Policy transfer and health policymaking process: The case of social health insurance in Ghana
Bibliographic record
Abstract
Since the introduction of the user fee system of healthcare financing in 1969 and its subsequent modifications, the burden of healthcare expenditure on residents of Ghana created health inequality. This system encouraged the poor and vulnerable to have limited access to essential drugs and services. Policy entrepreneurs contributed to raising awareness about the poor and vulnerable people in Ghana not having access to health due to the user fee system as a public policy problem. This awareness began to spread among political leaders, the masses, and professional groups, warranting the attention of policymakers. As significant public dissatisfaction and agitation against the user fee policy continued, the media continued to hold the government responsible for initiating the policy. The democratization process and election period between 1998 and 2000 provided a window of opportunity that led to the idea of health policy change. In 2003, Ghana established the National Social Health Insurance, a form of Social Health Insurance. This study examines the process of establishing the social health insurance scheme through policy transfer framework. First, the paper examines Ghana’s health policy after independence, the National Health Service, and the User Fee Policy that was implemented in 1985. Second, the paper accessed the policy transfer framework and applied it to the transfer of social health insurance. Third, the paper explains the radical change from the user fee policy to the social health insurance model. This essay uses time series analysis and comparative analysis to assess the impact of the social health insurance on the under-five mortality ratio, maternal mortality ratio and out-of-pocket expenditure. The assessment results show that the social health insurance scheme has a positive impact on under-five mortality, maternal mortality and out-of-pocket payment compared to Nigeria without social health insurance for the poor and other vulnerable groups. The paper concludes that policy transfer alone cannot be a single variable to explain radical health policy change, but when combined with other complementary perspectives, an empirically grounded account of policy change can be developed.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".