In Chapter 1, we argued that good health policy can have a direct impact on improving health outcomes. Exactly which policy to pursue is decided from a complicated mixture of politics, available funding, and technical expertise. The technical elements of this mixture are determined, to varying degrees, by the evidence available for policymaking. Ideally, policy should always be evidencebased, but this is obviously not always the case. Oftentimes, policy is made without evidence—a situation that demands that policy be evaluated in vivo to determine if it is having its intended impact. Other times, policy is made that ignores the available evidence. Creating evidence-based policy, therefore, faces twin challenges: high-quality data must be used during the policymaking (or policy revision) process, and policy made in the absence of evidence must be implemented cautiously until its impact is properly understood.
Data are important for policy analysis for a simple reason: Better data should generate or lead to better policy. Better policy, in turn, is expected to lead to better health outcomes—the ultimate goal of health policymakers.
Do better data actually guide policymaking? It is not hard to demonstrate that information and scientific investigation are used to inform health policy, and there are many examples of this relationship in Asia. For example, data from observational studies have shown that sexually transmitted diseases (STDs) are associated with cervical cancer and the spread of HIV.