A digitalized program to improve antenatal health care in a rural setting in North-Western Burundi: Early evidence-based lessons

Abstract

In Burundi, the north-western region continues to grapple with the lowest level of antenatal care (ANC) attendance rate which is constantly about half the national average of 49% ANC4 coverage. Despite a dearth of empirical evidence to understand the determinants of this suboptimal attendance of ANC, widespread evidence informs that women forget scheduled ANC appointments. We designed and tested a digital intervention that uses a reminder model aimed at increasing the number of women who attend at least 4 ANC visits in this region. We enrolled a cohort of 132 pregnant women who were followed until childbirth using a single arm pre- and post-test design. The digital model builds on the collaboration between midwives or nurses, community health workers (CHWs), and pregnant women who are centrally connected through regular automated communications generated by the cPanel of the digital intervention. In addition to ANC attendances, we nested a cross-sectional survey to understand mothers' perceptions and acceptability of the digital intervention using the acceptability framework by Sekhon et al. (2017). Descriptive analyses were performed to observe the trend in ANC attendance and logistic regressions fitted to seize determinants affecting mothers' acceptability of the intervention. Of 132 enrolled pregnant women, 1 (0.76%) dropped out. From a baseline of 23%, nearly 73.7% of mothers attended their subsequent ANC visits after the start of the intervention. From the third month of intervention, about 80% of mothers constantly attended ANC appointments; which corresponds to greater than 200% increase from the baseline. Findings showed that 96.2% of mothers expressed satisfaction, 77.1% positively reacted to automated reminders (attitudes), 70.2% expressed willingness to participate, and 86.3% had the ability to actively participate to the intervention. Conversely, half of mothers confirmed that participation to this programme somewhat affected their time management. A key learning is that digital interventions have a lot of promise to improve pregnancy monitoring in rural settings. However, the overall user acceptability was low especially among mothers lacking personal mobile phone.

Fig 1. Baseline ANC attendance rate in Murwi Health Centre.

Fig 1 is a graphical depiction of ANC attendance rates before intervention. Data on the first ANC visit (blue line), second ANC visit (red line), third ANC visit (black line) and fourth ANC visit (green line) were collected for a period of six months preceding intervention. Averages were computed and depicted on a run chart to observe the baseline trend.

Fig 2. Digitalized ANC intervention.

In the first instance, a nurse or midwife schedules a pregnant woman for ANC visit. Immediately, both the pregnant woman (1) and the cPanel (2) receive schedule notification as “pop-up message”. In the second time, the cPanel sends automated ANC reminders to the pregnant woman (3). The first reminder was generated seven days before, the second three days before, and the third reminder the day before a scheduled appointment. When a woman attends the scheduled ANC appointment (4), the nurse confirms the show-up which is captured by the cPanel (5). The digital platform had an option for live chat and direct free call between nurses and women. Any data going through was stored by the cPanel.

Fig 3. Consumer acceptability framework.

Fig 4. ANC attendance in Murwi Health Centre before and during intervention.

Fig 4 is a graphical representation of pooled ANC attendance rates before and during intervention. Each datapoint is a mean ANC attendance rate obtained by dividing the total number of women who attended ANC (ANC 1 + ANC 2 + ANC 3 + ANC 4) by 4 and reported as a percentage. Datapoints were plotted on a run chart to observe change in trend before and during intervention. The graph shows an exponential increase of ANC attendance rate as a result of the intervention.