Outreach services to improve access to health care in South Africa: lessons from three community health worker programmes
Bibliographic record
Abstract
INTRODUCTION: In South Africa, there are renewed efforts to strengthen primary health care and community health worker (CHW) programmes. This article examines three South African CHW programmes, a small local non-governmental organisation (NGO), a local satellite of a national NGO, and a government-initiated service, that provide a range of services from home-based care, childcare, and health promotion to assist clients in overcoming poverty-related barriers to health care. METHODS: The comparative case studies, located in Eastern Cape and Gauteng, were investigated using qualitative methods. Thematic analysis was used to identify factors that constrain and enable outreach services to improve access to care. RESULTS: The local satellite (of a national NGO), successful in addressing multi-dimensional barriers to care, provided CHWs with continuous training focused on the social determinants of ill-health, regular context-related supervision, and resources such as travel and cell-phone allowances. These workers engaged with, and linked their clients to, agencies in a wide range of sectors. Relationships with participatory structures at community level stimulated coordinated responses from service providers. In contrast, an absence of these elements curtailed the ability of CHWs in the small NGO and government-initiated service to provide effective outreach services or to improve access to care. CONCLUSION: Significant investment in resources, training, and support can enable CHWs to address barriers to care by negotiating with poorly functioning government services and community participation structures.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 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".