Clinical Data Models and Data Quality Assessments

Clinical Data Models and Data Quality Assessments

This course is part of Clinical Data Science Specialization

Instructors: Laura K. Wiley, PhD

Access provided by SGCSRC

8,676 already enrolled

5 modules

Gain insight into a topic and learn the fundamentals.

66 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

66 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Relational Databases

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

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There are 5 modules in this course

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 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

9 videos Total 54 minutes

Welcome to Clinical Data Models and Data Quality Assessments 2 minutes
Clinical Research Data Warehouses 9 minutes
Entity Relationship Diagrams (ERDs) 4 minutes
Clinical Data Models 4 minutes
Why Common Data Models? 10 minutes
A Quick Tour of a Common Data Model: i2b2 7 minutes
A Quick Tour of a Common Data Model: OMOP 6 minutes
A Quick Tour of a Common Data Model: Sentinel 6 minutes
A Quick Tour of a Common Data Model: PCORNet 6 minutes

5 readings Total 150 minutes

Get help and meet other learners in this course. Join your discussion forums! 5 minutes
Introduction to Specialization Instructors 5 minutes
Course Policies 5 minutes
Accessing Course Data and Technology Platform 15 minutes
Readings and Course Materials for Module 1 120 minutes

1 assignment Total 30 minutes

Clinical Data Models and Common Data Models 30 minutes

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

6 videos Total 59 minutes

A Deep Dive into the MIMIC-III Data Model 5 minutes
Querying MIMIC-III 10 minutes
A Deep Dive into OMOP Data Model 14 minutes
Querying OMOP 12 minutes
Comparing the MIMIC and OMOP Data Models 11 minutes
The OHDSI Community Ecosystem 7 minutes

1 reading Total 90 minutes

Readings and Course Materials for Module 2 90 minutes

1 assignment Total 30 minutes

Tools: Querying Clinical Data Models 30 minutes

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

6 videos Total 53 minutes

The ETL Task 7 minutes
Structural versus Terminology Mapping 6 minutes
Data Profiling with White Rabbit 10 minutes
Data Mapping with the Rabbit in a Hat Tool 9 minutes
Terminology Mapping 11 minutes
Example mapping of MIMIC Patient to OMOP Person 9 minutes

1 reading Total 120 minutes

Readings and Course Materials for Module 3 120 minutes

1 assignment Total 30 minutes

Techniques: Extract-Transform-Load and Terminology Mapping 30 minutes

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

5 videos Total 52 minutes

Data quality dimensions / fitness for use 7 minutes
Data profiling for data quality assessment 10 minutes
Data quality assessment using SQL 13 minutes
Callahan and Khare rules 9 minutes
OHDSI Achilles and Achilles Heel 13 minutes

1 reading Total 90 minutes

Readings and Course Materials for Module 4 90 minutes

1 assignment Total 30 minutes

Techniques: Data Quality Assessments 30 minutes

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.