This research will develop, train, test, and evaluate a machine learning classifier to identify risk for HIV acquisition or transmission among hospitalized patients with substance misuse.
This research will study the effectiveness of a virtual in-home program designed to reduce hospital readmissions among COPD patients post-hospitalization.
This research will adapt and implement a digital mental health intervention to improve care coordination of mental health services in ambulatory care settings.
This research continues to build the Clinical Decision Support Innovation Collaborative (CDSiC) to advance the field of patient-centered clinical decision support, including a focus on conducting CDS research initiatives and projects in real-world applications.
This research will assess the impact of AHRQ’s 2016 clinical decision support (CDS) initiative, understand the current state of patient-centered CDS, and identify gaps for future research.
This project will evaluate the feasibility of implementing a quality improvement-driven, health information technology-enabled method for capturing patient-reported outcomes (PROs) after ambulatory surgical procedures.
This research developed and evaluated the Prevent Diabetes Mellitus Clinical Decision Support tool and found that its use improved processes related to care.
This research used a depression screening questionnaire administered via a patient portal and compared its use to usual in-clinic care. Research findings showed that questionnaire administration via the portal increased the number of patients both screened and monitored for depression.
This project will expand, implement, and evaluate the use of a cancer screening platform, the Oncology Symptom Screening Initiative (OSSI), to improve psychosocial screening of cancer patients.
This research studied whether clinical decision support could reduce contextual errors, improve patient healthcare outcomes, and reduce misuse and overuse of medical services.
