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The role of a data manager has evolved considerably during the last few years. From primarily having responsibilities dedicated to one Electronic Data Collection system (EDC), such as collecting, securely storing, and ensuring the compliance of data, to today’s data managers having many more accountabilities. They play a vital role in supporting the smooth operation of any organization that captures and processes data, in any capacity and for any industry.

For part one of this blog, we’ve interviewed Jorge Torres Borrero, Senior Clinical Data Manager here at Veramed, to find out more about what is involved in his day-to-day role.   

Hi Jorge, thanks for taking the time to talk to us today. So, what is clinical data management?

Data management is a broad discipline that deals with a range of responsibilities relating to data, including: 

  • Capture of data through the development of different databases 
  • Flow of information and data into separate systems through various forms of integrations 
  • Quality assurance of the data and interpretation by ensuring data cleanliness and that it is fit for use in informing business decisions 

What does a “normal” day look like for you?

What happens in my day can vary a lot depending on which stage of the trial process I’m working on.

Through startup and database updates, I connect regularly with clients to ensure that the specifications of each database meet their requirements and are in accordance with Standard Data Tabulation Model (SDTM) and Clinical Data Acquisition Standards Harmonization (CDASH) guidelines.

In the study maintenance phase, I follow up with status reports for database progress, regularly review and query data for quality assurance and work with the clinical operations teams to ensure that all data entry is up to date and any issues are resolved so that the database is “lock-ready”. This is important as locking is a technique used to control access to data so that multiple transactions or processes don’t interfere with one another and lead to inconsistencies or corruption of interpretation results. At the end of the trial, I make sure that all reports are cleaned and fully explained, that stakeholders are happy with the quality of the data and then decommission the database as required.

I’m also personally involved in data analytics on the studies that I work on, and for me, it’s a highlight of my role. I love helping study teams understand data trends, and I firmly believe that leveraging our data and learning from these trends is how we improve data quality and drug development timelines. Any time a trendline or data values are unexpected is an opportunity to reflect on our study conduct and determine if there’s been any bias affecting it. We work in various programming languages in collaboration with biostatistics programming, but in data management, we also implement our own tools and knowledge to develop these reports and metrics for our clients on a regular basis.

What would you say are the main skills that a data manager needs?

The role of a data manager today is so much more than just being lost in data and data analysis 24/7. While data is still the greatest priority, my responsibilities have multiplied which means juggling many different priorities each day. To this, I need to deploy many different skills, including project management. As project managers, we take on the responsibility for managing the complete life cycle of a study database, and this requires forecasting various task deadlines and cross functional viewpoint considerations. Being able to handle various studies simultaneously and properly prioritize the many tasks we carry out day-to-day is essential.

Strong interpersonal skills are a very important skill for a data manager too. We collaborate with various teams, data vendors and stakeholders, therefore excellent communication with all parties involved in the study is essential. I always advocate for data managers to have some programming or data logic knowledge since it can help them to communicate effectively with biostatistics programmers and database developers. In my current role, I also carry out database programming, which is very helpful in understanding the overall structure of data, and how best to present that data to a client.

Are there any skills specific to clinical data management that you feel are important?

In addition to the skills I’ve already mentioned, I would say that a good understanding of industry standards, such as SDTM and FDA submission guidelines, is crucial for the success of downstream processes, such as reporting and biostatistics ingestion of the data for tables, listings, and figures. All stakeholders depend on us to have high-quality, accurate, and well-structured data and the best way to guarantee this is by following the guidelines set in our industry by multiple leadership groups.

How important is communication for a data manager?

Data Managers engage with many different groups of people who are working on various tasks, therefore knowing how to communicate and collaborate effectively are an essential part of the process and therefore vital skills required for the role. I’ve found that proactive communication on both intentions and concerns is important for the smooth progression of our work and to help avoid any conflicts. Although a lot of our communication is done through virtual interfaces, it’s just as important to be comfortable integrating with data teams in person – especially for investigator meetings, which is where many new developments in the study happen. Since we contribute heavily to the discussions surrounding how and when data collection occurs, it’s critical that we can communicate with everyone in the study development team, and the clinical teams treating the patients.

Fortunately, Veramed understands the importance of excellent communication, and this is a focus of our ongoing professional development, along with skills around developing emotional intelligence and diversity, which helps us to better understand and collaborate the different teams we work with.

In the next part of this blog, we’ll explore the relationship between data managers and statisticians in clinical trials, the responsibility of data managers for facilitating the implementation of novel trial designs, and how they maintain quality through good clinical data management practices as technology and trial designs become more complex.

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