- Remove Inpatient filter Inpatient
Search found 50 items
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 project will evaluate a computerized provider order entry (CPOE)-based function—medication voiding—that can be used to prospectively identify and document medication ordering errors.
This pilot project implemented a Social Knowledge Networking system and concluded that it supported progress toward meaningful use of medication reconciliation technology in an electronic health record.
This research created, piloted, and evaluated FIQS, the Family Input to Quality and Safety tool, that allows pediatric patients and their caregivers to provide safety reports regarding their inpatient care.
This research demonstrated primary care providers’ complementary use of “push” and “pull” health information exchange technologies to meet their information needs and provides evidence that “pull” exchange reduces potentially avoidable healthcare utilization.
The project will develop and test a large set of alerts at two large health systems to demonstrate that alerts can help prevent wrong-drug and wrong-patient errors and improve the completeness of the problem list.