It is estimated that up to 72% of patients that are eligible and eventually participate in clinical trials are part of the investigative sites patient population. It is just too time consuming and difficult to find them with current methods.
In the last two decades, technology has drastically changed how we conduct business and lead our personal lives. However, medicine and more specifically the business of clinical trials hasn’t kept up. Finding patients for clinical trials, or patient recruitment, is still conducted very much as it was 20 years ago with very little having changed.
It’s no surprise that enrolling a sufficient number of patients in trials remains a chief bottleneck in the drug development process, attributing to delays of up to six months or more in 45% of studies. Relying on manual chart review of patient records to identify eligible patients that match inclusion and exclusion criteria is burdensome, expensive and time intensive.
This White Paper takes an in-depth view of CNLP (Clinical Natural Language Processing) and demonstrates the power of automated pre-screening to find markedly more patients in less time.
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