Evaluating the Uptake, Acceptability, and Effectiveness of <i>Uliza!</i> Clinicians' HIV Hotline: A Telephone Consultation Service in Kenya
Bibliographic record
Abstract
OBJECTIVE: Many clinical sites that serve patients who are HIV positive face challenges of insufficient staffing levels and staff training and have limited access to consultation resources including specialists on site. Uliza! (Swahili for "ask") Clinicians' HIV Hotline was launched in April 2006 in Nyanza province in Kenya as a HIV telephone consultation service for healthcare providers. Hotline users called an Uliza! consultant who discussed the patients' problems and helped the caller work through a solution, as well as reinforced national guidelines. This objective of this study was to evaluate the uptake, acceptability, and effectiveness of Uliza! MATERIALS AND METHODS: Consultants completed a form with details of each call, and healthcare workers completed satisfaction surveys during site visits. All available medical records were audited to determine whether the advice given by the consultant was implemented. RESULTS: After a year of service, Uliza! responded to 296 calls. Clinical officers (64%) followed by nurses (21%) most frequently used the service. Most callers had questions regarding antiretroviral therapy (36%) or tuberculosis (18%). Thirty-six percent of all consults were pediatric questions. Ninety-four percent of users rated the service as useful. Advice given to providers was implemented and documented in the medical records in 72% of the charts audited. CONCLUSION: Healthcare providers in HIV clinics will use a telephone consultation service when easily accessible. Clinicians using Uliza! found it useful, and advice given was usually implemented. Uliza! increased access to current information for quality care in a rural and resource limited setting and has potential for scale-up to a national level.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".