ArticleResearch square2026
What it Takes to Implement Population-Based Genomic Screening: A Multi-Site Qualitative Study of Implementation Determinants Across Health Systems.
Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
14 authors.
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Abstract
Background: Population-based genomic screening (PGS) holds promise for identifying individuals at elevated risk for hereditary conditions. However, the absence of implementation guidance limits the scalability and impact of these programs. This qualitative study aimed to identify facilitators and barriers to PGS implementation among healthcare settings at different phases of PGS implementation. Methods: We conducted qualitative interviews with implementation team members, including genetic counselors, physicians, information technology and informatics personnel, study coordinators, and institutional leaders across 10 PGS sites. Sites were categorized as pre-adoption, implementing, and sustaining. Interviews explored implementation experiences, from the decision to adopt a PGS program through the return of results. Transcripts were coded using a rapid qualitative analysis approach using the Consolidated Framework for Implementation Research (CFIR) 2.0. We completed a data matrix heat map to visualize differences in CFIR 2.0 determinants across phases of PGS implementation. Results: We completed 34 interviews across 10 PGS sites (four pre-adoption, four implementing, and two sustaining). We identified 13 key CFIR 2.0 determinants across sites. Pre-adoption sites reported barriers related to financing, low institutional priority, workflow complexity, and limited patient and provider genomic knowledge, with mixed views on compatibility and resources. Implementing sites cited complexity in building out workflows and infrastructure, gaps in downstream clinical capacity, and uneven provider engagement; external partnerships, supportive leadership, and strong digital infrastructure facilitated progress. Sustaining sites identified persistent knowledge gaps and resource strain despite mature workflows, but benefited from robust partnerships, strong relational connections with clinical champions and lab partners, and continued leadership engagement. Conclusions: PGS implementation is shaped by phase-specific inflection points and ongoing barriers and facilitators that evolve across implementation phases. Financing and institutional prioritization were critical to moving programs from pre-adoption to implementing, while partnerships and relational connections were essential for implementing and sustaining sites. Barriers identified across CFIR domains such as policy constraints, and ongoing knowledge assessments require adaptive strategies that are specific to the phase of implementation, rather than one-time solutions. These results underscore the importance of dynamic implementation strategies that evolve alongside the PGS program.
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