Successful healthcare analysts require a solid grasp of statistical inference as a foundation of their work. Designed for clinical and operational analysts, this course introduces concepts in healthcare epidemiology, outcomes research and experimental studies. The course focuses on four domains: 1) fundamentals of data and statistics 2) techniques to assess relationships between exposure and outcomes 3) study design and 4) measuring main effects and error. Through online lectures and hands-on practice, students will explore methods to analyze healthcare data, contrast efficacy and effectiveness trials, and learn strategies to adjust for patient, provider and hospital characteristics in a statistical model. All topics will be covered in the context of their direct application to health care. By the end of this course students will be able to design a healthcare study; assess confounding, biases, internal and external validity; and understand variance.
Learning Outcomes
- Demonstrate an understanding of statistical techniques widely used to conduct healthcare research
- Develop a study design to appropriately address a research question
- Differentiate between the various components in a statistical model (variables, parameters, error)
- Calculate performance characteristics of a clinical assay (sensitivity, specificity, predictive value)
- Conduct a simple analysis of [at least] three variables (predictor, outcome and other) using statistical software
Skills You Will Gain
- Applied statistics
- Epidemiology and applications to healthcare
- Analysis and reporting
- Statistics theory
- Measurements of precision and accuracy in models