The notion of having an efficient health system at a cost–effective value for money, is of most interest to policymakers (Mirella, 2013). Health care financiers including governments, insurers and households are interested in knowing which health system has the largest health benefitsyet spends at a minimal cost (Tulchinsky,2014). Cross-country comparison and benchmarkingare useful tools to assess and compare health systems. However, frail comparisons of health systems may bring inaccurate insights to policy makers (Lopes, 2015). Thus, this study will generate a scale that compare countries accurately by addressing the fractality of the data.The Current health expenditure data is highly fractal with highly unequal distribution of health spending globally. Because of the wide disparity of data, median is the best positional average to use instead of the mean. This will give a more accurate representation of the health spending of all countries. Through fractal analysis we can generate a scale that will place corresponding countries on a continuum with respect to their CHE for cross country comparisons. Through generating a scale that can place countries in a continuum, there will be a fair comparison of the health outcomes.This CHE scale is a better reference because it addresses the fractality of the CHE data. Those belonging to the same cluster are self-affine countries. Self-affine countries are similarly comparable enough to make a fair comparison of health outcomes. Nine scales were created. Countries belonging to the same scale are comparably similar enough to make an inferential finding. In line with the findings of the study, the following conclusions were drawn: (1) That the fractal dimension of current health index of 2015 is 1.003 which means that the extent of self-similarity is low; (2) that the generated scaling may be used for comparison for self-affine countries; (3) the Philippines can benchmark from self-affine countries.