Federally Qualified Health Center
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.
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 project studied patient portals, their use in primary care, and the impact of use on chronic conditions, and identified opportunities to improve adoption of patient portals.
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 research team developed a smartphone application that notifies primary care providers when patients receive care in the hospital or emergency department, allowing for rapid followup care.
This project aims to improve access to high quality mental health services for diverse populations by implementing asynchronous telepsychiatry consultations combined with automated online interpreting.
This project assessed the feasibility and measurability care coordination activities and found that the electronic health record was infrequently used to support care coordination.
This project compared high and low intensity support for implementation of clinical decision support (CDS) and found that the low intensity support may be sufficient to help community health centers improve their use of CDS over a relatively short time period.
The goal of this study was to develop and evaluate electronic health record-based tools to improve diagnosis and treatment of overweight and obesity in primary care.
This project developed nine obesity care quality measures and developed and validated the use of an automated method using natural language processing to utilize the measures.