Implementation of HIV treatment as prevention strategy in 17 Canadian sites: immediate and sustained outcomes from a 35-month Quality Improvement Collaborative
Bibliographic record
Abstract
BACKGROUND: Rapid scale-up of effective antiretroviral therapy (ART) is required to meet global targets to eliminate new HIV infections and AIDS-related deaths. Yet, gaps persist in all nations striving for these targets. In the intervention setting of British Columbia (BC), Canada, where ART is publicly funded, 73% of HIV-diagnosed were on ART in 2011, and only 49% were achieving viral suppression. METHODS: An observational case descriptive study of HIV care sites in BC recruited to participate in a 35-month Breakthrough Series Quality Improvement Collaborative and sustainability network. Sites collected four quality indicators, qualitative change descriptions and implemented the chronic care model (CCM) and HIV care and treatment guidelines. Two reviewers assigned monthly implementation scores to evaluate site progress (January 2011-2012). All quality indicators were pooled and analysed using probability-based run chart rules. RESULTS: Seventeen teams with a pooled median population of 2296 HIV patients joined the initiative. Comprehensive CCM implementation and evidence of improvement was achieved by 29% of sites (implementation score of 4.0 or higher on 5.0 scale). Evidence of sustained improvement was observed for patient engagement (88.8-90.4%), ART uptake among patients unequivocally in need (92.9-94.8%), and ART uptake (≥6 months) and achieving viral suppression (57.3-78.4%) (all p<0.05). CONCLUSIONS: This study shows evidence of sustained improvements in HIV care processes and treatment outcomes for an estimated population of 2296 HIV patients in 17 BC sites. Overall success points to opportunities for other high-income countries seeking to improve HIV health outcomes.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".