Background: This paper attempts to capture the institutional factors of regulatory incentive policies and the nature of industry structure on healthcare insurance premium rate-making, through isolating them from fixed effects to price determination, by using mixed model analysis techniques. The properties of Mixed Model techniques provide facilities for fitting the variance of outcome variables of economic activity such as healthcare premiums, against the behavior of explicit deterministic variables, relative to, the behavior of implicit random variables. Materials: The data in this case study is that of the population of registered medical schemes and their members in South Africa. The study design was a cross-sectional comparison analysis between 2009 and 2013 data. The inclusion criteria were schemes that submitted complete data on the variables of interests. A multi-level model was employed to assess the effect of independent variables of the dependent variables such as the average age of enrollees and their claiming patterns. Results: The results revealed a pattern between average age, claims ratio, and the level of health insurance paid by families enrolled to health insurance carriers. This is enriched when the prevalence of benefit option is brought into the analysis. The current research showed that market dominance by few players and that’s smaller schemes, particularly in the open sector continue to be swallowed by big schemes. Lastly two biggest medical schemes combined with over four million beneficiaries accounted for half of all beneficiaries in 2013. Conclusion: The average age of beneficiaries was shown to be an important variable that informs how health insurance carriers manage the pure risks related to covered risk pools. The study also revealed that claims pattern can also be used to determine the predictive nature of health claims over a period of time. Both these variables are thus central to the operational performance of health insurance carriers and, are also assumed to be controllable by internal management.