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Continuous Flow Diagrams in Clinical Research

We frequently get feedback from customers about how intuitive and easy-to-use Ready Room’s interface is.  There’s a good reason for that: Our interface is based on a Kanban board, a tool that was developed to help software development teams visualize the status of their work in progress.  In Ready Room, the Kanban board helps the front and back room inspection teams visualize the status of each inspection request.

The Kanban board gave rise to the continuous flow diagram, or CFD, a chart that shows the changes in a particular workflow over time.  Continuous flow diagrams are useful for analyzing a workflow to determine which parts are getting bogged down, and who might be waiting around with nothing to do.  You don’t need to track your work on a Kanban board to utilize a continuous flow diagram; as long as you have time- or date-stamped data, you can generate a diagram that helps you visualize your workflow.

Continuous flow diagrams are useful in clinical operations for visualizing the progress over time of multi-step processes.  eCRF completion, for example, is typically expressed in metrics like this:

  • eCRFs initiated:  5,050
  • eCRFs completed:  2,710
  • eCRFs SDV’d:  1,200
  • eCRFs locked:  620

This list provides useful data about the current status of these activities, but it doesn’t give us information about how the process is working over time. Are eCRFs being processed quickly or slowly? Where are the bottlenecks? We can’t even tell if the numbers are cumulative or incremental.

In contrast, below is a continuous flow diagram that captures the flow of eCRFs week by week:

The red band represents all the CRFs that are automatically generated by the system as new subjects are enrolled.  The yellow band is the site’s work in completing those CRFs.  The green band represents the site monitors’ work in source verifying the completed CRFs. The blue band is data management, resolving queries and locking the CRFs.

The width of each band gives us useful information about the workflow. Ideally, after an initial ramp-up, all the bands should be roughly the same width, which would indicate the sites are completing CRFs as fast as the system is initiating them; the site monitors are SDVing CRFs as fast as the sites are entering them; and data management is locking CRFs as fast as site monitors are SDVing them.  Instead, we see that the bands get progressively narrower the further “down” the process we go.  The red band is also getting bigger over time, showing that sites are particularly backed up with data entry.  Looking at this graph, we might apply additional resources at the sites.

Below is a different team’s work with the same number of CRFs over the same period of time:

In Week 4, the site saw an uptick in enrollment, but by Week 5 they had caught up with data entry. In Week 8, we see a narrowing of the green band, meaning that the pace of source data verification is not keeping up with CRF entry.  The blue band – CRF lock – is strong from Week 5 onward, showing us that data management is adequately resourced. This team is working in fits and starts, compared to the previous team, but ultimately they are locking a steadily increasing number of eCRFs each week.

A continuous flow diagram is a terrific example of the type of metric that lets you “course-correct,” as we discussed in an earlier blog post.

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