Quantifying the Use of Routine Health Service Data to Inform Policy and Interventions in Maternal and Child Healthcare Experience from Tanzania
Abstract
Ahmad Mohamed Makuwani, Ismail Rutakyamirwa Habib, Rose Mpembeni, Leonard Kamanga Katalambula, Diego Duque, Adiel Mushi, Golden Mwakibo Masika and Secilia Kapalata Ngâweshemi
Introduction: Global experts and agencies often downplay the value of routine Reproductive, Maternal, Newborn, Child and Adolescent Health (RMNCAH) data. Therefore, we demonstrate the significance of a Health Information Management System (HMIS) for tracking progress and determining the usefulness of RMNCAH data for improving healthcare systems, particularly in low-resource settings.
Methods: We utilised HMIS and related datasets to evaluate the availability and usefulness of RMNCAH routine data in Tanzania between 2014 and 2024.
Results: Increases in service delivery points correlated with the following improvements in key maternal health indicators: antenatal visits before 12 weeks (15.1% to 42.9%; 2014–2023), institutional births (64.4% to 85.8%; 2014–2023), cesarean sections (5.6% to 11.6%; 2014–2022), and postnatal visits (45.3% to 91.6%; 2014–2023). The RMNCAH scorecard transitioned from predominantly red in 2014 to green in 2024, reflecting improved maternal and perinatal mortality surveillance. Obstetric haemorrhage and pre-eclampsia accounted for two-thirds of maternal deaths; competency and accountability were critical determinants. Neonatal deaths and stillbirths during 2018–2023 numbered 50,123 and 82,995, respectively, with 80% of neonatal deaths attributed to prematurity, birth asphyxia, and sepsis. Limited neonatal services contributed to mortality, with only 14 hospitals containing neonatal care units in 2018, compared with 156 district and 28 regional hospitals in 2024.
Conclusion: When systematically tracked and analysed, routine RMNCAH data provide crucial evidence to inform policymaking and track RMNCAH intervention outcomes. Our findings highlight the value of stakeholders investing in routine data to enhance data-driven decision-making and real-time progress tracking.