Associate Staff
Director, Center for Populations Health Research
Email: daltonj@ccf.org
Location:
Cleveland Clinic Main Campus
My research expertise is in modeling complex systems by combining data from a variety of sources (for instance, electronic medical records, and neighborhood characteristics from agencies such as the U.S. Census and the U.S. Centers for Disease Control and Prevention). In particular, I am currently leading an effort to understand the extent to which various neighborhood and environmental characteristics can be helpful in identifying who is likely to have a heart attack or stroke.
https://www.mdmag.com/medical-news/inflammation-indicator-predict-risk-of-death-heart-disease-cancer
Dr. Dalton serves as Associate Staff in Quantitative Health Sciences, Director of the Center for Populations Health Research and Associate Professor of Medicine, Lerner College of Medicine. He began his 16-year career at Cleveland Clinic as a biostatistician, working on the design, analysis and facilitation of clinical trials and observational cohort studies.
Dr. Dalton received a Bachelor of Science in Mathematics, Business and Computer Science from Muskingum University, a Master of Arts in Applied Statistics from University of Michigan and a Doctorate of Philosophy in Epidemiology and Biostatistics from Case Western Reserve University. He subsequently completed postdoctoral (KL2) training in translational research through the Cleveland Clinical and Translational Research Collaborative
My research involves understanding and integrating into clinical practice social, behavioral and environmental factors that affect health. My current research project, which is funded through the National Institute on Aging, involves understanding how the primary drivers of cardiovascular risk might vary across the age spectrum and across the socioeconomic spectrum. Our team is also investigating ways to dynamically adapt cardiovascular risk predictions in response to changes in health status and treatments over time. This work involves the integration of regional electronic medical record data with location-based data from public sources (such as the U.S. Census Bureau, the Environmental Protection Agency, the Centers for Disease Control and Prevention, etc.). We have supported this work by developing open-source software tools for a variety of biomedical research-oriented tasks, primarily through the R statistical programming language.
Cleveland Clinic and MetroHealth researchers to use $3.14 million NIH grant to build data models for investigating place-based healthcare inequities.
With a new grant from the National Heart, Lung, and Blood Institute, Drs. Dalton and Valapour will develop an improved risk modeling approach to help prioritize patients with advanced lung diseases who need a transplant.