The study will create, implement, and test a patient-centric web app to support older adults with chronic conditions in comprehending, managing, and acting upon their lab test results.
This research will enhance, refine, and evaluate an artificial intelligence-supported tool that collects patient-reported outcomes to inform care and improve glycemic control for patients with poorly controlled diabetes.
This research will enhance an existing mobile platform to support self-management and shared decision making for those with asthma. Researchers will use patient-reported outcomes and calculate a Respiratory Symptoms Risk Score using voice biomarkers, with the aim of improving outcomes.
This research is developing and evaluating a machine learning algorithm that uses existing electronic health record data to predict childhood asthma treatment response and better inform personalized treatment.
This research will utilize user-centered design to develop and implement a self-management education and support module called Support-Engage-Empower-Diabetes (SEE-Diabetes) to improve diabetes management in older adults.
This research will develop, implement, and evaluate an artificial intelligence-enabled workflow that would allow for online reading and same-day diagnostic imaging following screening mammography in breast cancer screening clinics.
To assist pregnant individuals with pre-pregnancy type 2 diabetes with Medicaid coverage in reaching and maintaining normal blood sugars, this research will develop, test, and evaluate a digital health solution called ACHIEVE that includes a mobile health application, a provider dashboard, continuous glucose monitoring, and team-based coaching for medical needs and nonmedical health-related social needs.
This study will develop, evaluate, and disseminate a multicomponent intervention including a mobile health application and digital navigator training to support safe care transitions for patients with multiple chronic conditions.
This research will apply Substitutable Medical Applications, Reusable Technologies (SMART)-on-Fast Healthcare Interoperability Resources (FHIR) standards to a current patient-centered web-based application (app) for heart failure medication optimization and evaluate its effectiveness in guideline-directed medication prescribing for heart failure.
This research will refine an existing interoperable, patient-facing blood pressure control tool--the Collaboration Oriented Approach to Controlling High Blood Pressure (COACH) application--evaluate its implementation into three diverse clinical settings; conduct a randomized trial to assess its impact on lowering blood pressure; and develop a shareable, interoperable mechanism to aid in the dissemination of patient-facing clinical decision support tools.
