Clinical Data Models and Data Quality Assessments
Master clinical data modeling, ETL processes, and quality assessment using MIMIC-III and OMOP frameworks.
Master clinical data modeling, ETL processes, and quality assessment using MIMIC-III and OMOP frameworks.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Clinical Data Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.2
(63 ratings)
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English
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What you'll learn
Create and analyze Entity-Relationship Diagrams
Implement ETL processes for clinical data
Assess data quality using multiple dimensions
Query MIMIC-III and OMOP data models
Perform terminology mapping and data transformation
Skills you'll gain
This course includes:
4.3 Hours PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course focuses on clinical data models and common data models in healthcare. Students learn to interpret and evaluate data model designs using Entity-Relationship Diagrams (ERDs), work with MIMIC-III and OMOP frameworks, and perform ETL processes. The course covers data quality assessments, terminology mapping, and practical applications in clinical data transformation. Using Google BigQuery, students gain hands-on experience in querying and manipulating healthcare data models.
Introduction: Clinical Data Models and Common Data Models
Module 1 · 3 Hours to complete
Tools: Querying Clinical Data Models
Module 2 · 2 Hours to complete
Techniques: Extract-Transform-Load and Terminology Mapping
Module 3 · 3 Hours to complete
Techniques: Data Quality Assessments
Module 4 · 2 Hours to complete
Practical Application: Create an ETL Process to Transform a MIMIC-III Table to OMOP
Module 5 · 4 Hours to complete
Fee Structure
Instructors
Leader in Clinical Informatics and Pediatric Research
Dr. Michael G. Kahn is a distinguished Professor of Pediatrics at the University of Colorado Denver, where he also serves as the Biomedical Informatics Core Director for the Colorado Clinical and Translational Sciences Institute and co-Director of the Colorado Center for Personalized Medicine. As the Director of Research Informatics at Children’s Hospital Colorado, he spearheads initiatives that enhance data integration and research capabilities in pediatric care. Dr. Kahn leads Health Data Compass, a cloud-based research data warehouse that aggregates data from multiple clinical, financial, and research institutions, as well as state and federal sources, facilitating advanced research in healthcare. His research interests primarily focus on data model harmonization and the development of sharable data quality measures within distributed research networks. Through his involvement in various regional, national, and international clinical data research networks, Dr. Kahn is committed to improving healthcare outcomes by leveraging informatics to enhance data accessibility and quality for research purposes.
Innovator in Precision Medicine and Biomedical Informatics
Dr. Laura K. Wiley is an Associate Professor in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus, where she focuses on leveraging electronic health records (EHR) for precision medicine discovery and implementation. With a Ph.D. in Human Genetics from Vanderbilt University, Dr. Wiley has developed computational phenotyping algorithms for EHR-linked biobanks and explored precision dosing of medications like warfarin, particularly in African American populations. She serves as the Chief Data Scientist for Health Data Compass, a cloud-based research data warehouse that integrates data from multiple institutions to enhance clinical research capabilities. Dr. Wiley has been actively involved in various initiatives, including a NIH Cancer Moonshot-funded project aimed at creating comprehensive tobacco cessation services at the University of Colorado Cancer Center. Her contributions to the field are recognized through her leadership roles in the American Medical Informatics Association and her involvement in developing the Coursera Clinical Data Science Specialization, which educates students on clinical research informatics skills. Through her research and teaching, Dr. Wiley is dedicated to advancing the integration of data science in healthcare to improve patient outcomes and foster innovation in medical practices.
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4.2 course rating
63 ratings
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