Routine Measurement of Reproductive, Maternal, and Newborn Health Programs in the Pacific Region: A Review of Health Management Information System (HMIS) Indicators and Data Availability

Routine service data are necessary for informing reproductive, maternal, and newborn health (RMNH) services management including human resource capacity, domestic resource mobilisation, and quality improvement. They also play a key role in national and international program monitoring. However, many national health management information systems (HMISs) in the Pacific Region do not generate quality data on RMNH. The purpose of this project was to benchmark data availability in six Pacific Island countries against international and national RMNH indicators with an HMIS data source to identify gaps and opportunities for improvement.

Experiences with Implementing an Essential Package of Neonatal Care and Reporting System in the Public Hospitals of KwaZulu-Natal, South Africa, 2018-2022 

In 2015, an external audit of neonatal care was conducted in all 51 public hospitals of the KwaZulu-Natal (KZN) Province, South Africa, revealing varying levels of quality of care and mortality rates. To ensure equitable access to an appropriate standard of neonatal care and service delivery platform, and to embed a system of self-assessment and quality improvement in all hospitals, the Provincial Department of Health (DOH) developed an Essential Package of Neonatal Care (EPOC).

Fast Progressors in Low Birthweight National Routine Data Systems in Low- and Middle-Income Countries 

Measurement of low birthweight (LBW) is key in tracking Sustainable Development Goal (SDG) mortality and health targets, but it is impeded by major gaps in data coverage and quality, especially in the highest burden regions. Some low- and middle-income countries (LMICs), however, have achieved remarkable progress in recent decades to capture LBW in national data systems. This study aimed to identify LMICs with improvements in capturing LBW data in national routine data systems over two time periods (2000–2004 and 2015–2019).

Measuring Care for Small and Sick Newborns: Co-design of a Minimal Neonatal Inpatient Dataset and Multicountry Learning to Inform Tracking of Every Newborn Targets 

Every Newborn Action Plan (ENAP) coverage targets require national scale-up of level-2+ small and sick newborn care (SSNC) in more than 90 countries. Routine neonatal inpatient data is fundamental for measuring quality of care, identifying equity gaps, and enabling data-based action at individual and national levels. Current neonatal inpatient data tool options vary in purpose, size, complexity, and collection processes. We describe the co-design and operationalisation of a core inpatient dataset to drive quality of care and track outcomes for small and sick newborns in low- and middle-income settings.