Pediatric informatics

The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approach. We retrospectively gathered medical data from 13 440 pediatric patients slated for surgery from 2018 to 2021. Following data preprocessing, we utilized random forests, logistic regression, linear support vector machines, gradient boosting trees, and extreme gradient boosting trees to predict these abrupt cancellations...

Background: Medication dosing calculation errors can cause significant harm to patients, especially in the pediatric population. Crushing tablets for dose division purposes may increase the risk of calculation errors, which can lead to incorrect dosing and compromised patient safety. This study aimed to develop a calculator to eliminate calculation errors associated with dose division. Methods: Using the Wix platform, a group of pharmacists created a user-friendly webpage "Dose 4 You." To enable accurate dose division calculations, the advanced language model Chat GPT and Visual Studio were used...

Artificial intelligence (AI) broadly describes a branch of computer science focused on developing machines capable of performing tasks typically associated with human intelligence. Those who connect AI with the world of science fiction may meet its growing rise with hesitancy or outright skepticism. However, AI is becoming increasingly pervasive in our society, from algorithms helping to sift through airline fares to substituting words in emails and SMS text messages based on user choices. Data collection is ongoing and is being leveraged by software platforms to analyze patterns and make predictions across multiple industries...

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...

Continuous improvement in the clinical performance of neonatal intensive care units (NICU) depends on the use of locally relevant, reliable data. However, neonatal databases with these characteristics are typically unavailable in NICUs using paper-based records, while in those using electronic records, the inaccuracy of data and the inability to customize commercial data systems limit their usability for quality improvement or research purposes. We describe the characteristics and uses of a simple, neonatologist-centered data system that has been successfully maintained for 30 years, with minimal resources and serving multiple purposes, including quality improvement, administrative, research support and educational functions...

A major barrier to deploying healthcare AI is trustworthiness. One form of trustworthiness is a model's robustness across subgroups: while models may exhibit expert-level performance on aggregate metrics, they often rely on non-causal features, leading to errors in hidden subgroups. To take a step closer towards trustworthy seizure onset detection from EEG, we propose to leverage annotations that are produced by healthcare personnel in routine clinical workflows-which we refer to as workflow notes-that include multiple event descriptions beyond seizures...

BACKGROUND: Dental phobia (DP) and injection phobia (IP) are common in children and adolescents and are considered some of the biggest obstacles to successful treatment in pediatric dentistry. Cognitive behavioral therapy (CBT) is an evidence-based treatment for anxiety and phobias. As the availability of CBT in dentistry is low, internet-based CBT (ICBT) was developed. Open trials have shown that ICBT is a promising intervention, but randomized trials are lacking. OBJECTIVE: This randomized controlled trial tests whether therapist-guided ICBT supported by a parent could reduce fear, allowing children and adolescents with DP or IP to receive dental treatment...

OBJECTIVE: Our objective was to evaluate the usability of an automated clinical decision support (CDS) tool previously implemented in the pediatric intensive care unit (PICU) to promote shared situation awareness among the medical team to prevent serious safety events within children's hospitals. METHODS: We conducted a mixed-methods usability evaluation of a CDS tool in a PICU at a large, urban, quaternary, free-standing children's hospital in the Midwest. Quantitative assessment was done using the System Usability Scale, while qualitative assessment involved think-aloud usability testing...

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are poised to have a substantial impact in the health care space. While a plethora of web-based resources exist to teach programming skills and ML model development, there are few introductory curricula specifically tailored to medical students without a background in data science or programming. Programs that do exist are often restricted to a specific specialty. OBJECTIVE: We hypothesized that a 1-month elective for fourth-year medical students, composed of high-quality existing web-based resources and a project-based structure, would empower students to learn about the impact of AI and ML in their chosen specialty and begin contributing to innovation in their field of interest...

BACKGROUND: Diagnostic codes are commonly used as inputs for clinical prediction models, to create labels for prediction tasks, and to identify cohorts for multicenter network studies. However, the coverage rates of diagnostic codes and their variability across institutions are underexplored. The primary objective was to describe lab- and diagnosis-based labels for 7 selected outcomes at three institutions. Secondary objectives were to describe agreement, sensitivity, and specificity of diagnosis-based labels against lab-based labels...

