Teaching

UNIVERSITY OF MICHIGAN

BIOSTAT 830:
Analysis of EHR Data

Tuesday 12:00PM - 3:00PM at SPH II, M1170

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Course overview

The growing availability of administrative healthcare data such as the electronic health record (EHR) data is opening new opportunities for research. EHRs are routinely collected longitudinal data containing demographics, medical diagnosis and procedure, medication, immunization, laboratory test results, radiology images, vital signs, and billing information. Ongoing efforts have been made to integrate large scale EHR data across healthcare systems, as well as to link EHR data with biobank, insurance claims, registries, and death indices. With such cost-effective data sources, the health of an individual is now characterized with unprecedented precision and depth, facilitating contemporary research that makes the transition from data to knowledge. This course will offer an overview of modern analytical methods and research applications using EHR data. Upon completion of the course, participants i) will have a broader understanding of the opportunities and challenges of secondary use of EHR data for research and ii) will be prepared to generate and further explore new questions, new perspectives, and new methodological development. Course syllabus Download

COURSE MATERIALS

Lecture slides

Original course links preserved
  1. 01Introduction to EHR dataSlides ↗
  2. 02Opportunities and ChallengesSlides ↗
  3. 03Observational StudiesSlides ↗
  4. 04Unmeasured ConfoundingSlides ↗
  5. 05Phenotyping AlgorithmSlides ↗
  6. 06Curating Towards Research QualitySlides ↗
  7. 07Project ProposalNo slide link in archive
  8. 08Risk Stratification and Risk PredictionSlides ↗
  9. 09Transfer LearningSlides ↗
  10. 10Privacy Preserving AlgorithmsSlides ↗
  11. 11FairnessSlides ↗
  12. 12Pragmatic TrialsSlides ↗

ADDITIONAL TEACHING

Short courses & workshops

A half-day short course at the New England Statistical Society (NESS) symposium: Link to slides

Course materials ↗

VERITY 2021 Bioinformatics Course on Bioinformatics in Clinical Data L ink to materials

Course materials ↗