The competition between recruitment companies, who are searching for eligible patients for clinical trials, is expanding rapidly.
All of our colleagues in the business of patient recruitment are in a constant competition of making an outreach to different patient profiles on a global scale.
Audit from several studies has proven that patient enrollment is one of the most time consuming aspects of clinical trials. This makes patient recruitment one of the most common bias in missed deadlines – in the worst case, up to 30 % of the clinical trial timeline.
Optimization of patient recruitment is one of the best ways to accelerate clinical trials and hereby reduce time to market.
Technology is rapidly changing. We now have new media channels, such as social networks and AdWords, which are changing the way information is distributed. Therefore, it is time to think intelligently to reduce the time to market and optimize the return on investment related to patient recruitment.
iRecruit is a new player in the Patient Recruitment business. We believe that with our expertise generated through more than 15 years within the field of Clinical Research we are able reduce time significantly by using our unique Affiliate-network strategy.
Welcome to iRecruit – Intelligent Driven Patient Recruitment
Customers using iRecruit are able to:
Reach planned target
iRecruit uses a unique pre-recruitment strategy,
in which we pre-select potential subjects in our database.
Through our media partner strategy, we are able to
pre-recruit patients before the study is initiated.
The entire recruitment funnel is visualized from
first visit to delivery on the specific site.
Increase the enrollment
Through our affiliate network, we are able to
target a large number of potential subjects.
Previous studies have shown that iRecruit increases
the enrollment with up to 76 % (best case) 28 % (worst case).
Our responce rate is on average 87 %.
Reduce the drop-out rate
Our two-string recruitment strategy is your
guarantee for high retention.
Previous studies has shown a drop-out rate < 10% (worst case)
Our fail-respond-rate is < 7%.