Automated matching software for clinical trials eligibility: measuring efficiency and flexibility.
BACKGROUND
Clinical trials (CT) serve as the media that translates clinical research into standards of care. Low or slow recruitment leads to delays in delivery of new therapies to the public. Determination of eligibility in all patients is one of the most important factors to assure unbiased results from the clinical trials process and represents the first step in addressing the issue of under representation and equal access to clinical trials.


METHODS
This is a pilot project evaluating the efficiency, flexibility, and generalizibility of an automated clinical trials eligibility screening tool across 5 different clinical trials and clinical trial scenarios.


RESULTS
There was a substantial total savings during the study period in research staff time spent in evaluating patients for eligibility ranging from 165h to 1329h. There was a marked enhancement in efficiency with the automated system for all but one study in the pilot. The ratio of mean staff time required per eligible patient identified ranged from 0.8 to 19.4 for the manual versus the automated process.


CONCLUSIONS
The results of this study demonstrate that automation offers an opportunity to reduce the burden of the manual processes required for CT eligibility screening and to assure that all patients have an opportunity to be evaluated for participation in clinical trials as appropriate. The automated process greatly reduces the time spent on eligibility screening compared with the traditional manual process by effectively transferring the load of the eligibility assessment process to the computer.
Dept of Internal Medicine, School of Medicine, Virginia Commonwealth University, Massey Cancer Center, United States. lpenbert@vcu.edui
Lynne
L
Penberthy
Richard
R
Brown
Federico
F
Puma
Bassam
B
Dahman
D000293:Adolescent; D000328:Adult; D002986:Clinical Trials as Topic; D003256:Community Participation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018579:Patient Selection; D010865:Pilot Projects; D012107:Research Design; D012189:Retrospective Studies; D012984:Software; D055815:Young Adult