Econometric accounting of the Australian corporate tax rates: A firm panel example

The paper presents an econometric accounting of the e§ective corporate tax rate in Australia for the years 1993 to 1996. The estimation is a panel of Australian firms that uses a specially gathered financial data base. Using fixed and random e§ects, the model specifies that the statutory tax rate is estimated as the constant term of the model. An ability to find an estimated statutory tax rate that is close to the actual rate suggests a certain confidence in the estimated e§ects of the others factors a§ecting the e§ective tax rate. The results show importance for interest expenses, depreciation allowances, debt/asset structures, and the foreign ownership of firms. There is support for an Australian role as a preferential tax location

Health state utilities of a population of Nigerian hypertensive patients

<p>Abstract</p> <p>Background</p> <p>Establishment of the health impact of hypertension on quality of life of Nigerians is a step towards controlling the disease. The study aimed to provide a Nigerian specific reference list of utility scores of hypertensive patients with various interacting conditions.</p> <p>Findings</p> <p>An interviewer-based, cross-sectional study was conducted using hypertensive patients in two purposively selected tertiary hospitals located in South-Eastern Nigeria. Health Utility Index Mark 3 (HUI3) was used.</p> <p>A total of 384 participants with either hypertension alone or with hypertension-associated complications were interviewed in the two tertiary hospitals.</p> <p>The overall mean utility score was 0.35 +/- 0.42. Patients with hypertension alone had the highest overall mean utility score (0.57 +/- 0.29) while hypertensive patients with stroke had the lowest overall mean score (0.04 +/- 0.36). Being a male, increase in age and mean arterial blood pressure, emergency visit and loss of work due to illness were associated with significant decrease in overall utility scores.</p> <p>Conclusions</p> <p>This study presented a reference for health state utilities of a population of Nigerian hypertensive patients.</p

Construct validation of the Health Utilities Index and the Child Health Questionnaire in children undergoing cancer chemotherapy

The objective of this study was to evaluate the construct validity of two questionnaire-based measures of health-related quality of life (HRQL) in children undergoing cancer chemotherapy: the Health Utilities Index (HUI) and the Child Health Questionnaire (CHQ). Subjects were children hospitalised for chemotherapy. To examine construct validity: (1) a priori expected relations between CHQ concepts and HUI attributes were examined; (2) HUI and CHQ summary scores were compared to visual analogue scale (VAS) scores. Ease of completion was rated using a 5-point categorical scale and completion time was recorded. A total of 36 subjects were included. The maximum score was seen in 15 (47%) of HUI3 assessments. As predicted, CHQ body pain was moderately correlated with HUI3 pain (r=0.51), CHQ physical functioning was moderately correlated with HUI2 mobility (r=0.58) and CHQ mental health was moderately correlated with HUI2 emotion (r=0.53). Only the CHQ psychosocial subscale (and not HUI) was correlated with VAS (r=0.44). The CHQ and the HUI were both easy to use. The HUI questionnaires required less time to complete (mean=3.1, s.d.=1 min) compared with CHQ (mean=13.1, s.d.=3.4 min, P<0.0001). In conclusion, HUI and CHQ demonstrated construct validity in children undergoing cancer chemotherapy. The Health Utilities Index is subject to a ceiling effect whereas CHQ requires more time to complete

Are symbols useful and culturally acceptable in health-state valuation studies? An exploratory study in a multi-ethnic Asian population

10.2147/PPA.S4142Patient Preference and Adherence2271-27

Preferred reporting items for studies mapping onto preference-based outcome measures: The MAPS statement

'Mapping' onto generic preference-based outcome measures is increasingly being used as a means of generating health utilities for use within health economic evaluations. Despite publication of technical guides for the conduct of mapping research, guidance for the reporting of mapping studies is currently lacking. The MAPS (MApping onto Preference-based measures reporting Standards) statement is a new checklist, which aims to promote complete and transparent reporting of mapping studies. The primary audiences for the MAPS statement are researchers reporting mapping studies, the funders of the research, and peer reviewers and editors involved in assessing mapping studies for publication. A de novo list of 29 candidate reporting items and accompanying explanations was created by a working group comprised of six health economists and one Delphi methodologist. Following a two-round, modified Delphi survey with representatives from academia, consultancy, health technology assessment agencies and the biomedical journal editorial community, a final set of 23 items deemed essential for transparent reporting, and accompanying explanations, was developed. The items are contained in a user friendly 23 item checklist. They are presented numerically and categorised within six sections, namely: (i) title and abstract; (ii) introduction; (iii) methods; (iv) results; (v) discussion; and (vi) other. The MAPS statement is best applied in conjunction with the accompanying MAPS explanation and elaboration document. It is anticipated that the MAPS statement will improve the clarity, transparency and completeness of reporting of mapping studies. To facilitate dissemination and uptake, the MAPS statement is being co-published by eight health economics and quality of life journals, and broader endorsement is encouraged. The MAPS working group plans to assess the need for an update of the reporting checklist in five years' time. This statement was published jointly in Applied Health Economics and Health Policy, Health and Quality of Life Outcomes, International Journal of Technology Assessment in Health Care, Journal of Medical Economics, Medical Decision Making, PharmacoEconomics, and Quality of Life Research

