Clinical Research Informatics: Data Management and Analysis
( 30 Modules )

Module #1
Introduction to Clinical Research Informatics
Overview of the field of clinical research informatics and its importance in clinical trials

Module #2
Key Concepts and Terminology
Definitions and explanations of key terms and concepts in clinical research informatics

Module #3
History and Evolution of Clinical Research Informatics
Historical context and development of clinical research informatics as a field

Module #4
Data Management Principles
Fundamental principles of data management in clinical research, including data quality, integrity, and security

Module #5
Data Collection and Capture
Methods and tools for collecting and capturing data in clinical research, including electronic data capture (EDC) systems

Module #6
Data Cleaning and Quality Control
Techniques and strategies for ensuring data quality and cleaning data in clinical research

Module #7
Introduction to Statistical Analysis
Basic concepts and principles of statistical analysis in clinical research

Module #8
Descriptive Statistics and Data Visualization
Methods and tools for summarizing and visualizing data in clinical research

Module #9
Inferential Statistics and Hypothesis Testing
Techniques for making inferences and testing hypotheses in clinical research

Module #10
Regression Analysis and Modeling
Introduction to regression analysis and modeling techniques in clinical research

Module #11
Survival Analysis and Time-to-Event Data
Methods and techniques for analyzing time-to-event data in clinical research

Module #12
Advanced Topics in Statistical Analysis
Coverage of advanced statistical topics, including machine learning and predictive analytics

Module #13
Clinical Trials Management Systems (CTMS)
Overview of CTMS and their role in clinical research

Module #14
Electronic Health Records (EHRs) and Clinical Research
Use of EHRs in clinical research and their integration with clinical trials

Module #15
Mobile Health (mHealth) and Wearable Technologies
Use of mHealth and wearable technologies in clinical research

Module #16
Artificial Intelligence (AI) and Machine Learning (ML) in Clinical Research
Applications of AI and ML in clinical research

Module #17
Data Sharing and Collaboration in Clinical Research
Strategies and best practices for sharing and collaborating on data in clinical research

Module #18
Regulatory Considerations and Compliance in Clinical Research Informatics
Overview of regulatory requirements and compliance issues in clinical research informatics

Module #19
Case Study:Regulatory Submission and Approval
Real-world example of using clinical research informatics in regulatory submission and approval

Module #20
Case Study:Real-World Evidence and Observational Research
Real-world example of using clinical research informatics in real-world evidence and observational research

Module #21
Case Study:Clinical Trials Optimization and Risk-Based Monitoring
Real-world example of using clinical research informatics in clinical trials optimization and risk-based monitoring

Module #22
Case Study:Precision Medicine and Personalized Healthcare
Real-world example of using clinical research informatics in precision medicine and personalized healthcare

Module #23
Case Study:Data Analytics and Visualization in Clinical Research
Real-world example of using clinical research informatics in data analytics and visualization

Module #24
Case Study:Wearable Technologies and Digital Health in Clinical Research
Real-world example of using clinical research informatics in wearable technologies and digital health

Module #25
Capstone Project Introduction
Overview of capstone project requirements and expectations

Module #26
Capstone Project:Data Management and Analysis
Application of clinical research informatics principles to a real-world dataset

Module #27
Capstone Project:Specialized Topics and Applications
Application of specialized topics in clinical research informatics to a real-world dataset

Module #28
Capstone Project:Case Study and Presentation
Development of a case study and presentation of findings

Module #29
Final Assessment:Written Exam
Comprehensive written exam covering course material

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Clinical Research Informatics: Data Management and Analysis career

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Clinical Research Informatics: Data Management and Analysis ( 30 Modules )

Clinical Research Informatics: Data Management and Analysis
( 30 Modules )