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Record W4392607060 · doi:10.1016/j.gimo.2024.101458

P559: A novel alternate service delivery model for genetic counseling in a rural population: The New Brunswick experience

2024· article· en· W4392607060 on OpenAlexaffabout
Katherine Hodson, Y. Zhu, Lynn Macrae, Mouna Ben Amor

Bibliographic record

VenueGenetics in Medicine Open · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsDr. Georges-L.-Dumont University Hospital Centre
Fundersnot available
KeywordsService delivery frameworkGenetic counselingService modelService (business)Rural populationPopulationPsychologyBusinessSociologyDemographyBiologyGeneticsMarketing

Abstract

fetched live from OpenAlex

Patients accessing genetics services in traditional in-person clinic settings have historically faced multiple barriers, including geographical, socioeconomic, and health-related challenges. Canada’s vast geography, coupled with 1 in 5 Canadians residing in rural areas, exacerbates these difficulties, as most genetics clinics are concentrated in urban regions. The COVID-19 pandemic accelerated the adoption of alternate service delivery models (SDMs) for genetic counseling, such as telephone and videoconferencing, which were found to provide care of equal quality compared to in-person counseling. We present an innovative alternate service delivery model, the first of its kind in Canada, implemented in New Brunswick, a predominantly rural province. Established in 2018, this clinic utilizes public-private partnerships to offer remote genetic counseling to residents throughout the province, enabling patients to access care including genetic testing, directly from their homes. The clinic serves nearly 600 patients annually, significantly improving the accessibility of genetics services. This approach ensures rapid access for urgent oncology patients and offers relatively short wait times for non-urgent cases. The success of this model suggests its potential application in addressing challenges related to hard-to-recruit positions, mainstreaming, and in regions lacking in-house genetics clinics. This model holds promise for improving access to genetics services for underserved populations, particularly those in rural areas across Canada.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.880

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 science0.0010.000
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 head0.039
GPT teacher head0.352
Teacher spread0.313 · 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 designSimulation or modeling
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

Citations0
Published2024
Admission routes2
Has abstractyes

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