Estimating a Preference-Based Single Index Measuring the Quality-of-Life Impact of Self-Management for Diabetes. (August 2018)

• Record Type: Journal Article
• Authors: Rowen, Donna; Labeit, Alexander; Stevens, Katherine; Elliott, Jackie; Mulhern, Brendan; Carlton, Jill; Basarir, Hasan; Brazier, John
• Is Part Of: Medical decision making. Volume 38:Number 6(2018)
• Page Start: 699
• Page End: 707
• Publication Date: 2018-08
• Subjects: diabetes -- discrete choice experiment -- health-related quality of life -- preference-based measures -- quality-adjusted life years (QALY) -- quality of life -- self-management; Medical policy -- Periodicals; Clinical medicine -- Decision making -- Periodicals; Medicine -- Periodicals; Médecine clinique -- Prise de décision -- Périodiques; 362.1
• DOI: 10.1177/0272989X18784291
• Languages: English
• ISSNs: 0272-989X

Abstract

Objective. Self-management is becoming increasingly important in diabetes but is neglected in conventional preference-based measures. The objective of this paper was to generate health state utility values for a novel classification system measuring the quality-of-life impact of self-management for diabetes, which can be used to generate quality-adjusted life years (QALYs).Methods. A large online survey was conducted using a discrete choice experiment (DCE), with duration as an additional attribute, on members of the UK general population ( n = 1, 493) to elicit values for health (social limitations, mood, vitality, hypoglycaemia) and non-health (stress, hassle, control, support) aspects of self-management in diabetes. The data were modelled using a conditional fixed-effects logit model and utility estimates were anchored on the one to zero (full health to dead) scale.Results. The model produced significant and consistent coefficients, with one logical inconsistency and 3 insignificant coefficients for the milder levels of some attributes. The anchored utilities ranged from 1 for the best state to −0.029 for the worst state (meaning worse than dead) defined by the classification system.Conclusion. The results presented here can potentially be used to generate utility values capturing the day to day impact of interventions in diabetes on both health and self-management. These utility values can potentially be used to generate QALYs for economic models of the cost-effectiveness of interventions in diabetes.