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Stephany Duda, PhD
and
Paul Harris, PhD
This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research.
Read more
This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research.
Read more
This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research.
Understanding and implementing solid data management principles is critical for any scientific domain. Regardless of your current (or anticipated) role in the research enterprise, a strong working knowledge and skill set in data management principles and practice will increase your productivity and improve your science. Our goal is to use these modules to help you learn and practice this skill set.
This course assumes very little current knowledge of technology other than how to operate a web browser. We will focus on practical lessons, short quizzes, and hands-on exercises as we explore together best practices for data management.
Register for this course and see more details by visiting:
OpenCourser.com/course/0vuhyp/data
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What's inside
Syllabus
Research Data Collection Strategy
This introductory module reviews the course structure and basic concepts in clinical research. We also discuss best practices for designing your clinical research data collection.
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Syllabus
Research Data Collection Strategy
This introductory module reviews the course structure and basic concepts in clinical research. We also discuss best practices for designing your clinical research data collection.
Read more
Electronic Data Capture Fundamentals
This module covers standards for study processes, concepts for regulatory compliance, and electronic data capture fundamentals.
Planning a Data Strategy for a Prospective Study
This module reviews the process of planning data elements for a real-world research study.
Practicing What We've Learned: Implementation
This week, we set up an Electronic Data Capture (EDC) instrument in REDCap for the Morphine vs. Marinol Study. We also review data processes that occur during the running of a study, including an overview of key data quality operations.
Post-Study Activities and Other Considerations
In this week, we cover activities to wrap up your study and share data and results, as well as two lectures on other electronic sources of data that can be used in research. In response to learner requests, we've also added several lectures on clinical data management in resource-limited settings, in collaboration with research colleagues from Indiana University. This is a long week of videos, but next week will be short on videos in exchange!
Data Collection with Surveys
In the final week, we cover how to collect data using surveys and review an example together. This week's assignment includes designing, distributing, and reporting on your own survey.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational knowledge and skills in clinical research data management from the ground up
Provides practical examples and hands-on exercises to solidify understanding and promote skill development
Taught by two expert instructors in clinical research and data management: Stephany Duda, PhD, and Paul Harris, PhD
Addresses topics relevant for both beginners and those seeking to enhance their data management skills in clinical research
Covers a comprehensive range of aspects related to data collection, storage, and dissemination in clinical research
Assumes minimal technical knowledge, making it accessible to individuals with diverse backgrounds
Save this course
Save Data Management for Clinical Research to your list so you can find it easily later:
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Reviews summary
Understanding clinical research data management
learners say this largely positive course on data management for clinical research provides engaging assignments and hands-on practice with REDCap, a widely used electronic data capture system. Vanderbilt University instructors cover the basics, from data collection and storage to analysis and reporting. Students create surveys and learn how to manage data securely and ethically.
features well received instructors who are passionate about their subject matter.
"This was a very helpful course with interesting quizzes and assessments. Very practical and easy to understand."
"I enjoyed this course and also the professionalism of the trainers is to be congratulated."
"Instructors were great and materials were appropriate. I enjoyed learning every bit of it. It was very close to having an in person experience when I see the instructors face to face.(although virtual) Definitely recommend! Thank you Paul, Stephany and team!"
"The primary teachers are great. The material is very germane to the today's environment. If you are involved with data management at any level this course will help."
"I found this course very elaborate and a course that takes one slowly but surely from a level of ignorance to knowledge."
"The presenters on the course are obviously well knowledgeable in their field and that shines through in their very nice and informative presentations!"
covers well received topics, including data collection, data analysis, and electronic health records.
"learners say this largely positive course on data management for clinical research provides engaging assignments and hands-on practice with REDCap, a widely used electronic data capture system. Vanderbilt University instructors cover the basics, from data collection and storage to analysis and reporting. Students create surveys and learn how to manage data securely and ethically."
"This was a very helpful course with interesting quizzes and assessments. Very practical and easy to understand."
"Comprehensive course lectures and REDCap Exercises were very helpful to get hands-on experience."
develops engaging assignments using REDCap software, including survey design and data management.
