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Clinical Data Models and Data Quality Assessments

Laura K. Wiley, PhD and Michael G. Kahn, MD, PhD

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.

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What's inside

Syllabus

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.

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Teaches foundational data science concepts, which are highly relevant to the field of medical research

Taught by experts in the field of clinical data modeling

Provides hands-on experience with real-world clinical data sets

Requires some prior knowledge of SQL and data modeling concepts

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Reviews summary

Clinical data models and data quality essentials

According to learners, this course provides a clear understanding of clinical data models such as MIMIC-III and OMOP. Students find the lectures well-structured and the content highly relevant for careers in clinical data management and related fields. A significant highlight is the practical ETL exercise, which many found to be challenging yet very rewarding, helping to solidify concepts. The section on data quality assessments was also noted as particularly relevant. However, some reviewers felt the course assumes some prior knowledge of databases and SQL , and the practical application section could benefit from more detailed guidance .

Section on data quality is highly relevant.

"Very comprehensive coverage of data quality assessments and terminology mapping. The examples provided were realistic."

"Found the data quality section particularly relevant."

"A valuable course for understanding clinical data structures and quality."

Well-structured and easy to understand modules.

"The lectures are well-structured and easy to follow."

"Clear explanations in lectures."

"The modules are well-organized."

"Provides a clear understanding of clinical data models..."

In-depth look at key clinical data models.

"Provides a clear understanding of clinical data models like MIMIC-III and OMOP."

"Excellent deep dive into MIMIC and OMOP."

"Solid foundation in clinical data models. MIMIC and OMOP examples are great."

Hands-on exercise solidifies key concepts.

"The hands-on exercise for ETL was very helpful and practical."

"The practical ETL exercise was the highlight for me. It really solidified the concepts taught in the lectures."

"The ETL part is key for real-world application."

"Practical ETL was tricky but valuable."

Directly applicable to clinical data careers.

"Highly relevant for my job in clinical data management."

"Covers essential concepts for clinical data professionals."

"Great course for professionals."

"Recommended for anyone working with healthcare data."

May be difficult without database/SQL basics.

"The course provides a decent overview, but it assumes some prior knowledge of databases and SQL."

Practical section needs more detailed guidance.

"ETL practical was relevant but could be explained a bit better."

"The practical exercise was challenging without more detailed guidance."

"Okay course. The theory is fine, but the practical application felt a bit rushed."

"Need more detailed steps for the ETL project..."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Clinical Data Models and Data Quality Assessments with these activities:

Review Entity Relationship Diagrams

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Review these key concepts to ensure a strong foundational understanding of clinical data models.

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Read the course syllabus' section on Introduction to Clinical Data Models and Common Data Models.
Review your notes on ERDs from previous coursework or study materials.
Complete the practice questions provided in the syllabus.

Review Entity-Relationship Diagrams (ERDs)

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Refresh your knowledge of ERDs, which are essential for understanding data models.

Browse courses on Entity-Relationship Diagrams

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Review course materials on ERDs
Study examples of ERDs
Practice creating ERDs for simple scenarios

Follow SQL Tutorial

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Develop stronger SQL skills. This will greatly aid you throughout the course.

Browse courses on SQL

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Identify a well-regarded online SQL tutorial.
Follow the tutorial, completing all exercises and assignments.
Complete additional practice problems to solidify your understanding.

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Follow tutorials on data model design

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Reinforce your understanding of data model design by following online tutorials.

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Search for tutorials on data model design
Follow the tutorials step-by-step
Practice creating data models based on the tutorials

Practice data model design exercises

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Reinforce your understanding of data model design through hands-on practice.

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Find online exercises or create your own
Practice designing data models based on given scenarios
Compare your solutions to provided answers or discuss with peers

Discuss data modeling challenges with peers

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Engage in discussions with peers to share experiences and insights about the challenges of data modeling in clinical settings.

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Find a peer group or online forum.
Discuss specific data modeling challenges you have encountered.
Share ideas and solutions with your peers.

Practice SQL statements using Google BigQuery

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Practice writing and executing SQL statements to retrieve data from the MIMIC3 clinical data model and the OMOP common data model.

Browse courses on SQL

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Set up a Google BigQuery account and create a project.
Load the MIMIC3 and OMOP datasets into your BigQuery project.
Write and execute SQL statements to query the datasets.

Participate in peer study groups

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Enhance your learning by discussing concepts and solving problems with peers.

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Find a study group or create your own
Discuss the course material and ask questions
Work together on assignments and projects

Attend a workshop on data modeling

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Gain practical experience and insights by attending a workshop on data modeling.

Browse courses on Data Modeling

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Find a relevant workshop and register
Attend the workshop and participate actively
Take notes and ask questions to enhance your understanding

Tutorial: ETL process to transform MIMIC3 data to OMOP

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Follow a tutorial to create an ETL process to transform data from the MIMIC3 clinical data model to the OMOP common data model.

Browse courses on ETL

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Find a suitable tutorial online.
Follow the steps in the tutorial to create the ETL process.
Test the ETL process to ensure it is working correctly.

Query Clinical Data Models using SQL

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Practice querying clinical data models which will prepare you for the hands-on ETL exercise in the course.

Browse courses on SQL

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Find a dataset that is similar to MIMIC3 or OMOP.
Write SQL queries to extract data from the dataset.
Validate your queries by comparing them to expected results.

Start a data visualization project

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Create a data visualization project to solidify your understanding of clinical data models and common data models.

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Gather data from MIMIC3 and OMOP
Clean and transform the data
Create data visualizations using Python or R
Interpret the results and draw conclusions

Create a data model diagram for a clinical scenario

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Create an Entity-Relationship Diagram (ERD) to represent the data model for a clinical scenario, such as patient demographics, diagnoses, and treatments.

