A Systematic review of macro - and meso - determinants of national health insurance enrolment among older adults in Ghana
Bibliographic record
Abstract
: Achieving universal health coverage (UHC) through the National Health Insurance Scheme (NHIS) has been a priority for Ghanaian governments. Despite the plethora of studies conducted to explore the various factors that influence enrolment into the scheme, there remains a dearth in the literature with regards to a systematic review of the health- and system-level determinants of NHIS enrolment among older adults in Ghana. This study aimed to synthesize evidence on macro- and meso-level determinants of NHIS enrolment among older adults in Ghana. With literature from data repositories including Wiley Web of Science, PubMed, PsycINFO, Scopus, Ovid, Science Direct and Sage, we performed a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Out of 124 studies screened, the systematic review included 11 articles. The study identified 4 macro- and 3 meso-determinants of national health insurance enrolment among older adults in Ghana. Macro-determinants identified were perceived scheme benefits, affordability, proximity to NHIS offices, quality of administrative service delivery. Physical accessibility, quality of care, and staff attitude were identified as meso-determinants. The study recommends improving physical accessibility, quality of care, and staff attitude. Additionally, it suggests addressing perceived scheme benefits and improving the quality of administrative service delivery.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".