Evaluating the Impact of Determinants of Health
There are known individual, social, economic, medical and environmental factors, known as determinants of health (DOH)1,2 that influence overall wellbeing, and physiological decline. Identification and evaluation of this impact on wellbeing may provide insights for early prevention and intervention to, not only as an adjuvant to health, but to prevent and reduce poor outcomes associated with physiological decline. We aim to identify and assess interrelated conditions and factors that influence health and wellbeing of population over time. Agent-Based Models (ABM)3, an Artificial Intelligence technique provides the mechanisms for dynamically modelling the impact of DOH on the general population to gather insights into the cumulative effects of DOH on the overall wellbeing over time.
Dr. Sordo is a Senior Medical Informatician at the Brigham and Women’s Hospital and Massachusetts General Hospital, and an Instructor of General Internal Medicine and Primary Care at Harvard Medical School. Her research and scholarly writing include elicitation and representation of clinical knowledge, artificial intelligence and machine learning techniques in medicine and healthcare to further advance clinical decision support. Current work focuses on the application of complex adaptive systems to evaluate the impact of determinants of health and public health policies on individual health.