Adverse Drug Event Clinical Trial
Official title:
Drug-Related Problems in Neonatal Patients
Drug-related problems in newborn babies have been reported with a rate of 4-30%. It is estimated that the higher rates of these problems in hospitalized children under the age of two are related to the variety of drugs used and the differences in the age, weight and diagnosis of the patients. In this context, with the clinical parameters and demographic data obtained in the first 24 hours of the patients hospitalized in the neonatal intensive care unit, machine learning algorithms are used to predict the risks that may arise from possible drug-related problems (prescribing and administration errors, side effects and drug-drug interactions) that may occur during hospitalization. The algorithm, which will be created by modeling with a high number of big data pool, is planned to be transformed into a clinical decision support system software that can be used easily in clinical practice with online and mobile applications. By processing the data of the patients to be included in the model, it is aimed to prevent and manage drug-related problems before they occur, as well as to provide cost-effective medşcation treatment to patients hospitalized in the neonatal intensive care unit, together with a reduction in the risk of drug-related mortality and morbidity.
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