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 .
Economic evaluation in short bowel syndrome (SBS): an algorithm to estimate utility scores for a patient-reported SBS-specific quality of life scale (SBS-QoL™)
Purpose Condition-specific preference-based measures can offer utility data where they would not otherwise be available or where generic measures may lack sensitivity , although they lack comparability across conditions . This study aim ed to develop an algorithm for estimating utilities from the short bowel syndrome health-related quality of life scale ( SBS-QoL ™ ) . Methods SBS-QoL ™ items were selected based on factor and item performance analysis of a European SBS-QoL ™ data set and consultation with 3 SBS clinical experts . Six-dimension health states were developed using 8 SBS-QoL ™ items ( 2 dimensions combined 2 SBS-QoL ™ items ) . SBS health states were valued by a UK general population sample ( N = 250 ) using the lead-time time trade-off method . Preference weights or ‘ utility decrements ’ for each severity level of each dimension were estimated by regression models and used to develop the scoring algorithm . Results Mean utilities for the SBS health states ranged from −0.46 ( worst health state , very much affected on all dimensions ) to 0.92 ( best health state , not at all affected on all dimensions ) . The r and om effects model with maximum likelihood estimation regression had the best predictive ability and lowest root mean squared error and mean absolute error , and was used to develop the scoring algorithm . Conclusions The preference-weighted scoring algorithm for the SBS-QoL ™ developed is able to estimate a wide range of utility values from patient-level SBS-QoL ™ data . This allows estimation of SBS HRQL impact for the purpose of economic evaluation of SBS treatment benefits
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 .