This research will assess the validity of patient-level computable social factor phenotypes used to predict a patient’s risk of increased healthcare utilization and costs.
This research study will pilot test BedsideNotes—a new capability within the inpatient portal to share physicians’ admission and daily notes with parents of children hospitalized on hematology/oncology and neonatal intensive care units.
This research will develop, train, test, and evaluate a machine learning classifier to identify risk for HIV acquisition or transmission among hospitalized patients with substance misuse.
This research will study the effectiveness of a virtual in-home program designed to reduce hospital readmissions among COPD patients post-hospitalization.
This research will study how a safety-net hospital responds to a pandemic, specifically COVID-19, to identify how information needs are met and how decisions are made and communicated to other individuals internal and external to the institution.
This is a questionnaire designed to be completed by physicians and clinical staff in a hospital. The tool includes questions to assess the current state of electronic health records/electronic medical record.
