ChatGPT Use Among Pediatric Health Care Providers: Cross-Sectional Survey Study.

Background: The public launch of OpenAI's ChatGPT platform generated immediate interest in the use of large language models (LLMs). Health care institutions are now grappling with establishing policies and guidelines for the use of these technologies, yet little is known about how health care providers view LLMs in medical settings. Moreover, there are no studies assessing how pediatric providers are adopting these readily accessible tools.

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.

Changes Made to Orders Placed by Overnight Admitting Residents on Teaching Rounds the Next Day.

Objectives: Increased focus on health care quality and safety has generally led to additional resident supervision by attending physicians. At our children's hospital, residents place orders overnight that are not explicitly reviewed by attending physicians until morning rounds. We aimed to categorize the types of orders that are added or discontinued on morning rounds the morning after admission to a resident team and to understand the rationale for these order additions and discontinuations.

COVID-19 Impact on Intern Exposure to Common Inpatient Diagnoses.

Objective: We sought to understand the impact of the coronavirus disease 2019 (COVID-19) pandemic on the clinical exposure of pediatric interns to common pediatric inpatient diagnoses.

Methods: We analyzed electronic medical record data to compare intern clinical exposure during the COVID-19 pandemic from June 2020 through February 2021 with the same academic blocks from 2017 to 2020. We attributed patients to each pediatric intern on the basis of notes written during their pediatric hospital medicine rotation to compare intern exposures with common inpatient diagnoses before and during the pandemic.

COVID-19 Impact on Intern Exposure to Common Inpatient Diagnoses.

Objective: We sought to understand the impact of the coronavirus disease 2019 (COVID-19) pandemic on the clinical exposure of pediatric interns to common pediatric inpatient diagnoses.

Methods: We analyzed electronic medical record data to compare intern clinical exposure during the COVID-19 pandemic from June 2020 through February 2021 with the same academic blocks from 2017 to 2020. We attributed patients to each pediatric intern on the basis of notes written during their pediatric hospital medicine rotation to compare intern exposures with common inpatient diagnoses before and during the pandemic.

A Quality Improvement Initiative to Decrease Platelet Ordering Errors and a Proposed Model for Evaluating Clinical Decision Support Effectiveness.

Background And Objectives: Clinical decision support (CDS) and computerized provider order entry have been shown to improve health care quality and safety, but may also generate previously unanticipated errors. We identified multiple CDS tools for platelet transfusion orders. In this study, we sought to evaluate and improve the effectiveness of those CDS tools while creating and testing a framework for future evaluation of other CDS tools.