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Related Concept Videos

Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...

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A real-time screening alert improves patient recruitment efficiency.

Chunhua Weng1, Candido Batres, Tomas Borda

  • 1Department of Biomedical Informatics, Columbia University, New York, NY 10032, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|December 24, 2011
PubMed
Summary

A new real-time patient identification alert significantly improved clinical research screening efficiency. This automated prescreening tool aids research coordinators, enhancing patient recruitment for clinical studies.

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Area of Science:

  • Clinical Research
  • Health Informatics

Background:

  • Cost-effective patient identification is crucial for clinical research but remains a significant challenge.
  • Existing research recruitment alerts offer limited support to clinical researchers.

Purpose of the Study:

  • To evaluate the efficacy of a real-time patient identification alert for clinical research coordinators.
  • To assess the alert's impact on screening efficiency and patient enrollment rates in a prospective cohort study.

Main Methods:

  • Retrospective data analysis of electronic screening logs and informal interviews with research coordinators.
  • Triangulation of data from log analysis and interviews to evaluate alert performance.
  • Comparison of enrollment rates between the real-time alert and two conventional recruitment methods.

Main Results:

  • Over 12 months, 11,295 patients were electronically screened, 1,449 interviewed, and 282 enrolled.
  • The real-time alert achieved an enrollment rate of 4.65%, significantly higher than conventional methods (2.01% and 1.34%).
  • A taxonomy of eligibility status was developed, and ineligibility factors were analyzed for correlations with age and gender.

Conclusions:

  • The automatic prescreening alert enhances screening efficiency for clinical research coordinators.
  • This automated tool is an effective aid for improving patient identification and enrollment in clinical studies.
  • Understanding ineligibility factors can further optimize patient recruitment strategies.