This symposium will explore the complex issues involved in designing and analyzing studies that sample from the electronic health record.

Tianxi Cai, ScD
Professor of Biostatistics, Harvard T.H. Chan School of Public Health
Efficient Use Of EHR For Discovery Research
Presentation slides [PDF]

Victor Castro, MS
Team Lead, Research Information Science and Computing, Mass General Brigham
Identifying Causal Effects from Electronic Health Record Data with Coarsened Exact Matching
Presentation slides [PDF]

Sebastien Haneuse, PhD
Associate Professor of Biostatistics, Harvard T.H. Chan School of Public Health
Adjusting for Selection Bias in Electronic Health Records-Based Research
Presentation slides [PDF]

Miguel Hernan, MD, DrPH
Kolokotrones Professor of Biostatistics and Epidemiology, Harvard T.H. Chan School of Public Health
Designing Analyses of Healthcare Databases to Emulate Randomized Trials
Presentation slides [PDF]

Douglas MacFadden, MS
Chief Informatics Officer, Harvard Catalyst, Harvard Medical School
The Harvard Shrine Network: The Harvard Catalyst Tool for Querying EHR Data Across Harvard Hospitals

Elizabeth Mostofsky, ScD
Instructor, Department of Epidemiology, Harvard T.H. Chan School of Public Health
Observational Study Designs for Highly Stratified Data
Presentation slides [PDF]

David Sontag, PhD
Assistant Professor, Department of Electrical Engineering and Computer Science, Institute for Medical Engineering & Science, Massachusetts Institute of Technology
Machine Learning on Electronic Health Records
Presentation slides [PDF]

Holly Barr-Vermilya, MHA
Mass General Brigham eCare Research Core (PeRC) Director
and
Adrian Zai, MD, PhD
Assistant Professor of Medicine, Harvard Medical School
Mass General Brigham eCare Research Core
Presentation slides [PDF]

Jose Zubizarreta, PhD
Assistant Professor, Department of Health Care Policy, Harvard Medical School
Building Representative Matched Samples in Large-Scale Observational Studies with Multivalued Treatments