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This study examines the effects of use of an automated computer protocol to correct a common error in utility elicitations--namely, scoring of a health state with a greater impairment as being more desirable than one with lesser impairment. The authors studied the protocol in a sample of 563 members of the Internet-using public. Results revealed that errors were common (17% of ratings) but were typically successfully repaired (individuals who made only 1 or 2 errors had a 75% chance of repairing them). The values of individuals who repaired errors were similar to those without apparent error. In contrast, individuals who refused to repair errors had lower scores for the best health state in the series and higher ones for the worst health state. Results suggest that the repair procedures were successful and that inclusion of utility scores from individuals who fail to repair illogically ordered ratings may bias estimates of mean utilities.

The article presents a medical research study which examined the potential survival benefit of anterior temporal lobe resection for patients with pharmacoresistant epilepsy in comparison to medical management of the disorder. A decision analysis using a Monte Carlo simulation model populated with quality-of-life data obtained directly from the patients and data from medical literature was used for the study. Life expectancy and quality-adjusted life expectancy were the main outcome measures. Researchers concluded that substantial gains in life expectancy and quality-adjusted life expectancy would be achieved with anterior temporal lobe resection compared with medical management .

Background: Most tools for estimating utilities use clinical trial data from general health status models, such as the 36-Item Short-Form Health Survey (SF-36). A disease-specific model may be more appropriate. The objective of this study was to apply a disease-specific utility mapping function for schizophrenia to data from a large, 1-year, open-label study of long-acting risperidone and to compare its performance with an SF-36-based utility mapping function. Methods: Patients with schizophrenia or schizoaffective disorder by DSM-IV criteria received 25, 50, or 75 mg long-acting risperidone every 2 weeks for 12 months. The Positive and Negative Syndrome Scale (PANSS) and SF-36 were used to assess efficacy and health-related quality of life. Movement disorder severity was measured using the Extrapyramidal Symptom Rating Scale (ESRS); data concerning other common adverse effects (orthostatic hypotension, weight gain) were collected. Transforms were applied to estimate utilities. Results: A total of 474 patients completed the study. Long-acting risperidone treatment was associated with a utility gain of 0.051 using the disease-specific function. The estimated gain using an SF-36-based mapping function was smaller: 0.0285. Estimates of gains were only weakly correlated (r = 0.2). Because of differences in scaling and variance, the requisite sample size for a randomized trial to confirm observed effects is much smaller for the disease-specific mapping function (156 versus 672 total subjects). Conclusion: Application of a disease-specific mapping function was feasible. Differences in scaling and precision suggest the clinically based mapping function has greater power than the SF-36-based measure to detect differences in utility. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia is a common severe syndrome with a highly variable pattern of symptoms. The medications used to treat this disorder are expensive and may cause severe adverse effects. Little is known about how the public perceives health outcomes in schizophrenia or the potential adverse effects of antipsychotic medication. This complicates the use of standard cost-effectiveness analysis to set priorities for health resource allocation.Objective: In this study, we measured utility weights for a set of health states derived from Positive and Negative Symptom Scale (PANSS) scores, and a set of health states that included the presence of common adverse effects of medication, thus creating utility mapping function for clinical data.Methods: We presented a convenience sample of members of a large commercial Internet survey panel with digital video materials portraying eight different patterns of schizophrenia with varying levels of positive, negative and cognitive symptoms, and five common adverse effects of antipsychotic medications. We then elicited their standard gamble (SG) and visual analog scale (VAS) ratings using iMPACT3 computer program, with an automated error repair feature, deliberately over-sampling minority ethnic groups in the panel. We censored subjects with uncorrected errors in ratings and estimated utilities for each state by re-weighting responses to match United States population demographics.Subjects: 620 well-educated, ethnically diverse volunteers (54% Caucasian), who spanned a broad range of age groups and geographical regions of the US participated in this study.Results: Because of evidence of bias in ratings, 175 (29%) subjects with internal inconsistencies in ratings were censored from estimates of mean population utilities. In the remaining 441 subjects, SG utilities, re-weighted to match US population demographic profiles, ranged from 0.88 for mild schizophrenia to 0.47 extremely severe schizophrenia. Variability in the types of symptoms exhibited (positive, negative or cognitive) was less important to participants than the overall severity of each state. Modest reductions in symptoms (for example, from severe to moderate or moderate to mild) were associated with relatively large changes in utility (0.12-0.19). Adverse effects decreased utilities for states by amounts ranging from 0.09 (pseudo-parkinsonism) to 0.05 (obesity).Conclusions: The public views schizophrenia is a very disabling syndrome and treatments that reduce symptoms produce important gains in utility, even if they do not induce a complete remission. Adverse effects significantly reduce utilities for states; therefore, cost-effectiveness analyses for this disorder should take adverse effects of treatment into consideration. [ABSTRACT FROM AUTHOR]