Improving the measurement of QALYs in dementia: Developing patient- and carer-reported health state classification systems using Rasch analysis

Objectives: Cost-utility analysis is increasingly used to inform resource allocation. This requires a means of valuing health states before and after intervention. Although generic measures are typically used to generate values, these do not perform well with people with dementia. We report the development of a health state classification system amenable to valuation for use in studies of dementia, derived from the DEMQOL system, a measure of health-related quality of life in dementia by patient self-report (DEMQOL) and carer proxy-report (DEMQOL-Proxy). Methods: Factor analysis was used to determine the dimensional structure of DEMQOL and DEMQOL-Proxy. Rasch analysis was subsequently used to investigate item performance across factors in terms of item-level ordering, functioning across subgroups, model fit and severity-range coverage. This enabled the selection of one item from each factor for the classification system. A sample of people with a diagnosis of mild/moderate dementia (n=644) and a sample of carers of those with mild/moderate dementia (n=683) were used. Results: Factor analysis found different 5-factor solutions for DEMQOL and DEMQOL-Proxy. Following item reduction and selection using Rasch analysis, a 5-dimension classification for DEMQOL and a 4-dimension classification for DEMQOL-Proxy were developed. Each item contained 4 health state levels. Conclusion: Combining Rasch and classical psychometric analysis is a valid method of selecting items for dementia health state classifications from both the patient and carer perspectives. The next stage is to obtain preference weights so that the measure can be used in the economic evaluation of treatment, care and support arrangements for dementia

Short form 36 (SF-36) health survey questionnaire: which normative data should be used? Comparisons between the norms provided by the omnibus survey in Britain, the Health Survey for England and the Oxford Healthy Life Survey

Background Population norms for the attributes included in measurement scales are required to provide a standard with which scores from other study populations can be compared. This study aimed to obtain population norms for the Short Form 36 (SF-36) Health Survey Questionnaire, derived from a random sample of the population in Britain who were interviewed at home, and to make comparisons with other commonly used norms.Methods The method was a face-to-face interview survey of a random sample of 2056 adults living at home in Britain (response rate 78 per cent). Comparisons of the SF-36 scores derived from this sample were made with the Health Survey for England and the Oxford Healthy Life Survey.Results Controlling for age and sex, many of mean scores on the SF-36 dimensions differed between the three datasets. The British interview sample had better total means for Physical Functioning, Social Functioning, Mental Health, Energy/Vitality, and General Health Perceptions. The Health (interview) Survey for England had the lowest (worst) total mean scores for Physical Functioning, Social Functioning, Role Limitations (physical) Bodily Pain, and Health Perceptions. The postal sample in central England had the lowest (worst) total mean scores for Role Limitations (emotional), Mental Health and Energy/Vitality.Conclusion Responses obtained from interview methods may suffer more from social desirability bias (resulting in inflated SF-36 scores) than postal surveys. Differences in SF-36 means between surveys are also likely to reflect question order and contextual effects of the questionnaires. This indicates the importance of providing mode-specific population norms for the various methods of questionnaire administration

Mathematical coupling may account for the association between baseline severity and minimally important difference values

Objective: To generate anchor-based values for the “minimally important difference” (MID) for a number of commonly used patient-reported outcome (PRO) measures and to examine whether these values could be applied across the continuum of preoperative patient severity. Study Design and Setting: Six prospective cohort studies of patients undergoing elective surgery at hospitals in England and Wales. Patients completed questionnaires about their health and health-related quality of life before and after surgery. MID values were calculated using the mean change score for a reference group of patients who reported they were “a little better” after surgery minus the mean change score for those who said they were “about the same.” Pearson's correlation was used to examine the association between baseline severity and change scores in the reference group. Baseline severity was expressed in two ways: first in terms of preoperative scores and second in terms of the average of pre- and postoperative scores (Oldham's method). Results: Of the 10 PRO measures examined, eight demonstrated a moderate or high positive association between preoperative scores and MID values. Only two measures demonstrated such an association when Oldham's measure of baseline severity was used. Conclusion: In general, there is little association between baseline severity and MID values. However, a moderate association persists for some measures, and it is recommended that researchers continue to test for this relationship when generating anchor-based MID values from change scores

The organization and financing of dialysis and kidney transplantation services in New Zealand

End-stage renal disease, Dialysis, Health care financing, Medical Costs, Reimbursement, New Zealand, I10, I11, I12, I18,