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.
Clinical Data Models and Data Quality Assessments
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Clinical Data Models and Data Quality Assessments
This course is part of Clinical Data Science Specialization
Instructors: Laura K. Wiley, PhD
7,852 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.2
(63 reviews)
Intermediate level
Some related experience required
17 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in English
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This course is part of the Clinical Data Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
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.
What's included
9 videos5 readings1 assignment
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.
What's included
6 videos1 reading1 assignment
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.
What's included
6 videos1 reading1 assignment
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.
What's included
5 videos1 reading1 assignment
In this module, you gather everything you’ve learned to complete a real-world hands-on exercise using ETL methods to convert MIMIC3 data into the OMOP common data model.
What's included
6 videos1 reading1 peer review
Instructors
Instructor ratings
4.2 (9 ratings)Offered by
Recommended if you're interested in Data Analysis
University of Colorado Boulder
Northeastern University
Google Cloud
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Learner reviews
4.2
63 reviews
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52.38%
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26.98%
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11.11%
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4.76%
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Showing 3 of 63
FG
4
Reviewed on Dec 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.
MK
5
Reviewed on Nov 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!!
JJ
5
Reviewed on Sep 13, 2019
Good instructor who took time to explain and walked through each steps of the ETL process. Highly recommended.
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Frequently asked questions
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