Conclusion Various methods have been used at all stages of CSPBM development .
The choice between developing a classification system de novo or from an existing instrument may depend on the availability of a suitable existing measure , while the choice between a decomposed or composite approach appears to be determined primarily by the purpose for which the instrument is design ed .
Background Health state utility values ( HSUVs ) are required to calculate quality -adjusted life-years ( QALYs ) .
They are frequently derived from generic preference-based measures of health .
However , such generic measures may not capture health attributes of relevance to specific conditions .
In such cases , a condition-specific preference-based measure ( CSPBM ) may be more appropriate .
Objective This systematic review aim ed to identify all published accounts of developing CSPBMs to describe and appraise the methods used .
Estimation of a Preference-Based Index from a Condition-Specific Measure: The King's Health Questionnaire
Background . Generic preference-based measures of health may not adequately cover the impact of some conditions . There is therefore increasing interest in developing condition-specific preference-based measures . Objectives . The purpose of this study was to estimate a preference-based measure from a condition-specific measure of health for urinary incontinence , the 21-item King 's Health Question naire , for use in economic evaluation . Methods . The King 's Health Question naire ( KHQ ) was revised into a 5-dimensional health state classification amenable to valuation using items selected using psychometric evidence . Forty-nine states were valued using st and ard gamble by a representative sample of patients with urinary incontinence attending UK hospital outpatient clinics . Each respondent was asked to value 9 health states . Models have been estimated for predicting health state valuations for all 1024 states defined by the KHQ classification . The modeling had to cope with the clustering of data by respondent and its skewed distribution . Results . In total , 110 usable interviews were obtained from 169 patients approached to participate in the study . These responders generated 959 health state valuations . Mean health state values ranged from 0.77 to 0.98 . Models were estimated using mean health state values and r and om effects models of individual-level health state values . These models generated robust estimates of the ` main effects , ` and in general , the results support the ordinality of the KHQ health state classification . There were problems modeling interaction effects , and a number of alternatives were explored . Conclusion . The recommended model for estimating a preference-based measure from the condition-specific KHQ is presented
Conclusion Various methods have been used at all stages of CSPBM development .
The choice between developing a classification system de novo or from an existing instrument may depend on the availability of a suitable existing measure , while the choice between a decomposed or composite approach appears to be determined primarily by the purpose for which the instrument is design ed .
Background Health state utility values ( HSUVs ) are required to calculate quality -adjusted life-years ( QALYs ) .
They are frequently derived from generic preference-based measures of health .
However , such generic measures may not capture health attributes of relevance to specific conditions .
In such cases , a condition-specific preference-based measure ( CSPBM ) may be more appropriate .
Objective This systematic review aim ed to identify all published accounts of developing CSPBMs to describe and appraise the methods used .