Effects of the Pregnancy and Newborn Diagnostic Assessment (PANDA) App on Antenatal Care Quality in Burkina Faso: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The Pregnancy and Newborn Diagnostic Assessment (PANDA) system is a digital clinical decision support tool that can facilitate diagnosis and decision-making by health care personnel in antenatal care (ANC). Studies conducted in Madagascar and Burkina Faso showed that PANDA is a feasible system acceptable to various stakeholders. OBJECTIVE: This study primarily aims to evaluate the effects of the PANDA system on ANC quality at rural health facilities in Burkina Faso. The secondary objectives of this study are to test the effects of the PANDA system on women's satisfaction, women's knowledge on birth preparedness and complication readiness, maternal and child health service use, men's involvement in maternal health service utilization, and women's contraception use at 6 weeks postpartum. Further, we will identify the factors that hinder or promote such an app and contribute to cost-effectiveness analysis. METHODS: This is a randomized controlled trial implementing the PANDA system in 2 groups of health facilities (intervention and comparison groups) randomized using a matched-pair method. We included pregnant women who were <20 weeks pregnant during their first antenatal consultation in health facilities, and we followed up with them until their sixth week postpartum. Thirteen health centers were included, and 423 and 272 women were enrolled in the intervention and comparison groups, respectively. The primary outcome is a binary variable derived from the quality score, coded 1 (yes) for women with at least 75% of the total score and 0 if not. Data were collected electronically using tablets by directly interviewing the women and by extracting data from ANC registers, delivery registers, ANC cards, and health care records. The study procedures were standardized across all sites. We will compare unadjusted and adjusted primary outcome results (ANC quality scores) between the 2 study arms. We added a qualitative evaluation of the implementation of the PANDA system to identify barriers and catalysts. We also included an economic evaluation to determine whether the PANDA strategy is more cost-effective than the usual ANC strategy. RESULTS: The enrollment ran from July 2020 to January 2021 due to the COVID-19 pandemic. Data collection ended in September 2022. Data analyses started in January 2023, ended in June 2023, and the results are expected to be published in February 2024. CONCLUSIONS: The PANDA system is one of the most comprehensive apps for ANC because it has many features. However, the use of computerized systems for ANC is limited. Therefore, our trial will be beneficial for evaluating the intrinsic capacity of the PANDA system to improve the quality of care. By including qualitative research and economic evaluation, our findings will be significant because electronic consultation registries are expected to be used for maternal health care in the future in Burkina Faso. TRIAL REGISTRATION: Pan-African Clinical Trials Registry (PACTR) PACTR202009861550402; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=12374. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37136.
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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 | 0.047 | 0.044 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.007 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.064 | 0.008 |
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".