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A pragmatic implementation research study for In Our DNA SC: a protocol to identify multi-level factors that support the implementation of a population-wide genomic screening initiative in diverse populations

Authors :
Caitlin G, Allen
Daniel P, Judge
Elissa, Levin
Katherine, Sterba
Kelly, Hunt
Paula S, Ramos
Cathy, Melvin
Karen, Wager
Kenneth, Catchpole
Catherine, Clinton
Marvella, Ford
Lori L, McMahon
Leslie, Lenert
Source :
Implementation Science Communications. 3
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

Background In 2021, the Medical University of South Carolina (MUSC) partnered with Helix, a population genetic testing company, to offer population-wide genomic screening for Centers for Disease Control and Preventions’ Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia to 100,000 individuals in South Carolina. We developed an implementation science protocol to study the multi-level factors that influence the successful implementation of the In Our DNA SC initiative. Methods We will use a convergent parallel mixed-methods study design to evaluate the implementation of planned strategies and associated outcomes for In Our DNA SC. Aims focus on monitoring participation to ensure engagement of diverse populations, assessing contextual factors that influence implementation in community and clinical settings, describing the implementation team’s facilitators and barriers, and tracking program adaptations. We report details about each data collection tool and analyses planned, including surveys, interview guides, and tracking logs to capture and code work group meetings, adaptations, and technical assistance needs. Discussion The goal of In Our DNA SC is to provide population-level screening for actionable genetic conditions and to foster ongoing translational research. The use of implementation science can help better understand how to support the success of In Our DNA SC, identify barriers and facilitators to program implementation, and can ensure the sustainability of population-level genetic testing. The model-based components of our implementation science protocol can support the identification of best practices to streamline the expansion of similar population genomics programs at other institutions

Details

ISSN :
26622211
Volume :
3
Database :
OpenAIRE
Journal :
Implementation Science Communications
Accession number :
edsair.doi.dedup.....841405fb22a3b5fcf85e98cf327131bf
Full Text :
https://doi.org/10.1186/s43058-022-00286-2