Abstract
Background Hospitals use antibiograms to guide optimal empiric antibiotic therapy, reduce inappropriate
antibiotic usage, and identify areas requiring intervention by antimicrobial stewardship
programs. Creating a hospital antibiogram is a time-consuming manual process that
is typically performed annually.
Objective We aimed to apply visual analytics software to electronic health record (EHR) data
to build an automated, electronic antibiogram (“e-antibiogram”) that adheres to national
guidelines and contains filters for patient characteristics, thereby providing access
to detailed, clinically relevant, and up-to-date antibiotic susceptibility data.
Methods We used visual analytics software to develop a secure, EHR-linked, condition- and
patient-specific e-antibiogram that supplies susceptibility maps for organisms and
antibiotics in a comprehensive report that is updated on a monthly basis. Antimicrobial
susceptibility data were grouped into nine clinical scenarios according to the specimen
source, hospital unit, and infection type. We implemented the e-antibiogram within
the EHR system at Children's Hospital of Philadelphia, a tertiary pediatric hospital
and analyzed e-antibiogram access sessions from March 2016 to March 2017.
Results The e-antibiogram was implemented in the EHR with over 6,000 inpatient, 4,500 outpatient,
and 3,900 emergency department isolates. The e-antibiogram provides access to rolling
12-month pathogen and susceptibility data that is updated on a monthly basis. E-antibiogram
access sessions increased from an average of 261 sessions per month during the first
3 months of the study to 345 sessions per month during the final 3 months.
Conclusion An e-antibiogram that was built and is updated using EHR data and adheres to national
guidelines is a feasible replacement for an annual, static, manually compiled antibiogram.
Future research will examine the impact of the e-antibiogram on antibiotic prescribing
patterns.
Keywords
antibiogram - electronic health records - clinical decision support systems - analytics
- data visualization - pediatrics - quality improvement
