Neonatal inpatient dataset for small and sick newborn care in low- and middle-income countries: systematic development and multi-country operationalisation with NEST360.

BACKGROUND: Every Newborn Action Plan (ENAP) coverage target 4 necessitates national scale-up of Level-2 Small and Sick Newborn Care (SSNC) (with Continuous Positive Airway Pressure (CPAP)) in 80% of districts by 2025. Routine neonatal inpatient data is important for improving quality of care, targeting equity gaps, and enabling data-driven decision-making at individual, district, and national-levels. Existing neonatal inpatient datasets vary in purpose, size, definitions, and collection processes. We describe the co-design and operationalisation of a core inpatient dataset for use to track outcomes and improve quality of care for small and sick newborns in high-mortality settings. METHODS: A three-step systematic framework was used to review, co-design, and operationalise this novel neonatal inpatient dataset in four countries (Malawi, Kenya, Tanzania, and Nigeria) implementing with the Newborn Essential Solutions and Technologies (NEST360) Alliance. Existing global and national datasets were identified, and variables were mapped according to categories. A priori considerations for variable inclusion were determined by clinicians and policymakers from the four African governments by facilitated group discussions. These included prioritising clinical care and newborn outcomes data, a parsimonious variable list, and electronic data entry. The tool was designed and refined by > 40 implementers and policymakers during a multi-stakeholder workshop and online interactions. RESULTS: Identified national and international datasets (n = 6) contained a median of 89 (IQR:61-154) variables, with many relating to research-specific initiatives. Maternal antenatal/intrapartum history was the largest variable category (21, 23.3%). The Neonatal Inpatient Dataset (NID) includes 60 core variables organised in six categories: (1) birth details/maternal history; (2) admission details/identifiers; (3) clinical complications/observations; (4) interventions/investigations; (5) discharge outcomes; and (6) diagnosis/cause-of-death. Categories were informed through the mapping process. The NID has been implemented at 69 neonatal units in four African countries and links to a facility-level quality improvement (QI) dashboard used in real-time by facility staff. CONCLUSION: The NEST360 NID is a novel, parsimonious tool for use in routine information systems to inform inpatient SSNC quality. Available on the NEST360/United Nations Children's Fund (UNICEF) Implementation Toolkit for SSNC, this adaptable tool enables facility and country-level comparisons to accelerate progress toward ENAP targets. Additional linked modules could include neonatal at-risk follow-up, retinopathy of prematurity, and Level-3 intensive care

Health facility assessment of small and sick newborn care in low- and middle-income countries: systematic tool development and operationalisation with NEST360 and UNICEF.

BACKGROUND: Each year an estimated 2.3 million newborns die in the first 28 days of life. Most of these deaths are preventable, and high-quality neonatal care is fundamental for surviving and thriving. Service readiness is used to assess the capacity of hospitals to provide care, but current health facility assessment (HFA) tools do not fully evaluate inpatient small and sick newborn care (SSNC). METHODS: Health systems ingredients for SSNC were identified from international guidelines, notably World Health Organization (WHO), and other standards for SSNC. Existing global and national service readiness tools were identified and mapped against this ingredients list. A novel HFA tool was co-designed according to a priori considerations determined by policymakers from four African governments, including that the HFA be completed in one day and assess readiness across the health system. The tool was reviewed by > 150 global experts, and refined and operationalised in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania between September 2019 and March 2021. RESULTS: Eight hundred and sixty-six key health systems ingredients for service readiness for inpatient SSNC were identified and mapped against four global and eight national tools measuring SSNC service readiness. Tools revealed major content gaps particularly for devices and consumables, care guidelines, and facility infrastructure, with a mean of 13.2% (n = 866, range 2.2-34.4%) of ingredients included. Two tools covered 32.7% and 34.4% (n = 866) of ingredients and were used as inputs for the new HFA tool, which included ten modules organised by adapted WHO health system building blocks, including: infrastructure, pharmacy and laboratory, medical devices and supplies, biomedical technician workshop, human resources, information systems, leadership and governance, family-centred care, and infection prevention and control. This HFA tool can be conducted at a hospital by seven assessors in one day and has been used in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania. CONCLUSION: This HFA tool is available open-access to adapt for use to comprehensively measure service readiness for level-2 SSNC, including respiratory support. The resulting facility-level data enable comparable tracking for Every Newborn Action Plan coverage target four within and between countries, identifying facility and national-level health systems gaps for action