This project integrated a validated anxiety-specific screening tool in an existing clinical decision support system and tested it with a randomized feasibility pilot that found the tool did not increase detection of anxiety in pediatric primary care.
The project team developed a technical brief on the current literature around core functionalities for pediatric electronic health records to describe current practice and to provide a framework for future research.
This project developed, implemented, and evaluated a program that includes clinical decision support to improve diagnosis of hypertension in children.
This project developed a tool to promote activation, communication, engagement, and self-management of pediatric blood and marrow transplant patients and their parents and found that patient-centric tools can successfully engage caregivers in hospital care.
This research applied machine learning to develop a model predicting surgical cancellations among pediatric patients, and found the feasibility in using these algorithms as a cost-effective quality-improvement measure.
This project will evaluate and compare different tools within electronic health records to assist pediatric primary care clinicians with providing higher quality childhood obesity care to help slow weight gain in children with obesity.
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 assessed the use of a multi-risk adolescent interactive health assessment screening tool in pediatric primary care settings, which found an increased rate of clinician counseling for endorsed behaviors, but no significant change in reported risk behaviors or patient satisfaction.
This research study addressed the overuse of blood cultures to diagnose sepsis by developing an electronic health record-embedded clinical decision support tool that draws upon the strengths of analytical and naturalistic decision making.
This project enhanced the Children’s Electronic Health Record Format (Format) by identifying a high priority set of 47 functional requirements from the initial larger set, and creating a list of 16 recommended uses of the Format along with implementation notes.
