Comparing the incomparable? A systematic review of competing techniques for converting descriptive measures of health status into QALY-weights.
BACKGROUND
Algorithms for converting descriptive measures of health status into quality-adjusted life year (QALY)--weights are now widely available, and their application in economic evaluation is increasingly commonplace. The objective of this study is to describe and compare existing conversion algorithms and to highlight issues bearing on the derivation and interpretation of the QALY-weights so obtained.


METHODS
Systematic review of algorithms for converting descriptive measures of health status into QALY-weights.


RESULTS
The review identified a substantial body of literature comprising 46 derivation studies and 16 studies that provided evidence or commentary on the validity of conversion algorithms. Conversion algorithms were derived using 1 of 4 techniques: 1) transfer to utility regression, 2) response mapping, 3) effect size translation, and 4) "revaluing" outcome measures using preference-based scaling techniques. Although these techniques differ in their methodological/theoretical tradition, data requirements, and ease of derivation and application, the available evidence suggests that the sensitivity and validity of derived QALY-weights may be more dependent on the coverage and sensitivity of measures and the disease area/patient group under evaluation than on the technique used in derivation.


CONCLUSIONS
Despite the recent proliferation of conversion algorithms, a number of questions bearing on the derivation and interpretation of derived QALY-weights remain unresolved. These unresolved issues suggest directions for future research in this area. In the meantime, analysts seeking guidance in selecting derived QALY-weights should consider the validity and feasibility of each conversion algorithm in the disease area and patient group under evaluation rather than restricting their choice to weights from a particular derivation technique.
Mortimer
Duncan
D
Centre for Health Economics, Faculty of Business & Economics, Monash University, Melbourne, Clayton, Australia. duncan.mortimer@buseco.monash.edu.au
Segal
Leonie
L
D000465:Algorithms; D015276:Health Care Rationing; D006304:Health Status; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data; D019057:Quality-Adjusted Life Years; D012720:Severity of Illness Index; D014739:Victoria