Non‐physician clinician provided HIV treatment results in equivalent outcomes as physician‐provided care: a meta‐analysis
Bibliographic record
Abstract
INTRODUCTION: A severe healthcare worker shortage in sub-Saharan Africa is inhibiting the expansion of HIV treatment. Task shifting, the transfer of antiretroviral therapy (ART) management and initiation from doctors to nurses and other non-physician clinicians, has been proposed to address this problem. However, many health officials remain wary about implementing task shifting policies due to concerns that non-physicians will provide care inferior to physicians. To determine if non-physician-provided HIV care does result in equivalent outcomes to physician-provided care, a meta-analysis was performed. METHODS: Online databases were searched using a predefined strategy. The results for four primary outcomes were combined using a random effects model with sub-groups of non-physician-managed ART and -initiated ART. TB diagnosis rates, adherence, weight gain and patient satisfaction were summarized qualitatively. RESULTS: Mortality (N=59,666) had similar outcomes for non-physicians and physicians, with a hazard ratio of 1.05 (CI: 0.88-1.26). The increase in CD4 levels at one year, as a difference in means of 2.3 (N=17,142, CI: -12.7-17.3), and viral failure at one year, as a risk ratio of 0.89 (N=10,344, CI: 0.65-1.23), were similar for physicians and non-physicians. Interestingly, loss to follow-up (LTFU) (N=53,435) was reduced for non-physicians with a hazard ratio of 0.72 (CI: 0.56-0.94). TB diagnosis rates, adherence and weight gain were similar for non-physicians and physicians. Patient satisfaction appeared higher for non-physicians in qualitative components of studies and was attributed to non-physicians spending more time with patients as well as providing more holistic care. CONCLUSIONS: Non-physician-provided HIV care results in equivalent outcomes to care provided by physicians and may result in decreased LTFU rates.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.025 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".