Assessing the effectiveness of the Pregnancy And Newborn Diagnostic Assessment system on the quality of antenatal care in Burkina Faso: A cluster-randomised controlled trial

Introduction: The Pregnancy and Newborn Diagnostic Assessment (PANDA) system is a mobile application designed to facilitate diagnosis and decision-making by healthcare staff in antenatal care (ANC). This study aimed to evaluate its effectiveness in improving the quality of ANC.

Methods: This randomised controlled trial implemented the PANDA system in two groups of health facilities (intervention and comparison groups) using a matched-pair method in the Koupéla health district, Burkina Faso. Six health centres were included in each group. We included pregnant women presenting with more than 20 weeks of amenorrhea during their first antenatal consultation, and we followed them up until their sixth week postpartum. The primary outcome was a binary variable derived from the ANC quality score, coded yes or no. Six components of ANC quality were identified: welcoming the woman, history taking and dietary habits, physical examination, obstetric examination, preventive care, and counselling and advice. We used Poisson regression with robust variance to compare the unadjusted and adjusted primary outcomes results between the two study arms.

Results: We included 319 and 272 women in the intervention and comparison groups, respectively. In the intervention group, 15.67% (50 out of 319) of the women had at least 75% of the total ANC quality score, compared to 6.25% (17 out of 272) in the comparison group. Adjusted results showed that women in the intervention group were 2.71 times more likely to have an excellent total ANC quality score than women in the comparison group (RR = 2.71; 95% CI [1.60-4.60]; p < .001).

Conclusion: Although the proportion of women with good ANC quality was low, this study showed that the PANDA system significantly improves the ANC quality. These results are vital because Burkina Faso has decided to use these computerised clinical decision support systems for maternal and child health.