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Creating a personalized evaluation framework for patient-reported outcomes: an illustration using the EQ-5D visual analogue scale.
Expert Review of Pharmacoeconomics & Outcomes Research 2018 September 7
BACKGROUND: This paper outlines the creation of an intuitive, personalized evaluation framework for Patient-Reported Outcomes, using the EQ-5D visual analog scale (VAS) as an illustration.
METHODS: A draft framework asked patients to divide and label the EQ-5D-VAS into different levels or categories of health. Comprehension of the framework and patient-defined health level labels, and how they map onto the EQ-5D-VAS, were tested through in-person, semi-structured interviews with individuals self-reporting cardiovascular disease. Interviews were conducted in three waves, with the framework revised between waves.
RESULTS: Analyses included 14 participants. Eight participants (57.1%) felt that four levels of health were appropriate and there was general agreement on the labels; Poor, Fair, Good, and Excellent. There was substantial variability in where patients drew lines to indicate the level boundaries; Poor ranged between 0 and 50; Fair 10-75; Good 40-91; Excellent 60-100. In wave 3, all participants demonstrated appropriate comprehension of the framework.
CONCLUSIONS: The framework was well understood. The wide range of margins and the extent of overlap between the levels provide strong evidence for the relevance of the personalized evaluation framework approach, and specifically a personalized EQ-5D-VAS evaluation framework, to better understand and interpret each individual's response to the item.
METHODS: A draft framework asked patients to divide and label the EQ-5D-VAS into different levels or categories of health. Comprehension of the framework and patient-defined health level labels, and how they map onto the EQ-5D-VAS, were tested through in-person, semi-structured interviews with individuals self-reporting cardiovascular disease. Interviews were conducted in three waves, with the framework revised between waves.
RESULTS: Analyses included 14 participants. Eight participants (57.1%) felt that four levels of health were appropriate and there was general agreement on the labels; Poor, Fair, Good, and Excellent. There was substantial variability in where patients drew lines to indicate the level boundaries; Poor ranged between 0 and 50; Fair 10-75; Good 40-91; Excellent 60-100. In wave 3, all participants demonstrated appropriate comprehension of the framework.
CONCLUSIONS: The framework was well understood. The wide range of margins and the extent of overlap between the levels provide strong evidence for the relevance of the personalized evaluation framework approach, and specifically a personalized EQ-5D-VAS evaluation framework, to better understand and interpret each individual's response to the item.
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