An Exploration of the Unintended Consequences of Performance-Based Financing in 6 Primary Healthcare Facilities in Burkina Faso
Bibliographic record
Abstract
BACKGROUND: Performance-based financing (PBF) is promoted to improve the quality and quantity of healthcare services in low-income countries. Despite the complexity of the intervention, little attention has been given to studying its unintended consequences. Our objective is to increase evidence on the unintended consequences of PBF in Burkina Faso. METHODS: Using the diffusion of innovations theory, we conducted a multiple case study. The cases were 6 healthcare facilities in two districts. Between April 2015 and 2016, we collected data through 101 semi-structured interviews, discussions, observations, and documents. We conducted thematic analysis using a hybrid deductive-inductive approach. Secondary data was used to illustrate the evolution of reported services. We conducted a cross-case synthesis to identify the results arising independently from more than 1 case. RESULTS: A desirable unintended consequence of PBF was that 3 facilities limited the sale of non-prescribed medication to encourage patients to consult. Undesirable unintended consequences were found in the majority of facilities including fixation on measures rather than on underlying objectives, the pursuit of narrow and less relevant performance indicators, gaming, and teaching trainees improper practices. Providers in all facilities deliberately manipulated medical registers and documents, such that the reported quantity and quality of care differed from what was actually delivered. While most participants indicated that PBF was more advantageous than previous practices, the long payment delays were a source of dissatisfaction and demotivation across all facilities. Dissatisfaction also emerged in relation to the distribution of subsidies and the non-attribution of quality points for services delivered by certain staff considered "unqualified" in guidelines. Results in many facilities revealed suboptimal planning, a perception of the intervention as "budgetivorous," as well as tensions related to the principle of managerial autonomy. CONCLUSION: PBF led to numerous unintended consequences that could undermine the intervention's effectiveness. The findings contribute to a more comprehensive picture of the consequences of implementing PBF. Policy-makers can use the results of this study to devise effective strategies before, during and after the implementation of the intervention to minimize undesirable unintended consequences and promote desirable ones.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".