Why Hasn’t Technology Paid Off in Clinical Research?

There’s a telling figure at the end of an April 2012 discussion paper from The Institute of Medicine of the National Academies, “Transforming the Economics of Clinical Trials.”

The authors, Judith M. Kramer and Kevin A. Schulman of Duke University, sum up the disappointing results to date of adopting new technologies in clinical research, with EDC the most prominent example:

image for 2-6 post“Over the last decade, electronic data capture (EDC) has made some progress in transforming this model. [EDC] has produced some efficiency gains as edit-checks reduce the cost of the manual data-query process. However, the EDC platform was largely embedded in the traditional clinical research business model, with legacy concepts around site monitoring and validation. New opportunities for central statistical monitoring of data in these systems were not widely embraced (Morrison et al., 2011). Patient screening and recruitment costs remained largely unchanged.”

Kramer and Schulman do an excellent job of explaining at a macro level some strategies that might enable the industry to realize the productivity gains that should flow from technology. They conclude: “A concerted, multi-stakeholder effort to address adoption of new business models for clinical research is a critical step in unlocking the potential economic transformation of clinical research in the coming decade.”

While I am in sympathy with the multi-stakeholder effort that Kramer and Schulman call for, I think there’s a lot we can do now. We don’t have to wait and see what that effort produces. For example, you’ll find a discussion of process change as a requirement for reaping the benefits of technology in The Agile Approach to Adaptive Research: Optimizing Efficiency in Clinical Development. Wiley 2010. In a chapter entitled “The Agile Platform,” the book discusses infrastructure and process requirements for improving efficiency in individual trials and programs.

The key is enabling earlier, better decisions based on deploying technology to provide a stream of timely actionable information. That’s why this blog often discusses technology-enabled steps we can take to improve the efficiency of monitoring, enrollment and other key operational areas. You will find more posts on such themes over the next several months.

But for now, take another look at the figure above.  Compare your organization’s trajectory to the curves in the figure. Even with the industry-wide cost trajectory pointing in the wrong direction, there are bound to be exceptions. We think successful implementation of adaptive monitoring and other innovations is enabling our organization to buck the disastrous productivity trend shown in the figure.

Ask yourself if your organization is bucking the trend. If not, why not?

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