Triggers for active surveillance of adverse drug events in newborns

The study aimed to verify the application and performance of triggers for adverse drug events in hospitalized newborns. This prospective cohort study was conducted in the neonatal care units of a university hospital from March to September 2015. A list of triggers was developed for the identificatio...

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Veröffentlicht in:Cadernos de saúde pública 2018-09, Vol.34 (9), p.e00069817-e00069817
Hauptverfasser: Fabretti, Sandra de Carvalho, Brassica, Sandra Cristina, Cianciarullo, Marco Antonio, Romano-Lieber, Nicolina Silvana
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Sprache:eng ; por
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Zusammenfassung:The study aimed to verify the application and performance of triggers for adverse drug events in hospitalized newborns. This prospective cohort study was conducted in the neonatal care units of a university hospital from March to September 2015. A list of triggers was developed for the identification of adverse drug events in this population. The list included antidote, clinical, and laboratory triggers. A total of 125 newborns who had received drugs during the hospitalization were included. Neonatal patient charts were screened to detect triggers. When a trigger was found, the patient chart was reviewed to identify possible adverse drug events. Each trigger's yield in the identification of adverse drug events was calculated and then classified according to its performance. Nine hundred and twenty-five triggers identified 208 suspected adverse drug events. The triggers' overall yield was 22.5%. The most frequently identified triggers were: drop in oxygen saturation, increased frequency of bowel movements, medications stop, and vomiting. The triggers with the best performance in the identification of adverse drug events were: increased creatinine, increased urea, necrotizing enterocolitis, prescription of flumazenil, hypercalcemia, hyperkalemia, hypernatremia, and oversedation. The triggers identified in this study can be used to track adverse drug events in similar neonatal care services, focusing on the triggers with the best performance and the lowest workload in the identification.
ISSN:1678-4464
DOI:10.1590/0102-311X00069817