Adults
Clusters of health-related social needs among adult primary care patients.
Enhancing patient engagement and understanding: Is providing direct access to laboratory results through patient portals adequate?
Association rule mining of real-world data: Uncovering links between race, glycemic control, lipid profiles, and suicide attempts in individuals with diabetes.
Predicting suicide attempts among people with diabetes using a large multicenter electronic health records dataset.
Cultural adaptations of psychological interventions for prevalent sleep disorders and sleep disturbances: A systematic review of randomized controlled trials in the United States.
Complexity, Incidence, and Costs Related to Delayed Diagnosis of Venous Thromboembolism in Urban and Rural Primary and Urgent Care Settings
This research aims to improve the early detection of venous thromboembolism in primary and urgent care by using mixed methods (stakeholder interviews and surveys, electronic health records, and machine learning) to better understand missed and delayed diagnoses, identify risk factors, and develop tools to enhance patient safety.
Examining the Feasibility and Effectiveness of an mHealth Solution Designed to Enhance Clinical Outcomes Among Patients Attending Physical Therapy for Musculoskeletal Pain
This research examines whether remote therapeutic monitoring can improve physical therapy outcomes by increasing patient engagement, adherence to home exercises, and communication with providers, while also assessing its impact on healthcare costs and feasibility for broader implementation.
Identifying Sepsis Phenotypes Associated with Antibiotic-Resistant Pathogens Using Large Language Models and Machine Learning
This research uses large language models and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis and identify patterns in treatment outcomes, with the goal of shaping future clinical guidelines that help doctors select the most effective antibiotics for each patient, reduce unnecessary use of broad-spectrum antibiotics, lower the risks of drug resistance, and ultimately improve patient outcomes.
Guiding the Safe and Effective Integration of Ambient Digital Scribes into Primary Care
This study will develop a prototype guide for the safe and effective integration of ambient digital scribes into primary care, providing insights into how this artificial intelligence-driven technology transforms workflows while addressing critical safety and burnout concerns in diverse healthcare settings.