A Real-Time Automated Patient Screening System for Clinical Trials Eligibility in an Emergency Department: Design and Evaluation.

ABSTRACT:

Background

One critical hurdle for clinical trial recruitment is the lack of an efficient method for identifying subjects who meet the eligibility criteria. Given the large volume of data documented in electronic health records (EHRs), it is labor-intensive for the staff to screen relevant information, particularly within the time frame needed. To facilitate subject identification, we developed a natural language processing (NLP) and machine learning-based system, Automated Clinical Trial Eligibility Screener (ACTES), which analyzes structured data and unstructured narratives automatically to determine patients' suitability for clinical trial enrollment. In this study, we integrated the ACTES into clinical practice to support real-time patient screening.

Objective

This study

SUBMITTER: Ni Y 

PROVIDER: S-EPMC6685132 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature