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

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

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

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 population health in the United States and Canada

<p>Abstract</p> <p>Background</p> <p>The objective of the paper is to compare population health in the United States (US) and Canada. Although the two countries are very similar in many ways, there are potentially important differences in the levels of social and economic inequality and the organization and financing of and access to health care in the two countries.</p> <p>Methods</p> <p>Data are from the Joint Canada/United States Survey of Health 2002/03. The Health Utilities Index Mark 3 (HUI3) was used to measure overall health-related quality of life (HRQL). Mean HUI3 scores were compared, adjusting for major determinants of health, including body mass index, smoking, education, gender, race, and income. In addition, estimates of life expectancy were compared. Finally, mean HUI3 scores by age and gender and Canadian and US life tables were used to estimate health-adjusted life expectancy (HALE).</p> <p>Results</p> <p>Life expectancy in Canada is higher than in the US. For those < 40 years, there were no differences in HRQL between the US and Canada. For the 40+ group, HRQL appears to be higher in Canada. The results comparing the white-only population in both countries were very similar. For a 19-year-old, HALE was 52.0 years in Canada and 49.3 in the US.</p> <p>Conclusions</p> <p>The population of Canada appears to be substantially healthier than the US population with respect to life expectancy, HRQL, and HALE. Factors that account for the difference may include access to health care over the full life span (universal health insurance) and lower levels of social and economic inequality, especially among the elderly.</p

Choosing between measures: comparison of EQ-5D, HUI2 and HUI3 in persons with hearing complaints

OBJECTIVES: To generate insight into the differences between utility measures EuroQol 5D (EQ-5D), Health Utilities Index Mark II (HUI2) and Mark III (HUI3) and their impact on the incremental cost-effectiveness ratio (ICER) for hearing aid fitting METHODS: Persons with hearing complaints completed EQ-5D, HUI2 and HUI3 at baseline and, when applicable, after hearing aid fitting. Practicality, construct validity, agreement, responsiveness and impact on the ICER were examined. RESULTS: All measures had high completion rates. HUI3 was capable of discriminating between clinically distinctive groups. Utility scores (n = 315) for EQ-5D UK and Dutch tariff (0.83; 0.86), HUI2 (0.77) and HUI3 (0.61) were significantly different, agreement was low to moderate. Change after hearing aid fitting (n = 70) for HUI2 (0.07) and HUI3 (0.12) was statistically significant, unlike the EQ-5D UK (0.01) and Dutch (0.00) tariff. ICERs varied from 647,209 euros/QALY for the EQ-5D Dutch tariff to 15,811 euros/QALY for HUI3. CONCLUSION: Utility scores, utility gain and ICERs heavily depend on the measure that is used to elicit them. This study indicates HUI3 as the instrument of first choice when measuring utility in a population with hearing complaints, but emphasizes the importance of a clear notion of what constitutes utility with regard to economic analyse

How dynamic capabilities drive performance in the Indian IT industry : the role of information and co-ordination

This study examines key issues and effects of capability management on a fast-growing area of knowledge-intensive global business services &ndash; IT outsourcing and offshoring. An exploratory study is undertaken of Indian companies providing complex process-oriented offshore IT services to their global customers. The analysis of the data related to the service provider side shows that developing dynamic capabilities is strongly driven by management and top-clients and results in the development of business processes and in establishing a strategic partnership with the client organization. Key findings are that information exchange and coordination are the key to a leveraging firm performance.<br /

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