Equity impact analysis of medical approaches to cardiovascular diseases prevention in Tanzania
Peer reviewed, Journal article
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Primary medical prevention of cardiovascular disease (CVD) has received low priority in Tanzania, despite evidence of the rising prevalence of CVD risk factors. Different guidelines have been proposed for medical CVD prevention, including the European Society of Cardiology (ESC) and the World Health Organization (WHO) guidelines, which recommend medical prevention for all individuals based on the consideration of single CVD risk thresholds. A third alternative is differentiated risk thresholds according to age. This paper compares the WHO and the differentiated risk threshold by age approaches against a baseline of no medical CVD prevention and a best scenario identical to the ESC approach in Tanzania. Assuming fixed budgets, we evaluate the guidelines according to three outcome measures, namely: efficiency, inequality and the combination of efficiency and inequality. We ran a Markov analysis for an estimated Tanzanian population at risk of CVD employing a 40 years time horizon to estimate the total expected costs and CVD deaths associated with provision of the different guidelines. The results were then used to calculate three outcomes: life expectancy at age 40 as a proxy for efficiency, the Gini coefficient (a measure of inequality), and the achievement index (which combines concerns of efficiency and inequality). Our results suggest that higher life expectancy (28.3 vs. 26.6 years) and more equally distributed health (Gini coefficient of 0.22 vs. 0.24) could be attained if medical CVD prevention was based on the differentiated risk threshold approach compared to the WHO single risk threshold, when the total cost of these approaches is the same. Preventing CVD based on differentiating risk thresholds by age seems to be the better alternative when concerns of both efficiency and inequality are considered important. However, further research on the country-specific distribution of CVD risk levels and budget impact analysis are important to assess the feasibility of its implementation.