BIOSTAT 830: Analysis of EHR Data
Course schedule: Tuesday 12:00PM - 3:00PM at SPH II, M1170
Abstract: 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
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Abstract: 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
Slides
Lecture 1 Introduction to EHR data
Lecture 2 Opportunities and Challenges
Lecture 3 Observational Studies
Lecture 4 Unmeasured Confounding
Lecture 5 Phenotyping Algorithm
Lecture 6 Curating Towards Research Quality
Lecture 7 Project Proposal
Lecture 8 Risk Stratification and Risk Prediction
Lecture 9 Transfer Learning
Lecture 10 Privacy Preserving Algorithms
Lecture 11 Fairness
Lecture 12 Pragmatic Trials
Lecture 1 Introduction to EHR data
Lecture 2 Opportunities and Challenges
Lecture 3 Observational Studies
Lecture 4 Unmeasured Confounding
Lecture 5 Phenotyping Algorithm
Lecture 6 Curating Towards Research Quality
Lecture 7 Project Proposal
Lecture 8 Risk Stratification and Risk Prediction
Lecture 9 Transfer Learning
Lecture 10 Privacy Preserving Algorithms
Lecture 11 Fairness
Lecture 12 Pragmatic Trials
A half-day short course at the New England Statistical Society (NESS) symposium:
Link to slides
Link to slides
VERITY 2021 Bioinformatics Course on Bioinformatics in Clinical Data
Link to materials
Link to materials