Back

Strengthening Maternal Referral Systems: A Policy Qualitative Analysis In Indonesia

Angelina, S. R.; Putri, L. P.; Trisnantoro, L.

2025-03-30 health policy
10.1101/2025.03.27.25324569 medRxiv
Show abstract

BackgroundIndonesia continues to face high maternal mortality rates despite efforts to strengthen maternal healthcare systems. The introduction of various referral systems, from both national and sub-national governments, were aiming to improve referral efficiency, including for maternal emergency cases. This study examines the barriers and opportunities utilizing the various referral information systems from the policy content and real-world implementation. MethodsWe applied a qualitative policy analysis by analyzing the content of the existing policies and interviewing key informants working in community health centers, hospitals, and district authorities. Content analysis was performed towards the policy documents and the interview transcripts. ResultsThe key barriers in implementing maternal referral systems include standard and monitoring, quality of care, and communication. There were lacking standard on definition of cases for referral as well as classification of health facilities capable to treat maternal and neonatal emergency cases. The monitoring of systems utilization was limited. The standardized emergency maternal training should be provided for both health and non-health staff involved in the maternal referral systems. ConclusionTo enhance usefulness and effectiveness of maternal referral systems, health authorities should classify maternal cases by severity, map facility capacities, establish clear communication guidelines, and provide integrated training covering clinical, managerial, and digital skills. Regular monitoring should be conducted to refine program implementation and improve maternal health outcomes.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.