost every global region. Current estimates indicate that 10–20% of older people in developed countries have mild cognitive impairment (MCI), with these percentages predicted to rise markedly by 2050. Objective Our objective was to apply eye-tracking technology to investigate the information processes adopted by older people with and without MCI in determining preferences for health states in the five-level EuroQol-5 Dimensions (EQ-5D-5L) instrument. Methods Older people (aged ≥ 65 years; including both patients and family carers) attending outpatient memory clinics in Southern Adelaide between July 2017 and June 2018, competent to read and converse in English and with a Mini-Mental State Examination (MMSE) cognition score of ≥ 19 were invited to participate. In total, 52 people met the inclusion criteria, of whom 20 (38%) provided informed consent and fully participated. Participants were categorised into two subgroups (each n = 10) for comparison based upon established MMSE cognition thresholds (19–23, lower MMSE indicative of MCI; ≥ 24, higher MMSE indicative of good cognition). A discrete-choice experiment (DCE) comprising a series of pairwise choices between alternative EQ-5D-5L health states of varying survival duration with differential levels of task complexity (approximated by the degree of attribute level overlap in each choice), was administered as a face-to-face interview with the participant wearing an eye-tracking device. Results Attribute non-attendance (ANA) was higher for the lower MMSE subgroup than for the higher MMSE subgroup, although these differences were generally not statistically significant. ANA remained relatively low and consistent for participants with good cognition regardless of task complexity. In contrast, ANA increased notably in participants exhibiting MCI, increasing from 10% on average per participant in the lower MMSE subgroup with five attribute level overlap to 23% on average per participant in the lower MMSE subgroup with zero attribute level overlap. Conclusions This exploratory study provided important insights into the information processes adopted by older people with varying levels of cognitive functioning when choosing between alternative EQ-5D-5L health states of varying survival duration and specifically the relationships between cognitive capacity, task complexity and the extent of ANA. Recent advances in econometric modelling of health state valuation data have demonstrated the added value of capturing ANA information as this can be accounted for in the DCE data analysis, thereby improving the precision of model estimates. Eye-tracking technology can usefully inform the design, conduct and econometric modelling of DCEs, driving the inclusion of this rapidly growing population traditionally excluded from preference-elicitation studies of this nature.

Suggested Citation

  • Kaiying Wang & Chris Barr & Richard Norman & Stacey George & Craig Whitehead & Julie Ratcliffe, 2021. "Using Eye-Tracking Technology with Older People in Memory Clinics to Investigate the Impact of Mild Cognitive Impairment on Choices for EQ-5D-5L Health States Preferences," Applied Health Economics and Health Policy, Springer, vol. 19(1), pages 111-121, January.
  • Handle: RePEc:spr:aphecp:v:19:y:2021:i:1:d:10.1007_s40258-020-00588-3
    DOI: 10.1007/s40258-020-00588-3
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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. Uggeldahl, Kennet & Jacobsen, Catrine & Lundhede, Thomas Hedemark & Olsen, Søren Bøye, 2016. "Choice certainty in Discrete Choice Experiments: Will eye tracking provide useful measures?," Journal of choice modelling, Elsevier, vol. 20(C), pages 35-48.
    3. Seda Erdem & Danny Campbell & Arne Risa Hole, 2015. "Accounting for Attribute‐Level Non‐Attendance in a Health Choice Experiment: Does it Matter?," Health Economics, John Wiley & Sons, Ltd., vol. 24(7), pages 773-789, July.
    4. Richard Norman & Paula Cronin & Rosalie Viney, 2013. "A Pilot Discrete Choice Experiment to Explore Preferences for EQ-5D-5L Health States," Applied Health Economics and Health Policy, Springer, vol. 11(3), pages 287-298, June.
    5. Dan Rigby & Caroline Vass & Katherine Payne, 2020. "Opening the ‘Black Box’: An Overview of Methods to Investigate the Decision-Making Process in Choice-Based Surveys," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 13(1), pages 31-41, February.
    6. John Cairns & Marjon van der Pol & Andrew Lloyd, 2002. "Decision making heuristics and the elicitation of preferences: being fast and frugal about the future," Health Economics, John Wiley & Sons, Ltd., vol. 11(7), pages 655-658, October.
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    1. Chris Sampson’s journal round-up for 1st February 2021
      by Chris Sampson in The Academic Health Economists' Blog on 2021-02-01 12:00:03

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    1. Haode Wang & Donna L. Rowen & John E. Brazier & Litian Jiang, 2023. "Discrete Choice Experiments in Health State Valuation: A Systematic Review of Progress and New Trends," Applied Health Economics and Health Policy, Springer, vol. 21(3), pages 405-418, May.

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