Big Data Research in Neuro-Ophthalmology Promises and Pitfalls

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Title Big Data Research in Neuro-Ophthalmology Promises and Pitfalls
Creator Heather E. Moss; Charlotte E. Joslin; Daniel S. Rubin; Steven Roth
Affiliation Departments of Ophthalmology and Neurology & Neurological Sciences (HEM), Stanford University, Palo Alto, California; Departments of Ophthalmology and Visual Sciences (CEJ), University of Illinois, School of Public Health, College of Medicine, Epidemiology and Public Health, Chicago, Illinois; Department of Anesthesia and Critical Care (DSR), University of Chicago, Chicago, Illinois; and Departments of Anesthesiology, Ophthalmology and Visual Sciences (SR), College of Medicine, University of Illinois, Chicago, Illinois
Abstract Background: Big data clinical research involves application of large data sets to the study of disease. It is of interest to neuro-ophthalmologists but also may be a challenge because of the relative rarity of many of the diseases treated. Evidence acquisition: Evidence for this review was gathered from the authors' experiences performing analysis of large data sets and review of the literature. Results: Big data sets are heterogeneous, and include prospective surveys, medical administrative and claims data and registries compiled from medical records. High-quality studies must pay careful attention to aspects of data set selection, including potential bias, and data management issues, such as missing data, variable definition, and statistical modeling to generate appropriate conclusions. There are many studies of neuro-ophthalmic diseases that use big data approaches. Conclusions: Big data clinical research studies complement other research methodologies to advance our understanding of human disease. A rigorous and careful approach to data set selection, data management, data analysis, and data interpretation characterizes high-quality studies.
Subject Big Data; Datasets as Topic; Eye Diseases / epidemiology; Humans; Nervous System Diseases / epidemiology; Neurology / statistics & numerical data; Ophthalmology / statistics & numerical data; Registries
OCR Text Show
Date 2019-12
Language eng
Format application/pdf
Type Text
Publication Type Journal Article
Source Journal of Neuro-Ophthalmology, December 2019, Volume 39, Issue 4
Collection Neuro-Ophthalmology Virtual Education Library: Journal of Neuro-Ophthalmology Archives: https://novel.utah.edu/jno/
Publisher Lippincott, Williams & Wilkins
Holding Institution Spencer S. Eccles Health Sciences Library, University of Utah
Rights Management © North American Neuro-Ophthalmology Society
ARK ark:/87278/s6qc5vkp
Setname ehsl_novel_jno
ID 1645534
Reference URL https://collections.lib.utah.edu/ark:/87278/s6qc5vkp
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