BMI 569: Data Analytics

Practical coursework in R/SQL for our hybrid Data Analytics Course taught with Kaiser Permanente.

course
data-science
Authors

Ted Laderas

Mark Klick

Aaron Coyner

Published

April 20, 2020

Course Description

Practical coursework in R/SQL for our hybrid Data Analytics Course taught with Kaiser Permanente. This course has been taught from 2013 to the present during summer quarter for students in the Biomedical Informatics program at OHSU.

This repo includes the practical coursework in R/SQL for our hybrid Data Analytics Course taught with Kaiser Permanente. This course has been taught from 2013 to the present during summer quarter for students in the Biomedical Informatics program at OHSU.

Please note that this is only half of the course, which also includes discussions on organizational behavior, implementing analytics projects within an organization, and discussions of the LACE score.

Learning Objectives:

  • Understand the basics of using R/Rstudio
  • Learn and apply basic SQL queries to a synthetic patient cohort
  • Implement a metric for predicting 30 day hospital readmissions (LACE score) for this patient cohort.
  • Learn, understand, and apply simple visualizations to communicate findings
  • Understand how to build and interpret logistic regression models

Licensing

This course material is released under an Apache 2.0 License.

Citation

BibTeX citation:
@online{laderas2020,
  author = {Ted Laderas and Ted Laderas and Mark Klick and Aaron Coyner},
  title = {BMI 569: {Data} {Analytics}},
  date = {2020-04-20},
  url = {https://laderast.github.io//edu/2021-03-20-bmi-569-data-analytics},
  langid = {en}
}
For attribution, please cite this work as:
Ted Laderas, Ted Laderas, Mark Klick, and Aaron Coyner. 2020. “BMI 569: Data Analytics.” April 20, 2020. https://laderast.github.io//edu/2021-03-20-bmi-569-data-analytics.