AI Chart Review: Automated Patient Eligibility Analysis for Clinical Research

Imagine a tool where you can upload a patient’s medical records and it determines whether the patient is eligible or not for each of your trial's Inclusion/Exclusion (I/E) criteria in mere seconds

Quri’s AI Chart Review feature is designed to vastly automate your patient evaluation process. Our HIPAA-Compliant AI engine, Aura: 

• Understands the depth and nuance of the trial's requirements, comprehensively ingesting and interpreting the inclusion/exclusion (I/E) criteria and prohibitive medication requirements of the study.

• Intelligently parses through a potential participant's medical records, including labs and procedure, analyzing both structured and unstructured (including hand-written) patient data.

• Discerns and determines the patient's eligibility for your clinical trials, providing a thorough report of its conclusion (showcasing the reasoning of both explicit information and nuanced insights.

The Problem

Clinical trials are the engine of medical advancement. Often overlooked, clinical sites provide the FDA with the quality data needed to bring new treatments to patients who need them most. This journey from research to approval is fraught with complexities, particularly in the patient recruitment and enrollment process for Phase III or Phase IV studies. These late-stage trials have stringent inclusion/exclusion (I/E) criteria to ensure the safety and efficacy of the treatment for a specific patient population. While necessary, these criteria introduce significant challenges for clinical research sites, often making patient recruitment an expensive and time-consuming task.

One of the most significant bottlenecks in the patient screening process is the retrieval and validation of medical records. Many trials require the review of patient medical records, which can be hundreds of pages long and take 30-40 minutes per record. Whether a site works with an electronic medical record system or paper records, clinical research staff must spend countless hours collecting and evaluating these records to determine if the patients are eligible and properly qualify for the study

Managing multiple studies simultaneously further complicates this process. Each study has its own I/E criteria, making it challenging to keep all criteria in mind while reviewing charts. It’s not uncommon for a patient to be ineligible for one study but a perfect candidate for another. Identifying these opportunities efficiently requires a level of coordination and data analysis that is often beyond the capacity of manual processes.

The Solution: AI Chart Review

Saving Time and Enhancing Efficiency:

In a recent case study, our AI tool reduced the chart review time from an average of 40 minutes to just 4 minutes. This dramatic reduction in time allowed the clinical site to screen more patients efficiently, focusing their efforts on patient care and trial management instead of getting bogged down by lengthy reviews.

Empowering Quality Control:

Beyond matching patients to trials, our AI tool serves as a powerful quality control tool. It provides comprehensive reports that detail the reasoning behind each eligibility decision, backed by data and analysis. This transparency aids in maintaining high QC standards and provides valuable insight on recruitment barriers.

Seamlessly Managing Multiple Studies:

Our platform is uniquely equipped to handle the complexity of managing multiple studies simultaneously. By analyzing patient data across various trials, the AI tool can quickly identify where patients might be a better fit, optimizing recruitment efforts and improving the chances of exceeding enrollment goals.