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Casey Overby Lab
Research in the Casey Overby Lab focuses on the intersection of public health genomics and biomedical informatics. We’re currently developing applications to support the translation of genomic research to clinical and population-based health care settings. We’re also working to develop knowledge-based ways to use big data — including electronic health records — to improve population health.
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Christopher Chute Lab
Work in the Christopher Chute Lab involves the management of clinical data to enable effective evidence-based clinical practice and translational research. Recently, we developed an EHR-based genetic testing knowledge base to be integrated into the genetic testing ontology (GTO) and identified potential barriers to pharmacogenomics clinical decision support (CDS) implementation.
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Fawaz Al Ammary Lab
Dr. Al Ammary’s research focuses on (1) increasing live kidney donation safely to ensure optimal outcomes for donors and (2) advancing utilization of digital health technology and electronic health records to impact the precision and value of health care for live kidney donors and kidney transplant recipients.
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Hadi Kharrazi Lab
Research in the Hadi Kharrazi Lab focuses primarily on contextualizing clinical decision support (CDS) into population health informatics (PHI) to be used at different HIT levels of managed care, including electronic health records (EHRs) and consumer health informatics (CHI) solutions. Our team has modified and regenerated electronic quality measures (eQM) based on PHI-derived CDS to represent a population aspect of the health quality measurements. Through the Center for Population Health IT (CPHIT) at the Bloomberg School of Public Health, we are pursuing PHI research that provides direct population-based CDS to providers, patients and payers.
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Harold Lehmann Lab
Researchers in the Harold Lehmann Lab study evidence-based medicine. We are currently examining the informatics infrastructure of research and the secondary use of electronic health record data for research. The team is also evaluating the value of classic evidence reports versus social media versus links to community services for community health workers.
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Jonathan Weiner Lab
The Jonathan Weiner Lab researches the impact of electronic health records (EHRs), e-health and other health information technology (HIT) on populations, integrated delivery systems and public health agencies.
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Maura McGuire Lab
The Maura McGuire Lab focuses on the improvement of quality and safety in ambulatory medicine through care management, point-of-care laboratory testing, and electronic health records and care delivery optimization. We also study the use of assessment and technology to augment learning in health care professionals and primary care physicians.
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Morgan Grams Lab
Dr. Morgan Grams and her colleagues are involved in a wide range of clinical research projects applying quantitative methods to multidimensional data to develop actionable clinical indicators. Along with Dr. Josef Coresh, Dr. Grams leads the Chronic Kidney Disease (CKD) Prognosis Consortium, a global consortium of over 200 investigators and >11 million participants (https://ckdpc.org). They have developed and validated several risk calculators that are now widely used in clinical practice (https://ckdpcrisk.org). She holds a joint appointment in the Bloomberg School of Public Health, where she is a member of the Center of Drug Safety and Effectiveness. Her research in pharmacoepidemiology leverages electronic health records from multiple countries to evaluate the risks and benefits of commonly used medications across the spectrum of kidney function. Together with her team, Dr. Grams also focuses on identifying targetab...le pathways or biomarkers that underlie the development of chronic kidney disease using multi-omic approaches.
Dr. Grams received the 2019 Frederick Brancati Mentoring Award. Currently, four of her mentees are supported by NIH K awards. More of their research can be found here: http://www.ncbi.nlm.nih.gov/myncbi/browse/collection/40940579/?sort=date&direction=descending view more
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