This course aims to teach the concepts of clinical data models and common data models. Upon completion of this course, learners will be able to interpret and evaluate data model designs using Entity-Relationship Diagrams (ERDs), differentiate between data models and articulate how each are used to support clinical care and data science, and create SQL statements in Google BigQuery to query the MIMIC3 clinical data model and the OMOP common data model.
This course is part of the Clinical Data Science Specialization
Offered By
Clinical Data Science SpecializationUniversity of Colorado SystemAbout this Course
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Learner Career Outcomes
40%
got a tangible career benefit from this course
25%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 17 hours to complete
English
Subtitles: English
Learner Career Outcomes
40%
got a tangible career benefit from this course
25%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 17 hours to complete
English
Subtitles: English
Offered by
University of Colorado System
The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.
Syllabus - What you will learn from this course
4 hours to complete
Introduction: Clinical Data Models and Common Data Models
This week describes clinical data models and explains the need for and use of common data models in national and international data networks. We will also cover the features of Entity-Relationship Diagrams (ERDs) to describe the key technical features of data models.
4 hours to complete
9 videos (Total 54 min), 4 readings, 1 quiz
9 videos
Clinical Research Data Warehouses9m
Entity Relationship Diagrams (ERDs)4m
Clinical Data Models4m
Why Common Data Models?10m
A Quick Tour of a Common Data Model: i2b26m
A Quick Tour of a Common Data Model: OMOP5m
A Quick Tour of a Common Data Model: Sentinel6m
A Quick Tour of a Common Data Model: PCORNet5m
4 readings
Introduction to Specialization Instructors5m
Course Policies5m
Accessing Course Data and Technology Platform15m
Readings and Course Materials for Module 12h
1 practice exercise
Clinical Data Models and Common Data Models30m
3 hours to complete
Tools: Querying Clinical Data Models
We take a deep dive into the technical features of clinical data models using MIMIC3 as our example and research common data models using OMOP as our example.
3 hours to complete
6 videos (Total 59 min), 1 reading, 1 quiz
6 videos
Querying MIMIC-III9m
A Deep Dive into OMOP Data Model13m
Querying OMOP12m
Comparing the MIMIC and OMOP Data Models10m
The OHDSI Community Ecosystem7m
1 reading
Readings and Course Materials for Module 21h 30m
1 practice exercise
Tools: Querying Clinical Data Models30m
3 hours to complete
Techniques: Extract-Transform-Load and Terminology Mapping
This module teaches learners about the processes and challenges with extracting, transforming and loading (ETL) data with real-world examples in data and terminology mapping.
3 hours to complete
6 videos (Total 53 min), 1 reading, 1 quiz
6 videos
Structural versus Terminology Mapping6m
Data Profiling with White Rabbit10m
Data Mapping with the Rabbit in a Hat Tool9m
Terminology Mapping10m
Example mapping of MIMIC Patient to OMOP Person8m
1 reading
Readings and Course Materials for Module 32h
1 practice exercise
Techniques: Extract-Transform-Load and Terminology Mapping30m
3 hours to complete
Techniques: Data Quality Assessments
We explore the dimensions of data quality by reviewing its challenges, data quality measurements used to measure it, and data quality rules to assess its acceptability for use.
3 hours to complete
5 videos (Total 52 min), 1 reading, 1 quiz
5 videos
Data profiling for data quality assessment10m
Data quality assessment using SQL13m
Callahan and Khare rules8m
OHDSI Achilles and Achilles Heel12m
1 reading
Readings and Course Materials for Module 41h 30m
1 practice exercise
Techniques: Data Quality Assessments30m
Reviews
TOP REVIEWS FROM CLINICAL DATA MODELS AND DATA QUALITY ASSESSMENTS
by MKJul 21, 2019
Gives a great understanding of ETL and the surrounding concepts from Zero. I personally found that a little boring, but for a total newbie to data and computers this is a perfect course.
by FGDec 12, 2019
An excellent course that provides great guidelines for clinical data models. There are plenty of exercises to cement each block of learning material.
by MKNov 4, 2019
What a great course!! Kudos to the professor for being so detail oriented!! I learned a great deal about the clinical data models from this course!!
by VTSep 13, 2019
Good instructor who took time to explain and walked through each steps of the ETL process. Highly recommended.
About the Clinical Data Science 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!
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