Relevance of a Toll-Free Call Service Using an Interactive Voice Server to Strengthen Health System Governance and Responsiveness in Burkina Faso
Bibliographic record
Abstract
BACKGROUND: In Africa, health systems are poorly accessible, inequitable, and unresponsive. People rarely have either the confidence or the opportunity to express their opinions. In Burkina Faso, there is a political will to improve governance and responsiveness to create a more relevant and equitable health system. Given their development in Africa, information and communication technologies (ICTs) offer opportunities in this area. METHODS: This article presents the results of an evaluation of a toll-free call service coupled with an interactive voice server (TF-IVS) tested in Ouagadougou, Burkina Faso, to assess its relevance for improving health systems governance. The approach consisted of a 2-phased action research project to test 2 technologies: recorded messages and touch keypad. Using a concurrent mixed approach, we assessed the technological, social, and instrumental relevance of the service. RESULTS: The call service is available everywhere, 24 hours per day, seven days per week. The equipment and its physical location were not adequately protected against technological hazards. Of the 278 days of operation, 49 were non-functional. In 8 months, there were 13 877 calls, which demonstrated the popularity of ICTs and the ease of access to telephone networks and mobile technologies. The TF-IVS was free, anonymous, and multilingual, which fostered the expression of public opinion. However, cultural context (religion, ethnic culture) and fear of reprisals may have had a negative influence. In the end, questions remained regarding people's capacity to use this innovative service. In the first trial, 49% of callers recorded their message and in the second, 48%. Touch key technology appeared more relevant for automated and real-time data collection and analysis, but there was no comprehensive strategy for translating the information collected into a response from healthcare actors or the government. CONCLUSION: This study showed the relevance and feasibility of implementing a TF-IVS to strengthen health system responsiveness in one of the world's poorest countries. Public opinion expressed through data collected in real-time is helpful for improving system responsiveness to meet care needs and enhance equity. However, the strategy for developing this tool must take into account the implementation context and the activities needed to influence the mechanisms of social responsibility (eg, information provision, citizen action, and state response).
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".