According to a new report by Cutting Edge Information (www.cuttingedgeinfo.com), 42.6% of companies that have the internal infrastructure in place to manage Phase IV studies in-house still choose to outsource much of the work associated with their post-marketing studies. The report, “Phase IV Clinical Trials: Post-Marketing Study Management Structure, Strategy & Benchmarks,” finds that company size influences the outsourcing of Phase IV activities.
Of the companies surveyed, only 44% of small companies and 40% of mid-sized companies have the internal infrastructure to support Phase IV management. This lack of internal infrastructure leads to 68% of small companies’ total Phase IV workload being outsourced. Mid-size companies outsource even more at an average of 80% of their total Phase IV workload.
Even though the majority of large companies (80%) have the means to handle Phase IV activities in-house, 57% still choose to outsource much of their post- marketing operations. High outsourcing percentages can be contributed to the fact that conducting the trials in-house would mean implementing a single platform across the clinical operations organization.
In larger companies with multiple disciplines, this standardization can be very taxing, according to the study authors.
“Outsourcing Phase IV activities is a strategy that has both benefits and downfalls,” says Jon Hess, research team leader and lead author of the report. “Outsourcing allows companies to not have to manage a field force and staffing logistics, but that comes at the cost of relinquishing control over study execution.”
The report also contains lists of performance measures employed by the pharmaceutical, biotech, and medical device companies profiled in the report, as well as target and actual performance metrics. Among the metrics included in the report are: cycle times (such as “time from first patient in to last patient out” and “time from database lock to statistical tables complete”), resource-based measures (including “patients per CRA”), and efficiency or operational metrics (such as “data errors” and “patient retention rates”).