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Finding Patients For 
Clinical Trials Shouldn’t Be Such A Trial

Finding patients for clinical trials is difficult, expensive, and time consuming. Efficiently and consistently sifting through data from multiple sources to screen for eligibility can be the limiting factor in how large, robust, or timely a clinical trial can be. 

Our Solution for Clinical Trials

We bring the power of artificial intelligence to make screening for patients smarter.

Select Stage:

The Load is Great

Multiply Your Efforts

Work Smarter
How It Works
Clinical Knowledge
Meet Where You Are

You Are On The Case, But The Load Is Too Great

 

Investigators of all types run into a similar problem. You know exactly who you are looking for and the steps you need to go through, but the volume of potential candidates is overwhelming. Replicating your screening efforts across the potentially thousands of possible trial participants would take countless hours—hours you obviously don’t have. If you had a way to automate many of the repetitive tasks involved in the screening process, you could gain back that time to focus your efforts on higher-level needs.

Multiply Your Efforts

You need a way to clone yourself—or at least your process. You and your team need a consistent way to delve into medical profiles across multiple systems, read structured data and unstructured clinician notes, and determine a patient’s possible eligibility. The size of the screening pool and the speed of the screening process currently limit your ability to identify qualified participants for your clinical trial. Speed and efficiency could change that. The larger the pool of patients you can screen, the larger the pool of eligible patients for a trial ultimately will be. The faster you can deliver eligible patients to a trial, the more timely your research can be.

Work Smarter

The solution is Artificial Intelligence (AI). AI can be trained to replicate what you would do if you had the time. It learns to apply the same logic, look for the same criteria, and make the same determinations as you would—but at scale. Now you can expand the possibilities to multiple sources that can be screened consistently, accurately, and efficiently, so you can find the right patients to participate in your trials. 

 

How it Works

Our software can aggregate both structured and unstructured data across multiple sources to screen for your trial’s patient criteria. Our Natural Language Processing (NLP) is able to read through clinicians’ notes, just like you would, to find information that may not be in structured data fields. Machine Learning means the process only gets smarter and more efficient over time. 

Pieces Predict Is Steeped in Our Clinical Knowledge

Pieces Predict has been developed by working clinicians, so our AI is already based on thinking like you do. We understand the process of screening for trial participants firsthand. We’ve been working with multiple EHRs and are very familiar with the quirks of all the major systems. Our algorithms have been developed, tested, and verified through our Clinician-in-the-Loop® process and our process has been peer-reviewed—all to give you confidence in the end result. Pieces Predict is adaptable to work across multiple data systems to deliver you clean, actionable data in easy-to-read dashboards.

We’ll Meet You Where You Are

Whether you are at the initial stage of an RFP, or you have already started recruiting for your clinical trial, we can help. It all starts with a conversation.

Let’s Talk

We’d like to show you Pieces Predict in action so you can see how screening for clinical trials can be wider, faster, and more efficient. 

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