TY - JOUR
AU - Smeeth, Liam
AB - s.denaxas@ucl.ac.uk Institute of Health Informatics, Background: The ability of external investigators to reproduce published scientific University College London, 222 findings is critical for the evaluation and validation of biomedical research by the wider Euston Road, NW1 2DA London, UK community. However, a substantial proportion of health research using electronic Farr Institute of Health Informatics Research, 222 Euston Road, London, health records (EHR), data collected and generated during clinical care, is potentially UK not reproducible mainly due to the fact that the implementation details of most data Full list of author information is available at the end of the article preprocessing, cleaning, phenotyping and analysis approaches are not systematically made available or shared. With the complexity, volume and variety of electronic health record data sources made available for research steadily increasing, it is critical to ensure that scientific findings from EHR data are reproducible and replicable by researchers. Reporting guidelines, such as RECORD and STROBE, have set a solid foundation by recommending a series of items for researchers to include in their research outputs. Researchers however often lack the technical tools and methodological approaches to actuate such recommendations in an efficient and sustainable manner. Results: In this paper, we review 
TI - Methods for enhancing the reproducibility of biomedical research findings using electronic health records
JO - BioData Mining
DO - 10.1186/s13040-017-0151-7
DA - 2017-09-11
UR - https://www.deepdyve.com/lp/springer-journals/methods-for-enhancing-the-reproducibility-of-biomedical-research-ehFejHJwRW
SP - 1
EP - 19
VL - 10
IS - 1
DP - DeepDyve
ER -