Design and Implementation of a Visual Analytics Electronic Antibiogram within an Electronic Health Record System at a Tertiary Pediatric Hospital

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.

[1]  Jorge A. Gálvez,et al.  Visual analytical tool for evaluation of 10-year perioperative transfusion practice at a children's hospital , 2014, J. Am. Medical Informatics Assoc..

[2]  Jorge A. Gálvez,et al.  A visual analytics antibiogram dashboard as part of a comprehensive approach to perioperative antibiotic administration , 2014, AMIA.

[3]  P. Tamma,et al.  Pediatric Antimicrobial Susceptibility Trends across the United States , 2013, Infection Control & Hospital Epidemiology.

[4]  Jorge A. Gálvez,et al.  Optimization of drug-drug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard , 2015, J. Am. Medical Informatics Assoc..

[5]  R. Humphries,et al.  Anticipating the Unpredictable: A Review of Antimicrobial Stewardship and Acinetobacter Infections , 2017, Infectious Diseases and Therapy.

[6]  W. Bilker,et al.  Comparison of Unit-Specific and Hospital-Wide Antibiograms Potential Implications for Selection of Empirical Antimicrobial Therapy , 2006, Infection Control & Hospital Epidemiology.

[7]  S. Cosgrove The relationship between antimicrobial resistance and patient outcomes: mortality, length of hospital stay, and health care costs. , 2006, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[8]  R. Banerjee,et al.  Comparison of hospital-wide and age and location - stratified antibiograms of S. aureus, E. coli, and S. pneumoniae: age- and location-stratified antibiograms , 2013, SpringerPlus.

[9]  Y. Carmeli,et al.  The negative impact of antibiotic resistance. , 2016, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.

[10]  P. Dayan,et al.  Current State of Antimicrobial Stewardship in Children’s Hospital Emergency Departments , 2017, Infection Control & Hospital Epidemiology.

[11]  J. Jorgensen,et al.  Medical Microbiology: New Consensus Guidelines from the Clinical and Laboratory Standards Institute for Antimicrobial Susceptibility Testing of Infrequently Isolated or Fastidious Bacteria , 2007 .

[12]  K. Kaye,et al.  Infections Caused by Resistant Gram‐Negative Bacteria: Epidemiology and Management , 2015, Pharmacotherapy.

[13]  John Stelling,et al.  Medical Microbiology: Analysis and Presentation of Cumulative Antibiograms: A New Consensus Guideline from the Clinical and Laboratory Standards Institute , 2007 .

[14]  Joshua D. Courter,et al.  Sharing Antimicrobial Reports for Pediatric Stewardship (SHARPS): A Quality Improvement Collaborative , 2017, Journal of the Pediatric Infectious Diseases Society.

[15]  Chandler Stolp,et al.  The Visual Display of Quantitative Information , 1983 .

[16]  R. Weber,et al.  Stratification of cumulative antibiograms in hospitals for hospital unit, specimen type, isolate sequence and duration of hospital stay. , 2008, The Journal of antimicrobial chemotherapy.

[17]  James J. Thomas,et al.  Defining Insight for Visual Analytics , 2009, IEEE Computer Graphics and Applications.