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Introduction: Quality of life is included in the economic evaluation of health services by measuring the preference for health states, i.e. health state utilities. However, most intervention studies include a disease-specific, not a utility, instrument. Consequently, there has been increasing use of statistical mapping algorithms which permit utilities to be estimated from a disease-specific instrument. The present paper provides such algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and six multi-attribute utility (MAU) instruments, the Euroqol (EQ-5D), the Short Form 6D (SF-6D), the Health Utilities Index (HUI) 3, the Quality of Wellbeing (QWB), the 15D (15 Dimension) and the Assessment of Quality of Life (AQoL-8D). Methods: Heart disease patients and members of the healthy public were recruited from six countries. Non-parametric rank tests were used to compare subgroup utilities and MacNew scores. Mapping algorithms were estimated using three separate statistical techniques. Results: Mapping algorithms achieved a high degree of precision. Based on the mean absolute error and the intra class correlation the preferred mapping is MacNew into SF-6D or 15D. Using the R squared statistic the preferred mapping is MacNew into AQoL-8D. Implications for research: The algorithms reported in this paper enable MacNew data to be mapped into utilities predicted from any of six instruments. This permits studies which have included the MacNew to be used in cost utility analyses which, in turn, allows the comparison of services with interventions across the health system. [ABSTRACT FROM AUTHOR]

The article focuses on a study which examines large-scale observational evidence of cross-cultural differences in facial behavior using advanced in computer science. Topics discussed include the automated facial coding used, the reliability of the facial action unit detection algorithms across different testing subsets, multilevel regression estimates predicting each facial action's base rate percentage.

Background and purpose An internet-based discrete choice experiment (DCE) was conducted to elicit preferences for a wide range of Dupuytren's contracture (DC)-related health states. An algorithm was subsequently developed to convert these preferences into health state utilities that can be used to assess DC's impact on quality of life and the value of its treatments. Methods Health state preferences for varying levels of DC hand severity were elicited via an internet survey from a sample of the UK adult population. Severity levels were defined using a combination of contractures (0, 45, or 90 degrees) in 8 proximal interphalangeal and metacarpophalangeal joints of the index, middle, ring, and little fingers. Right-handed, left-handed, and ambidextrous respondents indicated which hand was preferable in each of the 10 randomly-selected hand-pairings comparing different DC severity levels. For consistency across comparisons, anatomically precise digital hand drawings were used. To anchor preferences onto the traditional 0-1 utility scale used in health economic evaluations, unaffected hands were assigned a utility of 1.0 whereas the utility for a maximally affected hand (i.e., all 8 joints set at 90 degrees of contracture) was derived by asking respondents to indicate what combination of attributes and levels of the EQ-5D-5L profile most accurately reflects the impact of living with such hand. Conditional logistic models were used to estimate indirect utilities, then rescaled to the anchor points on the EQ-5D-5L. Results Estimated utilities based on the responses of 1,745 qualified respondents were 0.49, 0.57, and 0.63 for completely affected dominant hands, non-dominant hands, or ambidextrous hands, respectively. Utility for a dominant hand with 90-degree contracture in t h e metacarpophalangeal joints of the ring and little fingers was estimated to be 0.89. Separately, reducing the contracture of metacarpophalangeal joint for a little finger from 50 to 12 degrees would improve utility by 0.02. Interpretation DC is associated with substantial utility decre- ments. The algorithms presented herein provide a robust and flexible framework to assess utility for varying degrees of DC severity. [ABSTRACT FROM AUTHOR]