Roberts Emily

The emerging threat of antimicrobial resistant organisms is a pressing public health concern. Surveillance for antimicrobial resistance can prevent infections, protect patients in the healthcare setting and improve antimicrobial use. In 2018, the Utah Department of Health mandated the reporting of antimicrobial susceptibility panels performed on selected organisms. Utah utilizes the Electronic Message Staging Area (EMSA), a home-grown application to translate, process, and enter electronic laboratory results into UT-NEDSS, Utah'™s integrated disease surveillance system. Processing these results electronically is challenging due to the need to interpret results based on the antimicrobial agent combined with the organism it was performed on. The receipt of antimicrobial susceptibility panels has required enhancements to EMSA for these results to be automatically processed.

Objective: Illustrate how the Utah Department of Health automatically processes antimicrobial susceptibility results that are received electronically

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)’s 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 Utah’s 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.

In 2013, the Utah Department of Health (UDOH) began working with hospital and reference laboratories to implement electronic laboratory reporting (ELR) of reportable communicable disease data. Laboratories utilize HL7 message structure and standard terminologies such as LOINC and SNOMED to send data to UDOH. These messages must be evaluated for validity, translated, and entered into Utah’s communicable disease surveillance system (UT-NEDSS), where they can be accessed by local and state investigators and epidemiologists. Despite the development and use of standardized terminologies, reporters may use different, outdated versions of these terminologies, may not use the appropriate codes, or may send local, home-grown terminologies. These variations cause problems when trying to interpret test results and automate data processing. UDOH has developed a two-step translation process that allows us to first standardize and clean incoming messages, and then translate them for consumption by UT-NEDSS. These processes allow us to efficiently manage several different terminologies and helps to standardize incoming data, maintain data quality, and streamline the data entry process.

Objective:

The objective of this abstract is to illustrate how the Utah Department of Health processes a high volume of electronic data. We do this by translating what reporters send within an HL7 message into "epidemiologist" language for consumption into our disease surveillance system.