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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

  • Original Research Article
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Applied Health Economics and Health Policy Aims and scope Submit manuscript

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.

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Data Availability

The dataset and software code underpinning this research are available upon request from the study authors.

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Author information

Authors and Affiliations

  1. College of Medicine and Public Health, Flinders University, Bedford Park, Adelaide, SA, 5042, Australia

    Kaiying Wang & Craig Whitehead

  2. College of Nursing and Health Sciences, Flinders University, Bedford Park, Adelaide, SA, 5042, Australia

    Chris Barr, Stacey George & Julie Ratcliffe

  3. School of Public Health, Curtin University, Perth, WA, 6102, Australia

    Richard Norman

Authors
  1. Kaiying Wang
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  2. Chris Barr
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  3. Richard Norman
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  4. Stacey George
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  5. Craig Whitehead
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  6. Julie Ratcliffe
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Contributions

All authors conceived and designed the study. JR and CB oversaw the data analysis. KW performed the data analysis. JR led and KW, CB, RN, SG and CW contributed to drafting the article. All authors read and approved the final article.

Corresponding author

Correspondence to Kaiying Wang.

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Funding

This study was funded in part by an advanced studies scholarship awarded by Flinders University to Kaiying Wang.

Conflict of interest

Julie Ratcliffe, Kaiying Wang, Chris Barr, Richard Norman, Stacey George and Craig Whitehead have no conflicts of interest that are directly relevant to the content of this article.

Ethics approval

This study was approved by the Human Research Ethics Committee (Australia; HREC/17/SAC/58) and was performed in accordance with the ethical standards of the Declaration of Helsinki. Informed consent was obtained from all individual participants included in the study.

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Wang, K., Barr, C., Norman, R. et al. 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. Appl Health Econ Health Policy 19, 111–121 (2021). https://doi.org/10.1007/s40258-020-00588-3

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  • DOI: https://doi.org/10.1007/s40258-020-00588-3

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