| Literature DB >> 29857423 |
Diego Cobo González1, Marta Fernández Batalla1, Sara Gasco González1, Sergio Martínez Botija1, Ma Lourdes Jiménez Rodríguez1, José Ma Santamaría García1, Sylvia Claudine Ramírez Sánchez2, Niurka Vialart Vidal2, Daniel Flavio Condor Camara2.
Abstract
Prediction in healthcare is essential in order to promote safe and quality care. Taking adequate care of blood donors, who perform an altruistic act towards society, is paramount. Therefore, the use of tools which allow to predict the risk of Vasovagal Syndrome during the act of blood donation is necessary. The objective of this study is to design a predictive engine of an expert system to determine the risk of Vasovagal Syndrome through the use of deductive methodology. Five clusters of predictors of this syndrome were obtained by applying grouping tables of the variables established by logical formulation in such a way that after combinatorial variables, 5 values were obtained for the determination of risk using a Lickert scale. With these results we could design the predictive engine that will allow the development of a computational tool to improve the quality of care of blood donors.Entities:
Keywords: Adverse effects; Blood donation; Syncope Vasovagal
Mesh:
Year: 2018 PMID: 29857423
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630