Johns Hopkins University
Clinical Trials Data Management and Quality Assurance
Johns Hopkins University

Clinical Trials Data Management and Quality Assurance

Janet Holbrook, PhD, MPH
Ann-Margret Ervin, PhD, MPH
David M. Shade, JD

Instructors: Janet Holbrook, PhD, MPH

11,375 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.8

(130 reviews)

Beginner level

Recommended experience

6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.8

(130 reviews)

Beginner level

Recommended experience

6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Collect and manage clinical trials data

  • Assemble and share clinical trials data

  • Conduct statistical performance monitoring

  • Perform quality assurance for clinical trials

Details to know

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Assessments

6 assignments

Taught in English

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This course is part of the Clinical Trials Operations Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course

This module covers the design and organization of data collection instruments to be used in a clinical trial. A well-designed data collection instrument is critically important to the success of a trial because it determines the way that the data are defined, collected, and organized. A study without a well-designed data collection instrument is likely to encounter otherwise avoidable problems.

What's included

6 videos1 reading1 assignment

In this module, you’ll learn about data management in the context of clinical trials. You’ll learn definitions and core concepts and explore a few different frequently used data management systems. We’ll look closely at Excel and other spreadsheet programs because they are widely used and help illustrate broader data management principles. You'll also learn about data integrity, which incorporates features of data security, redundancy, and preservation.

What's included

5 videos1 assignment

Data assembly involves preparing data for distribution to others. In this module, you’ll learn the necessary steps for creating datasets for sharing. We’ll cover data freezes and data locking as well as cleaning, de-identification, sharing, and standards that you and your team can use to make your data more useful.

What's included

5 videos1 assignment

In this module, you’ll learn how to conduct performance monitoring in clinical trials. Specifically, we’ll discuss a framework for monitoring clinical center performance and protocol adherence through all phases of the trial from start-up through follow-up. The module will conclude with a brief overview of site visits, an important part of a performance monitoring toolkit.

What's included

3 videos1 assignment

In this module, you’ll learn about the principles of managing treatment interventions. There’s a considerable amount of heterogeneity in clinical trials, so a number of factors can influence how you deal with the intervention. Factors include the hypothesis, the design, whether it is an improved intervention, and whether it is licensed or experimental. You’ll also learn about different types of drug formulations and how they factor into masking protocols.

What's included

4 videos1 assignment

In this module, you’ll learn about quality assurance, which refers to the various measures that you and your team can take to help prevent mistakes or problems in your clinical trial. These measures can differ throughout the stages of the trial, so we’ll discuss the specific context in which these measures should be used.

What's included

6 videos1 reading1 assignment

Instructors

Instructor ratings
4.8 (31 ratings)
Janet Holbrook, PhD, MPH
Johns Hopkins University
4 Courses165,725 learners
Ann-Margret Ervin, PhD, MPH
Johns Hopkins University
3 Courses24,038 learners
David M. Shade, JD
Johns Hopkins University
2 Courses13,938 learners

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4.8

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