Increasing the efficiency of trial-patient matching: automated clinical trial eligibility pre-screening for pediatric oncology patients.

ABSTRACT:

Background

Manual eligibility screening (ES) for a clinical trial typically requires a labor-intensive review of patient records that utilizes many resources. Leveraging state-of-the-art natural language processing (NLP) and information extraction (IE) technologies, we sought to improve the efficiency of physician decision-making in clinical trial enrollment. In order to markedly reduce the pool of potential candidates for staff screening, we developed an automated ES algorithm to identify patients who meet core eligibility characteristics of an oncology clinical trial.

Methods

We collected narrative eligibility criteria from ClinicalTrials.gov for 55 clinical trials actively enrolling oncology patients in our institution between 12/01/2009 and 10/31/2011. In parallel, our E

SUBMITTER: Ni Y 

PROVIDER: S-EPMC4407835 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature