UC Berkeley

In Mexico, as in many other countries, HIV/AIDS strategies are developed at the federal level and implemented at the state level. Local programs are expected to use data, in particular surveillance data, to drive their decisions on programmatic activities and prioritize populations with which the program will engage. Since the early 1980s Mexico has engaged a complex and consistent strategy to address HIV and as a result, a great deal of data is available to help target prevention efforts. However, data utilization varies by state due to a number of factors that influence the process. This dissertation uses the case of state HIV/AIDS programs in Mexico to identify and explore the factors that influence data utilization and evaluate their effect on these programs. Three distinct papers are used to explore this topic.

The first paper is a literature review that provides an overview of factors that have been previously identified to influence data and research uptake by decision-makers. These factors are sorted into three categories--macro political, resource and data characteristics--to develop a model for influencing decisions. This model is then superimposed over the cycle for surveillance data in order to clearly ascertain the effect these factors have on data utilization. In the second paper the model developed in the first paper is evaluated through a study in four state programs in Mexico. Interviews and a survey were conducted to assess how the influence factors facilitate and impede data utilization at the local level. Issues around communication, decision-making power, budgeting, data quality and dissemination were the primary concerns identified. The third and final paper explores decision space in these state programs. Specifically, this paper reviews the negative side effects that enforcing an existing policy against sharing antiretroviral drugs between states has had on the decision space of programs at the local level.

The results from this research show that in addition to the expected barriers to using data for decision-making, there are also a variety of subtle forces affecting local actors that also need to be taken into account if data utilization is to be improved. One of the main contributions of this study is the approach of studying macro political, resource and data factors simultaneously in order to assess the combined effect they have on decision-makers. This study also helps identify potential areas that both local and national-level actors can leverage to move towards data-driven programming, such as improving local capacity for data analysis and strategic changes to current data dissemination practices. Future research directions include additional comparative studies in Mexico as well as in other middle- and lower-income countries, further explorations of constrained decision space and how it affects program performance and an evaluation of the relative value of experiential knowledge in settings were data are absent or unreliable.