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

Area of Science:

• Oncology
• Health Informatics
• Clinical Trial Management

Background:

• Clinical trial enrollment faces significant delays due to the time-intensive patient screening process.
• The Veterans Health Administration (VHA) prioritizes enhancing Veteran access to high-quality cancer clinical trials.

Purpose of the Study:

• To develop and evaluate the MPACT (Matching Patients to Accelerate Clinical Trials) platform.
• To improve the efficiency of the clinical trial screening process for research coordinators.

Main Methods:

• Developed the MPACT platform with input from research coordinators.
• Integrated Natural Language Processing (NLP) and Data Science for eligibility criteria phenotyping.
• Implemented workflows for trial prescreening and patient screening.
• Included functionality for tracking patient eligibility status over time.

Main Results:

• MPACT employs NLP and Data Science to generate reliable phenotypes of trial eligibility criteria.
• The platform supports both prescreening and screening workflows.
• Users reported a reduction in the time required to identify eligible patients.
• Qualitative feedback indicates promising improvements in screening efficiency.

Conclusions:

• The MPACT platform effectively addresses the time burden in clinical trial screening.
• MPACT enhances efficiency in identifying eligible patients for cancer clinical trials within the VHA.
• The use of NLP and Data Science in MPACT shows potential for broader application in clinical trial matching.