Strengthening Maternal and Perinatal Death Surveillance and Response Data Use at Kawempe National Referral Hospital, Kampala, Uganda

In 2012, the Uganda Ministry of Health (MOH) adopted Maternal and Perinatal Death Surveillance and Response (MPDSR), an essential quality improvement intervention to identify, notify, quantify, and determine the causes of maternal deaths, stillbirths, and early neonatal deaths to prevent future mortality. Since 2020, the U.S. Agency for International Development (USAID) Maternal Child Health and Nutrition (MCHN) Activity has supported functionalization of MPDSR at the national level and in Kampala district, including Kawempe National Referral Hospital (KNRH).

Mothers' and Caregivers' Perceived Acceptability of a Digital Data Capture and Clinical Decision Support Intervention (Neotree) in Neonatal Intensive Care Units in Two Low-Resource Settings 

Neotree is a digital intervention that aims to improve quality of newborn care in low-resource settings by supporting health care professionals (HCPs) to complete an electronic health care record (EHR) for every admitted baby, conduct standardised clinical assessments, and adhere to evidence-based clinical guidelines in the diagnosis and management of neonates. Few digital interventions co-developed with HCPs in low-resource settings have been evaluated from the patient/caregiver perspective. Yet this is critical to ensure that care is patient centred. Our aim was to assess the acceptability of Neotree from the perspective of mothers and caregivers of neonates (end beneficiaries) admitted to three neonatal intensive care units (NICUs) in Malawi and Zimbabwe.

Data-Driven Decision-Making: Enabling District Health Management to Strengthen Maternal, Newborn, and Child Health Services 

Use of local data for health system planning and decision-making in maternal, newborn, and child health (MNCH) services is limited in lower- and middle-income countries, despite advances in data gathering. Among health stakeholders there is an underdeveloped culture of data sharing and collaborative planning. Yet while service delivery processes are a trend of health system research, scant attention is paid to health system management research, despite this being the key to effective MNCH services. The Data-Informed Platform for Health (DIPH) is a health system strengthening intervention that promotes structured decision-making by health administrators and managers using local data. DIPH entails quality decision-making: (a) defining problems using a health system framework, (b) reviewing data, (c) considering alternative options, (d) value-based prioritisation, and (e) a consultative process to develop, commit to, and follow up on action plans. Central to DIPH is a package of job aids and guidelines providing tools and knowledge for structured decision-making using available data. DIPH's strategy was conceptualised, developed, and tested over 10 years.

Leveraging Geospatial Intelligence/Evidence to Inform Maternal and Newborn Health Care (MNHC) Infrastructure Investment 

Like other resource-constrained settings, Zambia is characterized by high maternal and infant mortality rates. This is in spite of recent progress made towards reducing mortality rates, from 398 per 100,000 live births in 2014 to 278 per 100,000 live births in 2018. The major factors contributing to high maternal and infant mortality rates (MMR) in Zambia are associated with the three delays in accessing health services: the delay in deciding to seek care, the delay in accessing health facilities, and the delay in accessing the services of a skilled health worker. Within the context of the three delays, the choice of facility location is critical. However, identifying and prioritizing the precise location with the greatest potential of increasing access to maternal services is in practice not a straightforward process, more so in resource-constrained settings where the need for infrastructure is pervasive. A baseline study conducted in Eastern and Southern provinces of Zambia established that 72% of eligible facilities in Eastern and 65% in Southern had no capacity to support maternal services. However, estimates of the investment outlay required to close the capacity gap was $41.8 million.