BACKGROUND: Evidence supports the effectiveness of serious games in health education, but little is known about their effects on the psychosocial well-being of children in the general population. OBJECTIVE: This study aimed to investigate the potential of a mobile game-based safety education program in improving children's safety and psychosocial outcomes. METHODS: Safe City is a mobile roleplaying game specifically designed to educate children in Hong Kong about safety...

BACKGROUND: Infants born at extremely preterm gestational ages are typically admitted to the neonatal intensive care unit (NICU) after initial resuscitation. The subsequent hospital course can be highly variable, and despite counseling aided by available risk calculators, there are significant challenges with shared decision-making regarding life support and transition to end-of-life care. Improving predictive models can help providers and families navigate these unique challenges. OBJECTIVE: Machine learning methods have previously demonstrated added predictive value for determining intensive care unit outcomes, and their use allows consideration of a greater number of factors that potentially influence newborn outcomes, such as maternal characteristics...

OBJECTIVES: The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and provide insights into the extent and nature of the disparities in the ED setting. MATERIALS AND METHODS: The study analyzed a cross-sectional dataset encompassing ED visits from January 2019 to April 2021. The study utilized analytical techniques, including K-mean clustering (KNN), multivariate adaptive regression splines (MARS), and natural language processing (NLP) embedding...

BACKGROUND: There is a global shortage of healthcare professionals, especially in developing countries, leading to disparities in access to healthcare, worsened by the pandemic. Telemedicine is emerging as a solution, with growing adoption worldwide due to advancements in technology and increased awareness. Research Problem . The establishment of telemedicine depends on resources, infrastructure, and knowledge about healthcare needs. Further studies are needed to monitor and address evolving issues in telemedicine...

BACKGROUND:  Observational research has shown its potential to complement experimental research and clinical trials by secondary use of treatment data from hospital care processes. It can also be applied to better understand pediatric drug utilization for establishing safer drug therapy. Clinical documentation processes often limit data quality in pediatric medical records requiring data curation steps, which are mostly underestimated. OBJECTIVES:  The objectives of this study were to transform and curate data from a departmental electronic medical record into an observational research database...

OBJECTIVE: The Pediatric Cancer Data Commons (PCDC)-a project of Data for the Common Good-houses clinical pediatric oncology data and utilizes the open-source Gen3 platform. To meet the needs of end users, the PCDC development team expanded the out-of-box functionality and developed additional custom features that should be useful to any group developing similar data commons. MATERIALS AND METHODS: Modifications of the PCDC data portal software were implemented to facilitate desired functionality...

BACKGROUND: Dental age is crucial for treatment planning in pediatric and orthodontic dentistry. Dental age calculation methods can be categorized into morphological, biochemical, and radiological methods. Radiological methods are commonly used because they are non-invasive and reproducible. When radiographs are available, dental age can be calculated by evaluating the developmental stage of permanent teeth and converting it into an estimated age using a table, or by measuring the length between some landmarks such as the tooth, root, or pulp, and substituting them into regression formulas...

BACKGROUND: Medication errors are common during transitions of care, such as discharge from the emergency department (ED) or urgent care (UC). The Joint Commission has identified medication reconciliation as a key safety practice. Our aim was to increase the percentage of patients with completed medication reconciliation at discharge from our pediatric ED and 4 UCs from 25% to 75% in 12 months. METHODS: Key stakeholders included ED and UC physicians and nurses, informatics, and quality management...

OBJECTIVE: Beginning in October 2021 in the USA and elsewhere, cases of severe paediatric hepatitis of unknown aetiology were identified in young children. While the adenovirus and adenovirus-associated virus have emerged as leading aetiological suspects, we attempted to investigate a potential role for SARS-CoV-2 in the development of subsequent liver abnormalities. DESIGN: We conducted a study using retrospective cohorts of deidentified, aggregated data from the electronic health records of over 100 million patients contributed by US healthcare organisations...

In this study, StyleGAN2 was trained with panoramic radiographs, and original images were projected into the latent space of StyleGAN2. The resulting latent vectors were input into StyleGAN2, and corresponding images were generated to reconstruct the original images. The original and reconstructed images were evaluated by pediatric dentists and found to be similar. Our results suggest that StyleGAN2 could be applied to the anonymization and data compression of medical images.