RESULTS ( 1 ) EQ-5D was valid and responsive for skin conditions and most cancers ; in vision , its performance varied according to aetiology ; and performance was poor for hearing impairments .
The HUI3 performed well for hearing and vision disorders .
It also performed well in cancers although evidence was limited and there was no evidence in skin conditions .
Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30 .
In an exploratory analysis , a limited dependent variable mixture model performed better than an equivalent linear model .
3 ) The exploratory valuation study found that bolt-on items for vision , hearing and tiredness had a significant impact on values of the health states , but the direction and magnitude of differences depended on the severity of the health state .
The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated .
EQ-5D performs well in studies of cancer and skin conditions .
Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered .
For conditions where EQ-5D was found to be inappropriate , including some vision disorders and for hearing , bolt-ons provide a promising solution .
BACKGROUND The National Institute for Health and Care Excellence recommends the use of generic preference-based measures ( GPBMs ) of health for its Health Technology Assessment s ( HTAs ) .
However , these data may not be available or appropriate for all health conditions .
OBJECTIVES To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate .
( 2 ) Potential modelling approaches to ' map ' EQ-5D values from condition-specific and clinical measures of health [ European Organisation for Research and Treatment of Cancer Quality -of-life Question naire Core 30 ( EORTC QLQ-C30 ) and Functional Assessment of Cancer Therapy - General Scale ( FACT-G ) ] are compared for predictive ability and goodness of fit using two separate data sets . (
Effect of hearing aids on hearing disability and quality of life in the elderly
The aim of this study was to assess the effects of fitting a hearing aid by measuring the benefits derived from hearing aid use . Besides audiologic tests , a short version of the Hearing H and icap Inventory for the Elderly , and the EuroQol question naire were used in a prospect i ve study . Ninety-eight first-time hearing aid users were interviewed prior to , and six months after , the fitting of their  first hearing aids .  The total HHIE-S score changed from 28.7 before , to 12.7 six months after , hearing aid fitting . Altogether 40%–60 % of the users reported fewer social or emotional problems . There was a statistically significant positive change in the EQ-VAS score . According to the HHIE-S , hearing aids clearly alleviated hearing disability . The EQ-5D question naire was not sensitive enough for measuring the health-related quality of life of subjects with hearing impairment . Sumario El objetivo de este estudio fue evaluar los efectos de la adaptación de AA midiendo los beneficios derivados de su uso . Además de las pruebas audiológicas se usaron en un estudio prospect ivo los Cuestionarios de Discapacidad Auditiva en los ancianos ( HHIE-S ) , en versión corta y el EuroQol . Se entrevistaron 98 usuarios de AA de primera vez , antes y seis meses después de la adaptación de sus primeros AA . La puntuación total del HHIE-S cambió de 28.7 en el estudio basal a 12.7 seis meses después de la adaptación . Alrededor del 40 - 60 % de los usuarios reportaron pocos problemas sociales o emocionales . Se apreció un cambio positivo , estadísticamente significativo , en la puntuación del EQ-VAS . De acuerdo con el HHIE-S , los AA claramente mitigaron la discapacidad auditiva . El cuestionario EQ-5D no fue lo suficientemente sensible para medir la calidad de vida relacionada con la salud , en las personas con impedimento auditivo
RESULTS ( 1 ) EQ-5D was valid and responsive for skin conditions and most cancers ; in vision , its performance varied according to aetiology ; and performance was poor for hearing impairments .
The HUI3 performed well for hearing and vision disorders .
It also performed well in cancers although evidence was limited and there was no evidence in skin conditions .
Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30 .
In an exploratory analysis , a limited dependent variable mixture model performed better than an equivalent linear model .
3 ) The exploratory valuation study found that bolt-on items for vision , hearing and tiredness had a significant impact on values of the health states , but the direction and magnitude of differences depended on the severity of the health state .
The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated .
EQ-5D performs well in studies of cancer and skin conditions .
Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered .
For conditions where EQ-5D was found to be inappropriate , including some vision disorders and for hearing , bolt-ons provide a promising solution .
BACKGROUND The National Institute for Health and Care Excellence recommends the use of generic preference-based measures ( GPBMs ) of health for its Health Technology Assessment s ( HTAs ) .
However , these data may not be available or appropriate for all health conditions .
OBJECTIVES To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate .
( 2 ) Potential modelling approaches to ' map ' EQ-5D values from condition-specific and clinical measures of health [ European Organisation for Research and Treatment of Cancer Quality -of-life Question naire Core 30 ( EORTC QLQ-C30 ) and Functional Assessment of Cancer Therapy - General Scale ( FACT-G ) ] are compared for predictive ability and goodness of fit using two separate data sets . (