title: Use of a visual analogue scale in a daily patient diary: modelling cross-sectional time-series data on health-related quality of life.
abstract: An economic evaluation of beta interferon therapy collected quality of life data from 62 people with relapsing-remitting multiple sclerosis, currently in remission. Each completed a postal questionnaire consisting of the Euroqol EQ-5D questionnaire, the MSQOL-54 (a disease-specific measure incorporating the SF36) and other data including health services use. This was completed at the beginning and end of 6-weeks during which a daily diary was kept. The diary asked about daily activities, symptoms experienced, the impact of symptoms, general health status and current health status using the Euroqol Visual Analogue Scale (EQ VAS). The diary had an excellent completion rate, producing data with good face validity. The resulting cross-sectional time-series data provide information about the stability and variability of the EQ VAS in repeated measurement and its sensitivity to health state changes. EQ VAS scores were stable at the population level over time; greater variation in scores was observed between rather than within individuals. Panel data techniques are used to relate EQ VAS scores to recorded symptoms and baseline general health status, paying particular attention to the role of individual heterogeneity and the dynamic nature of responses. The EQ VAS was sensitive to the presence of symptoms, their severity and their type. It is concluded that appropriately analysed panel data can provide insights useful in the measurement of health-related quality of life.
authors.affiliation: City Health Economics Centre, Department of Economics, City University, Northampton Square, London EC1V 0HB, UK. d.parkin@city.ac.uk
authors.forename: David
authors.initials: D
authors.lastname: Parkin
authors.forename: Nigel
authors.initials: N
authors.lastname: Rice
authors.forename: Ann
authors.initials: A
authors.lastname: Jacoby
authors.forename: Julie
authors.initials: J
authors.lastname: Doughty
mesh_terms: D000328:Adult; D003625:Data Collection / Q000379:methods*; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D015233:Models, Statistical; D009103:Multiple Sclerosis; D011788:Quality of Life; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D006113:United Kingdom