It is a common perception that the role of a Data Manager is only to perform what we call “Data Cleaning”; making sure the data is consistent and in line with the protocol by sending, answering, and closing queries (questions sent to the site through the system). However, a Data Manager’s role is more than that and it starts soon after the final version of the protocol is released and is available. From building the eCRF to the end of the study lock, a data manager must anticipate, decide, coordinate and control.
In this blog, I share an example of one of my studies in a rare disease where the sponsor wanted a trial extension of one of its studies that was about to be locked, I had to perform these steps:
Anticipate: The first step is to find out what the client wants in its eCRF and other tasks (SAE reconciliation, Protocol Deviations etc.). This is when you engage in important discussions with the sponsor and the data manager has to explain their point of view, lay out the limitations in terms of time, activities and budget, and also provide the reasons for why some things can be agreed on and some cannot, as well as offer solutions. In this study, some subjects from the initial study were about to make their last visit, meaning they would immediately be enrolled in the new one. So, the priority was to make sure that the sponsor’s needs were met within the allocated timeframe.
Decide: At this stage, we begin creating the documentation and the eCRF. For this study, it was complicated at times because I was put in touch with different people and the internal discussions took longer. Considering the timelines and budget, I presented the merits of some of my ideas for the project. My role was also to ensure that the client had all the information they needed and answer all their questions and concerns. Due to several requests, the study could not be pushed live at the scheduled time, and I instead offered a solution to go for a split go-live. At first, we would push the database live without the edit checks and then take time to list and to program all the checks they would want as per the allocated budget.
Coordinate: The data managers need to be proactive and good at anticipating any challenges. We faced some delays in getting feedback from the sponsor. But eventually, with efforts from both parties, regular reminders, and great teamwork, we managed to push live in good conditions.
Control: The work does not end for a data manager once the study is live. I then had to make sure that the rest of the activities were under control to avoid any surprises.
Read the interview with Jessica Bhoyroo to get more insights on data management.
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About the Guest Author of Blog:
Jessica Bhoyroo is a Clinical Data Manager at Cytel and she is based in Basel, Switzerland. Before joining Cytel, Jessica worked in several international profiles.
