A better process for recruiting patients to the right clinical trials is deceptively simple: produce a single source for massive quantities of comprehensive, quality data and sophisticated trial algorithms. The hard part is that it can only be achieved by long, hard, detailed work that doesn’t skip a single step.
It begins with deeply understanding the patient population, it requires identifying the patients of tomorrow and it means finding the right sites where the patient populations can be found for the specific clinical trials that will produce the discoveries we need to take giant leaps forward in the quality of care.
Here’s how it works. The right data and tools can help researchers improve the scale and precision of clinical trial recruitment.
While the number of available clinical trials is increasing, the reality is that about 50% of trials do not meet recruitment goals. Proper adoption of a clinical workflow based on new digital tools with the right data can ameliorate this challenge, but simply being data-driven is not enough. The core value of putting patients over process must rule the day so that the industry migrates efforts toward drug development tailored to patient population.
The goal is to use real-world data (RWD) to improve clinical trial design, as well as to find consistent and predictable methods to accelerate clinical trial recruitment. This means that sponsors and their clinical research organizations (CROs) must use digital tools to decipher which patients should be enrolled and where clinical trials should be opened.
Related article: New Study Could Speed Up Drug Trials
We need to focus on helping to find eligible patients faster, today. We need to provide early insights to broaden or enrich a trial’s patient population with the use of specific EHR data fields like diagnosis codes, histologies, treatment pathways to trial, laboratory tests around the time of trial availability, and comorbidities at and before trial availability.
All of this information is currently spread out among many different clinical settings and systems – hospital EMRs, practice management systems, lab information systems, biobanks, and registries. Centralizing this information into one repository is one way to get one source of truth, where researchers can draw evidence-based insight to help design better inclusion and exclusion criteria.
Patient recruiting can be improved through the use of digital technology and automation to identify and match eligible patients. Automation and technology can help clinical site personnel discover much more information about the uniqueness of the patient population in terms of geographic location, as well as the patient’s age, gender, type and stage of a disease, treatment history, and other medical conditions that affect the patient’s ability to participate in a clinical trial.