Evaluating the 'timeliness' of data used in the Salmonella outbreak detection algorithm

The epidemiology of Salmonella is changing. It is being associated with a new array of vehicles and is causing large and challenging outbreaks spread over many states and nations. While laboratory surveillance systems, coupled with tools for cluster identification and rapid communication have been developed to meet this challenge, their effectiveness in rapidly identifying outbreaks depends on the availability of timely data. This pioneering exploratory study evaluated the timeliness of data collected by the National Salmonella Surveillance System (NSSS), a national laboratory-based system that collects data electronically from public health laboratories. Additionally, it probed further into the causes of untimely reporting by identifying key factors that affect public health laboratories' abilities to report timely data for national surveillance. Finally, this study proposed solutions and made recommendations for improving timeliness.; This study carried out a secondary analysis of data collected by the NSSS in 1999 to evaluate timeliness and its association with reporting frequency and volume of isolates reported. To identify key issues affecting timely reporting, content analysis of researcher's logbooks, documenting her interactions with reporting sites, was conducted.; This study documented an overall median time lag of twenty-three days with only one of forty-one sites meeting the acceptable timeliness standard of 7 days. Timeliness was not linearly associated with the number of specimen reported; however, timeliness and the frequency of transmission had a significant negative linear association with a high frequency of transmission being associated with a low time lag. The key identified as affecting timely reporting included shortage of manpower resources, information system issues, inadequate support and training, technical/infrastructure issues and lack of an incentive to report.; The results of this study provided baseline information about the timeliness of NSSS data and illustrated the need for having an ongoing audit process to ensure data quality. Additionally, this pioneering study developed an audit process that could be routinely applied to NSSS data to monitor timeliness. Finally, by identifying key areas that affect timely reporting, it provided insights into approaches that could be initiated to improve timeliness.