The Listeria Initiative was launched in 2004 to aid in the investigation of listeriosis clusters and outbreaks by decreasing the time from outbreak detection to public health intervention. Molecular subtyping (i.e., pulsed-field gel electrophoresis, whole genome sequencing) is performed on clinical, food, and environmental isolates of L. monocytogenes and patient interviews are conducted as cases are reported. Molecular subtyping results allow for identification of clusters; prompt patient interviews enable quick comparison of food consumption histories of patients with cluster-associated illnesses to patients with sporadic illnesses to identify foods possibly associated with the cluster. Barriers to rapid cluster analysis include delays in obtaining patient interviews, incomplete food histories, and molecular subtyping not being performed. In 2012, surveillance metrics for the Listeria Initiative were introduced as a way to measure timeliness and completeness of reporting of epidemiologic information; 2-year national reporting goals were proposed. While some metrics have improved, none have met the proposed 2-year national reporting goals. Strategies for improving on the areas assessed by these metrics will be discussed. The effectiveness of the Listeria Initiative is maximized when molecular subtyping data are integrated with epidemiological data. In 2013, data closeout included a new component where states reviewed existing linkages between epidemiologic and molecular subtyping data to identify errors, link un-linked data, and help identify reasons why epidemiologic or molecular subtyping data remained missing or un-linked. This process increased cases with epidemiologic data linked to molecular subtyping data by 7% and identified challenges that states face in collecting linked data. Given this success, CDC plans to implement a new ongoing process to continually monitor linkages between molecular subtyping and epidemiologic data, alerting states to situations in which either has not been reported. Ongoing evaluation of these linkages can help identify strategies for improvement. We are requesting feedback on this proposed process and discussion on ways to overcome challenges in obtaining linked data. Improvement in reporting timeliness and completeness of epidemiologic data in conjunction with maximized linkages between epidemiological and molecular subtyping data will allow for quicker identification of foods possibly associated with clusters.