Matching Patients to Accelerate Clinical Trials (MPACT): Enabling Technology for Oncology Clinical Trial Workflow.

Summary

The MPACT platform uses natural language processing and data science to automate the identification of cancer patients who meet specific clinical trial eligibility criteria. This technology reduces the manual screening burden on research coordinators, allowing veterans to access high-quality clinical trials more efficiently.

Key result

The MPACT platform utilizes natural language processing and data science to reduce the time research coordinators spend identifying eligible patients for oncology clinical trials.

Abstract

Clinical trial enrollment is impeded by the significant time burden placed on research coordinators screening eligible patients. With 50,000 new cancer cases every year, the Veterans Health Administration (VHA) has made increased access for Veterans to high-quality clinical trials a priority. To aid in this effort, we worked with research coordinators to build the MPACT (Matching Patients to Accelerate Clinical Trials) platform with a goal of improving efficiency in the screening process. MPACT supports both a trial prescreening workflow and a screening workflow, employing Natural Language Processing and Data Science methods to produce reliable phenotypes of trial eligibility criteria. MPACT also has a functionality to track a patient's eligibility status over time. Qualitative feedback has been promising with users reporting a reduction in time spent on identifying eligible patients.

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