Steps to Manage Clinical Trial data
By Anders Lindquist, Independent Clinical Research Consultant
A standard operating procedure (SOP) simply and clearly describes how a particular task is to be performed by staff at an organization. When tasks are performed consistently, it allows personnel to be more efficient and productive. In the context of properly maintaining an electronic data capture (EDC) system, standard operating procedures (SOPs) are essential to ensuring that regulatory and organizational policies are met. Training for new staff and workload distribution activities are also enhanced by SOPs.
Furthermore, sponsors and other affiliate clients are typically impressed when questions of site performance and processes are addressed in standard operating procedures. However, the actual task of writing an SOP is not easy. The best examples are simple to read and allow staff to quickly understand how their specific role contributes to the team. So what is the best approach for creating an SOP? The best approach involves developing a plan with all staff members that are involved with data collection at your institution, and defining the relevant roles and responsibilities. This article will look one recommended approach for creating an SOP.
1) Collect a list of required activities
Start by collecting a list of activities that are required. Ask staff members who are involved with data collection to provide this list. This means that if your site has 2 to 3 people involved with data collection on any given study, ask them to write down steps that they typically accomplish with each study. Try to fill in the gaps and answer questions as they come up. The goal is to provide this SOP to anyone at your site, so they can clearly understand responsibilities and timelines. In the beginning, don’t be overly concerned about making the process more efficient or easier to follow. That piece will come down the road.
BMC Medical Research Methodology at the 35th Annual Conference of the .. — BMC Pediatrics
The conference will focus on issues such as design and analysis of clinical trials, methods in biostatistics and development of clinical prediction models.