Anne M Rentz1, Jonathan W Kowalski2, John G Walt2, Ron D Hays3, John E Brazier4, Ren Yu1, Paul Lee5, Neil Bressler6, Dennis A Revicki1. 1. Evidera, Bethesda, Maryland. 2. Allergan Inc, Irvine, California. 3. Department of Medicine, University of California, Los Angeles. 4. School of Health and Related Research, Sheffield University, Sheffield, England. 5. Duke University, Durham, North Carolina6now with Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor. 6. Retina Division, Wilmer Eye Institute, Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Abstract
IMPORTANCE: Understanding how individuals value health states is central to patient-centered care and to health policy decision making. Generic preference-based measures of health may not effectively capture the impact of ocular diseases. Recently, 6 items from the National Eye Institute Visual Function Questionnaire-25 were used to develop the Visual Function Questionnaire-Utility Index health state classification, which defines visual function health states. OBJECTIVE: To describe elicitation of preferences for health states generated from the Visual Function Questionnaire-Utility Index health state classification and development of an algorithm to estimate health preference scores for any health state. DESIGN, SETTING, AND PARTICIPANTS: Nonintervention, cross-sectional study of the general community in 4 countries (Australia, Canada, United Kingdom, and United States). A total of 607 adult participants were recruited from local newspaper advertisements. In the United Kingdom, an existing database of participants from previous studies was used for recruitment. INTERVENTIONS: Eight of 15,625 possible health states from the Visual Function Questionnaire-Utility Index were valued using time trade-off technique. MAIN OUTCOMES AND MEASURES: A θ severity score was calculated for Visual Function Questionnaire-Utility Index-defined health states using item response theory analysis. Regression models were then used to develop an algorithm to assign health state preference values for all potential health states defined by the Visual Function Questionnaire-Utility Index. RESULTS: Health state preference values for the 8 states ranged from a mean (SD) of 0.343 (0.395) to 0.956 (0.124). As expected, preference values declined with worsening visual function. Results indicate that the Visual Function Questionnaire-Utility Index describes states that participants view as spanning most of the continuum from full health to dead. CONCLUSIONS AND RELEVANCE: Visual Function Questionnaire-Utility Index health state classification produces health preference scores that can be estimated in vision-related studies that include the National Eye Institute Visual Function Questionnaire-25. These preference scores may be of value for estimating utilities in economic and health policy analyses.
IMPORTANCE: Understanding how individuals value health states is central to patient-centered care and to health policy decision making. Generic preference-based measures of health may not effectively capture the impact of ocular diseases. Recently, 6 items from the National Eye Institute Visual Function Questionnaire-25 were used to develop the Visual Function Questionnaire-Utility Index health state classification, which defines visual function health states. OBJECTIVE: To describe elicitation of preferences for health states generated from the Visual Function Questionnaire-Utility Index health state classification and development of an algorithm to estimate health preference scores for any health state. DESIGN, SETTING, AND PARTICIPANTS: Nonintervention, cross-sectional study of the general community in 4 countries (Australia, Canada, United Kingdom, and United States). A total of 607 adult participants were recruited from local newspaper advertisements. In the United Kingdom, an existing database of participants from previous studies was used for recruitment. INTERVENTIONS: Eight of 15,625 possible health states from the Visual Function Questionnaire-Utility Index were valued using time trade-off technique. MAIN OUTCOMES AND MEASURES: A θ severity score was calculated for Visual Function Questionnaire-Utility Index-defined health states using item response theory analysis. Regression models were then used to develop an algorithm to assign health state preference values for all potential health states defined by the Visual Function Questionnaire-Utility Index. RESULTS: Health state preference values for the 8 states ranged from a mean (SD) of 0.343 (0.395) to 0.956 (0.124). As expected, preference values declined with worsening visual function. Results indicate that the Visual Function Questionnaire-Utility Index describes states that participants view as spanning most of the continuum from full health to dead. CONCLUSIONS AND RELEVANCE: Visual Function Questionnaire-Utility Index health state classification produces health preference scores that can be estimated in vision-related studies that include the National Eye Institute Visual Function Questionnaire-25. These preference scores may be of value for estimating utilities in economic and health policy analyses.
Authors: Donna Rowen; John Brazier; Tracey Young; Sabine Gaugris; Benjamin M Craig; Madeleine T King; Galina Velikova Journal: Value Health Date: 2011 Jul-Aug Impact factor: 5.725
Authors: David Feeny; Karen Spritzer; Ron D Hays; Honghu Liu; Theodore G Ganiats; Robert M Kaplan; Mari Palta; Dennis G Fryback Journal: Med Decis Making Date: 2011-10-18 Impact factor: 2.583
Authors: Phoebe S Y Lo; Michael C F Tong; Dennis A Revicki; Ching Chyi Lee; John K S Woo; Henry C K Lam; C Andrew van Hasselt Journal: Qual Life Res Date: 2006-06 Impact factor: 4.147
Authors: Kelly W Muir; Cecile Santiago-Turla; Sandra S Stinnett; Leon W Herndon; R Rand Allingham; Pratap Challa; Paul P Lee Journal: Am J Ophthalmol Date: 2006-08 Impact factor: 5.258
Authors: Li Ming Dong; Ashley L Childs; Carol M Mangione; Eric B Bass; Neil M Bressler; Barbara S Hawkins; Marta J Marsh; Päivi Miskala; Harrris A Jaffee; Lee A McCaffrey Journal: Am J Ophthalmol Date: 2004-07 Impact factor: 5.258
Authors: K Thiran Jayasundera; Rebhi O Abuzaitoun; Gabrielle D Lacy; Maria Fernanda Abalem; Gregory M Saltzman; Thomas A Ciulla; Mark W Johnson Journal: Am J Ophthalmol Date: 2021-08-22 Impact factor: 5.258
Authors: Philip Hykin; A Toby Prevost; Sobha Sivaprasad; Joana C Vasconcelos; Caroline Murphy; Joanna Kelly; Jayashree Ramu; Abualbishr Alshreef; Laura Flight; Rebekah Pennington; Barry Hounsome; Ellen Lever; Andrew Metry; Edith Poku; Yit Yang; Simon P Harding; Andrew Lotery; Usha Chakravarthy; John Brazier Journal: Health Technol Assess Date: 2021-06 Impact factor: 4.014
Authors: Elizabeth A Sugar; Vidya Venugopal; Jennifer E Thorne; Kevin D Frick; Gary N Holland; Robert C Wang; Robert Almanzor; Douglas A Jabs; Janet T Holbrook Journal: Ophthalmology Date: 2017-06-16 Impact factor: 14.277
Authors: Mohammad O Tallouzi; David J Moore; Nicholas Bucknall; Philip I Murray; Melanie J Calvert; Alastair K Denniston; Jonathan M Mathers Journal: BMJ Open Ophthalmol Date: 2020-07-21
Authors: Rachel L Z Goh; Yu Xiang George Kong; Colm McAlinden; John Liu; Jonathan G Crowston; Simon E Skalicky Journal: Transl Vis Sci Technol Date: 2018-01-23 Impact factor: 3.283