With the rise of complexity in clinical research, companies are constantly seeking innovative ways to optimize their patient recruitment processes for research trials. EMRs are not designed to search for medical terms in patient records, which limits accurate enrollment projections and increases time dedicated to manual chart review. Aspen Forge integrates with the EMR and “searchifies” patient records to give clinical researchers increased oversight into their connected patient population, more accurate feasibility projections, and patient match lists based on the input inclusion/exclusion criteria.
In this blog post, we will explore how simple it is to integrate our machine learning technology, Aspen Forge, into your recruitment process.
Aspen Forge is offered in three tiers and offers a range of data-driven solutions to enhance and accelerate your clinical research recruitment & workflows.
Step 1: Connect one or multiple EMR sources to a single instance of Forge. It doesn’t matter which EMR you use or how many different ones you have. Unify all patient health records from all EMRs into a single search platform.
Step 2: Identify which studies to pursue with our Population Analysis tool. Our machine learning software leverages natural language processes which enable quick searches through your EMR patient records to identify potential clinical trial candidates.
Step 3: Apply for study award by generating a data-driven Feasibility Analysis results for your connected population. See your recruitable population filtered by inclusion and exclusion criteria on a single dashboard.
Step 4: Win the trial!
Step 5: Begin searching for candidates based on the extensive inclusion/exclusion trial criteria using our Candidate Identification capabilities, complete with detailed reasoning as to why candidates were matched.
Step 6: Perform candidate outreach and track interest with our Recruitment Tracking solution.
Step 7: Push candidates into CTMS for screening and the next steps for enrollment.
With this 7-Step process, our sites have experienced up to 4x the revenue per study than traditional methods by identifying higher quality candidates more quickly. Aspen Forge can eliminate up to 66 hours of manual chart review per study (or 1500 hours per year when conducting 20 trials per year) on average because it enables complex search of clinical data, both structured and unstructured in ways that the EMR cannot. To learn more about our platform or to schedule a demo, reach out to us!