Developing preference‐based measures for diabetes: DHP‐3D and DHP‐5D. Issue 9 (1st June 2017)

• Record Type: Journal Article
• Authors: Mulhern, B.; Labeit, A.; Rowen, D.; Knowles, E.; Meadows, K.; Elliott, J.; Brazier, J.
• Is Part Of: Diabetic medicine. Volume 34:Issue 9(2017)
• Page Start: 1264
• Page End: 1275
• Publication Date: 2017-06-01
• Subjects: Diabetes -- Periodicals; 616.462
• DOI: 10.1111/dme.13377
• Languages: English
• ISSNs: 0742-3071

Abstract

Abstract: Aims: The aim of this study was to develop two diabetes‐specific preference‐based measures [the Diabetes Health Profile–3 Dimension (DHP‐3D) and the Diabetes Health Profile–5 Dimension (DHP‐5D)] for use in the calculation of Quality Adjusted Life Years, a key outcome in economic evaluation. These measures were based on the non‐preference‐based instrument the Diabetes Health Profile. Methods: For DHP‐3D, psychometric and Rasch analyses were used to develop a health state classification system based on the Diabetes Health Profile–18 (DHP‐18). The DHP‐5D added two dimensions to the DHP‐3D to extend the range of impacts measured. Each classification system was valued by 150 general public respondents in the United Kingdom using Time Trade Off (TTO). Multivariate regression was used to estimate utility value sets. The matched dimensions across each measure were compared using z ‐score tests. Results: The DHP‐3D included three dimensions defined as mood, eating and social limitations, and the DHP‐5D added dimensions defined as hypoglycaemic attacks and vitality. For both, the random effects generalized least squares regression model produced consistent value sets, with the DHP‐3D and DHP‐5D ranging from 0.983 (best state) to 0.717 (worst state), and 0.979 to 0.618 respectively. The addition of the two extra dimensions leads to significant differences for the more severe levels of each matched dimension. Conclusions: We have developed two diabetes‐specific preference‐based measures that, subject to psychometric assessment, can be used to provide condition‐specific utility values to complement generic utilities from more widely validated measures such as the EuroQol‐5 Dimension. What's new?: We have developed the first diabetes‐specific preference‐based measures with United Kingdom value sets. The measures can be used to estimate Quality Adjusted Life Years for use the economic evaluation of diabetes‐specific interventions.