Guest Column | June 7, 2018

6 Insights To Broaden Your Understanding Of Clinical Trial Data Management

By Kunal Sampat, Senior Manager, Clinical Research, Abbott Vascular

Data Folder

In your opinion, what’s the No. 1 problem when it comes to clinical trials?

The top three problems that come to my mind are:

  1. Enrollment takes longer than expected
  2. Unexpected regulatory and compliance hurdles are encountered
  3. Study doesn’t meet the protocol-defined endpoints

Here is what I’ve discovered: Clinical data can be the cause or the solution to all your clinical trial challenges.

  1. If you had clinical data, you could modify your protocol inclusion and exclusion criteria and enroll faster.
  2. If you were proactively managing poor-quality data issues, you may have fewer regulatory and compliance hurdles.
  3. If you were able to perform interim analysis, you would have an opportunity to course-correct so your study can be a success.

In this article, I’ll share with you six insights to broaden your understanding about clinical data management.

The goal of this article is to get you one step closer to higher-quality clinical data. This will ultimately allow you and your team to experience success in the clinical trial journey.

1. Data managers are an integral part of any clinical study.

According to Karen Green, senior director of clinical data management at Forty Seven, Inc., data managers are responsible for the “collection of data, cleaning the data, and making sure it’s an accurate representation of the patients that you have on your studies.”

Given the responsibility of data managers in clinical trials, companies of all sizes will benefit from engaging with data managers during the early phases of protocol development. You don’t want to finalize your protocol and then onboard a data manager to develop your case report forms. Data managers have a unique skill to pierce through protocol inconsistencies. For example, a data manager can quickly identify if the language in the protocol doesn’t match the schedule of assessments.

2. Writing skills are essential for communicating data issues

Data managers are involved in the development of case report forms, data management, and data review plans. But most data managers can get through these tasks with the use of templates from historical studies.

What’s more challenging is effectively communicating with clinical trial sites. The choice of words, sentence structure, and grammar a data manager utilizes to generate data queries is what matters the most. According to Gina Budman, a data management expert at Leading Edge CDM Solutions, “Make sure the site knows the problem and the possible solutions. Don’t say, ‘Correct this, change it,  this is wrong.’ You don’t want a lot of words there to bury the query request, but be really straightforward, as the sites are really busy.”

3. Take the time to understand your electronic data capture (EDC) requirements

If you’re in the market to purchase an EDC solution, you and your functional team need to take the time to understand your needs before contacting potential suppliers.

A quick search on Capterra reveals that there are at least 100 EDC solutions on the market. Your clinical team doesn't have the resources or bandwidth to evaluate each supplier. Below are some questions you need to ask your internal team before you start reaching out to suppliers.

  • What is it that you want your EDC system to do for you?
  • Do you want your EDC system to integrate with other systems? If yes, why?
  • What does success with a EDC platform look like for you?
  • As a company, how much and what kinds of risks can you tolerate?

Every study is unique, so your requirements for an EDC system will be unique. The more you can understand your business needs and clarify your end goal, the better choice you’ll make with your EDC solution.

4. Focus on standards, not on changing EDC vendors

Every time a new clinical EDC solution comes on the market, a data manager or senior manager will want to test drive the new piece of software.

Some data managers will want to swap their existing EDC with a new system, thinking about ways they can put an end to their current challenges. By swapping one EDC with another, you’ll introduce a new set of challenges, such as change management, training clinical sites, data migration, and more.

Instead, you want to focus on developing standards. For example, document the process for creating case report forms, develop a question bank for standard EDC questions, formulate a process for issuing, answering, and closing data queries, and develop a process for generating standard data cleansing listings.

5. Data managers with project management experience are priceless

Once the protocol is finalized, it’s handed off to the data manager to generate case report forms. This process requires the data manager to pull together a cross-functional team that includes a safety monitor, a scientist, and a statistician. The data manager also works with the programmers to configure the EDC.

To execute this well, a data manager will need to create a timeline from protocol sign-off to EDC go-live. Several meetings will need to be scheduled to review and approve case report form fields, data management plan, data review plan, and user acceptance testing.

These activities require a data manager to be a strong project manager. You can hire talent to handle each of the various data management activities, but you still need someone to pull it all together. This is why a data manager with project management experience is priceless.

6. Data review is not just a data management task

Once EDC is live and patients are enrolled in the study, clinical data starts to trickle in. Ongoing clinical data review is necessary and underappreciated. Usually, the data manager is performing the lonely task of looking at clinical data and working with sites to resolve open queries. But review of key safety and medical data fields requires additional review by a cross-functional team, not just the data manager.

For example, a safety monitor can tell if adverse events and medications are appropriate from a safety standpoint. Also, if sites are repeatedly entering incorrect data on a specific case report form, the data manager will need to collaborate with the study team to discuss the impact of incorrect date entry. For these reasons, execution of the data review plan is not just a data manager’s responsibility.

Interested in learning more about what Karen Green and Gina Budman have to say about clinical data management? Read this interview transcript from a recent Collaborations in Clinical Research event.

Which data management insight are you planning to implement next? Let me know in the comments section below.

About The Author:

Kunal Sampat is a senior manager, clinical research at Abbott Vascular and also the founder of Clinical Trial Podcast, a podcast for clinical research professionals. His goal is to help you accelerate your clinical research career and be a more effective leader. He enjoys connecting like-minded people, introducing new ideas, and immersing himself in an environment of continuous learning. You can find him on LinkedIn.

Note: This article reflects the author’s personal opinions and has nothing to do with his place of employment.