Clinical Data Models and Data Quality Assessments
- 4.2
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Approx. 17 hours to complete
Course Summary
This course provides an in-depth exploration of clinical data models and data quality assessments, focusing on practical applications in healthcare settings. Students will learn how to use industry-standard data models to organize and manage clinical data, as well as how to assess data quality and ensure accuracy.Key Learning Points
- Learn about clinical data models and their applications in healthcare settings
- Explore data quality assessments and techniques for ensuring accuracy
- Gain practical skills for organizing and managing clinical data
Related Topics for further study
- Clinical Data Models
- Data Quality Assessments
- Healthcare Informatics
- Clinical Data Management
- Healthcare Data Analysis
Learning Outcomes
- Apply industry-standard clinical data models to organize and manage healthcare data
- Evaluate data quality and implement techniques to ensure accuracy
- Develop practical skills for clinical data management and analysis
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of healthcare terminology and concepts
- Familiarity with data management and analysis software
Course Difficulty Level
IntermediateCourse Format
- Online Self-Paced
- Video Lectures
- Hands-On Exercises
Similar Courses
- Healthcare Data Analytics
- Clinical Informatics for Patient-Centered Care
Related Education Paths
- Certified Health Data Analyst (CHDA)
- Certified Professional in Healthcare Information and Management Systems (CPHIMS)
Notable People in This Field
- Chief Innovation Officer, Brigham and Women's Hospital
- Former Assistant Secretary for Health, U.S. Department of Health and Human Services
Related Books
Description
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.
Outline
- Introduction: Clinical Data Models and Common Data Models
- Welcome to Clinical Data Models and Data Quality Assessments
- Clinical Research Data Warehouses
- Entity Relationship Diagrams (ERDs)
- Clinical Data Models
- Why Common Data Models?
- A Quick Tour of a Common Data Model: i2b2
- A Quick Tour of a Common Data Model: OMOP
- A Quick Tour of a Common Data Model: Sentinel
- A Quick Tour of a Common Data Model: PCORNet
- Introduction to Specialization Instructors
- Course Policies
- Accessing Course Data and Technology Platform
- Readings and Course Materials for Module 1
- Clinical Data Models and Common Data Models
- Tools: Querying Clinical Data Models
- A Deep Dive into the MIMIC-III Data Model
- Querying MIMIC-III
- A Deep Dive into OMOP Data Model
- Querying OMOP
- Comparing the MIMIC and OMOP Data Models
- The OHDSI Community Ecosystem
- Readings and Course Materials for Module 2
- Tools: Querying Clinical Data Models
- Techniques: Extract-Transform-Load and Terminology Mapping
- The ETL Task
- Structural versus Terminology Mapping
- Data Profiling with White Rabbit
- Data Mapping with the Rabbit in a Hat Tool
- Terminology Mapping
- Example mapping of MIMIC Patient to OMOP Person
- Readings and Course Materials for Module 3
- Techniques: Extract-Transform-Load and Terminology Mapping
- Techniques: Data Quality Assessments
- Data quality dimensions / fitness for use
- Data profiling for data quality assessment
- Data quality assessment using SQL
- Callahan and Khare rules
- OHDSI Achilles and Achilles Heel
- Readings and Course Materials for Module 4
- Techniques: Data Quality Assessments
- Practical Application: Create an ETL Process to Transform a MIMIC-III Table to OMOP
- Review of the ETL process
- Example: Transforming MIMIC Patient to OMOP Person Steps 1 and 2
- Example: Transforming MIMIC Patient to OMOP Person Step3
- Example: Transforming MIMIC Patient to OMOP Person Step 4
- Example: Transforming MIMIC Patient to OMOP Person Steps 5 and 6
- Example: Transforming MIMIC Patient to OMOP Person Step 7
- Welcome to Practical Applications!
Summary of User Reviews
This course on Clinical Data Models and Data Quality Assessments has received positive reviews from users. Many users found the course to be informative and well-structured.Key Aspect Users Liked About This Course
Informative and well-structured course contentPros from User Reviews
- In-depth coverage of clinical data models and data quality assessments
- Expert instructors with practical experience in the field
- Hands-on exercises to reinforce learning
- Good value for money compared to other similar courses
- Flexible schedule allows for self-paced learning
Cons from User Reviews
- Some users found the course to be too technical
- Limited interaction with instructors and other students
- Lack of real-world case studies
- No certificate of completion offered for free course enrollment
- Course content may be outdated or not applicable to all healthcare settings
Laura K. Wiley, PhD
4.2 Raiting
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