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Record W2992249114 · doi:10.12927/hcpol.2015.24148

Use of Compassionate Supply of Antiretroviral Drugs to Avoid Treatment Interruptions or Delayed Treatment Initiation among HIV-Positive Patients Living in Ontario: A Retrospective Review

2015· review· en· W2992249114 on OpenAlexaffvenueabout
Deborah Yoong, Mark Naccarato, Kevin Gough, Jordan D. Lewis, Ahmed M. Bayoumi

Bibliographic record

VenueHealthcare policy · 2015
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsInstitute for Work & HealthInstitute of Health Services and Policy ResearchUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineCompassionate UseRetrospective cohort studyHuman immunodeficiency virus (HIV)DrugAntiretroviral therapyFamily medicinePublic healthDrug treatmentEnvironmental healthIntensive care medicineViral loadSurgeryInternal medicinePharmacologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Without a national pharmacare plan in Canada, HIV-infected patients across the nation differ in their ability to obtain essential HIV therapy. Despite the fact there are public insurance programs in Ontario, patients are unable to access medication. The authors described how frequently patients in their urban clinic could not access medications and why they required a compassionate supply of HIV drugs, with the goals of minimizing treatment delays and avoiding interruptions. METHODS: The authors conducted a retrospective review and collected information about demographic characteristics, current drug insurance and the challenges encountered. RESULTS: Over one year, the authors provided 2,886 days of free HIV drugs to 42 patients who were predominantly citizens or permanent residents of Canada (88%). The most common obstacles were associated with the Trillium Drug Program and the total value of all drugs supplied was $134,860. INTERPRETATION: This study suggests that Ontario's catastrophic drug insurance plan leaves some patients with significant gaps in drug coverage.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0020.001
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 head0.478
GPT teacher head0.492
Teacher spread0.014 · 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.

Study designObservational
Domainnot available
GenreReview

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

Citations4
Published2015
Admission routes3
Has abstractyes

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