High-risk pregnancy identification and management through antenatal, intrapartum, and postnatal care: an implementation research study protocol

Introduction As per WHO, in 2023 more than 700 women died every day from preventable causes related to pregnancy and childbirth. Early identification and management of high-risk pregnancies are essential for improved maternal and child health outcomes and reduced mortality rates. Objectives The study objectives are: (a) To identify the barriers and facilitators in implementing existing national programs and the continuum of care for high-risk pregnant women. (b) To co-develop, optimize and implement a context-specific, scalable, and sustainable model of implementation strategies that will help achieve population-based coverage of high-risk pregnancy identification and management. (c) To evaluate the effect of the optimised and contextualised implementation model on the key performance indicators (d) To document the processes of evolution implementation, adoption, adaptation and fidelity of the implementation model. Methods The study will utilize the Consolidated Framework for Implementation Research and will be implemented in Nagaur district of Rajasthan, India. The study involves formative research and situational analysis, as well as developing a package of implementation strategies through an iterative process of concurrent implementation, evaluation, and model refinement based on programme learnings. The intervention package will include refresher training of ASHA/ANM workers, strengthened community awareness, and monthly Pradhan Mantri Surakshit Matritva Abhiyan specialist camps. Expected outcome The study is expected to improve the identification and management of high-risk pregnancies and enhance the quality of institutional deliveries by strengthening the continuum of care across all stages of pregnancy. Thus, the study is expected to improve maternal and child health outcomes by developing sustainable strategies for scaling up evidence-based, context-specific interventions. Implication The study will generate a scalable implementation model that can be adopted more widely to streamline high-risk pregnancy care and contribute to long-term improvements in maternal and child health outcomes.