IMPROVING THE DELIVERY OF HIV OUTPATIENT SERVICES IN SUB-SAHARAN AFRICA
Bibliographic record
Abstract
Introduction The majority of care for the 22.9 million people with HIV in Sub-Saharan Africa is provided by HIV outpatient services. While the palliative care needs of HIV patients are well documented, it is not known how well HIV outpatient services meet these needs and evidence to improve service provision is lacking. Aims and Methods To explore the care provided by outpatient HIV services in Uganda and Kenya and identify ways of improving care to meet patient and family needs. Qualitative interviews were conducted with patients, carers and staff at 12 HIV outpatient facilities (six in Kenya, six in Uganda), translated into English and analysed thematically. Results 189 people were interviewed (83 patients, 47 caregivers, 59 staff). Positive aspects of care related to staff attributes and teamwork, holistic care, medication provision and patient education. Gaps/challenges in care related to service efficiency, paediatric services, reaching rural areas, poverty and sustaining services financially. Services struggled to meet patient demand through lack of staff, resources and space. Drug availability was variable, but when good was highly valued by service users. Recommendations included improving existing services (organisation, medication provision and staff training) and providing additional services and outreach (transport, public health initiatives, nutritional programmes, financial support and care for extended family). Conclusions Outpatient services struggled to meet the multidimensional needs of people living with HIV in the face of significant resource challenges. Findings can be used to improve outpatient care and direct financial resources. Collaboration with palliative care services may help to improve HIV outpatient care.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".