Barriers and Facilitators to the Implementation of Clinical Genome-Wide Sequencing in Health Systems
Bibliographic record
Abstract
Background: Use of genome-wide sequencing (GWS) (i.e., exome sequencing (ES) and genome sequencing (GS)) for rare disease diagnostics achieves higher diagnostic yield compared to conventional testing strategies. Implementing GWS as a publicly funded test is not uniform across or within countries. It remains uncertain whether barriers and facilitators to implementing genomic services, like GWS, are universally experienced or if specific barriers and facilitators are unique to regions or countries. Methods: This thesis examined the barriers and facilitators to implementing clinical GWS in different healthcare systems, with a particular focus on Canada. First, a scoping review was conducted to describe the global landscape of genetic and genomic services and the factors that influence GWS implementation. Then, a multiple case study was conducted to understand the variability in provincial genetic service delivery and clinical GWS implementation approach in four Canadian provinces. The case study also aimed to identify perceived and experienced barriers and facilitators to clinical GWS implementation. Qualitative interviews and document review were used for data collection. Data were thematically analyzed using a mixed, deductive-inductive approach. Results: The scoping review and the case study identified both shared and unique factors that influence clinical GWS implementation across diverse healthcare systems. The scoping review identified common barriers to clinical GWS implementation across countries with varying capacities for delivering genetic services. These included shortage of a trained workforce, lack of a national genomics strategy, and the low prioritization of genomics within the healthcare system, all of which contribute to delays in advancing genomic services. The case study identified a common, centralized approach to clinical ES implementation across the four Canadian provinces. The approach to implementation in each province was driven by significant resource requirements, specialized expertise, and the need for coordination between the clinical services and diagnostic laboratories. The case study also identified shared barriers and facilitators to provincial GWS implementation, while also highlighting factors that are more salient in specific provinces. Conclusions: This thesis presents evidence on critical factors for clinical GWS implementation in different health systems, offering valuable insights for jurisdictions seeking to prioritize the development and implementation of novel genomic technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.101 | 0.195 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".