Why is Enrollment So Hard?

Although enrollment is one of the most pivotal determinants of study success, most researchers acknowledge doing poorly yet seem unable to improve their methods. As an industry, our performance is shockingly feeble: on average, a paltry 15% of studies enroll on time. In most businesses, that kind of performance would be a clear definition of failure. Combine this with other surprising metrics such as spending 1/3 of study budgets on rework and you begin to wonder how long you would survive if you were in any other industry.

Extended timelines directly hurt study costs – take the painful change order that is a staple of the CRO. Most study budgets end up being at least 20-30% over original pricing, often 100%, and this is driven primarily by slow enrollment. A far bigger price is the indirect cost of delayed time to market, where opportunity costs range between 4 and 80 million dollars a month and can transform a potential market leader into an also-ran.

Taking a lesson from other industries, particularly manufacturing, the answer is remarkably simple – a matter of having certain fundamental tools and access to timely information that enables competent decision making. This basic principle, timely and actionable information, is what is largely (but not entirely) lacking in pharma. This issue is: what information do I need to access to be able to know how to improve enrollment? Three important questions affect enrollment:

• What is getting people in the door?
• What then prevents people from getting into the study?
• Why do we lose people during a study?

With these questions answered, the majority of the issues faced in the enrollment process are no longer troublesome. A project manager who is aware of all these aspects of her study can uncover and share best practices among sites in order to solve these common enrollment issues. Below I’ll provide some examples of how information access and empowered decision making by study project managers made a substantial difference in the success of enrollment. These examples are taken from actual studies that utilize sophisticated technology.

First let’s look at an example of getting people in the door. In this instance, the study was for a new STD treatment. The project manager had systems that provided immediate field data of enrollment rates by site. When she noticed that one site was enrolling much faster than the rest, she quickly determined from the site coordinator why: recruitment flyers in the restrooms of local nightclubs and bars. The project manager swiftly notified the other sites of this technique and the three sites which chose to implement this method subsequently showed a substantial increase in enrollment rate, allowing the study to enroll several months ahead of schedule. Timely knowledge of the success of an unusual idea at one site made all the difference.

Next, let’s look at a case of enrolling people into a study once we’ve gotten them into the door. Oftentimes this can be a tricky piece of the enrollment puzzle. In the case of a pediatric growth hormone study, the project manager noticed a sudden surge in screen fails at a key site in the study. He immediately contacted the site coordinator to start investigating the cause of the spike. It was soon discovered that potential patients were screen failing due to an issue with the QC of the instrument being used to test samples. Once they fixed that issue, the kits from those subjects were once again usable. It was an analysis issue, and not that the subjects themselves were out of range. In a study that was otherwise difficult to enroll, many viable patients would have been excluded if the project manager had not been able to quickly spot the issue and work to solve it.

The moral of the story is to ensure access to actionable, role-specific information in near real-time. This is the rare exception in pharma, but this approach is being implemented by some CROs right now. It’s time for the rest of pharma to catch up.

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