The utilization of clinical decision support tools to identify neonatal hypothermia and its associated risk factors: A prospective observational study - Mary Kakuru Muhindo; Joshua Bress; Jean Armas; Elon Danziger; Andrew Wu; Ryan C. L. Brewster (Public Library of Science (PLoS), 2023)
Hypothermia (axillary temperature less than 36.5°) is a major source of neonatal morbidity and mortality, with a disproportionate burden of disease in low- and middle-income countries. Despite the importance of thermoregulation on newborn outcomes, the global epidemiologic landscape of neonatal hypothermia is poorly characterized. Clinical decision support (CDS) software provides point-of-care recommendations to guide clinical management and may support data capture in settings with limited informatics infrastructure. Towards this end, we conducted a prospective observational study of the NoviGuide, a novel CDS platform for newborn care, at four health facilities in Uganda between September 2022 to May 2021. Data were extracted from clinical information (e.g. axillary temperature, birth weight, gestational age) entered into the NoviGuide by nurses and midwives on newborns within 24 hours of delivery. Descriptive statistics and multivariable logistic regression were used to evaluate neonatal temperature profiles and the association between hypothermia and clinical features. Among 1,027 completed assessments, 30.5% of entries had neonatal hypothermia with significant variation across study sites. On multivariable logistic regression analysis, we found that hypothermia was independently associated with pre-term birth (Adjusted Odd's Ratio [aOR] 2.62, 95% Confidence interval [CI] 1.38-4.98), sepsis/concern for sepsis (aOR 2.73, 95% CI 2.90-3.94), and hypoglycemia/concern for hypoglycemia (aOR 1.78, 95% CI 1.17-2.72). Altogether, neonatal hypothermia was commonly entered into the NoviGuide and associated clinical characteristics aligned with previous studies based on conventional data collection instruments. Our results should be contextualized within unique technical and operational features of CDS tools, including a bias towards acutely ill patients and limited quality control. Nonetheless, this study demonstrates that a CDS used voluntarily by clinicians has the potential to fill key data gaps and drive quality improvement towards reducing neonatal hypothermia in low resource settings.