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 establish the Clinical Decision Support Innovation Collaborative 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 aims to examine a health system’s four telehealth programs in response to the COVID-19 pandemic.
This research developed a publicly available cost-effectiveness model for programs combining pharmacogenomics testing with clinical decision support alerts, so that decision makers may more robustly evaluate whether or not to implement such a program.
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 research will develop, implement, disseminate, and evaluate reusable, shareable clinical decision support for both patients and clinicians in the area of chronic pain management.
This research will develop, implement, disseminate, and evaluate reusable, shareable clinical decision support for both patients and clinicians in the area of chronic pain management.
This research will evaluate the lifecycle of clinical decision support (CDS), as currently implemented at most health systems, against a future CDS state that incorporates the use of shareable CDS resources created using the Agency for Healthcare Research and Quality’s CDS Connect tools.
This study used learning health system methods to systematically apply U.S. Preventive Services Task Force’s evidence-based recommendations with the goal of advancing individualized precision prevention.
The 2018-2020 annual Conference on Health IT & Analytics connected a wide range of academic disciplines, Federal agencies, policymakers, funders, practitioners, patient advocates, and industry professionals to develop a health information technology and analytics (HIT+A) research agenda and materials that were widely disseminated to identify trends and knowledge gaps in HIT+A.
