National initiatives, such as Meaningful Use, are automating the detection and reporting of reportable disease events to public health, which has led to more complete, timely, and accurate public health surveillance data. However, electronic reporting has also lead to significant increases in the number of cases reported to public health. In order for this data to be useful to public health, it must be processed and made available to epidemiologists and investigators in a timely fashion for intervention and monitoring. To meet this challenge, the Utah Department of Health (UDOH)âs Disease Control and Prevention Informatics Program (DCPIP) has developed the Electronic Message Staging Area (EMSA). EMSA is a system capable of automatically filtering, processing, and evaluating incoming electronic laboratory reporting (ELR) messages for relevance to public health, and entering those laboratory results into Utahâs integrated disease surveillance system (UT-NEDSS) without impacting the overall efficiency of UT-NEDSS or increasing the workload of epidemiologists.
Objective:
The objective of this abstract is to illustrate how the Utah Department of Health processes a high volume of electronic data in an automated way. We do this by a series of rules engines that does not require human intervention.