Secondary analysis of large datasets involves the utilization of existing data that has typically been collected for other purposes to advance scientific knowledge. This is an established methodology applied in health services research with the unique advantage of efficiently identifying relationships between predictor and outcome variables but which has been underutilized for hepatology research. Our review of 1431 abstracts published in the 2013 European Association for the Study of Liver (EASL) abstract book showed that less than 0.5% of published abstracts utilized secondary analysis of large database methodologies.This review paper describes existing large datasets that can be exploited for secondary analyses in liver disease research. It also suggests potential questions that could be addressed using these data warehouses and highlights the strengths and limitations of each dataset as described by authors that have previously used them. The overall goal is to bring these datasets to the attention of readers and ultimately encourage the consideration of secondary analysis of large database methodologies for the advancement of hepatology. (C) 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Secondary analysis of large databases for hepatology research

de Pretis, Nicolo;
2016-01-01

Abstract

Secondary analysis of large datasets involves the utilization of existing data that has typically been collected for other purposes to advance scientific knowledge. This is an established methodology applied in health services research with the unique advantage of efficiently identifying relationships between predictor and outcome variables but which has been underutilized for hepatology research. Our review of 1431 abstracts published in the 2013 European Association for the Study of Liver (EASL) abstract book showed that less than 0.5% of published abstracts utilized secondary analysis of large database methodologies.This review paper describes existing large datasets that can be exploited for secondary analyses in liver disease research. It also suggests potential questions that could be addressed using these data warehouses and highlights the strengths and limitations of each dataset as described by authors that have previously used them. The overall goal is to bring these datasets to the attention of readers and ultimately encourage the consideration of secondary analysis of large database methodologies for the advancement of hepatology. (C) 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
2016
Health care delivery research
Health services research
Liver diseases
Outcomes research
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1093595
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