Introduction: Telehealth approaches have demonstrated benefits in improving positive airway pressure (PAP) compliance in patients with obstructive sleep apnea (OSA), improving access to healthcare resources, and improving health outcomes for rural communities. Methods: This quality improvement (QI) pilot study implemented weekly telemedicine visits for four weeks of PAP therapy in rural patients newly diagnosed with OSA. Epworth Sleepiness Scale (ESS) scores were compared prior to and at one month of therapy. PAP compliance was compared between rural patients who received the telemedicine intervention and a group of patients not receiving the telemedicine intervention. Results: Compliance rates were higher in the intervention group. There was not a significant difference in compliance for the intervention group (M = 63.22, SD = 32.78) versus the control group (M = 46.40, SD = 36.24), t (46) = 1.69, p = 0.099. ESS scores were significantly greater prior to one month of therapy (M = 8.38, SD = 5.70) compared to after one month of therapy (M = 2.83, SD = 2.65), t (23) = 5.22, p < 0.001, d = 1.07. Discussion: This QI pilot study utilized telemedicine to remove barriers to care, improve PAP compliance, and improve health outcomes for this underserved, rural population.

Objectives: Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States, with a lifetime prevalence of more than 80%. HPV is associated with cervical cancer, which affects thousands of US women each year. A vaccine was introduced in 2006 to mitigate the prevalence and mortality of HPV-associated cancers. Although HPV vaccine adherence has increased over time,...

Background/Objectives: Pediatric obstructive sleep apnea (OSA) is a complex disorder with a variable presentation and often challenging diagnostic testing. The history and physical examination in pediatric OSA frequently differ from those in adults. The treatment options are multifaceted and must be tailored to the individual patient. Artificial intelligence (AI) modalities currently employed in pediatric sleep medicine face several important limitations: modality fragmentation, lack of explainability, and limited semantic integration. Method: Our team proposes a new vision for AI and pediatric sleep medicine. This platform is based on a knowledge graph (KG) framework integrating structured and unstructured data to enable reasoning, personalization, and clinical decision support. Results: This framework represents a conceptual architecture; it has not yet been empirically implemented, and the use cases described herein are illustrative of its intended capabilities. Components of the infrastructure developed for similar applications have been successfully implemented. The quantitative feasibility pilot KG represented 100% multimodal data with >90% semantic completeness. Conclusions: Fully realized and deployed into the clinical space, this pediatric OSA KG system will enhance tertiary care programs and help project tertiary-level pediatric care into underserved regions.