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Identify the entities involved in the clinical scenario.
Determine the relationships between the entities.
Create an ERD using a tool such as Lucidchart or draw.io.

Assist fellow learners in the course discussion forums.

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Teaching others is one of the best ways to solidify your own learning.

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Identify a discussion forum related to the course.
Monitor the forum for questions or discussions where you can offer assistance.
Provide helpful and thoughtful responses to other learners.

Create a presentation on data model design

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Solidify your knowledge by creating a presentation on data model design principles and best practices.

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Choose a topic related to data model design
Research the topic thoroughly
Create a presentation using slides or other visual aids
Present your findings to your classmates or colleagues

Develop a data quality assessment plan for a clinical dataset

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Develop a plan to assess the quality of a clinical dataset, including data completeness, consistency, and accuracy.

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Identify the data quality dimensions to be assessed.
Develop data quality rules to measure each dimension.
Create a data quality assessment report.

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

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This hands-on exercise will solidify your understanding of ETL and its application in transforming clinical data.

Browse courses on ETL

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Choose a MIMIC3 table and an OMOP target table.
Using the SQL skills you have developed, extract the data from the source table.
Transform the extracted data to conform to the target table schema.
Load the transformed data into the target table.
Test and validate the ETL process to ensure accuracy and completeness.

Create a blog post on data models

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Expand your understanding and share knowledge by writing a blog post on data models.

Browse courses on Data Models

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Choose a specific topic related to data models
Research the topic and gather information
Write a clear and concise blog post
Publish your blog post and share it with others

Career center

Learners who complete Clinical Data Models and Data Quality Assessments will develop knowledge and skills that may be useful to these careers:

Quality Assurance Analyst

Quality Assurance Analysts are responsible for ensuring that data meets the required standards for quality. A Clinical Data Models and Data Quality Assessments course may be useful for this role, as it provides the skills to evaluate and interpret data model designs using Entity-Relationship Diagrams (ERDs). This can help Quality Assurance Analysts to identify and correct errors in data, ensuring that it is accurate and reliable.

See salaries and explore the career path for Quality Assurance Analyst

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Data Analysts to understand the structure of clinical data and to extract meaningful insights from it.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists are responsible for developing and implementing data-driven solutions to business problems. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Data Scientists to understand the structure of clinical data and to develop models that can accurately predict outcomes.

See salaries and explore the career path for Data Scientist

Clinical Research Associate

Clinical Research Associates are responsible for managing clinical trials and ensuring that they are conducted in accordance with good clinical practice (GCP) guidelines. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Clinical Research Associates to understand the structure of clinical data and to ensure that it is collected and managed in a way that meets the requirements of GCP.

See salaries and explore the career path for Clinical Research Associate

Medical Writer

Medical Writers are responsible for writing and editing medical documents, such as clinical trial protocols, patient information sheets, and scientific papers. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to understand the structure of clinical data and to communicate it clearly and accurately.

See salaries and explore the career path for Medical Writer

Healthcare Consultant

Healthcare Consultants provide advice and guidance to healthcare organizations on a variety of topics, such as clinical data management, quality improvement, and strategic planning. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to understand the challenges and opportunities associated with clinical data.

See salaries and explore the career path for Healthcare Consultant

Healthcare Data Manager

Healthcare Data Managers are responsible for managing the collection, storage, and analysis of healthcare data. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Healthcare Data Managers to understand the structure of clinical data and to develop systems for managing it effectively.

See salaries and explore the career path for Healthcare Data Manager

Medical Librarian

Medical Librarians are responsible for providing access to and managing medical information resources. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to understand the structure of clinical data and to develop systems for organizing and retrieving it.

See salaries and explore the career path for Medical Librarian

Health Informatics Specialist

Health Informatics Specialists are responsible for designing, implementing, and managing health information systems. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Health Informatics Specialists to understand the structure of clinical data and to develop systems for managing it effectively.

See salaries and explore the career path for Health Informatics Specialist

Biostatistician

Biostatisticians are responsible for designing and conducting statistical analyses of medical data. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Biostatisticians to understand the structure of clinical data and to develop models for analyzing it effectively.

See salaries and explore the career path for Biostatistician

Clinical Data Manager

Clinical Data Managers are responsible for managing the collection, storage, and analysis of clinical data. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Clinical Data Managers to understand the structure of clinical data and to develop systems for managing it effectively.

See salaries and explore the career path for Clinical Data Manager

Database Administrator

Database Administrators are responsible for designing, implementing, and managing databases. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Database Administrators to understand the structure of clinical data and to develop systems for managing it effectively.

See salaries and explore the career path for Database Administrator

Data Architect

Data Architects are responsible for designing and implementing data architectures for organizations. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Data Architects to understand the structure of clinical data and to develop architectures for managing it effectively.

See salaries and explore the career path for Data Architect

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data pipelines. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Data Engineers to understand the structure of clinical data and to develop pipelines for managing it effectively.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software applications. A Clinical Data Models and Data Quality Assessments course may be helpful for this role, as it provides the skills to work with clinical data models and common data models. This can help Software Engineers to understand the structure of clinical data and to develop applications for managing it effectively.

See salaries and explore the career path for Software Engineer

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Clinical Data Models and Data Quality Assessments.

Data Virtualization for Business Intelligence...

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Provides a comprehensive overview of SQL. It valuable resource for anyone working with data.

Clinical Data Models and Data Quality Assessments

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What's inside

Syllabus

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Reviews summary

Clinical data models and data quality essentials

Activities

Career center

Reading list

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