My research focus is on medical data analytics, data mining, clinical decision support, and electronic health records. My interests include evidence-based decision support for low-resource clinical settings, data mining in electronic health records, and predictive healthcare analytics. As a research fellow at the National Library of Medicine, I published several papers on mHealth and eHealth applications for global medicine. During that time, I also founded a non-profit organization to develop and distribute medical software in low-resource environments. My current research focus is on predicting and intervening in exacerbations of chronic disease by mining big data for predictors of health outcomes, and using them to deliver point-of-care decision support. During my medical and doctoral studies, I have collaborated with clinicians and researchers on innovative projects in predictive analytics, population health management, big-data healthcare analytics, clinical decision support, accountable care, medical pedagogy, pharmacogenomics, and natural language processing. My passion and focus are on engaging teams of skilled investigators and thinkers, in any department or profession, to formulate and solve the problems of delivering better health care, at lower cost, to those who need it most urgently. I completed medical school in 2011 with a focus on rural primary care and public health, and my medical training taught me the realities of clinical workflow, information needs at the point of care, and real-time clinical decision support. I have over 20 years of industry experience in business analysis, software engineering, and project management. These skills and experiences give me a unique understanding of clinical informatics and enable me to communicate productively with clinicians and scientists in their own language.
