A clinical informatics approach to bronchopulmonary dysplasia: current barriers and future possibilities.

Bronchopulmonary dysplasia (BPD) is a complex, multifactorial lung disease affecting preterm neonates that can result in long-term pulmonary and non-pulmonary complications. Current therapies mainly focus on symptom management after the development of BPD, indicating a need for innovative approaches to predict and identify neonates who would benefit most from targeted or earlier interventions. Clinical informatics, a subfield of biomedical informatics, is transforming healthcare by integrating computational methods with patient data to improve patient outcomes. The application of clinical informatics to develop and enhance clinical therapies for BPD presents opportunities by leveraging electronic health record data, applying machine learning algorithms, and implementing clinical decision support systems. This review highlights the current barriers and the future potential of clinical informatics in identifying clinically relevant BPD phenotypes and developing clinical decision support tools to improve the management of extremely preterm neonates developing or with established BPD. However, the full potential of clinical informatics in advancing our understanding of BPD with the goal of improving patient outcomes cannot be achieved unless we address current challenges such as data collection, storage, privacy, and inherent data bias.

Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities.

Artificial intelligence (AI) offers tremendous potential to transform neonatology through improved diagnostics, personalized treatments, and earlier prevention of complications. However, there are many challenges to address before AI is ready for clinical practice. This review defines key AI concepts and discusses ethical considerations and implicit biases associated with AI. Next we will review literature examples of AI already being explored in neonatology research and we will suggest future potentials for AI work. Examples discussed in this article include predicting outcomes such as sepsis, optimizing oxygen therapy, and image analysis to detect brain injury and retinopathy of prematurity. Realizing AI's potential necessitates collaboration between diverse stakeholders across the entire process of incorporating AI tools in the NICU to address testability, usability, bias, and transparency. With multi-center and multi-disciplinary collaboration, AI holds tremendous potential to transform the future of neonatology.

Impact of a Pediatric Night Float on Medical Students' Education: Clerkship Student Perspectives.

OBJECTIVES: A night float, in which learners work successive overnight shifts, is increasingly used in undergraduate medical education, yet few studies have examined its impact on students. The study objective was to explore third-year medical students' perspectives on the impact on learning of a pediatric night float. METHODS: Informed by situated learning theory, we performed a qualitative study using grounded theory methodology to interview 19 third-year medical students who completed a pediatric night float between June 2019 and April 2021. Four coders analyzed data with the constant comparative method. Codes were built using an iterative approach and organized into themes. Discrepancies were resolved by consensus. RESULTS: Analysis yielded 4 themes: professional identity formation, learning activities, clinical experiences, and work-life balance. Students described positive and negative educational experiences, which were influenced by how well students integrated into the team. For some students, the night float provided opportunities to admit patients, increase confidence, and build camaraderie, which helped form professional identity. Students felt the night float was key residency preparation. Educational activities included experiential learning, teaching, and receiving feedback. Students admitted more patients and were exposed to a greater diversity of illnesses at night compared with day shifts. Fatigue was common and sending students home before morning handoff impeded their integration into the team. CONCLUSIONS: Students described varied impact of the night float on their education. A night float experience was felt to be key residency preparation. For students who felt included in the team a night float may promote professional identity formation.