Health financing policies in Sub-Saharan Africa: government ownership or donors’ influence? A scoping review of policymaking processes
Bibliographic record
Abstract
BACKGROUND: The rise on the international scene of advocacy for universal health coverage (UHC) was accompanied by the promotion of a variety of health financing policies. Major donors presented health insurance, user fee exemption, and results-based financing policies as relevant instruments for achieving UHC in Sub-Saharan Africa. The "donor-driven" push for policies aiming at UHC raises concerns about governments' effective buy-in of such policies. Because the latter has implications on the success of such policies, we searched for evidence of government ownership of the policymaking process. METHODS: We conducted a scoping review of the English and French literature from January 2001 to December 2015 on government ownership of decision-making on policies aiming at UHC in Sub-Saharan Africa. Thirty-five (35) results were retrieved. We extracted, synthesized and analyzed data in order to provide insights on ownership at five stages of the policymaking process: emergence, formulation, funding, implementation, and evaluation. RESULTS: The majority of articles (24/35) showed mixed results (i.e. ownership was identified at one or more levels of policymaking process but not all) in terms of government ownership. Authors of only five papers provided evidence of ownership at all reviewed policymaking stages. When results demonstrated some lack of government ownership at any of the five stages, we noticed that donors did not necessarily play a role: other actors' involvement was contributing to undermining government-owned decision-making, such as the private sector. We also found evidence that both government ownership and donors' influence can successfully coexist. DISCUSSION: Future research should look beyond indicators of government ownership, by analyzing historical factors behind the imbalance of power between the different actors during policy negotiations. There is a need to investigate how some national actors become policy champions and thereby influence policy formulation. In order to effectively achieve government ownership of financing policies aiming at UHC, we recommend strengthening the State's coordination and domestic funding mobilization roles, together with securing a higher involvement of governmental (both political and technical) actors by donors.
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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 | 0.077 | 0.240 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.029 | 0.033 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".