Clinical Data Science | University of Colorado

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About This Specialization

Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist!

This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data.

By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data.

This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment.

Language
English

Level
Intermediate

Specialization Overview

This Specialization has 6 Courses

Introduction
Clinical Data Models and Data Quality Assessments
Identifying Patient Populations
Clinical Natural Language Processing
Predictive Modeling and Transforming Clinical Practice
Advanced Clinical Data Science

For More Information or to Enroll

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Instructors:

Laura K. Wiley, PhD

Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus

Dr. Wiley develops methods for using data from electronic health records for precision medicine discovery and implementation. She developed computational phenotyping algorithms for use in EHR-linked biobanks, investigated new algorithms for precision dosing of warfarin in African Americans, and has served as the lead informatician on an NIH Cancer Moonshot-funded project to create a comprehensive tobacco cessation service at the University of Colorado Cancer Center. She is a principle investigator in the Colorado Center for Personalized Medicine and an Assistant Professor in the Division of Biomedical Informatics and Personalized Medicine at the University of Colorado Anschutz Medical Campus. She has served as an ex officio member of the American Medical Informatics Association Board of Directors and is Vice-Chair of the AMIA 2019 Annual Symposium.

Michael G. Kahn MD, PhD

Professor of Clinical Informatics
Department of Pediatrics, Anschutz Medical Campus

Dr. Kahn is a Professor of Pediatrics at the University of Colorado Denver; Biomedical Informatics Core Director of the Colorado Clinical and Translational Sciences Institute; co-Director of the Colorado Center for Personalized Medicine; and Director of Research Informatics at Children’s Hospital Colorado. Dr. Kahn also leads Health Data Compass, a cloud-based research data warehouse that combines data from four clinical, financial and research institutions plus state and federal sources. He participates in multiple regional, national, and international clinical data research networks. His informatics research focus areas are data model harmonization and developing sharable data quality measures in distributed research networks.