Development of a 51-hospital Chicagoland regional antibiogram and comparison to local hospital and national surveillance data.

ABSTRACT

OBJECTIVE: To develop a regional antibiogram within the Chicagoland metropolitan area and to compare regional susceptibilities against individual hospitals within the area and national surveillance data. DESIGN: Multicenter retrospective analysis of antimicrobial susceptibility data from 2017 and comparison to local institutions and national surveillance data. SETTING AND PARTICIPANTS: The analysis included 51 hospitals from the Chicago-Naperville-Elgin Metropolitan Statistical Area within the state of Illinois. Overall, 18 individual collaborator hospitals provided antibiograms for analysis, and data from 33 hospitals were provided in aggregate by the Becton Dickinson Insights Research Database. METHODS: All available antibiogram data from calendar year 2017 were combined to generate the regional antibiogram. The final Chicagoland antibiogram was then compared internally to collaborators and externally to national surveillance data to assess its applicability and utility. RESULTS: In total, 167,394 gram-positive, gram-negative, fungal, and mycobacterial isolates were collated to create a composite regional antibiogram. The regional data represented the local institutions well, with 96% of the collaborating institutions falling within ±2 standard deviations of the regional mean. The regional antibiogram was able to include 4-5-fold more gram-positive and -negative species with ≥30 isolates than the median reported by local institutions. Against national surveillance data, 18.6% of assessed pathogen-antibiotic combinations crossed prespecified clinical thresholds for disparity in susceptibility rates, with notable trends for resistant gram-positive and gram-negative bacteria. CONCLUSIONS: Developing an accurate, reliable regional antibiogram is feasible, even in one of the largest metropolitan areas in the United States. The biogram is useful in assessing susceptibilities to less commonly encountered organisms and providing clinicians a more accurate representation of local antimicrobial resistance rates compared to national surveillance databases.