146 research outputs found

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    Code Revision

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    Code Revision

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    Evaluating Health Workers' Potential Resistance to New Interventions: A Role for Discrete Choice Experiments

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    BACKGROUND: The currently recommended approach for preventing malaria in pregnancy (MiP), intermittent preventive treatment with sulphadoxine-pyrimethamine (SP-IPT), has been questioned due to the spread of resistance to SP. Whilst trials are underway to test the efficacy of future alternative approaches, it is important to start exploring the feasibility of their implementation. METHODS AND FINDINGS: This study uses a discrete choice experiment (DCE) method to assess the potential resistance of health workers to changing strategies for control of MiP. In Ashanti region in Ghana, 133 antenatal clinic health workers were presented with 16 choice sets of two alternative policy options, each consisting of a bundle of six attributes representing certain clinical guidelines for controlling MiP (type of approach and drug used), possible associated maternal and neo-natal outcomes, workload and financial incentives. The data were analysed using a random effects logit model. Overall, staff showed a preference for a curative approach with pregnant women tested for malaria parasites and treated only if positive, compared to a preventive approach (OR 1.6; p = 0.001). Increasing the incidence of low birth weight or severe anaemia by 1% would reduce the odds of preferring an approach by 18% and 10% respectively. Midwives were more resistant to potential changes to current guidelines than lower-level cadres. CONCLUSIONS: In Ashanti Region, resistance to change by antenatal clinic workers from a policy of SP-IPT to IST would generally be low, and it would disappear amongst midwives if health outcomes for the mother and baby were improved by the new strategy. DCEs are a promising approach to identifying factors that will increase the likelihood of effective implementation of new interventions immediately after their efficacy has been proven

    Canadian Valuation of EQ-5D Health States: Preliminary Value Set and Considerations for Future Valuation Studies

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    Background The EQ-5D is a preference based instrument which provides a description of a respondent's health status, and an empirically derived value for that health state often from a representative sample of the general population. It is commonly used to derive Quality Adjusted Life Year calculations (QALY) in economic evaluations. However, values for health states have been found to differ between countries. The objective of this study was to develop a set of values for the EQ-5D health states for use in Canada. Methods Values for 48 different EQ-5D health states were elicited using the Time Trade Off (TTO) via a web survey in English. A random effect model was fitted to the data to estimate values for all 243 health states of the EQ-5D. Various model specifications were explored. Comparisons with EQ-5D values from the UK and US were made. Sensitivity analysis explored different transformations of values worse than dead, and exclusion criteria of subjects. Results The final model was estimated from the values of 1145 subjects with socio-demographics broadly representative of Canadian general population with the exception of Quebec. This yielded a good fit with observed TTO values, with an overall R2 of 0.403 and a mean absolute error of 0.044. Conclusion A preference-weight algorithm for Canadian studies that include the EQ-5D is developed. The primary limitations regarded the representativeness of the final sample, given the language used (English only), the method of recruitment, and the difficulty in the task. Insights into potential issues for conducting valuation studies in countries as large and diverse as Canada are gained
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