Full course description
Overview
Participants will learn key concepts and engage with synthetic electronic health records to apply various analytical methodologies, enhancing their practical understanding of patient and population health analytics.
Topics
You will learn about:
- How identity and healthcare outcomes in the modern age are driven by how we socially construct and interpret data.
- Descriptive data analytics in patient and population health: Summarizing demographic information, patterns in medication usage, disease incidence rates, healthcare service utilization (over/under), hospital admission rates and stay duration.
- Exploratory data analytics in patient and population health: Correlations between different health conditions, uncovering trends in patient admissions, factors affecting treatment outcomes, spatial distribution of disease, text mining, social network analysis.
- Predictive data analytics in patient and population health: Likelihood of readmission for patients with chronic diseases, high risk of developing certain conditions, decision trees for ordering additional tests.
- Visualization of patient and population health data.
- Challenges and benefits of implementing data analytics in research, public health, and healthcare operations.