Understanding HIV Pre-Exposure Prophylaxis Questions of U.S. Health Care Providers: Unique Perspectives from the PrEPline Clinical Teleconsultation Service
Bibliographic record
Abstract
Introduction: Fewer than a quarter of people considered to have factors associated with HIV acquisition are prescribed pre-exposure prophylaxis (PrEP) in the United States. Prior studies demonstrate disparities in provider comfort and knowledge regarding PrEP, suggesting a need for provider capacity building to support widespread PrEP availability. This study examined real-world PrEP clinical questions/cases from providers to a teleconsultation service to identify knowledge gaps and improve PrEP-related training materials and clinical guidelines. Methods: The National Clinician Consultation Center (NCCC) PrEPline provides educational teleconsultation services on clinical decision-making related to PrEP for U.S. health care providers. The NCCC PrEP consultation data collected between 2017 and 2020 were reviewed and systematically categorized by clinical topics, subtopics, and complexity levels (low, moderate, and high). Results: Within the study period, the PrEPline provided 1,754 teleconsultations. More than three quarters came from advanced practice nurses and physicians. The topics of questions commonly focused on medication-based HIV prevention strategies (22.7%), PrEP laboratory ordering/monitoring (17.4%), and side effects and contraindications (14.6%). The majority of teleconsultations (57.9%) involved sharing information that was directly available/addressed in the Centers for Disease Control and Prevention (CDC) 2017 PrEP Guidelines (i.e., low complexity). Discussion: The low frequency of consultations from nonphysician and non-nurse practitioner providers may suggest a need for increased training and collaborative opportunities for other types of providers. The high percentage of low-complexity inquiries may reveal a desire for capacity-building materials specifically designed for practicing providers (e.g., abridged versions of guidelines). This study may inform future research, best clinical practices, and aid in the development of training materials to increase providers' HIV prevention comfort and knowledge.
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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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".