Document Detail


Too much information: research issues associated with large databases.
MedLine Citation:
PMID:  23392064     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
PURPOSE: : The purpose of this article was to discuss common issues associated with large databases and present possible solutions to improve the quality and usefulness of large database research.
BACKGROUND: : The volume of electronic healthcare-related data is growing exponentially. Some of these data are being stored in registries and administrative databases. These data repositories are increasingly common and can serve as sources of nurse-driven research and quality improvement activities. Although these large databases have a wealth of useful information, they have limitations that may bias results. These include missing data and cases, data accuracy and validity, and the statistical effect of large samples.
DESCRIPTION: : Researchers using large databases to address quality, safety, clinical, or systems issues have a variety of available techniques to deal with data issues. Proper data cleaning activities such as screening, visualization, and outlier/inlier identification are essential for addressing inaccurate values within large data sets. Common methods for addressing missing data include case analyses and various imputation techniques. Statistical approaches such as risk reductions and effect size are also useful when working with large sample sizes.
CONCLUSION/IMPLICATIONS: : Registries and administrative databases provide healthcare researchers with increasing opportunities to address a wide variety of important practice and patient care questions. Healthcare researchers are encouraged to explore large data sets as they look for ways to improve patient safety and quality care, develop evidence-based practice guidelines, and fulfill regulatory and accreditation requirements.
Authors:
Steven Talbert; Mary Lou Sole
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Clinical nurse specialist CNS     Volume:  27     ISSN:  1538-9782     ISO Abbreviation:  Clin Nurse Spec     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-02-08     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8709115     Medline TA:  Clin Nurse Spec     Country:  United States    
Other Details:
Languages:  eng     Pagination:  73-80     Citation Subset:  N    
Affiliation:
Author Affiliations: Assistant Professor (Dr Talbert) and Pegasus Professor and the Orlando Health Distinguished Professor in Nursing (Dr Sole), College of Nursing, University of Central Florida, Orlando.
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