AbstractObjectiveTo streamline carbapenem-resistant enterobacteriaceae (CRE)surveillance by integrating electronic laboratory reporting (ELR)data and electronic case reports (eCR) automatically into Illinois’extensively drug-resistant organism (XDRO) registry.IntroductionCRE are drug-resistant bacteria that have a mortality rate of up to50% in those infected1. Several clusters of CRE have been detected inIllinois, often in long-term acute care hospitals2. In response Illinoiscreated the XDRO registry, a mandatory reporting system designedto aid inter-facility communication concerning CRE.Despite being a high priority for control in the US, the casedefinition for CRE has been the subject of debate3. There are over70 Enterobacteriaceae which can have different mechanisms ofcarbapenem resistance3. Criteria for carbapenem resistance includesusceptibility results, and phenotypic or genotypic detection. Thecase definition for the XDRO registry is intentionally more exclusive(specific) than that used by CSTE (Table 1). CSTE utilizes adefinition designed to maximize sensitivity. Illinois’ XDRO registry’sdefinition is more specific, meant to reduce unnecessary adoption ofcontact precautions and the negative consequences some patients mayexperience.Currently, case reporting to the XDRO registry is a manual dataentry process, which has important advantages. However, transitioningto automatic ELR integration will streamline the reporting processand minimize data entry effort. Unfortunately, the clinical informationneeded to investigate XDROs is often not captured by ELR. The eCRis a new message type being piloted in Illinois that contains manyclinical data elements. We examined the feasibility of combining ELRand eCR into reports for the XDRO registry. In the construction ofthese reports we examined the impact of using CRE definitions fromCSTE and the XDRO registry.MethodsWe obtained sample HL7 CRE messages from Illinois’ ELRdatabase. Using these messages and the HL7 Implementation Guidefor Electronic Laboratory Reporting, we mapped ELR fields to thosein the XDRO registry. Specific codes corresponding to the registryfields were found though a systematic keyword search of LOINC,SNOMED, and sample messages. When there was no match for anXDRO field in ELR, we referred to the HL7 CDA ImplementationGuide for the Electronic Initial Case Report and sample eCRmessages. A collection of fields and codes was created to correspondto both the CSTE and Illinois CRE case definition.ResultsThe XDRO registry has 37 unique fields. Twenty-six can bepopulated from ELR, four can be found in the eCR, and seven aregenerated within the system. In sample ELR and eCR messages all ofthe necessary fields were populated with appropriate text and codes.The mapping process was straightforward for demographic andfacility information, but more complicated for culture and organisminformation. Some XDRO tests do not have corresponding LOINCor SNOMED codes, so we will develop a logic statement to fill thesebased on free-text. Addition of the eCR adds important informationto the registry report, notably encounter type and encounter/admissiondate. We were able to create separate mapping schemas for theCSTE and XDRO registry definitions for CRE. Using each of thesedefinitions, we will quantify how many ELR messages would becommitted to the XDRO registry.ConclusionsBy combining the data captured in ELR and eCR, it is possible topopulate the fields of the Illinois XDRO registry. When this merge iscompleted it should result in more complete and better quality dataon CRE in Illinois. As intended, the definition of CRE used by theregistry is less inclusive than that used by CSTE. Future work willshow the number of CRE lab results captured by each definition.Table 1: CRE Definition
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