Populating an economic model with health state utility values: moving toward better practice.
BACKGROUND
The methods used to estimate health-state utility values (HSUV) for multiple health conditions can produce very different values. Economic results generated using baselines of perfect health are not comparable with those generated using baselines adjusted to reflect the HSUVs associated with the health condition. Despite this, there is no guidance on the preferred techniques and little research describing the effect on cost per quality adjusted life-year (QALY) results when using the different methods.


METHODS
Using a cardiovascular disease (CVD) model and cost per QALY thresholds, we assess the consequence of using different baseline health-state utility profiles (perfect health, no history of CVD, general population) in conjunction with models (minimum, additive, multiplicative) frequently used to approximate scores for health states with multiple health conditions. HSUVs are calculated using the EQ-5D UK preference-based algorithm.


RESULTS
Assuming a baseline of perfect health ignores the natural decline in quality of life associated with age, overestimating the benefits of treatment. The results generated using baselines from the general population are comparable to those obtained using baselines from individuals with no history of CVD. The minimum model biases results in favor of younger-aged cohorts. The additive and multiplicative models give similar results.


CONCLUSIONS
Although further research in additional health conditions is required to support our findings, our results highlight the need for analysts to conform to an agreed reference case. We demonstrate that in CVD, if data are not available from individuals without the health condition, HSUVs from the general population provide a reasonable approximation.
University of Shefield, Shefield, UK. r.m.ara@sheffield.ac.uk
Roberta
R
Ara
John E
JE
Brazier
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002318:Cardiovascular Diseases / Q000191:economics* / Q000523:psychology; D003625:Data Collection; D003657:Decision Making; D004739:England; D005260:Female; D006304:Health Status; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D018803:Models, Economic; D010865:Pilot Projects; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D012107:Research Design; D011795:Surveys and Questionnaires; D055815:Young Adult