This research evaluated the impact of a telerehabilitation approach among stroke survivors with aphasia, finding it was a cost-effective, feasible approach with high patient satisfaction.
This project will develop and test a personalized motivational text messaging intervention to improve management of diabetes and depression in low-income populations.
In this study, researchers assessed the feasibility of using commercial off-the-shelf mobile technology, including phones and fitness trackers, to collect and report patient-generated health data and patient-reported outcomes from diverse, disadvantaged patients in an urban safety net health care system.
This research assessed the use of a health information exchange system in emergency department settings, finding that although overall usage is relatively low, additional functionalities such as single sign on add value to clinical decision making and enable faster retrieval of patient records from external sources compared to traditional methods when embedded into existing workflows.
This project will develop and disseminate an innovative communication system to identify and mitigate health risks for young African American women before pregnancy as a means of reducing health disparities in birth outcomes.
This research used natural language processing and machine learning to develop algorithms to recognize diagnostic criteria in free text for autism spectrum disorder, to increase earlier diagnosis and treatment.
This project will evaluate the comparative effectiveness of asynchronous telepsychiatry versus synchronous telepsychiatry in a skilled nursing facility population using a 12-month randomized controlled trial.
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.
This study showed the feasibility and value of creating a methodology and process for a health information technology black box to inform electronic health record design and usability.
This project will enhance novel algorithms for matching patient health information across data sources, implement them, and evaluate their accuracy.