Journal article
Data quality evaluation for observational multiple sclerosis registries
T Kalincik, J Kuhle, E Pucci, JI Rojas, M Tsolaki, CA Sirbu, M Slee, H Butzkueven
Multiple Sclerosis | SAGE PUBLICATIONS LTD | Published : 2017
Abstract
Objective: Objective and reproducible evaluation of data quality is of paramount importance for studies of 'real-world' observational data. Here, we summarise a standardised data quality, density and generalisability process implemented by MSBase, a global multiple sclerosis (MS) cohort study. Methods: Error rate, data density score and generalisability score were developed using all 35,869 patients enrolled in MSBase as of November 2015. The data density score was calculated across six domains (follow-up, demography, visits, MS relapses, paraclinical data and therapy) and emphasised data completeness. The error rate evaluated syntactic accuracy and consistency of data. The generalisability ..
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Grants
Awarded by National Health and Medical Research Council
Funding Acknowledgements
The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study was financially supported by National Health and Medical Research Council (practitioner fellowship 1080518, project grants 1083539 and 1032484 and centre for research excellence 1001216) and University of Melbourne (Faculty of Medicine, Dentistry and Health Sciences research fellowship). The MSBase Foundation is a not-for-profit organisation that receives support from Merck, Biogen, Novartis, Bayer Schering, Sanofi Aventis and BioCSL. The study was conducted separately and apart from the guidance of the sponsors.