Health-state utilities in a prisoner population : a cross-sectional survey

Background: Health-state utilities for prisoners have not been described. Methods: We used data from a 1996 cross-sectional survey of Australian prisoners (n = 734). Respondent-level SF-36 data was transformed into utility scores by both the SF-6D and Nichol's method. Socio-demographic and clinical predictors of SF-6D utility were assessed in univariate analyses and a multivariate general linear model. Results: The overall mean SF-6D utility was 0.725 (SD 0.119). When subdivided by various medical conditions, prisoner SF-6D utilities ranged from 0.620 for angina to 0.764 for those with none/mild depressive symptoms. Utilities derived by the Nichol's method were higher than SF-6D scores, often by more than 0.1. In multivariate analysis, significant independent predictors of worse utility included female gender, increasing age, increasing number of comorbidities and more severe depressive symptoms. Conclusion: The utilities presented may prove useful for future economic and decision models evaluating prison-based health programs

Comparing the health of low income and less well educated groups in the United States and Canada

<p>Abstract</p> <p>Background</p> <p>A limited number of health status and health-related quality of life (HRQL) measures have been used for inter-country comparisons of population health. We compared the health of Canadians and Americans using a preference-based measure.</p> <p>Methods</p> <p>The Joint Canada/United States Survey of Health (JCUSH) 2002–03 conducted a comprehensive cross-sectional telephone survey on the health of community-dwelling residents in Canada and the US (n = 8688). A preference-based measure, the Health Utilities Index Mark 3 (HUI3), was included in the JCUSH. Health status was analyzed for the entire population and white population only in both countries. Mean HUI3 overall scores were compared for both countries. A linear regression determinants of health model was estimated to account for differences in health between Canada and the US. Estimation with bootstraps was used to derive variance estimates that account for the survey's complex sampling design of clustering and stratification.</p> <p>Results</p> <p>Income is associated with health in both countries. In the lowest income quintile, Canadians are healthier than Americans. At lower levels of education, again Canadians are healthier than Americans. Differences in health among subjects in the JCUSH are explained by age, gender, education, income, marital status, and country of residence.</p> <p>Conclusion</p> <p>On average, population health in Canada and the US is similar. However, health disparities between Canadians and Americans exist at lower levels of education and income with Americans worse off. The results highlight the usefulness of continuous preference-based measures of population health such as the HUI3.</p

Mapping the disease-specific LupusQoL to the SF-6D

Purpose To derive a mapping algorithm to predict SF-6D utility scores from the non-preference-based LupusQoL and test the performance of the developed algorithm on a separate independent validation data set. Method LupusQoL and SF-6D data were collected from 320 patients with systemic lupus erythematosus (SLE) attending routine rheumatology outpatient appointments at seven centres in the UK. Ordinary least squares (OLS) regression was used to estimate models of increasing complexity in order to predict individuals’ SF-6D utility scores from their responses to the LupusQoL questionnaire. Model performance was judged on predictive ability through the size and pattern of prediction errors generated. The performance of the selected model was externally validated on an independent data set containing 113 female SLE patients who had again completed both the LupusQoL and SF-36 questionnaires. Results Four of the eight LupusQoL domains (physical health, pain, emotional health, and fatigue) were selected as dependent variables in the final model. Overall model fit was good, with R2 0.7219, MAE 0.0557, and RMSE 0.0706 when applied to the estimation data set, and R2 0.7431, MAE 0.0528, and RMSE 0.0663 when applied to the validation sample. Conclusion This study provides a method by which health state utility values can be estimated from patient responses to the non-preference-based LupusQoL, generalisable beyond the data set upon which it was estimated. Despite concerns over the use of OLS to develop mapping algorithms, we find this method to be suitable in this case due to the normality of the SF-6D data

Deriving utility scores for co-morbid conditions: a test of the multiplicative model for combining individual condition scores

BACKGROUND: The co-morbidity of health conditions is becoming a significant health issue, particularly as populations age, and presents important methodological challenges for population health research. For example, the calculation of summary measures of population health (SMPH) can be compromised if co-morbidity is not taken into account. One popular co-morbidity adjustment used in SMPH computations relies on a straightforward multiplicative combination of the severity weights for the individual conditions involved. While the convenience and simplicity of the multiplicative model are attractive, its appropriateness has yet to be formally tested. The primary objective of the current study was therefore to examine the empirical evidence in support of this approach. METHODS: The present study drew on information on the prevalence of chronic conditions and a utility-based measure of health-related quality of life (HRQoL), namely the Health Utilities Index Mark 3 (HUI3), available from Cycle 1.1 of the Canadian Community Health Survey (CCHS; 2000–01). Average HUI3 scores were computed for both single and co-morbid conditions, and were also purified by statistically removing the loss of functional health due to health problems other than the chronic conditions reported. The co-morbidity rule was specified as a multiplicative combination of the purified average observed HUI3 utility scores for the individual conditions involved, with the addition of a synergy coefficient s for capturing any interaction between the conditions not explained by the product of their utilities. The fit of the model to the purified average observed utilities for the co-morbid conditions was optimized using ordinary least squares regression to estimate s. Replicability of the results was assessed by applying the method to triple co-morbidities from the CCHS cycle 1.1 database, as well as to double and triple co-morbidities from cycle 2.1 of the CCHS (2003–04). RESULTS: Model fit was optimized at s = .99 (i.e., essentially a straightforward multiplicative model). These results were closely replicated with triple co-morbidities reported on CCHS 2000–01, as well as with double and triple co-morbidities reported on CCHS 2003–04. CONCLUSION: The findings support the simple multiplicative model for computing utilities for co-morbid conditions from the utilities for the individual conditions involved. Future work using a wider variety of conditions and data sources could serve to further evaluate and refine the approach