Far and wide: Exploring provider utilization of remote service provision for genome‐wide sequencing in Canada
Bibliographic record
Abstract
BACKGROUND: In Canada, funding for genome-wide sequencing (GWS; exome and whole genome) is provincially regulated. We characterized the uptake of GWS by genetics health professionals (GHPs) across Canada and describe how they use remote technologies for patient access to GWS and genomic counseling. METHODS: We distributed a survey to 574 Canadian GHPs addressing: GWS use, remote technologies (e.g., telephone, videoconferencing) for GWS and provider opinions regarding these technologies. Data were summarized using descriptive statistics. Associations between variables were evaluated using Chi-square and Fisher's Exact tests for categorical data, and t-tests or Mann-Whitney U tests for continuous data. RESULTS: Of 116 GHPs, 50% reported using GWS in the last year and 57% of GWS users reported using remote technologies. Clinical geneticists who did not use GWS reported lack of provincial funding as the principal reason. Remote technologies were most commonly used for informed consent and results, and rarely used for initial consultations. Average wait times for a GWS appointment were shorter for remote appointments (mean 44.2 (SD 40.2) weeks) than for in-person (mean 58.2 (SD 42.9), p = 0.036). CONCLUSION: The use of GWS varied across Canada, professional designation, and discipline. Funding remains a barrier to GWS access. Remote technologies increase patient access with reduced wait times.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".