"The course is really good. It explains the basics in clinical trails and very well focuses on data management. Also it gives good hands on experience of data collection instruments."
"This course was a fantastic, comprehensive overview of data management for clinical research. The opportunities built in for practice and application of the principles were quite helpful."
"A well organized course, very interesting topics and very good and clear instructors. The possibility of being able to download all the material is also very useful."
"This course was excellently executed, with informative lectures, and with innovative and practical learning plan which I could follow online and learned quite a lot of foundation and practical skills."
"I really liked taking this course, I learned a lot of new terminology, how to use the Red Cap system to do CRF, surveys."
"I found this course very elaborate and a course that takes one slowly but surely from a level of ignorance to knowledge."
"The assignments and peer-grading worked surprisingly well in my opinion."
"Thank you Vanderbilt university team for providing this wonderful course on data management for clinical research."
"I really appreciate course instructors for their excellent contribution towards the topics design and explanation ,which were clear and up to the mark."
may experience occasional technical issues with the software used in the course.
"REDCap issues with logging in, and you don't even know who to contact since their help email doesn't work anymore."
"The only benefit for me was to know how to use REDCap platform."
may include outdated material, especially in regard to software and references.
"While there is some helpful information about data management and good instructional videos for learning RedCap, it's nothing you can't find for free on youtube or any book on data management."
"A major issue with this course is the assignments being graded by other people taking this course, it would be fine as long as someone running the course checked the grades provided."
"I wish to point that the subtitles needs to be updated as it was occasionally misleading and out of sync."
uses a controversial peer review system for assignments.
"The worst part is the peer assignment grading system which I don't know if it's a Coursera thing or it depends on each university. I finished the whole course and still needed my peer grading from week 1 to get the certificate, and I had to repeatedly post and beg for other peers to review it until I got it, unbelievable."
"I had turned in an assignment for Week 1 and it took over 4 week AFTER I had already completed all of the other Assignments that the assignment from Week 1 was finally peer-reviewed."
"You can't leave a person at the mercy of others, you basically can't move forward until you get your peer reviews."
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 Data Management for Clinical Research with these
activities:
Review the course materials on data management in clinical research
Show steps
Reviewing the course materials can help you solidify your understanding of the principles and practices of data management in clinical research.
Browse courses on
Data Management
Show steps
-
Go over the course notes and slides
-
Rewatch the course videos
-
Review the assigned readings
Compile a resource list of data management tools and resources
Show steps
Compiling a list of data management tools and resources can help you identify the tools that are most appropriate for your research projects.
Browse courses on
Data Management
Show steps
-
Search for data management tools and resources online
-
Create a list of the tools and resources that you find
-
Organize the list by category or type of tool
Join a study group or discussion forum on data management in clinical research
Show steps
Participating in a study group or discussion forum can provide you with an opportunity to discuss data management principles and practices with other students.
Browse courses on
Data Management
Show steps
-
Find a study group or discussion forum on data management in clinical research
-
Join the group or forum and participate in the discussions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Take an online course on data management in clinical research
Show steps
Taking an online course can help you gain a foundational understanding of the principles and practices of data management in clinical research.
Browse courses on
Data Management
Show steps
-
Find an online course on data management in clinical research
-
Enroll in the course and complete the coursework
Attend a workshop on data management in clinical research
Show steps
Attending a workshop can provide you with an opportunity to learn from experts in the field of data management in clinical research.
Browse courses on
Data Management
Show steps
-
Find a workshop on data management in clinical research
-
Register for the workshop and attend the sessions
Create a structured data management plan for a clinical research study
Show steps
Drafting a structured data management plan will help solidify your understanding of the principles and practices of data management in clinical research.
Browse courses on
Data Management
Show steps
-
Identify the data that will be collected during the study
-
Determine how the data will be collected, stored, and processed
-
Develop a system for managing the data, including data security and privacy
-
Write a data management plan that outlines the plan for managing the data
Design and implement an electronic data capture system for a clinical research study
Show steps
Building an electronic data capture system will provide you with practical experience in applying data management principles to a real-world research project.
