(Analytics, Innovative Data and Analytics Transformation, Machine Learning/AI, Population Health — Course Level: Intermediate)
Ninety percent of the $3.3T spent in the U.S. annually for healthcare is for people with chronic and mental health conditions. It can be overwhelming to determine which data sources are best for segmenting the population to identify the patients that could benefit the most from population health interventions—critical for ensuring health during a pandemic. Are EMR data components, social determinants of health, claims data, clinical data, or other data the most relevant? This session will describe the use of various data sets to drive a machine learning platform, identify the relative contributions of the data, and discuss which sources are the most important for accurate predictive modeling.