TMHG 550 Data Management

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COURSE DESCRIPTION

Principles of good data management, case record form design, data management process, data management tools; data validation techniques

 

Prerequisites

Graduate in Bachelor degree in Health sciences, computer sciences, and ICT

 

Course Objectives

1. Describe principles of good data management practices
2. Design appropriate case record form for effective data collection
3. Discuss data management processes in clinical research
4. Apply appropriate data management tools to assist clinical data management
5. Use data validation and data handling techniques to appropriately prepare data for analysis

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Course Features

  • Lectures 58
  • Quizzes 2
  • Duration 50 hours
  • Skill level All levels
  • Language English
  • Students 22
  • Certificate No
  • Assessments Yes

  • Week 1: Principle of Clinical Data Management 14

    • Lecture1.1
      Course Overview
    • Lecture1.2
      Course Syllabus
    • Lecture1.3
      Weekly Activities
    • Lecture1.4
      Introduction to Clinical Data Management
    • Lecture1.5
      Data Collection Strategies
    • Lecture1.6
      Topic Discussion : Data Collection Strategies
    • Lecture1.7
      Data Management Process: Project initiation
    • Lecture1.8
      Data Management Process: Project Implementation
    • Lecture1.9
      Data Management Process: Project Closure
    • Lecture1.10
      Reading Assignment : Good data and record management
    • Lecture1.11
      Topic Discussion : Data Management Process
    • Quiz1.1
      Quiz Week 1 Principle of Clinical Data Management 10 questions
    • Assignment1.1
      Weekly Assignment : Principle of Clinical Data Management 0 day
    • Lecture1.12
      Course Evaluation

  • Week 2: Good Clinical Data Management Practice (GCDMP) 17

    • Lecture2.1
      Weekly Activities
    • Lecture2.2
      GCDMP-Data Collection
    • Lecture2.3
      GCDMP-Data Aquisition
    • Lecture2.4
      GCDMP-Database Setup
    • Lecture2.5
      GCDMP-Data Entry
    • Lecture2.6
      GCDMP-Data Quality
    • Lecture2.7
      GCDMP-Data Preparation
    • Lecture2.8
      Topic Discussion Wk2 Good Clinical Data Management Practice (GCDMP)
    • Lecture2.9
      Clinical Data Standards (CDISC)
    • Lecture2.10
      Additional resource : Clinical Data Standards (CDISC)
    • Lecture2.11
      Topic Discussion : Clinical Data Standards (CDISC)
    • Lecture2.12
      Case Report Form (CRF) Design
    • Lecture2.13
      Topic Discussion : CRF design
    • Assignment2.1
      Weekly Assignment (Student Project) 0 day
    • Lecture2.14
      Weekly Assignment 2 (Peer review) : (GCDMP)
    • Quiz2.1
      Quiz : Week 2 10 questions
    • Lecture2.15
      Course Evaluation

  • Week 3: Clinical Data Management System (CDMS) 14

    • Lecture3.1
      Weekly Activities
    • Lecture3.2
      Introduction to Clinical Data Management System (CDMS)
    • Lecture3.3
      Database Design
    • Lecture3.4
      OpenClinica Installation
    • Lecture3.5
      Getting Started with OpenClinica
    • Lecture3.6
      Create New Users
    • Lecture3.7
      Create New Study
    • Lecture3.8
      Database Setup
    • Lecture3.9
      Assign Study sites and Users
    • Lecture3.10
      Data Entry
    • Lecture3.11
      Data extraction
    • Lecture3.12
      Reading Assignment
    • Assignment3.1
      Weekly Assignment :CDMS (Student Project) 0 day
    • Lecture3.13
      Course Evaluation

  • Week 4: Mobile Data Collection Tools 9

    • Lecture4.1
      Weekly Activities
    • Lecture4.2
      Data Collection via Mobile Devices
    • Lecture4.3
      Create Case Record Form in Epicollect5
    • Lecture4.4
      Manage Users
    • Lecture4.5
      Data Entry
    • Lecture4.6
      View and Export data
    • Lecture4.7
      Additional Reading
    • Assignment4.1
      Weekly Assignment (Student Project) 0 day
    • Lecture4.8
      Course Evaluation

  • Week 5: Data Preparation for Analysis 11

    • Lecture5.1
      Weekly Activities
    • Lecture5.2
      Practice datasets
    • Lecture5.3
      Combining different data files
    • Lecture5.4
      Restructure data files
    • Lecture5.5
      Handling duplicate records
    • Lecture5.6
      Handling missing data
    • Lecture5.7
      Data transformation
    • Lecture5.8
      Handling variables
    • Lecture5.9
      Reading Materials : Data Preparation for Analysis
    • Assignment5.1
      Weekly Assignment : Data Preparation for Analysis 0 day
    • Lecture5.10
      Course Evaluation

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