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
Kaiying Wang (),
Chris Barr,
Richard Norman,
Stacey George,
Craig Whitehead and
Julie Ratcliffe
Additional contact information
Kaiying Wang: Flinders University
Chris Barr: Flinders University
Richard Norman: Curtin University
Stacey George: Flinders University
Craig Whitehead: Flinders University
Julie Ratcliffe: Flinders University
Applied Health Economics and Health Policy, 2021, vol. 19, issue 1, No 11, 121 pages
Abstract:
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.
Date: 2021
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DOI: 10.1007/s40258-020-00588-3
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