This research will use digital health tools leveraging patient-reported outcomes and data from electronic health records to engage individuals with multiple chronic conditions to improve understanding of individualized risk of adverse events during care transitions.
This research will examine the acceptability and usability of a shared decision making tool that incorporates risk information and patient and caregiver preferences for Hospital at Home, an acute care alternative to traditional inpatient hospitalization.
This research will study the implementation of Telehealth Education for Asthma Connecting Hospital and Home (TEACHH), a novel intervention designed to provide an effective asthma educational platform appropriate for all health literacy levels. The intervention includes initial instruction in the hospital and reinforcement at home using virtual visits to reduce barriers to self-management support for children who are hospitalized due to asthma.
Leveraging Health System Telehealth and Informatics Infrastructure to Create a Continuum of Services for COVID-19 Screening, Testing, and Treatment: A Learning Health System Approach
This research aims to examine a health system’s four telehealth programs in response to the COVID-19 pandemic.
This research aims to develop and evaluate a clinical decision support strategy to promote influenza vaccination among children who are hospitalized with the goal to identify insights that broadly apply to clinical decision support for health maintenance interventions in pediatric acute care settings.
This research will evaluate a novel, technology-enabled intervention that will determine the impact of bedside shift reporting and hourly rounding on nurse-sensitive patient outcomes.
This research will demonstrate the use of standards, including SMART on FHIR, combined with service-oriented architecture to bring vendor-agnostic clinical decision support (CDS) tools into commercial electronic health records, and provide evidence for how to implement validated CDS for important clinical domains, pulmonary, and venous thromboembolism, including for patients with COVID-19.
This project will develop and evaluate an electronic clinical decision support tool for care of patients with Acute Respiratory Distress Syndrome.
This research assessed the etiology of medication ordering errors, finding that errors stemmed from multi-level risk factors and showing the utility of a void alert tool to prospectively capture the broad range of errors that may occur in practice that may be missed by using traditional retrospective error reporting methods.