This multi-site qualitative study explores how hospitalist clinicians optimize the presence of medical learners on direct care teaching services. Dr. Catherine Callister and colleagues interviewed clinicians at 26 academic medical centers to understand the strategies, tensions, and values that shape learner engagement on busy inpatient teams. Findings reveal how hospitalists balance patient care demands with their teaching mission, often adapting workflows, communication patterns, and supervision approaches in real time. Themes include the importance of intentional team design, alignment of roles with learner level, and the tension between clinical work and time for education in busy clinical settings. This work sheds light on the real-world complexity of clinical education in hospital medicine and offers insights to guide the design of sustainable, high-value teaching services.

Children with sickle cell disease (SCD) often come to the emergency department (ED) for severe pain, but care can vary across hospitals. This study looked at more than 9,000 ED visits in the U.S. to see whether giving opioid pain medicine quickly affected hospital admissions. Children who received their first dose within 60 minutes were less likely to be hospitalized, and the chance of admission dropped even further when a second dose was given within 30 minutes. These findings highlight the importance of timely pain treatment and suggest that faster opioid delivery can improve outcomes and reduce unnecessary hospital stays for children with SCD.

A landmark study led by infectious diseases specialists at University of Colorado Anschutz Medical Campus/Children’s Hospital Colorado was recently published in The Lancet Infectious Diseases. The article is the first from a multicenter clinical research pilot study run through the National Institutes of Health's Vaccine Research Center’s Pandemic REsponse REpository through Microbial and Immune Surveillance and Epidemiology (PREMISE) program. The PREMISE pilot study conducts immunologic surveillance and data collected from the first year, 2022-2023, provides insight into what was driving the large post-pandemic rebound of common respiratory pathogens in children. Data also allowed for the recreation of past viral circulation patterns and model predictions for future outbreaks with greater accuracy and precision, helping hospitals, health agencies, and policymakers better prepare for future outbreaks.

Pediatric sepsis is a leading cause of death for children, and an emergency in which timely diagnosis and treatment are lifesaving. This study sought to address a gap in knowledge around approaches to diagnose pediatric sepsis in the earliest stages. In a cluster-randomized trial in four Children’s Hospital Colorado Emergency Departments, this study implemented decision support to predict septic shock and measured its effect on treatment and outcomes. The clinical decision support was developed at Children’s Hospital and the University of Colorado, based on models that use extant EHR data to predict septic shock. This was the first reported prospective, controlled trial of decision support intended to aid in early pediatric sepsis diagnosis and treatment. While papers have previously described implementation of consensus-based tools for sepsis diagnosis, few have been based on derived, validated models, and they have not been prospective trials. Findings indicate that implementation of decision support based on machine learning models to predict septic shock was feasible and acceptable to clinicians. However, it did not change the outcomes for patients, in this setting of EDs with pre-existing high-quality sepsis care.