The speed at which most countries with high burdens of multidrug-resistant tuberculosis (MDRTB) have scaled up their capacity to diagnose and treat individuals with these forms of TB has failed to keep pace with the problem. Limited availability of drug susceptibility testing, high costs and inefficiencies in the supply of second-line drugs, and inadequate capacity for the management of patients with MDRTB have contributed to the wide gap between the estimated need for and the delivery of MDRTB treatment. The most recent global estimates indicate that only about 1 in 20 individuals with incident MDRTB will be properly diagnosed; fewer still receive quality-assured treatment. As policy makers confront the threat of growing levels of drug-resistant TB, there is a clear role for improved surveillance methods that can facilitate more effective public health responses. In countries that cannot yet test all incident cases for drug resistance, analysis of programmatic data and use of periodic, efficient surveys can provide information to help prioritize the use of limited resources to geographic areas or population subgroups of greatest concern. We describe methods for the analysis of routinely collected data and alternative surveys that can help tighten the link between surveillance activities and interventions.