Repeat: a framework to assess empirical reproducibility in biomedical research

The reproducibility of research is essential to rigorous science, yet significant concerns of the reliability and verifiability of biomedical research have been recently highlighted. Ongoing efforts across several domains of science and policy are working to clarify the fundamental characteristics o...

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Bibliographic Details
Published in:	BMC medical research methodology Vol. 17; no. 1; p. 143
Main Authors:	McIntosh, Leslie D, Juehne, Anthony, Vitale, Cynthia R H, Liu, Xiaoyan, Alcoser, Rosalia, Lukas, J Christian, Evanoff, Bradley
Format:	Journal Article
Language:	English
Published:	England BioMed Central Ltd 18-09-2017 BioMed Central BMC
Subjects:	Accessibility Analysis Biomedical research Biomedical Research - standards Checklist - methods Citations Collaboration Data Accuracy Documentation Ehr Electronic health records Electronic Health Records - standards Evidence-Based Medicine - standards Humans Informatics Internet Libraries Literature reviews Medical informatics Medical records Medical research Replication Reproducibility Reproducibility of Results Research data management Researchers Science Technology Assessment, Biomedical - methods Technology Assessment, Biomedical - standards Transparency Transparency Accessibility Reproducibility Replication Secondary data re-use Electronic health records Ehr
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Summary:	The reproducibility of research is essential to rigorous science, yet significant concerns of the reliability and verifiability of biomedical research have been recently highlighted. Ongoing efforts across several domains of science and policy are working to clarify the fundamental characteristics of reproducibility and to enhance the transparency and accessibility of research. The aim of the proceeding work is to develop an assessment tool operationalizing key concepts of research transparency in the biomedical domain, specifically for secondary biomedical data research using electronic health record data. The tool (RepeAT) was developed through a multi-phase process that involved coding and extracting recommendations and practices for improving reproducibility from publications and reports across the biomedical and statistical sciences, field testing the instrument, and refining variables. RepeAT includes 119 unique variables grouped into five categories (research design and aim, database and data collection methods, data mining and data cleaning, data analysis, data sharing and documentation). Preliminary results in manually processing 40 scientific manuscripts indicate components of the proposed framework with strong inter-rater reliability, as well as directions for further research and refinement of RepeAT. The use of RepeAT may allow the biomedical community to have a better understanding of the current practices of research transparency and accessibility among principal investigators. Common adoption of RepeAT may improve reporting of research practices and the availability of research outputs. Additionally, use of RepeAT will facilitate comparisons of research transparency and accessibility across domains and institutions.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1471-2288 1471-2288
DOI:	10.1186/s12874-017-0377-6