Advanced Certificate in Health Equity: Data-Driven Approaches
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⢠Advanced Health Data Analysis: This unit covers the analysis of health data using advanced statistical techniques and data mining methods to identify health disparities and inequities.
⢠Health Equity Theories and Frameworks: This unit explores various theories and frameworks used to understand health equity and social determinants of health.
⢠Geographic Information Systems (GIS) for Health Equity: This unit introduces the use of GIS in identifying and addressing health disparities across different geographic areas.
⢠Data Visualization for Health Equity: This unit covers the use of data visualization techniques to communicate health equity findings to diverse audiences.
⢠Health Equity Policy Analysis: This unit examines the role of policy in shaping health equity and the use of policy analysis to identify opportunities for intervention.
⢠Machine Learning for Health Equity: This unit covers the application of machine learning techniques to health equity research, including predictive modeling and natural language processing.
⢠Health Equity Evaluation Methods: This unit introduces various evaluation methods used to assess the impact of health equity interventions.
⢠Ethical Considerations in Health Equity Research: This unit examines the ethical considerations involved in health equity research, including issues of privacy, consent, and community engagement.
⢠Health Equity and Healthcare Systems: This unit explores the role of healthcare systems in contributing to health disparities and strategies for addressing these disparities.
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