Implementing a Nurse-led HIV Pre-exposure Prophylaxis Service (PrEP-RN) in a Public Health Unit STI Clinic: A Public Health Reform Analysis
Bibliographic record
Abstract
HIV pre-exposure prophylaxis (PrEP) is an efficacious pharmacologic HIV prevention strategy aimed at persons who are high-risk for HIV infection.Historically, PrEP uptake has been limited by systems-level barriers relating to the high cost of medications and few prescriber access points.In Ottawa, a team of researchers and clinicians sought to increase PrEP access to priority groups by implementing a fully nurse-led PrEP service, known as PrEP-RN, as part of the public health unit's sexual health clinic.This program was the first of its kind in Canada and required consideration from multiple stakeholders within the public health unit, and the Ottawa community.Patients at highest risk for HIV acquisition were offered a referral to PrEP-RN through a provider-driven, active-offer process by public health nurses, and medication coverage was provided to uninsured patients to ensure equal access to PrEP services.Preliminary results showed a 40% uptake of PrEP referrals among high-risk patients, demonstrating that this reform has been effective at reaching some priority groups; however, many persons continue to decline PrEP due to individual perceptions of risk (i.e., feeling they do not need this HIV prevention intervention).La prophylaxie pré-exposition au VIH (PrEP) est une stratégie pharmacologique efficace de prévention du VIH destinée aux personnes à haut risque d'infection par le VIH.Historiquement, l'adoption de la PrEP a été limitée par des obstacles au niveau des systèmes liés au coût élevé des médicaments et par le nombre réduit de points d'accès pour les prescripteurs.À Ottawa, une équipe de chercheurs et de cliniciens a cherché à améliorer l'accès de la PrEP aux groupes prioritaires en mettant en place un service de PrEP dirigé par une infirmière, appelé PrEP-RN, dans le cadre de la clinique de santé sexuelle du bureau de santé publique.Ce programme était le premier du genre au Canada et a nécessité l'attention de nombreux intervenants au sein du bureau de santé publique et de la communauté d'Ottawa.Les infirmières de la santé publique ont proposé aux patientes présentant le risque le plus élevé de contracter le VIH d'être dirigées vers une RNP-RN dans le cadre d'une offre active, et une couverture en médicaments a été fournie aux patients non assurés afin d'assurer un accès égal aux services de PrEP.Les résultats préliminaires ont montré une acceptation de 40% des références à la PrEP chez les patients à haut risque, qui démontre que cette réforme a été efficace à fournir des services à quelques groupes prioritaires, mais plusieurs personnes continuent de refuser la PrEP à cause de leur perception du risque (c'est-à-dire, ils pensent ne pas être à risque pour le VIH).
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".