Task shifting roles, interventions and outcomes for kidney and cardiovascular health service delivery among African populations: a scoping review
Bibliographic record
Abstract
BACKGROUND: Human resources for health (HRH) shortages are a major limitation to equitable access to healthcare. African countries have the most severe shortage of HRH in the world despite rising communicable and non-communicable disease (NCD) burden. Task shifting provides an opportunity to fill the gaps in HRH shortage in Africa. The aim of this scoping review is to evaluate task shifting roles, interventions and outcomes for addressing kidney and cardiovascular (CV) health problems in African populations. METHODS: We conducted this scoping review to answer the question: "what are the roles, interventions and outcomes of task shifting strategies for CV and kidney health in Africa?" Eligible studies were selected after searching MEDLINE (Ovid), Embase (Ovid), CINAHL, ISI Web of Science, and Africa journal online (AJOL). We analyzed the data descriptively. RESULTS: Thirty-three studies, conducted in 10 African countries (South Africa, Nigeria, Ghana, Kenya, Cameroon, Democratic Republic of Congo, Ethiopia, Malawi, Rwanda, and Uganda) were eligible for inclusion. There were few randomized controlled trials (n = 6; 18.2%), and tasks were mostly shifted for hypertension (n = 27; 81.8%) than for diabetes (n = 16; 48.5%). More tasks were shifted to nurses (n = 19; 57.6%) than pharmacists (n = 6; 18.2%) or community health workers (n = 5; 15.2%). Across all studies, the most common role played by HRH in task shifting was for treatment and adherence (n = 28; 84.9%) followed by screening and detection (n = 24; 72.7%), education and counselling (n = 24; 72.7%), and triage (n = 13; 39.4%). Improved blood pressure levels were reported in 78.6%, 66.7%, and 80.0% for hypertension-related task shifting roles to nurses, pharmacists, and CHWs, respectively. Improved glycaemic indices were reported as 66.7%, 50.0%, and 66.7% for diabetes-related task shifting roles to nurses, pharmacists, and CHWs, respectively. CONCLUSION: Despite the numerus HRH challenges that are present in Africa for CV and kidney health, this study suggests that task shifting initiatives can improve process of care measures (access and efficiency) as well as identification, awareness and treatment of CV and kidney disease in the region. The impact of task shifting on long-term outcomes of kidney and CV diseases and the sustainability of NCD programs based on task shifting remains to be determined.
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 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 | 0.017 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".