Browse courses on
Data Management
Show steps
-
Choose an electronic data capture software platform
-
Design the electronic data capture forms
-
Implement the electronic data capture system
-
Test the electronic data capture system
-
Train the study staff on how to use the electronic data capture system
Develop a data analysis plan for a clinical research study
Show steps
Developing a data analysis plan will help you think critically about the data you will collect and how you will analyze it to answer your research questions.
Browse courses on
Data Management
Show steps
-
Identify the research questions that the study will address
-
Determine the data that will be collected to answer the research questions
-
Describe the statistical methods that will be used to analyze the data
Review the course materials on data management in clinical research
Show steps
Reviewing the course materials can help you solidify your understanding of the principles and practices of data management in clinical research.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Go over the course notes and slides
- Rewatch the course videos
- Review the assigned readings
Compile a resource list of data management tools and resources
Show steps
Compiling a list of data management tools and resources can help you identify the tools that are most appropriate for your research projects.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Search for data management tools and resources online
- Create a list of the tools and resources that you find
- Organize the list by category or type of tool
Join a study group or discussion forum on data management in clinical research
Show steps
Participating in a study group or discussion forum can provide you with an opportunity to discuss data management principles and practices with other students.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Find a study group or discussion forum on data management in clinical research
- Join the group or forum and participate in the discussions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Take an online course on data management in clinical research
Show steps
Taking an online course can help you gain a foundational understanding of the principles and practices of data management in clinical research.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Find an online course on data management in clinical research
- Enroll in the course and complete the coursework
Attend a workshop on data management in clinical research
Show steps
Attending a workshop can provide you with an opportunity to learn from experts in the field of data management in clinical research.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Find a workshop on data management in clinical research
- Register for the workshop and attend the sessions
Create a structured data management plan for a clinical research study
Show steps
Drafting a structured data management plan will help solidify your understanding of the principles and practices of data management in clinical research.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Identify the data that will be collected during the study
- Determine how the data will be collected, stored, and processed
- Develop a system for managing the data, including data security and privacy
- Write a data management plan that outlines the plan for managing the data
Design and implement an electronic data capture system for a clinical research study
Show steps
Building an electronic data capture system will provide you with practical experience in applying data management principles to a real-world research project.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Choose an electronic data capture software platform
- Design the electronic data capture forms
- Implement the electronic data capture system
- Test the electronic data capture system
- Train the study staff on how to use the electronic data capture system
Develop a data analysis plan for a clinical research study
Show steps
Developing a data analysis plan will help you think critically about the data you will collect and how you will analyze it to answer your research questions.
Browse courses on
Data Management
Show steps
Show steps
Show steps
- Identify the research questions that the study will address
- Determine the data that will be collected to answer the research questions
- Describe the statistical methods that will be used to analyze the data
Career center
Learners who complete Data Management for Clinical Research will develop knowledge and skills
that may be useful to these careers:
Clinical Data Manager
Clinical Data Manager
Clinical Data Managers closely oversee the handling of data from the very start of a clinical trial. They maintain and oversee the quality of clinical data from collection to analysis. The course gives a structured overview of the principles of clinical data management, which would be highly useful to someone in this role, particularly early in their career.
Medical Writer
Medical Writer
Medical Writers prepare medical documents meant for peers or the public. This typically includes writing protocols, reports, and abstracts, as well as literature reviews, grant proposals, and other scientific documentation. Learning data management principles and best practices would be of great value to a medical writer, and this course would provide a solid foundation for those just starting out, as well as those looking to advance in this career.
Biostatistician
Biostatistician
Biostatisticians apply statistics to biological data. This course would help provide a deeper understanding of the principles and practices behind data management, a key part of biostatistical work.
Health Informatics Specialist
Health Informatics Specialist
Health Informatics Specialists collect, store, and analyze health information. They use a combination of technical and clinical knowledge to manage data. This course would be a great help for those getting started in this growing field.
Clinical Research Associate
Clinical Research Associate
Clinical Research Associates serve as liaisons between sponsors, investigators, and research participants. They play a key role in managing and monitoring clinical trials. They manage budgets, timelines, and relationships in service of data collection completion. This course would be helpful for those just starting out in this role by providing a structured and detailed overview of data management in clinical research.
