Donor-funded project's sustainability assessment: a qualitative case study of a results-based financing pilot in Koulikoro region, Mali
Bibliographic record
Abstract
BACKGROUND: Results-based financing (RBF) is emerging as a new alternative to finance health systems in many African countries. In Mali, a pilot project was conducted to improve demand and supply of health services through financing performance in targeted services. No study has explored the sustainability process of such a project in Africa. This study's objectives were to understand the project's sustainability process and to assess its level of sustainability. METHODS: Sustainability was examined through its different determinants, phases, levels and contexts. These were explored using qualitative interviews to discern, via critical events, stakeholders' ideas regarding the project's sustainability. Data collection sites were chosen with the participation of different stakeholders, based on a variety of criteria (rural/urban settings, level of participation, RBF participants still present, etc.). Forty-nine stakeholders were then interviewed in six community health centres and two referral health centres (from 11/12/15 to 08/03/16), including health practitioners, administrators, and those involved in implementing and conceptualizing the program (government and NGOs). A theme analysis was done with the software © QDA Miner according to the study's conceptual framework. RESULTS: The results of this project show a weak level of sustainability due to many factors. While some gains could be sustained (ex.: investments in long-term resources, high compatibility of values and codes, adapted design to the implementations contexts, etc.) other intended benefits could not (ex.: end of investments, lack of shared cultural artefacts around RBF, loss of different tasks and procedures, need of more ownership of the project by the local stakeholders). A lack of sustainability planning was observed, and few critical events were associated to phases of sustainability. CONCLUSIONS: While this RBF project aimed at increasing health agents' motivation through different mechanisms (supervision, investments, incentives, etc.), these results raise questions on what types of motivation could be more stable and what could be the place of local stakeholders in the project; all this with the aim of more sustained and efficient results.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 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".