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Record W7017892638

Characterizing the impact of a novel electronic consultation platform on access to Hepatitis C treatment in a Manitoba context

2024· dissertation· en· W7017892638 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2024
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsReferralContext (archaeology)Hepatitis CHepatitis C viruseHealthTelemedicineStakeholderPrimary care
DOInot available

Abstract

fetched live from OpenAlex

Introduction Current Canadian guidelines recommend that all individuals living with Hepatitis C virus (HCV) be considered as candidates for HCV treatment, though treatment uptake in Manitoba remains limited. Access to HCV treatment requires a specialist referral in Manitoba, and the availability and location of specialists may serve as a barrier to HCV treatment. A potential solution to improving access to HCV treatment is through the use of a novel electronic consultation platform (eConsult). Using eConsults, primary care providers (PCPs) can link to HCV specialists through electronic means and receive specialist advice directly, without the need for a face-to-face patient visit. We aimed to characterize the impact of using the eConsult platform as it relates to HCV treatment in Manitoba, situated within a rich description of the local provincial context and perspectives of relevant stakeholders. Methods This was a single case study design that took place at Nine Circles Community Health Centre, utilizing a sequential explanatory mixed methods design. Chart reviews were conducted for individuals referred for HCV treatment via a traditional referral between December 1, 2016 and December 1, 2017; and for individuals referred via eConsult between December 2017 and December 31, 2019. Stakeholder interviews were completed with two PCPs, as well as the sole HCV specialist who received HCV treatment referrals. Results Individuals referred for HCV treatment via eConsult were more likely to be linked to specialist care (100% vs. 69%, p = 0.026), and complete HCV treatment (79% vs. 36%, p = 0.049). The time from referral to achieving each step of the HCV cascade of care was shorter for individuals referred via eConsult. A modified access to care framework was able to capture elements of availability; accessibility; accommodation; affordability; acceptability; and awareness that facilitated or created barriers to the success of eConsult. Additional themes of agility; adaptability; and altruism were also described. Conclusion The use of eConsult can help to expand access to HCV treatment in Manitoba, but its success may depend on its perceived agility; adaptability to a variety of clinical contexts; and the extent to which it relies on the altruism of health care providers.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.266
Teacher spread0.234 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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