Clinical Data Models and Data Quality Assessments

This course is part of Clinical Data Science Specialization

Instructors: Laura K. Wiley, PhD +1 more

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Skills you'll gain

  •   Clinical Data Management
  •   Data Validation
  •   Database Design
  •   SQL
  •   Relational Databases
  •   Data Modeling
  •   Health Informatics
  •   Data Integration
  •   Extract, Transform, Load
  •   Data Quality
  •   Data Transformation

    • 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.

    Tools: Querying Clinical Data Models

    Techniques: Extract-Transform-Load and Terminology Mapping

    Techniques: Data Quality Assessments

    Practical Application: Create an ETL Process to Transform a MIMIC-III Table to OMOP

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