Data Analyst
Data Analyst
Data Analysts clean, organize, and interpret data, helping businesses make decisions. This course would help those starting out in data analysis better understand the importance of data management practices, especially as they relate to clinical research.
Quality Assurance Specialist
Quality Assurance Specialist
Quality Assurance Specialists ensure that products and services meet quality standards. This course goes over essential quality control processes in data management, and would be especially useful to those early in their career.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. They typically manage budgets, timelines, and deliverables, and ensure that projects meet quality standards. This course provides a good overview of data management that would be useful in any project management role.
Research Scientist
Research Scientist
Research Scientists conduct and interpret scientific research. They typically specialize in a particular field, such as biology, chemistry, or physics. This course would be helpful because it provides an overview of how to manage data in a clinical research setting, and would be useful to scientists considering a career in clinical research or who work with a team of clinicians.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and distribution of disease in populations. They use data to make recommendations for preventing and controlling disease. This course goes over the basics of data management, which would be useful to an epidemiologist, particularly early in their career.
Medical Science Liaison
Medical Science Liaison
Medical Science Liaisons serve as a bridge between pharmaceutical companies and healthcare professionals. They provide information about new drugs and treatments to doctors and other healthcare professionals. This course would be helpful for those starting out in this role by providing a structured overview of data management in clinical research, and providing insights into data management on the pharmaceutical industry side.
Regulatory Affairs Specialist
Regulatory Affairs Specialist
Regulatory Affairs Specialists ensure that products and services comply with government regulations. This course would help those just starting out in this role better understand the importance of data management practices, especially as they relate to clinical research.
Clinical Research Coordinator
Clinical Research Coordinator
Clinical Research Coordinators assist with the day-to-day operations of clinical trials. They may be responsible for recruiting and screening participants, collecting and managing data, and monitoring participant safety. This course provides a structured and detailed overview of data management practices in clinical research, which would be helpful to someone just starting out in this role.
Data Entry Clerk
Data Entry Clerk
Data Entry Clerks input and manage data. They ensure that data is accurate and complete. This course would be helpful for someone just starting out in this role by providing a clear overview of the data entry process and quality standards in clinical research.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. They ensure that data is stored securely and efficiently. This course would be helpful for those just starting out in this role by providing a structured overview of data management practices, including data storage and security.
For more career information including salaries, visit:
OpenCourser.com/course/0vuhyp/data
Reading list
We've selected six 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
Data Management for Clinical Research.
Provides real-world experiences and illustrative examples, which will help learners of this course gain a deep understanding of data management practices at various stages of clinical trials.
Save
Offers a comprehensive guide to data management for clinical research studies. It provides valuable insights into data management planning, documentation, and regulatory compliance.
Save
Provides a practical guide to clinical trial design, covering all aspects of the process from protocol development to data analysis. It valuable resource for anyone involved in clinical research.
Similar to the previous book, this text offers a broader perspective on clinical trials but also includes a chapter on data management, providing additional information on data collection, storage, and analysis.
Is more advanced than the previous one on online surveys, providing a comprehensive overview of survey research methods and techniques.
Provides a concise guide to clinical data management, covering all aspects of the process from data collection to analysis. It valuable resource for anyone involved in clinical research.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0vuhyp/data
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Effort
6 weeks of study, 2-4 hours per week
Level
Introductory
Via
Coursera
Institution
Vanderbilt University
Instructors
Stephany Duda, PhD
Paul Harris, PhD
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
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Türkçe
Polski
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آذربایجان دیلی
Good to know
Develops foundational knowledge and skills in clinical research data management from the ground up
Provides practical examples and hands-on exercises to solidify understanding and promote skill development
Taught by two expert instructors in clinical research and data management: Stephany Duda, PhD, and Paul Harris, PhD
Addresses topics relevant for both beginners and those seeking to enhance their data management skills in clinical research
Covers a comprehensive range of aspects related to data collection, storage, and dissemination in clinical research
Assumes minimal technical knowledge, making it accessible to individuals with diverse backgrounds
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