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Record W3201202195 · doi:10.1002/mgg3.1784

Far and wide: Exploring provider utilization of remote service provision for genome‐wide sequencing in Canada

2021· article· en· W3201202195 on OpenAlexafffundabout
Emily A. Enns, Tasha Wainstein, Nick Dragojlovic, Nicola Kopac, Larry D. Lynd, Alison M. Elliott

Bibliographic record

VenueMolecular Genetics & Genomic Medicine · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsBC Children's HospitalCentre for Advancing Health OutcomesWomen's Health Research InstituteUniversity of British ColumbiaMcGill University
FundersProvincial Health Services AuthorityGenome British ColumbiaBC Children's HospitalChildren's Hospital FoundationCanadian Institutes of Health ResearchGenome CanadaMcGill University
KeywordsService providerBusinessService (business)Data scienceInternet privacyComputer scienceMarketing

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.250
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes3
Has abstractyes

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