Data analytics, big data, little data – whatever you want to call it – all boils down to one central theme: numbers tell stories. From trying to determine which marketing channel has the highest ROI to deciding how to recruit the most qualified participants for a clinical trial, you’ll be better off if you let the numbers guide your efforts. Use the tips below to leverage your datasets and optimize your recruitment efforts.
Find strength in numbers.
Most clinical trials, depending on the range of recruitment efforts, have a plethora of numbers from which we can derive insights. Whether it’s the number of website visits, recruitment totals, prequalified referrals, or active research sites, each data point presents an opportunity for optimization. For instance, many patient recruitment efforts have gone digital, including the creation of study-specific websites, which often allow users to prescreen for a clinical trial. By implementing an effective web analytics platform to measure user interaction, you can determine which questions are leading patients to disqualify. Using this information, you can then make amendments to the prescreener verbiage, switch up marketing tactics to reach more-qualified audiences, or even help identify stringent study protocols with minute restrictions that cause high disqualification rates.
Vary your sources.
Looking at website stats, homing in on enrollment logs, or monitoring research site activity are all good places to start, but to grasp the bigger picture of your recruitment efforts, it’s necessary to pull and cross-reference data from a variety of sources. To illustrate, your web analytics platform is an effective way to keep track of who is (and is not) prequalifying for your clinical trial, and the channel through which they arrived to your recruitment website. But once that potential referral prequalified, what happened next? Did they show up for their screening appointment? Did they lose interest? Did the research site ever follow up? Building a database that incorporates data from multiple recruitment touchpoints allows you to see large amounts of study-specific data in one centralized location and identify bottlenecks causing prolonged recruitment efforts.
Measure, report, repeat.
Optimizing your study prescreener should not be a one-time effort. The key to leveraging data analytics to improve prescreening results lies in constant measurement of recruitment results. Ongoing monitoring and reporting is the essential, final piece of the puzzle. Each time you examine your study prescreening efforts, it’s wise to compile a comprehensive report summarizing your findings and then generate specific recommendations to improve efforts. Sometimes even the smallest changes can have significant impact on converting disqualified screeners into prequalified referrals.
To learn more about what analytics can do for patient recruitment, check out our analytics capabilities.