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Record W4385271502 · doi:10.3138/canlivj-2022-0029

Province-to-province variability in hepatitis C testing, care, and treatment across Canada

2023· article· en· W4385271502 on OpenAlexaffvenueabout
Erin Mandel, Kate Underwood, Chelsea Masterman, Robert Kozak, Cheryl Dale, Melinda Hassall, Camelia Capraru, Hemant Shah, Harry L.A. Janssen, Jordan J. Feld, Mia J. Biondi

Bibliographic record

VenueCanadian Liver Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsToronto Liver CentreUniversity of TorontoSunnybrook HospitalYork UniversityWestern University
FundersGilead Sciences
KeywordsMedicineLegislationHepatitis C virusLegislatureTest (biology)Family medicineEquity (law)Hepatitis CHealth carePharmacyVenipunctureNursingPolitical scienceImmunologyVirus

Abstract

fetched live from OpenAlex

Background: Few countries have implemented the necessary policy changes to reduce the number of steps in the cascade of care to achieve hepatitis C virus (HCV) elimination, including Canada. The aim of this study was to describe and compare legislation, scope of practice, and policy as it relates to the provision of HCV care in each province. Methods: We reviewed grey literature and regulatory and legislative documents which affect various aspects of the HCV cascade of care. Findings were verified by content experts. Results: HCV RNA reflex testing ensures those that are antibody positive get an HCV RNA test; however only 80% of provinces have reflex test. Point-of-care antibody testing can be offered in most community non-health care settings, yet many types of health care providers are unable to do this independently. Following a positive test, it may not be feasible to complete venipuncture; however only a single province processes HCV RNA dried blood spot cards. In many provinces, training and verification are required for novice prescribers, and in some provinces prescribing continues to be restricted to specialists. Only a single province has task-shifted treatment to a non-physician non-nurse practitioner model, where pharmacists can prescribe treatment. Finally, 80% of provinces require authorization forms, and 30% require proof of investigations for treatment. Conclusions: No single province is optimizing the use of diagnostic tools and task shifting and decreasing paperwork to expedite treatment initiation. Collaboration between provinces is needed to streamline practice, update policy, and promote equity in HCV diagnosis, care, and treatment.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0040.002
Scholarly communication0.0020.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.297
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations12
Published2023
Admission routes3
Has abstractyes

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