The use of data in resource limited settings to improve quality of care

Quality improvement is driven by benchmarking between and within institutions over time and the collaborative improvement efforts that stem from these comparisons. Benchmarking requires systematic collection and use of standardized data. Low- and middle-income countries (LMIC) have great potential for improvements in newborn outcomes but serious obstacles to data collection, analysis, and implementation of robust improvement methodologies exist. We review the importance of data collection, internationally recommended neonatal metrics, selected methods of data collection, and reporting. The transformation from data collection to data use is illustrated by several select data system examples from LMIC. Key features include aims and measures important to neonatal team members, co-development with local providers, immediate access to data for review, and multidisciplinary team involvement. The future of neonatal care, use of data, and the trajectory to reach global neonatal improvement targets in resource-limited settings will be dependent on initiatives led by LMIC clinicians and experts.