This course is part of the Clinical Data Science Specialization

4.2
stars
52 ratings

Laura K. Wiley, PhD +1 more instructor

4,796 already enrolled

Offered By

Clinical Data Science SpecializationUniversity of Colorado System

About this Course

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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.

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Course 2 of 6 in the

Clinical Data Science Specialization

Intermediate Level

Approx. 17 hours to complete

English

Subtitles: English

Instructors

Instructor rating

3.6/5 (5 Ratings)

Laura K. Wiley, PhD

Assistant Professor

Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus

17,190 Learners

6 Courses

Michael G. Kahn, MD, PhD

Professor of Clinical Informatics

Department of Pediatrics, Anschutz Medical Campus

5,302 Learners

2 Courses

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 6 in the

Clinical Data Science Specialization

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

Week

Week 1

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

Welcome to Clinical Data Models and Data Quality Assessments2m

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

Week

Week 2

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

Week

Week 3

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

Week

Week 4

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

Reviews

4.2

16 reviews

5 stars
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4 stars
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3 stars
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2 stars
1.92%
1 star
3.84%

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.

View all reviews

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!

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

Clinical Data Models and Data Quality Assessments

About this Course