Evaluation of the Med Safety mobile app for reporting adverse events in Burkina Faso
Bibliographic record
Abstract
Smartphone applications (apps) for pharmacovigilance present an opportunity for integration as cost-effective healthcare service intervention into basic healthcare services in low-resource settings. This study aimed to (i) evaluate the implementation of the Med Safety app in Burkina Faso, and (ii) compare the characteristics of the reports sent by the Med Safety app with those sent on paper form. The study had two components: (i) a cross-sectional online survey assessing the Med Safety app, and (ii) a retrospective analysis comparing the characteristics of the Med Safety reports with those of the paper form, received by the National Pharmacovigilance Centre of Burkina Faso (CNVPS), from January 1, 2021 to December 31, 2022. We evaluated the success of the implementation of the Med Safety intervention using measures of acceptability, usefulness and feasibility. This assessment involved a set of 14 items rated on a 4-point Likert scale. Acceptability, feasibility, and usefulness were determined based on achieving a total score higher than the mean. Subsequently, we computed the proportion of participants whose overall score for all items exceeded the mean. Continuous and categorical variables were compared using the Wilcoxon rank-sum test and the Chi2 test, respectively. The significance level of the statistical test was set at 5%. The survey participation rate was 51.9% (160/308). Half of the respondents were in the 35-44 age group (50.6%), and participants were predominantly male (71.9%). The Med Safety app was acceptable, feasible, and useful to 58.1% of respondents. The most useful features of the app were “reporting” (53.1%), “news” (13.6%) and “watch list” (12.4%). During the period, a total of 1,472 reports were received, including 357 (24.3%) through Med Safety and 1,115 (75.7%) through the paper form. The reports of adverse events following immunization received at the CNVPS numbered 974 (66.2%), these were related to COVID-19 vaccines, with 256 (26.3%) through the Med Safety and 718 (73.7%) through the paper form. The median time to submit the reports to the CNVPS was 159 (IQR 59–187) days for the Med Safety and 166 (IQR 107–281) days for the paper form (p < 0.001). In Burkina Faso, the Med Safety was found to be acceptable, useful, and feasible by users surveyed. In addition, and compared to the paper form, the app reduces the time to submit a report, and with increase in use, the reporting timeframe could be further improved.
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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) | 0.000 | 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".