An Algorithm to Assess Guideline Concordance of Antibiotic Choice in Community-Acquired Pneumonia.

Background And Objective: This study aimed to develop and evaluate an algorithm to reduce the chart review burden of improvement efforts by automatically labeling antibiotic selection as either guideline-concordant or -discordant based on electronic health record data for patients with community-acquired pneumonia (CAP).

Methods: We developed a 3-part algorithm using structured and unstructured data to assess adherence to an institutional CAP clinical practice guideline. The algorithm was applied to retrospective data for patients seen with CAP from 2017 to 2019 at a tertiary children's hospital.

Digital Antimicrobial Stewardship Decision Support to Improve Antimicrobial Management.

Objectives: We sought to create a digital application to support clinicians in empiric and pathogen-directed antibiotic ordering based on local susceptibility patterns and evidence-based treatment durations, thereby promoting antimicrobial stewardship.

Methods: We formed a multidisciplinary team that met bimonthly from 2017 to 2018 to design and construct a web-based antimicrobial stewardship platform called Antibiogram + . We used an iterative and agile technical development process with frequent feedback from clinicians.

Design, Usability, and Acceptability of a Needs-Based, Automated Dashboard to Provide Individualized Patient-Care Data to Pediatric Residents.

Background And Objectives: Pediatric residency programs are required by the Accreditation Council for Graduate Medical Education to provide residents with patient-care and quality metrics to facilitate self-identification of knowledge gaps to prioritize improvement efforts. Trainees are interested in receiving this data, but this is a largely unmet need. Our objectives were to (1) design and implement an automated dashboard providing individualized data to residents, and (2) examine the usability and acceptability of the dashboard among pediatric residents.