Public–Private engagement and health systems resilience in times of health worker strikes: a Ghanaian case study
Bibliographic record
Abstract
In low and middle-income countries like Ghana, private providers, particularly the grouping of faith-based non-profit health providers networked by the Christian Health Association of Ghana (CHAG), play a crucial role in maintaining service continuity during health worker strikes. Poor engagement with the private sector during such strikes could compromise care quality and impose financial hardships on populations, especially the impoverished. This study delves into the engagement between CHAG and the Government of Ghana (GoG) during health worker strikes from 2010 to 2016, employing a qualitative descriptive and exploratory case study approach. By analysing evidence from peer-reviewed literature, media archives, grey literature and interview transcripts from a related study using a qualitative thematic analysis approach, this study identifies health worker strikes as a persistent chronic stressor in Ghana. Findings highlight some system-level interactions between CHAG and GoG, fostering adaptive and absorptive resilience strategies, influenced by CHAG's non-striking ethos, unique secondment policy between the two actors and the presence of a National Health Insurance System. However, limited support from the government to CHAG member facilities during strikes and systemic challenges with the National Health Insurance System pose threats to CHAG's ability to provide quality, affordable care. This study underscores private providers' pivotal role in enhancing health system resilience during strikes in Ghana, advocating for proactive governmental partnerships with private providers and joint efforts to address human-resource-related challenges ahead of strikes. It also recommends further research to devise and evaluate effective strategies for nations to respond to strikes, ensuring preparedness and sustained quality healthcare delivery during such crises.
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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 | 0.016 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".