Specialty Care

This research will evaluate the effectiveness of Bedside Notes, a digital health solution designed to provide caregivers with real-time access to clinical notes during their child’s hospitalization, with the goal of improving caregiver engagement in identifying and reporting safety concerns to reduce medical errors.

This research develops and evaluates an artificial intelligence-enhanced pretreatment peer-review process in radiation oncology, aiming to improve patient safety by reducing variability among providers in treatment planning, minimizing clinical errors, and enhancing overall treatment outcomes.

This study aims to optimize the use of donor hearts for infants and children awaiting heart transplantation by developing predictive models to assess in real-time the potential for transplant success and to evaluate risk. Researchers plan to display these data through intuitive visualizations on a custom-built interface to reduce clinicians’ cognitive burden, enhance decision making confidence, and help ensure the best donor match for pediatric patients.

The study will create and implement digital tools using the SMART on FHIR framework to support Age-Friendly care in clinical practice and institutional decision-making.

This research will implement, evaluate, and disseminate DDInteract, a shared decision making clinical decision support tool that aims to reduce harm from oral anticoagulant drug-drug interactions.

This research will develop, validate, and evaluate a decision support tool using a machine learning algorithm to standardize the approach to discontinuing disease-modifying therapies for multiple sclerosis.

This research will improve upon and evaluate a telehealth lung cancer surveillance program that combines patient-reported outcomes and assessment of remotely completed surveillance lung imaging with telehealth visits, to reduce barriers to lung cancer surveillance care. 

This research will culminate in a randomized controlled trial of the Peer PLUS (People Leveraging Urgent Support) mobile app and companion web-based platform that supports communication between those with substance use disorder and peer recovery coaches to determine if it contributes to long-term recovery for these individuals.

This research will design, develop, implement, and evaluate the Patient Centered Adaptive Treatment Strategies (PCATS) juvenile idiopathic arthritis (JIA) tool called “PCATS.JIA.” a shared decision-making tool for monitoring and treatment of polyarticular juvenile idiopathic arthritis in children.

This research will enhance an existing mobile platform to support self-management and shared decision making for those with asthma. Researchers will use patient-reported outcomes and calculate a Respiratory Symptoms Risk Score using voice biomarkers, with the aim of improving outcomes.